adjustable decisions for reducing the price of robustness of capacity expansion planning this paper proposes and implements robust optimization methodologies for making investment decisions in the capacity expansion planning cep of power systems in an uncertain environment uncertainties of fuel prices demand and transmission capacity are captured in an uncertainty set with adjustable robust optimization aro we represent all the decision variables as affine functions of multiple uncertain data this adjustability of decisions provides that the aro solution has significant less price of robustness than in traditional robust optimization ro aro models uncertainty in terms of parameter ranges called uncertainty sets an attractive attribute of utilizing uncertainty sets is that they facilitate computational tractability when simulating scenarios with multiple uncertainties we study the 40 year planning of a 5 region 13 technology us energy portfolio results show that 1 by appropriately selecting the decision rules in aro the price of robustness can be significantly reduced while maintaining the same levels of robustness and 2 the ro based models maintain high levels of robustness even under operational conditions provided by data coming from larger sizes of the uncertainty sets

strategic demand side response to wind power integration this paper explores the effects of allowing large price responsive consumers to provide reserves in a power system with significant penetration of wind energy a bilevel optimization model represents the utility maximization problem of a large consumer subject to a stochastic day ahead co optimization of energy and reserves that a system operator would solve to clear the market while considering wind power uncertainty an examination of the market outcomes from both an illustrative and a large scale study using this model allows analysis of a the effects of the type of behavior of the large consumer i e strategic vs competitive b limits on the amount of reserves it is allowed to provide and c variability and accuracy of characterization of wind power uncertainty

strategic offering for a wind power producer as a result of subsidies and technological maturity renewable electricity producers have grown in some jurisdictions to clearly dominant positions in the market under this context we propose an offering strategy for a wind power producer with market power that participates in the day ahead market as a price maker and in the balancing market as a deviator uncertainty pertaining to wind power production and balancing market price is represented through a set of correlated scenarios the proposed model is a stochastic mathematical program with equilibrium constraints mpec that can be recast as a tractable mixed integer linear programming milp problem which is solvable using available optimization software results from an illustrative example and two case studies show the effectiveness of the proposed model

risk neutral and risk averse approaches to multistage renewable investment planning under uncertainty abstract strategies for investing in renewable energy projects present high risks associated with generation and price volatility and dynamics existing approaches for determining optimal strategies are based on real options theory that often simplify the uncertainty process or on stochastic programming approaches that simplify the dynamic aspects in this paper we bridge the gap between these approaches by developing a multistage stochastic programming approach that includes real options such as postponing hedging with fixed forward contracts and combination with other sources the proposed model is solved by a procedure based on the stochastic dual dynamic programming sddp method the framework is extended to the risk averse setting a specific case study in investment in hydro and wind projects in the brazilian market is used to illustrate that the investment strategies generated by the proposed approach are efficient

a three level static milp model for generation and transmission expansion planning we present a three level equilibrium model for the expansion of an electric network the lower level model represents the equilibrium of a pool based market the intermediate level represents the nash equilibrium in generation capacity expansion taking into account the outcomes on the spot market and the upper level model represents the anticipation of transmission expansion planning to the investment in generation capacity and the pool based market equilibrium the demand has been considered as exogenous and locational marginal prices are obtained as endogenous variables of the model the three level model is formulated as a mixed integer linear programming milp problem the model is applied to a realistic power system in chile to illustrate the methodology and proper conclusions are reached

wind power investment a benders decomposition approach investment in wind power facilities involves a high level of uncertainty to properly model such uncertainty we consider a large number of scenarios and formulate this investment problem as a mathematical program with equilibrium constraints the target of this problem is to maximize the profit from wind power investment in a target year and it is subject to complementarity constraints describing a large number of market clearing conditions since the profit as a function of the investment variables has as sufficiently convex envelope the considered problem can be solved by benders decomposition thus we propose describe and analyze a benders decomposition algorithm to efficiently tackle the wind power investment problem

the value of urban tree cover a hedonic property price model in ramsey and dakota counties minnesota usa article i nfo urban tree cover benefits communities these benefits economic values however are poorly recognized and often ignored by landowners and planners we use hedonic property price modeling to estimate urban tree cover s value in dakota and ramsey counties mn usa predicting housing value as a function of structural neighborhood and environmental variables including tree cover using a spatial simultaneous autore gressive sar error model we measure tree cover as percent tree cover on parcels and within 100 250 500 750 and 1000 m results show that tree cover within 100 and 250 m is positive and statistically significant a 10 increase in tree cover within 100 m increases average home sale price by 1371 0 48 and within 250 m increases sale price by 836 0 29 in a model including both linear and squared tree cover terms tree cover within 100 and 250 m increases sale price to 40 60 tree cover beyond this point increased tree cover contributes to lower price tree cover beyond 250 m did not contribute significantly to sale price these results suggest significant positive effects for neighborhood tree cover for instance for the shading and aesthetic quality of tree lined streets indicating that tree cover provides positive neighborhood externalities

impact of forecast errors on expansion planning of power systems with a renewables target abstract this paper analyzes the impact of production forecast errors on the expansion planning of a power system and investigates the influence of market design to facilitate the integration of renewable generation for this purpose we propose a programming modeling framework to determine the generation and transmission expansion plan that minimizes system wide investment and operating costs while ensuring a given share of renewable generation in the electricity supply unlike existing ones this framework includes both a day ahead and a balancing market so as to capture the impact of both production forecasts and the associated prediction errors within this framework we consider two paradigmatic market designs that essentially differ in whether the day ahead generation schedule and the subsequent balancing re dispatch are co optimized or not the main features and results of the model set ups are discussed using an illustrative four node example and a more realistic 24 node case study

generation capacity expansion in energy markets using a two level game theoretic model with a significant number of states in the u s and countries around the world trading electricity in restructured markets a sizeable proportion of capacity expansion in the future will have to take place in market based environments however since a majority of the literature on capacity expansion is focused on regulated market structures there is a critical need for comprehensive capacity expansion models targeting restructured markets in this research we develop a two tier matrix game model and a novel solution algorithm that incorporates risk due to volatilities in profit via cvar intended for use by generators to make multi period multi player generation capacity expansion decisions we demonstrate the applicability of the model using a sample network from power world software and analyze the results

scenario reduction for futures market trading in electricity markets to make informed decisions in futures markets of electric energy stochastic programming models are commonly used such models treat stochastic processes via a set of scenarios which are plausible realizations throughout the decision making horizon of the stochastic processes the number of scenarios needed to accurately represent the uncertainty involved is generally large which may render the associated stochastic programming problem intractable hence scenario reduction techniques are needed to trim down the number of scenarios while keeping most of the stochastic information embedded in such scenarios this paper proposes a novel scenario reduction procedure that advantageously compares with existing ones for electricity market problems tackled via two stage stochastic programming

two stage robust generation expansion planning a mixed integer linear programming model this paper presents a new uncertainty handling framework for optimal generation expansion planning gep amalgamating the notions of single stage and two stage robust optimization ro the proposed multiyear robust gep methodology as a tractable mixed integer linear programming optimization problem copes with the inherent planning uncertainties associated with forecasted electricity load demand as well as estimated investment and operation costs through distribution free bounded intervals producing polyhedral uncertainty sets the optimal generation expansion plan obtained from the proposed ro approach is immunized against worst case planning uncertainties considering the adopted degree of conservatism for each uncertainty set therefore the proposed methodology is capable of controlling the robustness of the optimal investment schedule regarding the enforced planning uncertainties simulation results demonstrate the efficacy and efficiency of the proposed ro framework throughout gep studies

strategic wind power investment this paper considers the problem of identifying the optimal investment of a strategic wind power investor that participates in both the day ahead da and the balancing markets this investor owns a number of wind power units that jointly with the newly built ones allow it to have a dominant position and to exercise market power in the da market behaving as a deviator in the balancing market in which the investor buys sells its production deviations the model is formulated as a stochastic complementarity model that can be recast as a mixed integer linear programming milp model a static approach is proposed focusing on a future target year whose uncertainties pertaining to demands wind power productions and balancing market prices are precisely described the proposed model is illustrated using a simple example and two case studies

national strategic investment in european power transmission capacity abstract the transformation of the european electricity system requires substantial investment in transmission capacity to facilitate cross border trade and to efficiently integrate renewable energy sources however network planning in the eu is still mainly a national prerogative in contrast to other studies aiming to identify the pan european continental welfare optimal transmission expansion we investigate the impact of zonal planners deciding on network investment strategically with the aim of maximizing the sum of consumer surplus generator profits and congestion rents in their jurisdiction this reflects the inadequacy of current mechanisms to compensate for welfare re allocations across national boundaries arising from network upgrades we propose a three stage equilibrium model to describe the nash game between zonal planners i e national governments regulators or system operators each taking into account the impact of network expansion on the electricity spot market and the resulting welfare effects on the constituents within its jurisdiction we propose a novel way to solve the resulting gne epec type problem using a variation of a disjunctive constraints reformulation this allows to solve this problem without a priori assumptions on the relative valuation of shared constraints by each player using a four node sample network we identify several nash equilibria of the game between the zonal planners this example illustrates the failure to reach the first best welfare expansion in the absence of an effective framework for cross border cost benefit allocation

structural adjustment and the welfare of rural smallholders a comparative analysis from sub saharan africa the direction and level of changes in real incomes brought about by structural adjustment are determined by a variety of factors including sources of income patterns of expenditures and movements in relative prices in the wake of adjustment an econometric model is used to derive an index of real income which is employed for data from cote d ivoire ghana malawi madagascar and tanzania no systematic changes in relative prices and especially in the ratio of tradable to nontradable prices were noted after the beginning of adjustment although the diversity of income sources implies that the implications of movements in relative prices on smallholder welfare are indeed complex the results indicate that there is no unequivocal pattern of increase or decline in the real welfare of the rural poor but that there are marked differences among countries and regions

generation investment equilibria with strategic producers part i formulation the first of this two paper series proposes a methodology to characterize generation investment equilibria in a pool based network constrained electricity market where the producers behave strategically to this end the investment problem of each strategic producer is represented using a bilevel model whose upper level problem determines the optimal investment and the supply offering curves to maximize its profit and whose several lower level problems represent different market clearing scenarios this model is transformed into a mathematical program with equilibrium constraint mpec through replacing the lower level problems by their optimality conditions the joint consideration of all producer mpecs one per producer constitutes an equilibrium problem with equilibrium constraints epec to identify the solutions of this epec each mpec problem is replaced by its karush kuhn tucker kkt conditions which are in turn linearized the resulting mixed integer linear system of equalities and inequalities allows determining the epec equilibria through an auxiliary milp problem

finding multiple nash equilibria in pool based markets a stochastic epec approach we present a compact formulation to find all pure nash equilibria in a pool based electricity market with stochastic demands the equilibrium model is formulated as a stochastic equilibrium problem subject to equilibrium constraints epec the problem is based on a stackelberg game where the generating companies gencos optimize their strategic bids anticipating the solution of the independent system operator iso market clearing a finite strategy approach both in prices and quantities is applied to transform the nonlinear and nonconvex set of nash inequalities into a mixed integer linear problem milp a procedure to find all nash equilibria is developed by generating holes that are added as linear constraints to the feasibility region the result of the problem is the set of all pure nash equilibria and the market clearing prices and assigned energies by the iso a case study illustrates the methodology and proper conclusions are reached

the environmental economic impact of woodland a two stage hedonic price model of the amenity value of forestry in britain woodland is an important part of the environment providing economic benefits through its use in commercial timber production and through its value as an amenity as well as providing recreation for visitors woodland is also important to local residents for whom it provides leisure opportunities and a source of aesthetic enjoyment it is well known that the price of a house may reflect a household s willingness to pay to live near an environmental amenity such as a forest and to gain access to it the nature of this relationship may be examined by applying the hedonic price technique an econometric method which investigates house prices and the variation in structural and environment characteristics over space this study uses a two stage hedonic price model to explore the impact of forest type on house price and to estimate the demand for broadleaved woodland for a sample of houses adjacent to forestry commission land

profits and politics coordinating technology adoption in agriculture abstract this paper examines the political economy of government led coordination of economic activity in a simple two sector model in which individuals choice of agricultural technology affects industrialization we demonstrate the existence of multiple equilibria the economy is either characterized by the use of a traditional agricultural technology and a low level of industrialization or the use of a mechanized technology and a high level of industrialization relative to the traditional technology use of the mechanized technology increases output but leaves some population groups worse off we show that the distributional implications of choosing the mechanized technology restrict the possibility of pareto improving coordination by an elected policy maker even when we allow for income redistribution

welfare effects of expansions in equilibrium models of an electricity market with fuel network the welfare of electricity producers and consumers depends on congestion in the transmission grid generation costs that consist mainly of fuel costs and strategic behavior we formulate a game theoretic model of an oligopolistic electricity market where generation costs are derived from a fuel supply network the game consists of a fuel dispatcher that transports fuels at minimum cost to meet generator demands generators that maximize profit in cournot competition and an independent system operator iso that sets nodal prices to balance electricity supply with linear demand functions we prove the existence of an equilibrium if fuel supplies are unlimited the same equilibria hold in a simplified version of the game in which each generator optimizes its fuel acquisition from the network in some very simple examples under different assumptions about the rationality of generators with respect to iso decisions paradoxical effects on total welfare can occur from expanding either electricity transmission capacity or the transportation capacity of low cost fuel we find some instances in which the paradox occurs only under bounded rationality of the generators others where it occurs only if the generators are fully rational and still others where it occurs to different degrees under the two rationality assumptions

strategic generation capacity expansion planning with incomplete information to study the competitive behavior among individual generating companies gencos an incomplete information game model is proposed in this paper in which each genco is modeled as an agent each agent makes strategic generation capacity expansion decisions based on its incomplete information on other gencos the formation of this game model falls into a bi level optimization problem the upper level of this problem is the gencos own decision on optimal planning strategies and energy reserve bidding strategies the lower level problem is the iso s market clearing problem that minimizes the cost to supply the load which yields price signals for gencos to calculate their own payoffs a co evolutionary algorithm combined with pattern search is proposed to optimize the search for the nash equilibrium of the competition game with incomplete information the nash equilibrium is obtained if all gencos reach their maximum expected payoff assuming the planning strategies of other gencos remain unchanged the physical withholding of capacity is considered in the energy market and the herfindahl hirschman index is utilized to measure the market concentration the competitive behaviors are analyzed in three policy scenarios based on different market rules for reserve procurement and compensation

bi level game approaches for coordination of generation and transmission expansion planning within a market environment the main purpose of this paper is to develop methodologies for simultaneous generation and transmission expansion planning problem of power networks while investigating interactions between these two important sections in the proposed methodologies a transmission operator to operating under different incentives decides about investment in transmission network while anticipating the outcome of a purely competitive electricity market where several rival generation firms complete with each other to determine operating level of their generators amount of their sales and amount of their investment in generation capacity the proposed methodologies rely on bi level programming models whose upper level model represent the problem of investment in transmission by to and the lower level problems represent market outcomes obtained from clearing the market these bi level models are reduced to mixed integer linear and nonlinear programming using the duality theory and karush kuhn tucker kkt optimality conditions the results of the proposed models are analyzed and compared using two illustrative examples

market impacts of energy storage in a transmission constrained power system environmental concerns have motivated governments in the european union and elsewhere to set ambitious targets for generation from renewable energy re technologies and to offer subsidies for their adoption along with priority grid access however because re technologies like solar and wind power are intermittent their penetration places greater strain on existing conventional power plants that need to ramp up more often in turn energy storage technologies e g pumped hydro storage or compressed air storage are proposed to offset the intermittency of re technologies and to facilitate their integration into the grid we assess the economic and environmental consequences of storage via a complementarity model of a stylized western european power system with market power representation of the transmission grid and uncertainty in re output although storage helps to reduce congestion and ramping costs it may actually increase greenhouse gas emissions from conventional power plants in a perfectly competitive setting conversely strategic use of storage by producers renders it less effective at curbing both congestion and ramping costs while having no net overall impact on emissions

the political economy of food pricing an extended empirical test of the interest group approach several recent studies have documented the magnitude and impact of distortions in food pricing however little attention has been paid to the nature of the political agendas that determine the levels of direct and indirect protection granted to producers and consumers this paper offers evidence that regardless of the degree of economic development the level of political pressure wielded by interest groups in food markets and hence the level of protection they receive is an inverse function of the relative size of their constituencies the results recommend the application of collective action concepts to the understanding of agricultural policies in countries which are at different stages of development

geographic attribution of an electricity system renewable energy target local economic social and environmental tradeoffs the 2014 intergovernmental panel on climate change ipcc report asserts that investment in low carbon electricity production will need to rise by several hundred billion dollars annually before 2030 in order to stabilize greenhouse gas concentrations in the atmosphere by 2100 in recognition of this urgent need to mitigate climate change many governments have already established policies to spur renewable energy investment in the electricity sector one such policy measure is a renewable energy target ret which sets a target percentage of electricity production to be generated from renewable sources by a specified date variations on this policy have been implemented around the world from the eu 20 20 20 to diverse renewable portfolio standards in u s states and municipalities this work analyzes economic environmental and social aspects of a geographic attribution i e isolated regional or country of an ret to gain insights on the associated tradeoffs in the case study of the azores islands portugal the regional geographic attribution of an ret captures the best of all three tradeoffs

exploitation of electric drive vehicles in electricity markets the paper presents the optimization algorithm which may eventually be used by electric energy suppliers to coordinate charging and discharging of electric drive vehicles edvs exploited in electricity markets the research is focused on a day ahead market and a provision of system regulation in an ancillary service market the proposed optimization minimizes the charging costs that can be partly compensated with profits obtained from participation in the energy markets due to the stochastic nature of transportation patterns the monte carlo simulation is applied to model uncertainties presented by numerous scenarios to reduce the problem complexity the simulated driving patterns are not individually considered in the optimization but clustered into fleets using the gams scenred tool uncertainties of energy requirements in the market and energy prices are presented by statistical central moments that are further considered in hong s 2 point 1 estimation method in order to define points considered in the optimization finally each energy supplier has to offer competitive energy prices to edv users for transportation due to uncertainties the final prices cannot be deterministically calculated thus the paper proposes the risk based approach applying value at risk case studies illustrate the application of the proposed optimization in achieving competitive prices for edv users

dynamic pricing design for demand response integration in power distribution networks this paper presents optimal pricing design for demand response dr integration in the distribution network in particular we study the energy scheduling problem for a load serving entity lse that serves two types of loads namely inflexible and flexible loads inflexible loads are charged under a regular pricing tariff while flexible loads enjoy a dynamic pricing tariff that ensures cost saving for them moreover flexible loads are assumed to be aggregated by several dr aggregators the interaction between the lse and its customers is formulated as a bilevel optimization problem where the lse is the leader and dr aggregators are the followers the optimal solution of this problem corresponds to the optimal pricing tariff for flexible loads the key advantage of the proposed model is that it can be readily implemented thanks to its compatibility with existing pricing structures in the retail market extensive numerical results show that the proposed approach provides a win win solution for both the lse and its customers

generation capacity expansion in a risky environment a stochastic equilibrium analysis we cast models of the generation capacity expansion type formally developed for the monopoly regime into equilibrium models better adapted for a competitive environment we focus on some of the risks faced today by investors in generation capacity and thus pose the problem as a stochastic equilibrium model we illustrate the approach on the problem of the incentive to invest agents can be risk neutral or risk averse we model risk aversion through the cvar of plants profit the cvar induces risk adjusted probabilities according to which investors value their plants the model is formulated as a complementarity problem including the cvar valuation of investments an illustration is provided on a small problem that captures several features of today s electricity world a choice often restricted to coal and gas units a peaky load curve because of wind penetration uncertain fuel prices and an evolving carbon market we assess the potential of the approach by comparing energy only and capacity market organizations in this risky environment our results can be summarized as follows a deterministic analysis overlooks some changes of capacity structure induced by risk whether in the capacity market or energy only organizations the risk neutral analysis also misses a shift towards less capital intensive technologies that may result from risk aversion last risk aversion also increases the shortage of capacity compared to the risk neutral view in the energy only market when the price cap is low this may have a dramatic impact on the bill to the final consumer the approach relies on mathematical programming techniques and can be extended to full size problems the results are illustrative and may deserve more investigation

investigating the ability of demand shifting to mitigate electricity producers market power previous work on the role of the demand side in imperfect electricity markets has demonstrated that its self price elasticity reduces electricity producers ability to exercise market power however the concept of self price elasticity cannot accurately capture consumers flexibility as the latter mainly involves shifting of loads operation in time this paper provides for the first time theoretical and quantitative analysis of the beneficial impact of demand shifting ds in mitigating market power by the generation side quantitative analysis is supported by a multiperiod equilibrium programming model of the imperfect electricity market accounting for the time coupling operational constraints of ds as well as network constraints the decision making process of each strategic producer is modeled through a bi level optimization problem which is solved after converting it to a mathematical program with equilibrium constraints mpec and linearizing the latter through suitable techniques the oligopolistic market equilibria resulting from the interaction of multiple independent producers are determined by employing an iterative diagonalization method case studies on a test market reflecting the general generation and demand characteristics of the gb system quantitatively demonstrate the benefits of ds in mitigating producers market power by employing relevant indexes from the literature

robust optimization for transmission expansion planning minimax cost vs minimax regret due to the long planning horizon transmission expansion planning is typically subjected to a lot of uncertainties including load growth renewable energy penetration policy changes etc in addition deregulation of the power industry and pressure from climate change introduced new sources of uncertainties on the generation side of the system generation expansion and retirement become highly uncertain as well some of the uncertainties do not have probability distributions making it difficult to use stochastic programming techniques like robust optimization that do not require a probability distribution became desirable to address these challenges we study two optimization criteria for the transmission expansion planning problem under the robust optimization paradigm where the maximum cost and maximum regret of the expansion plan over all uncertainties are minimized respectively with these models our objective is to make planning decisions that are robust against all scenarios we use a two layer algorithm to solve the resulting tri level optimization problems then in our case studies we compare the performance of the minimax cost approach and the minimax regret approach under different characterizations of uncertainties

the economics of price scissors abstract in the context of a centrally planned developing economy evgeny preobrazhensky suggested the possibility of financing the accumulation process by turning the internal terms of trade against the peasantry without hurting the industrial proletariat which proposition has recently been questioned in a celebrated paper by sah and stiglitz 1984 in the present analysis we first show that consumer rationing is an essential component in preobrazhensky s analysis and that sah and stiglitz model since it relies on market equilibrium cannot be considered as a valid test of preobrazhensky s propositions the conditions under which preobrazhensky s thesis holds are then investigated together with an analysis of rural urban differential pricing policies

a game theoretic model for generation expansion planning problem formulation and numerical comparisons this paper presents an application of noncooperative game theory to generation expansion planning gep in a competitive electricity industry the authors apply the cournot model of oligopoly behavior to formulate a gep model that may characterize expansion planning in a competitive regime particularly in pool dominated generation supply industries numerical experiments are conducted on a test system to analyze generation investment and market participation decisions of candidate expansion units that vary in costs and forced outage rates the numerical results point to 1 greater industry expansion and system reliability under cournot competition than under centralized expansion planning and 2 higher probabilistic measures of reliability from multi player expansion than from expansion by a traditional monopolist with an equivalent reserve margin requirement furthermore the authors summarize analytical results involving a simplified version of the gep game

transmission expansion in an oligopoly considering generation investment equilibrium abstract transmission expansion planning tep is a sophisticated decision making problem especially in an oligopolistic electricity market in which a number of strategic price maker producers compete together a transmission system planner who is in charge of making tep decisions requires considering the future generation investment actions however in such an oligopolistic market each producer makes its own strategic generation investment decisions this motivates the transmission system planner to consider the generation investment decision making problem of all producers within its tep model the strategic generation investment problem of each producer can be represented by a complementarity bi level model the joint consideration of all bi level models one per producer characterizes the generation investment equilibrium that identifies the future evolution of generation investment in the market this paper proposes a tri level tep decision making model to be solved by the transmission system planner whose objective is to maximize the social welfare of the market minus the expansion costs and whose constraints are the transmission expansion limits as well as the generation investment equilibrium problem this model is then recast as a mixed integer linear programming problem and solved numerical results from an illustrative example and a case study based on the ieee 14 bus test system demonstrate the usefulness of the proposed approach

risk constrained multi stage wind power investment when deciding on wind power investments three major issues arise the production variability and uncertainty of wind facilities the eventual future decline in wind power investment costs and the significant financial risk involved in such investment decisions recognizing the above important issues this paper proposes a risk constrained multi stage stochastic programming model to make optimal investment decisions on wind power facilities along a multi stage horizon the proposed model is illustrated using a clarifying example and a case study

modeling competition in transmission expansion a transmission network plays a key role in allowing access to the most efficient generators to all consumers in most cases the new transmission projects are defined by a system operator which focuses on improving the bulk system s reliability and reducing short term operating problems because electricity market participants are prevented from investing in transmission facilities that may benefit them transmission expansion may not have been sufficient to stimulate competition within the market in this paper the authors show formally through a mathematical formulation based on the lagrangian relaxation technique that the investment on transmission capacity can be a profitable activity and therefore the introduction of competition in the transmission expansion could be possible such a competitive expansion of transmission capacity would allow the participants to improve the efficiency of the electricity market

transmission and generation investment in electricity markets the effects of market splitting and network fee regimes abstract we propose an equilibrium model that allows to analyze the long run impact of the electricity market design on transmission line expansion by the regulator and investment in generation capacity by private firms in liberalized electricity markets the model incorporates investment decisions of the transmission system operator and private firms in expectation of an energy only market and cost based redispatch in different specifications we consider the cases of one vs multiple price zones market splitting and analyze different approaches to recover network cost in particular lump sum generation capacity based and energy based fees in order to compare the outcomes of our multilevel market model with a first best benchmark we also solve the corresponding integrated planner problem using two test networks we illustrate that energy only markets can lead to suboptimal locational decisions for generation capacity and thus imply excessive network expansion market splitting heals these problems only partially these results are valid for all considered types of network tariffs although investment slightly differs across those regimes

a tri level model of centralized transmission and decentralized generation expansion planning for an electricity market part ii we study a tri level integrated transmission and generation expansion planning problem in a deregulated power market environment the collection of bi level sub problems in the lower two levels is an equilibrium problem with equilibrium constraints epec that can be approached by either the diagonalization method dm or a complementarity problem cp reformulation this paper is a continuation of its part i in which a hybrid iterative algorithm is proposed to solve the tri level problem by iteratively applying the cp reformulation of the tri level problem to propose solutions and evaluating them in the epec sub problem by dm it focuses on the numerical results obtained by the hybrid algorithm for a 6 bus system a modified ieee 30 bus system and an ieee 118 bus system in the numerical instances the approximate nash equilibrium point for the sub problem can be verified by examining local concavity

a transmission planning framework considering future generation expansions in electricity markets this paper proposes a transmission planning framework in a market environment in which only the generation sector is deregulated the proposed framework is based on modeling generation companies gencos strategic behavior and anticipating their expansion patterns from the viewpoint of a transmission system planner the transmission expansion planning problem in this paper is modeled as a four level optimization problem a solution method based on agent based systems and search based optimization techniques is proposed to determine the optimal transmission expansion plan

price scissors and the structure of the economy this paper undertakes three sets of tasks i it analyzes positive and normative aspects of price scissors the domestic terms of trade between agriculture and industry within nonsocialist as well as socialist ldcs the critical role of the economy s institutional features e g external trade environment wage and income determination and wage productivity effects is emphasized certain aspects of the soviet industrialization debate and subsequent collectivization are interpreted ii it develops simple rules to delineate who gains and who loses within agriculture from changes in terms of trade iii it presents powerful and informationally parsimonious rules for pareto improving price reforms for cash crops and agricultural inputs

generation capacity expansion analysis open loop approximation of closed loop equilibria in this paper we propose a methodology to approximate closed loop capacity equilibria using only open loop capacity equilibrium models in the closed loop model generation companies choose capacities that maximize their individual profit in the first stage while the second stage represents the conjectured price response market equilibrium in the open loop model firms simultaneously choose capacities and quantities to maximize their individual profit while each firm conjectures a price response to its output decisions the closed loop equilibrium model is an equilibrium problem with equilibrium constraints which belongs to a class of problems that is very hard to solve the open loop equilibrium model is much easier to solve however it is also less realistic with the approximation scheme proposed in this paper we are able to solve the closed loop model reasonably well when market behavior is closer to oligopoly than to perfect competition by smartly employing open loop models which reduces the computational time by two orders of magnitude we achieve this by transforming the open loop equilibrium problem into an equivalent convex quadratic optimization problem which can be solved efficiently finally a case study is presented in order to validate the proposed approximation scheme

equilibrium of interdependent gas and electricity markets with marginal price based bilateral energy trading the increasing interdependencies between natural gas systems and power systems create new business opportunities in coupled energy distribution markets this paper studies the marginal price based bilateral energy trading on the equilibrium of coupled natural gas and electricity distribution markets convex relaxation is employed to solve a multiperiod optimal power flow problem which is used to clear the electricity market a successive second order cone programming approach is utilized to solve a multiperiod optimal gas flow problem which is used to clear the gas market in addition the line pack effect in the gas network is considered which can offer storage capacity and provide extra operation flexibility for both networks in both problems locational marginal energy prices are recovered from the lagrangian multipliers associated with nodal balancing equations furthermore a best response decomposition algorithm is developed to identify the equilibrium of the coupled energy markets with bilateral gas and electricity trading which leverages the computational superiority of socps cases studies on two test systems validate the proposed methodology

marginal loss modeling in lmp calculation this paper discusses the pricing of marginal transmission network losses in the locational marginal pricing approach recently deployed in the iso new england iso ne standard market design smd project implemented by alstom s t d energy automation and information eai business the traditional loss model is studied and a new model is proposed the new model achieves more defendable and predictable market clearing results by introducing loss distribution factors to explicitly balance the consumed losses in the lossless dc power system model the distributed market slack reference is also introduced and discussed the lmp components produced by the two models are studied and compared under changes in slack reference numerical examples are presented to further compare the two models

estimation of house price differential of urban tree cover an application of sample selection approach hedonic valuation of urban forest amenities tends to assume that these attributes are exogenous to sample selection which might render the estimated results misleading this article intends to est

estimating the demand for tree canopy a second stage hedonic price analysis in portland oregon the benefits of large patches of tree canopy are estimated by applying a hedonic price model to the sale of single family residential properties in portland oregon the first stage analysis provides evidence of diminishing returns from increasing tree canopy past a certain level the second stage analysis uses a survey of property owners preferences and socioeconomic characteristics to overcome the problem of endogeneity average benefit estimates for the mean canopy cover within mile of properties in the study area using the second stage model are between 0 75 and 2 52 of the mean sale price

economic externalities in transmission network expansion planning abstract this paper discusses investing in transmission capacity and its link with investing in generation capacity since opportunity costs in transmission and generation capacity are dependent externalities arise when investment decisions are decentralized externalities are market failures which appear when a decision of a particular agent changes another agent s welfare but not vice versa when generation and transmission investment decisions are made separately generation investment introduces negative externalities to transmission planning a centralized multistage stochastic model is formulated for finding the pareto optimal solution of investments in transmission and generation capacity using the model we show some examples of externalities in transmission planning for the ieee 24 bus test system and the peruvian system finally we found that for the peruvian system simultaneous optimal planning of generation and transmission capacity gave significant savings around 585 million which represents 10 of the total cost

food prices wages and welfare in rural india this paper considers the welfare and distributional consequences of higher relative food prices in rural india through the lens of a specific factors general equilibrium trade model applied at the district level the evidence shows that nominal wages for manual labor both within and outside agriculture respond elastically to increases in producer prices that is wages rose faster in rural districts growing more of those crops with large price run ups over 2004 09 accounting for such wage gains the analysis finds that rural households across the income spectrum benefit from higher agricultural commodity prices indeed rural wage adjustment appears to play a much greater role in protecting the welfare of the poor than the public distribution system india s giant food rationing scheme moreover policies like agricultural export bans which insulate producers as well as consumers from international price increases are particularly harmful to the poor of rural india conventional welfare analyses that assume fixed wages and focus on households net sales position lead to radically different conclusions

market based generation and transmission planning with uncertainties this paper presents a stochastic coordination of generation and transmission expansion planning model in a competitive electricity market the monte carlo simulation method is applied to consider random outages of generating units and transmission lines as well as inaccuracies in the long term load forecasting the scenario reduction technique is introduced for reducing the computational burden of a large number of planning scenarios the proposed model assumes a capacity payment mechanism and a joint energy and transmission market for investors costs recovery the proposed approach simulates the decision making behavior of individual market participants and the iso it is an iterative process for simulating the interactions among gencos transcos and iso the iterative process might be terminated by the iso based on a pre specified stopping criterion the case studies illustrate the applications of proposed stochastic method in a coordinated generation and transmission planning problem when considering uncertainties

a bilevel approach to transmission expansion planning within a market environment we present a bilevel model for transmission expansion planning within a market environment where producers and consumers trade freely electric energy through a pool the target of the transmission planner modeled through the upper level problem is to minimize network investment cost while facilitating energy trading this upper level problem is constrained by a collection of lower level market clearing problems representing pool trading and whose individual objective functions correspond to social welfare using the duality theory the proposed bilevel model is recast as a mixed integer linear programming problem which is solvable using branch and cut solvers detailed results from an illustrative example and a case study are presented and discussed finally some relevant conclusions are drawn

strategic generation investment under uncertainty via benders decomposition we address the generation investment problem faced by a strategic power producer and consider a detailed description of the uncertain parameters involved namely rival producer investment and market offering and demand growth to identify optimal investment decisions we consider a target year and propose a bilevel model whose upper level problem determines investment and offering decisions to maximize expected profit and whose many lower level problems represent market clearing conditions per demand block and scenario since the producer total expected profit is sufficiently convex with respect to investment decisions a benders decomposition approach is proposed that results in a tractable formulation even if hundred of scenarios are used to describe uncertain parameters extensive numerical simulations based on realistic case studies show the good performance of the proposed decomposition approach

stochastic security constrained unit commitment this paper presents a stochastic model for the long term solution of security constrained unit commitment scuc the proposed approach could be used by vertically integrated utilities as well as the isos in electricity markets in this model random disturbances such as outages of generation units and transmission lines as well as load forecasting inaccuracies are modeled as scenario trees using the monte carlo simulation method for dual optimization coupling constraints among scenarios are relaxed and the optimization problem is decomposed into deterministic long term scuc subproblems for each deterministic long term scuc resource constraints represent fuel and emission constraints in the case of vertically integrated utilities and energy constraints in the case of electricity markets lagrangian relaxation is used to decompose subproblems with long term scuc into tractable short term mip based scuc subproblems without resource constraints accordingly penalty prices lagrangian multipliers are signals to coordinate the master problem and small scale subproblems computational requirements for solving scenario based optimization models depend on the number of scenarios in which the objective is to minimize the weighted average generation cost over the entire scenario tree in large scale applications the scenario reduction method is introduced for enhancing a tradeoff between calculation speed and accuracy of long term scuc solution numerical simulations indicate the effectiveness of the proposed approach for solving the stochastic security constrained unit commitment

transmission and wind power investment this paper jointly considers wind power investment and transmission reinforcement the proposed model is a mathematical program with equilibrium constraints mpec that seeks to identify the optimal wind projects to be developed and the required network reinforcements under the transmission system operator perspective this mpec seeks to minimize consumer payments and is constrained by investment conditions and the equilibria of the market under different operating conditions an array of subsidies is considered to promote independent wind power investment an example and two case studies illustrate the characteristics of the proposed model

market based coordination of transmission and generation capacity planning we propose an iso model for coordinating transmission expansion planning with competitive generation capacity planning in electricity markets the purpose of the model is a holistic simulation of generation and transmission capacity expansion in the market environment the solution represents an iterative process for simulating the interactions among gencos transcos and the iso which might be terminated by the iso based on a pre specified stopping criterion the proposed model adopts a joint energy and transmission auction market and a capacity mechanism the joint auction market enables competition to occur among generation and transmission resources the capacity mechanism offers incentives for market participant investments that reflect the locational values of additional capacity transmission capacity expansion decisions are made by merchant transmission lines that recover their capacity investments through transmission marginal pricing and capacity payments transmission network security is reflected in the proposed competitive resource planning model the examples illustrate a coordinated planning of generation and transmission in restructured power systems

improved cost benefit analysis for market based transmission planning a european perspective this paper addresses the problem of transmission planning in interconnected power systems under the uncertainty of future generation parks and fast varying marginal production costs the decision maker has to consider many different aspects during the denition of dierent transmission planning strategies that sometimes might even be contradicting major contributions are the incorporation of energy policy measurements in the evaluation process of candidate transmission plans and the inclusion of short and long term uncertainties the proposed methodology so called c trap is based on a semi dynamic heuristic approach that solves the social welfare maximization problem for several discrete steps considering different preferences for energy policy and transmission network reinforcements the flexibility provided through the heuristic analysis is very important for decision makers in the new uncertain environment in power systems

equilibria in an oligopolistic electricity pool with stepwise offer curves we study the equilibria reached by strategic producers in a pool based network constrained electricity market the behavior of each producer is modeled by a mathematical program with equilibrium constraints mpec whose objective is maximizing profit and whose complementarity constraints describe market clearing the joint solution of all these mpecs constitutes an equilibrium problem with equilibrium constraints epec the equilibria associated with the epec are analyzed by solving the strong stationarity conditions of all mpecs which can be linearized without approximation by mixed integer linear programming milp techniques the resulting mixed integer linear conditions can be reformulated as an optimization problem that allows establishing diverse objectives to differentiate among alternative equilibria

strategic offering and equilibrium in coupled gas and electricity markets the wide integration of gas fired units and implementation of power to gas technologies bring increasing interdependence among the natural gas and electricity infrastructures this paper studies the equilibrium of the coupled gas and electricity markets which is driven by the strategic offering behaviors each producer endeavours to maximize its own profit by taking the market clearing process into consideration the market equilibrium can be obtained from an equilibrium problem with equilibrium constraints a special diagonalization algorithm is devised in which the unilateral equilibrium of the gas or electricity market is found in the inner loop given the rivals strategies the interactions of the two markets are tackled in the outer loop case studies on two test systems validate the proposed methodology

exercise of market power on ramp rate in wind integrated power systems with an increasing penetration of wind power there is likely to be an increasing need for fast ramping generating units these generators ensure that no load is lost if supply drops due to the uncertainties in wind power generation however it is observed in practice that in a presence of network constraints fast ramping generating units are prone to act strategically and exercise market power by withholding their ramp rates in this paper we model this gaming behavior on ramp rates we assume a market operator who collects bids in form of marginal costs quantities and ramp rates he runs a ramp constrained economic dispatch given the generators bids forecasted demand and contingencies following the game theoretic concepts we set up a multi level optimization problem the lower level problem is the ramp constrained economic dispatch and the higher level represents the profit maximization problems solved by strategic generators the whole problem is formulated as an equilibrium problem with equilibrium constraints epec the outcome of the epec problem is a set of nash equilibria to tackle the multiple nash equilibria problem the concept of the extremal nash equilibria is defined and formulated we model the concept of extremal nash equilibria as a single stage mixed integer linear programming problem milp and demonstrate the application of this mathematical framework on an illustrative case and on a more realistic case study with tractable results

finding equilibria in the pool based electricity market with strategic wind power producers and network constraints this paper proposes a model to find the equilibria in the short term electricity market with large scale wind power penetration the behavior of each strategic player is modeled through a two stage mathematical problem with equilibrium constraints mpec where the upper level problem maximizes the profit of the strategic player and the lower level problem describes the clearing processes of the day ahead and real time markets while considering the network constraints the joint solution of all the mpecs constitutes an equilibrium problem with equilibrium constraints epec the uncertain wind power production and demand are represented by a set of plausible scenarios by using the duality theory and karush kuhn tucker condition each mpec is transferred into a mixed integer linear programing problem the nash equilibria of the electricity market are obtained by solving the epec using game theory and the diagonalization algorithm case studies are performed to show the effectiveness of the proposed model

strategic generation investment using a complementarity approach this paper provides a methodology to assist a strategic producer in making informed decisions on generation investment a single target year is considered with demand variations modeled through blocks the strategic behavior of the producer is represented through a bilevel model the upper level considers both investment decisions and strategic production actions and the lower level corresponds to market clearing prices are obtained as dual variables of power balance equations rival uncertainties on offering and investment are characterized through scenarios the resulting model is a large scale mixed integer lp problem solvable using currently available branch and cut techniques results pertaining to an illustrative example and a case study are reported and discussed

energy investment planning at a private company a mathematical programming based model and its application in turkey we consider a mid sized private electricity generating company that plans to enter the market that is partially regulated there is a cap and trade system in operation in the industry there are nine possible power plant types that the company considers to invest on through a planning horizon some of these plants may include a carbon capture and storage technology we develop a stochastic mixed integer linear program for this problem where the objective is to maximize the expected net present value of the profit obtained we include restrictions on the maximum and minimum possible amount of investment for every type of investment option we also enforce market share conditions such that the percentage of the total investments of the company over the total installed capacity of the country stay between upper and lower bounds moreover in order to distribute the investment risk the percentage of each type of power plant investment is restricted by some upper bound we tested the model for a hypothetical company operating in turkey the results show that the model is suitable to be used for determining the investment strategy of the company

multi stage flexible expansion co planning under uncertainties in a combined electricity and gas market natural gas is an important fuel source in the power industry electricity and natural gas are both energy that can be directly consumed to improve the overall efficiency of the energy infrastructure it is imperative that the expansion of gas power plants electricity transmission lines and gas pipelines can be co planned the co planning process is modeled as a mixed integer nonlinear programming problem to handle conflicting objectives simultaneously we propose a novel model to identify the optimal co expansion plan in terms of social welfare to evaluate the robustness of plans under different scenarios the flexibility criterion is used to identify each plan s adaptation cost to uncertainties such as demand growth fuel cost and financial constraints etc we developed a systematic and comprehensive planning model to understand develop and optimize energy grids in order to reach higher social welfare and is therefore of great importance in terms of supporting and guiding investment decisions for the power and gas industry meanwhile we use the sequential importance sampling sis to perform scenario reduction for achieving a higher computational efficiency a comprehensive case study on the integrated ieee 14 bus and a test gas system is conducted to validate our approach

optimal investments in power generation under centralized and decentralized decision making this work presents a novel model for optimization of investments in new power generation under uncertainty the model can calculate optimal investment strategies under both centralized social welfare and decentralized profit objectives the power market is represented with linear supply and demand curves a stochastic dynamic programming algorithm is used to solve the investment problem where uncertainty in demand is represented as a discrete markov chain the stochastic dynamic model allows us to evaluate investment projects in new base and peak load power generation as real options and determine optimal timing of the investments in a case study we use the model to compare optimal investment strategies under centralized and decentralized decision making a number of interesting results follow by varying the assumptions about market structure and price response on the demand side

assessing the impact of incentive regulation for innovation on res integration investing in innovative smart grids sgs technology can reduce overall investments in distribution systems with unpredictable renewable energy sources res regulators should therefore decide what incentives are desirable and design a flexible economic regulatory framework able to encourage distribution system operators dnos to decide for innovation in the sgs an innovative method that can support the regulators in encouraging res exploitation by determining the right incentives to favor investments in innovation in an electrical distribution network is proposed in this paper the method allows stakeholders like regulators distribution companies and developers evaluating the long term economic effects of their decisions the effectiveness of the proposed method based on non dominated sorting genetic algorithm nsga ii and on multi period optimal power flow mp opf is verified on an 84 bus network

investment in electricity markets with asymmetric technologies abstract capacity investments in electricity markets is one of the main issues in the restructuring process to ensure competition and enhance system security of networks we study competition between hydro and thermal electricity generators under demand uncertainty producers compete in quantities and each is constrained the thermal generator by capacity and the hydro generator by water availability we analyze a two period game emphasizing the incentives for capacity investments by the thermal generator we characterize both markov perfect and open loop equilibria in the markov perfect equilibrium investment is discontinuous in initial capacity and higher than it is in the open loop equilibrium however since there are two distortions in the model equilibrium investment can be either higher or lower than the efficient investment

toward fully renewable electric energy systems renewable energy sources are here to stay for a number of important reasons including global warming and the depletion of fossil fuels we explore in this paper how a thermal dominated electric energy system can be transformed into a renewable dominated one this study relies on a stochastic programming model that allows representing the uncertain parameters plaguing such long term planning exercise being the final year of our analysis 2050 we represent the transition from today to 2050 by allowing investment in both production and transmission facilities with the target of achieving a renewable dominated minimum cost system the methodology developed is illustrated using a realistic large scale case study finally policy conclusions are drawn

evaluating the strategic behavior of cement producers an equilibrium problem with equilibrium constraints abstract this paper investigates the equilibria reached by a number of strategic producers in the cement sector through a technological representation of the market we present a bilevel model for each producer that characterizes its profit maximizing behavior in the bilevel model the upper level problem of each producer is constrained by a lower level market clearing problem representing cement trading and whose objective function corresponds to social welfare replacing the lower level problem by its optimality condition yields a mathematical program with equilibrium constraints mpec then all strategic producers are jointly considered representing their interaction requires solving jointly the interrelated mpecs of all producers which results in an equilibrium problem with equilibrium constraints epec a parametric analysis concerning cost capacity and demand fluctuations has been conducted our analysis shows that the european cement sector is mature and has lost its competitiveness african cement market can assume a prominent role in international markets in the coming future if investments in new and efficient capacity are carried out finally the far east will remain the reference exporter of cement at worldwide level

generation investment equilibria with strategic producers part ii case studies this paper analyzes numerically the approach reported in the companion paper for identifying generation investment equilibria in an electricity market where the producers behave strategically to this end a two node illustrative example and a large scale case study based on the ieee reliability test system rts are examined and the results obtained are reported and discussed

capacity expansion equilibria in liberalized electricity markets an epec approach this paper presents a novel way to model the generation capacity expansion problem in a liberalized framework via a multi year bilevel equilibrium model in the upper level the competing generation companies maximize their individual profits while the lower level represents the market using a conjectured price response approach which allows us to vary the strategic spot market behavior to see how much the reigning competitive behavior impacts investment decisions the bilevel equilibrium model is formulated as an equilibrium problem with equilibrium constraints transformed into a mixed integer linear program and solved as such using diagonalization in order to verify equilibria we present a case study to apply this new modeling approach and to demonstrate that the proposed equilibrium problem with equilibrium constraints can have multiple solutions whose respective investments can vary

evaluation of lmp intervals considering wind uncertainty step changes in the curve of locational marginal prices lmp under load variation have been known characteristics given its present formulation identifying lmp intervals under wind uncertainty is important for market participants to assess and mitigate their risks when price forecast is needed this work proposes a bi level optimization model to calculate the lmp intervals under wind uncertainty without the repetitive monte carlo mc simulation the specific bus lmp maximization or minimization is the upper level problem while the iso s economic dispatch is the lower level problem case studies are presented to demonstrate the proposed methodology

beyond dualism agricultural productivity small towns and structural change in bangladesh this paper uses a framework that goes beyond rural urban dualism and highlights the role of small town economy in understanding structural change in a developing country it provides a theoretical and empirical analysis of the role of agricultural productivity in structural transformation in the labor market the empirical work is based on a general equilibrium model that formalizes the demand and labor market linkages the small town draws labor away from the rural areas to produce goods and services whose demand may depend largely on rural income the theory clarifies the role played by the income elasticity of demand and the wage elasticity with respect to productivity increase in agriculture for productivity growth to lead to a demand effect the wage elasticity has to be lower than a threshold when the demand for goods and services produced in small towns comes mainly from the adjacent rural areas the demand effect can outweigh the negative wage effect and lead to higher employment in the town goods sector using rainfall as an instrument the empirical analysis finds a significant positive effect of agricultural productivity on rice yield and agricultural wages productivity shock increases wages more in the rural sample compared with the small town economy sample but structural change in employment is more pronounced in the small town economy in the rural sample it increases employment only in small scale manufacturing and services in contrast a positive productivity shock has large and positive impacts on employment in construction and transport education health and other services and manufacturing employment in larger scale enterprises located in small towns and cities agricultural productivity growth induces structural transformation within the services sector in small towns with employment in skilled services growing at a faster pace than that of low skilled services

a multiple leader stackelberg model and analysis this paper presents a new multiple leader follower model that is a consistent extension of stackelberg s leader follower duopoly the development contrasts with other existing extensions by demonstrating how the leader firms can utilize the true reaction curve of the follower firms it also provides sufficient conditions for some useful convexity and differentiability properties of this function for the proposed model we conduct a static analysis and discuss the existence uniqueness and computation of an equilibrium solution as well as study certain issues regarding the relative profits of leader and follower firms since the cournot oligopoly and the stackelberg leader follower models are special cases of this model the analysis in this paper hopefully provides some further insights about these types of models

security constrained resource planning in electricity markets we propose a security based competitive generation resource planning model in electricity markets the objective of the model is to introduce the impact of transmission security in a multi genco generation resource planning the proposed approach is based on effective decomposition and coordination strategies lagrangian relaxation and benders decomposition are applied to decompose the original planning problem into tractable optimization subproblems locational price signal and security signal are defined for the simulation of competition among gencos and the coordination of security between gencos and the regulatory body iso the numerical examples exhibit the effectiveness of the proposed generation planning model in electricity markets

network expansion by a proactive transmission system operator a case study abstract complex planning procedures often amplify the difference in investment time between generation and transmission in this work we consider a transmission project in italy and relying on a recently proposed methodology we compare costs and benefits of anticipating the planning process before the connection of new power plants becomes certain whereas the system faces lower congestion costs if the network is reinforced immediately anticipation constitutes a sunk cost in case generation is not built for realistic load and generation scenarios anticipation costs as well as differences in investment times our results indicate that anticipation is the most efficient choice for a relatively low connection probability analyses of this sort are particularly relevant in light of the increasing complexity of public engagement processes and of the remarkable growth in renewable generation

what are the benefits of co optimizing transmission and generation investment eastern interconnection case study transmission planning has traditionally followed a generation first or reactive logic in which network reinforcements are planned to accommodate assumed generation build outs the emergence of renewables has revealed deficiencies in this approach in that it ignores the interdependence of transmission and generation investments for instance grid investments can provide access to higher quality renewables and thus affect plant siting disregarding this complementarity increases costs in theory this can be corrected by proactive transmission planning which anticipates how generation investment responds by co optimizing transmission and generation investments we evaluate the potential usefulness of co optimization by applying a mixed integer linear programming formulation to a 24 bus stakeholder developed representation of the u s eastern interconnection we estimate cost savings from co optimization compared to both reactive planning and an approach that iterates between generation and transmission investment optimization these savings turn out to be comparable in magnitude to the amount of incremental transmission investment we also evaluate three congestion metrics as screens for reducing the number of candidate transmission investments they each improve solution times but the estimated potential benefit metric is much more effective in identifying cost effective lines than the others

analysis of generation investment under different market designs in this paper a stochastic dynamic optimization model is used to analyze the effect of different market designs on generation investment and demand the expansion decisions of profit maximizing investors are simulated under four different market designs energy only capacity payment capacity obligation and capacity subscription the results show that the overall social welfare is reduced compared to a centralized social welfare optimization for the first three policies in particular an energy only market with a low price cap leads to insufficient generation investments capacity payments and obligations give additional investment incentives and more generating capacity but also result in a considerable transfer of wealth from consumers to producers due to the capacity payments in contrast the capacity subscription policy increases the social welfare and both producers and consumers benefit this is possible because capacity subscription explicitly utilizes differences in consumers preferences for uninterrupted supply this advantage must be weighed against the cost of implementation which is not included in the model

does risk aversion affect transmission and generation planning a western north america case study abstract we investigate the effects of risk aversion on optimal transmission and generation expansion planning in a competitive and complete market to do so we formulate a stochastic model that minimizes a weighted average of expected transmission and generation costs and their conditional value at risk cvar we show that the solution of this optimization problem is equivalent to the solution of a perfectly competitive risk averse stackelberg equilibrium in which a risk averse transmission planner maximizes welfare after which risk averse generators maximize profits this model is then applied to a 240 bus representation of the western electricity coordinating council in which we examine the impact of risk aversion on levels and spatial patterns of generation and transmission investment although the impact of risk aversion remains small at an aggregate level state level impacts on generation and transmission investment can be significant which emphasizes the importance of explicit consideration of risk aversion in planning models

induced wage effects of changes in food prices in egypt the trend in real agricultural wages in egypt over the two decades since the mid 1970s is well described by an inverted u shaped curve with a peak around 1985 but the rise and fall of real wages masks a complex dynamic process by which nominal wages adjust in response to changes in food prices we use governorate level panel data for 1976 93 to explore the nature of this adjustment process our results indicate that nominal wages adjust slowly there is a significant negative initial impact of rising food prices on real wages though wages do catch up in the long run

robust transmission planning under uncertain generation investment and retirement transmission planning is typically faced with a wide range of uncertainty including growth in demand renewable energy generation and fuel price the restructuring of the electric power industry the drive for energy independence and the push for a cleaner environment have led to additional sources of uncertainty in all aspects of power system operations and planning the more decentralized decision making implicates uncertainty in future generation investment and retirement of existing units such uncertainties are among the biggest challenges in transmission planning in power systems however existing approaches in the literature do not fully address this problem in this paper we construct a new robust transmission planning model representing generation investment and retirement uncertainty more realistically to improve the quantification and visualization of uncertainty and the impacts of environmental policies with this model we can manage the impacts of uncertainty in the time the size and the location of candidate generation additions as well as the retirement of units the corresponding algorithm we develop takes advantage of the structural characteristics of the model so as to obtain a computationally efficient solution methodology we present an extensive numerical study on the wecc 240 bus system and illustrate the effectiveness of our approach

generation capacity expansion in liberalized electricity markets a stochastic mpec approach this paper proposes a bilevel model to assist a generation company in making its long term generation capacity investment decisions considering uncertainty regarding the investments of the other generation companies the bilevel formulation allows for the uncoupling of investment and generation decisions as investment decisions of the single investing generation company are taken in the upper level with the objective to maximize expected profits and generation decisions by all companies are considered in the lower level the lower level represents the oligopolistic market equilibrium via a conjectured price response formulation which can capture various degrees of strategic market behavior like perfect competition the cournot oligopoly and intermediate cases

co planning of investments in transmission and merchant energy storage suitably located energy storage systems are able to collect significant revenue through spatiotemporal arbitrage in congested transmission networks however transmission capacity expansion can significantly reduce or eliminate this source of revenue investment decisions by merchant storage operators must therefore account for the consequences of potential investments in transmission capacity by central planners this paper presents a tri level model to co optimize merchant electrochemical storage siting and sizing with centralized transmission expansion planning the upper level takes the merchant storage owner s perspective and aims to maximize the lifetime profits of the storage while ensuring a given rate of return on investments the middle level optimizes centralized decisions about transmission expansion the lower level simulates market clearing the proposed model is recast as a bi level equivalent which is solved using the column and constraint generation technique a case study based on a 240 bus 448 line testbed of the western electricity coordinating council interconnection demonstrates the usefulness of the proposed tri level model

transmission congestion and competition on power generation expansion generation expansion planning involves decisions on location and capacity of new generation which may lead to adding or relieving congestion in transmission lines and to increasing or reducing competition in deregulated markets generation expansion may encounter congestion in the transmission network by constrained single line flows as well as flowgate transfer capabilities in this paper a model to study the interaction between competition and transmission congestion on power generation expansion is proposed the generation expansion problem is modeled as a cournot competition game network transmission constraints are included in the optimal generation expansion problem to comply with power flow limits results from a five bus power network and the ieee 24 bus system are presented and discussed