risk limiting economic dispatch for electricity markets with flexible ramping products the expected increase in the penetration of renewables in the approaching decade urges the electricity market to introduce new products in particular flexible ramping products to accommodate the renewables variability and intermittency a risk limiting economic dispatch scheme provides the means to optimize the dispatch and provision of these products in this paper we adopt the extended loss of load probability as the definition of risk we first assess how the new products distort the optimal economic dispatch by comparing to the case without such products specifically using parametric analysis we establish the relationship between the minimal generation cost and the two key parameters of the new products the up and down flexible ramping requirements such relationship yields a novel routine to efficiently solve the non convex risk limiting economic dispatch problem both theoretical analysis and simulation results suggest that our approach may substantially reduce the cost for incorporating the new products we believe our approach can assist the isos with utilizing the ramping capacities in the system at the minimal cost

optimal inventory and hedging decisions with cvar consideration abstract we consider a newsvendor who makes an ordering decision to meet stochastic demand and buys a put option written on the demand to hedge against the risk of low demand to maximize his expected utility which is measured by the conditional value at risk cvar the put option is fairly priced with specifications for the strike price and the strike quantity with the consideration of lost sale penalty cost we derive structural results on the optimal ordering and hedging polices we show that the newsvendor will not order more than that without the option contract when the strike quantity is pre determined and low and he will order more when the strike quantity is a decision variable moreover the optimal strike quantity is less than or equal to the optimal order quantity in the risk neutral setting and interestingly there are cases in which the optimal hedging ratio first increases then keeps constant as the newsvendor becomes less risk averse we also show that the value of the put option increases as the newsvendor becomes more risk averse and demand becomes more uncertain furthermore the effect of risk aversion on the value of the option highly depends on the magnitudes of the system parameters

stability analysis of electricity markets using tsk fuzzy modeling this paper discusses the stability properties of electricity markets and their implications for the deregulated market environment we formulate a takagi sugeno kang tsk fuzzy model for electricity markets to account for their uncertainty and nonlinearity and obtain realistic stability results the paper provides sufficient conditions for the stability and instability of electricity markets all the proposed stability and instability conditions can be tested using linear matrix inequalities simulation results demonstrate the application of the stability and instability tests to electric power market under different market conditions the tests also demonstrate the importance of the including nonlinearities and uncertainty in the electricity market when investigating its stability

the incentive for conservation investment in regulated utilities abstract some public utilities have implemented programs which call for their direct investment in residential energy conservation measures this paper examines the set of regulatory circumstances in which a rational regulated utility would have an incentive for such investment given this regulatory environment we determine whether or not the utility will invest in the correct amount in the sense of economic efficiency finally we analyze how corrective regulatory policy can aid in attaining the goal of economic efficiency

estimating energy savings due to conservation programmes the bpa residential weatherization pilot programme abstract the bonneville power administration operated a residential weatherization pilot programme from 1980 to 1982 the programme provided free home energy audits to more than 7000 electrically heated homes in the pacific northwest and gave zero interest loans to weatherize over 4000 of these homes the total cost of the programme was 11 million this paper describes several mehtods used to estimate the net energy saving effect of the bpa programme ie the electricity saving that could be directly attributed to the programme the simplest method ivolves estimation of weather adjusted annual electricity consumption for each household the second approach uses this weather adjusted consumption as the dependent variable in a pooled time series cross section regression model of electricity use the third approach involves estimation of qualitative choice models of the decisions to retrofit and to participate in the bpa programme results from these models are used to define mills ratio terms that are then used as explanatory variables in the regression model of the second approach the range in estimated programme saving given the diversity of analytical methods used is surprisingly small 3100 3300 kwh year per average programme participant

the stability of power system markets market equilibrium conditions can be derived from more general dynamic equations describing the marketplace dynamic equations provide insights into the behavior and stability of markets which are not available from static models for example markets with a single supplier with declining linear costs economies of scale may or may not be stable depending on specific cost characteristics markets with more than one supplier with declining linear costs are always unstable this paper illustrates a situation where the removal of congestion makes a market unstable

portfolio choice of government incentives the case of commercialization of a new coal based technology economic and financial incentives have become accepted tools for the implementation of government policies such as encouraging the widespread use of new technologies that offer significant economic and political benefits at the macroeconomic level but are not well perceived by managers at the micro level due to significant retrofitting costs this study using portfolio and real investment theories develops a quantitative methodology for selecting the optimal mix of incentives based on financial and operating factor sensitivities of the targeted firms in an uncertain environment the proposed methodology overcomes several shortcomings of previous studies the study applies the suggested method to a recent dod doe 1995 g project data that estimates the net benefits of a new coal based technology the results show that government policies based on a combination of incentives are more effective than individual incentive based policies the empirical analysis of firms which account for the 163 boiler sites in the sample reveals that the optimal incentive package is weighted about 2 1 in favor of tax incentives versus research and development subsidies

market equilibrium under incomplete and imperfect information in bilateral electricity markets in contrast to the centralized pool model bilateral markets present a decision making situation in which information plays a major role along with the physical and operative constraints of the network we propose a model that includes network constraints for competitive bilateral electricity markets based on an evolutionary bipartite complex network in which the nodes and weighted links represent the players and transactions respectively the strong stable equilibrium of the network is applied to detect possible market equilibria obtained through a dynamic game with incomplete and imperfect information in which the players form an evolutionary network while trying to maximize their own utilities the model is conceptually illustrated with a four bus test system and then applied to the ieee30 test system to analyze the impact of the transmission network and information on the equilibria and market performance

measuring the energy savings from home improvement investments evidence from monthly billing data an important factor driving energy policy over the past two decades has been the energy paradox the perception that consumers apply unreasonably high hurdle rates to energy saving investments we explore one possible explanation for this apparent puzzle that realized returns fall short of the returns promised by engineers and product manufacturers using a unique data set we find that the realized return to attic insulation is statistically significant but the median estimate 9 7 is almost identical to a discount rate for this investment implied by a capm analysis we conclude that the case for the energy paradox is weaker than has previously been believed

risk preferences and robust inventory decisions abstract recently in inventory management instead of maximizing expected profit or minimizing expected cost risk averse objective functions have been used for determining the optimal order quantity we use the well known newsvendor model to determine the optimal order quantity for an objective function with two risk parameters which can describe risk neutral risk averse as well as risk taking behaviour of the inventory manager this approach can also be applied to situations in which the demand distribution cannot be specified uniquely we consider robust optimization procedures maximin and minimax regret to determine optimal order quantities if the set of potential demand variables can be partially ordered by stochastic dominance rules

would a risk averse newsvendor order less at a higher selling price we model a risk averse newsvendor s decision making behavior with some commonly used classes of utility functions within the expected utility theory eut framework under fairly general conditions of eut we show that a risk averse newsvendor will order less than an arbitrarily small quantity as selling price gets larger if price is higher than a threshold value i e the optimal order quantity decreases as the selling price increases

the production tax credit for wind turbine powerplants is an ineffective incentive abstract the us energy policy act epact of 1992 created a production tax credit of 1 5 kwh available for 10 years to promote certain renewable energy technologies including wind turbines this paper argues that the impact of the wind turbine production tax credit will be minimal the argument depends entirely on the nature of the project finance structure used by the private power industry for wind turbine development we show that tax credits can only be absorbed by equity investors if there is a large fraction of equity in the project capital structure this raises the financing cost of wind turbine projects compared to conventional power technology which relies on a large fraction of low cost debt if the tax credit were paid as a cash subsidy the capital structure could be shifted to low cost debt and financing costs could be significantly reduced

newsvendor solutions via conditional value at risk minimization abstract in this paper we consider the minimization of the conditional value at risk cvar a most preferable risk measure in financial risk management in the context of the well known single period newsvendor problem which is originally formulated as the maximization of the expected profit or the minimization of the expected cost we show that downside risk measures including the cvar are tractable in the problem due to their convexity and consequently under mild assumptions on the probability distribution of products demand we provide analytical solutions or linear programming lp formulation of the minimization of the cvar measures defined with two different loss functions numerical examples are also exhibited clarifying the difference among the models analyzed in this paper and demonstrating the efficiency of the lp solutions

financial bilateral contract negotiation in wholesale electricity markets using nash bargaining theory bilateral contracts are important risk hedging instruments constituting a major component in the portfolios held by many electric power market participants however bilateral contract negotiation is a complicated process as it involves risk management strategic bargaining and multi market participation this study analyzes a financial bilateral contract negotiation process between a generation company and a load serving entity in a wholesale electric power market with congestion managed by locational marginal pricing nash bargaining theory is used to model a pareto efficient settlement point the model predicts negotiation outcomes under various conditions and identifies circumstances in which the two parties might fail to reach an agreement both analysis and simulation are used to gain insight regarding how these negotiation outcomes systematically vary in response to changes in the participants risk preferences and price biases

energy demand impact of incentive programmes a non parametric analysis for the canadian oil substitution program abstract a non parametric approach based on b splines is used to analyse the impact of the canadian oil substitution program cosp on the choice of heating systems in the residential sector in canada and in quebec our results suggest that the cosp did not achieve its main purpose of accelerating the decline in the use of oil between 1981 and 1985

stochastic valuation of energy storage in wholesale power markets abstract energy storage systems are well poised to mitigate uncertainties of renewable generation outputs grid scale energy storage projects are major investments which call for rigorous valuation and risk analysis this paper provides a stochastic energy storage valuation framework in wholesale power markets which considers all key revenue streams simultaneously as part of this framework an operational optimization model is developed to determine the energy storage system s optimal dispatch sequences a future curve model is built to capture the volatilities of electricity prices in addition a frequency regulation service price forecasting model is developed simulation results with a realistic battery storage system reveal that the majority of the market revenues comes from frequency regulation services simulation results also show that both round trip efficiency and power to energy ratio are crucial to the cost effectiveness of energy storage systems

a theory of buyer seller networks this paper introduces a new model of exchange networks rather than markets of buyers and sellers it begins with the empirically motivated premise that a buyer and seller must have a relationship a link to exchange goods networks buyers sellers and the pattern of links connecting them are common exchange environments this paper develops a methodology to study network structures and explains why agents may form networks in a model that captures characteristics of a variety of industries the paper shows that buyers and sellers acting strategically in their own self interests can form the network structures that maximize overall welfare

robust inventory decision under distribution uncertainty a cvar based optimization approach abstract we study the robust inventory decision making problem faced by risk averse managers with incomplete demand information in a newsvendor setting three basic models are developed expected profit maximization cvar based profit maximization and a combination of the two each model is robustly formulated under the assumption of ellipsoid discrete distribution and again under the box discrete distribution each robust model can be mathematically transformed into a second order cone program for ellipsoid uncertainty or into a general convex optimization problem for box uncertainty both transformed problems can be optimally solved directly we offer propositions with proof to show the equivalence of the transformed problems with the original ones numerical examples are given to validate the proposed approach we find that the performances under both ellipsoid and box uncertain distributions are robust finally sensitivity analysis with respect to risk averse levels and trade off coefficients is conducted to validate the proposed models and solution approaches

newsvendor problem with random shortage cost under a risk criterion abstract we study profit maximization vs risk approaches for the standard newsvendor problem with uncertainty in demand as well as a generalized version with uncertainty in the shortage cost as often applies in practice we consider two well known risk approaches value at risk var included as a constraint and conditional value at risk cvar we first derive the explicit expressions of the optimal solution with uncertainty of shortage cost under different risk measures and then perform a numerical analysis to quantify the effect of uncertainty in shortage cost and risk measures for the standard newsvendor problem we find that the optimal quantity under cvar is always lower than that under the var constraint which in turn is lower than the order quantity that maximizes the expected profit insightful explanations for this result are that a a higher degree of risk aversion drives the newsvendor to order fewer products increasing the likelihood that all will be sold b this effect is stronger for the cvar approach as this does not consider the expected profit at all another interesting and counter intuitive observation for the cvar approach is that a higher retail price may lead to a smaller order quantity as fewer items need to be sold in order to attain a sufficient profit these results show that one should be careful in employing the cvar risk measure for newsvendor type problems the results remain valid if the shortage cost becomes uncertain however increased uncertainty of this type does improve the relative profitability under the cvar approach by increasing the order quantity under that criterion whilst there is no effect under the other criteria

risk aversion in inventory management traditional inventory models focus on risk neutral decision makers i e characterizing replenishment strategies that maximize expected total profit or equivalently minimize expected total cost over a planning horizon in this paper we propose a framework for incorporating risk aversion in multiperiod inventory models as well as multiperiod models that coordinate inventory and pricing strategies we show that the structure of the optimal policy for a decision maker with exponential utility functions is almost identical to the structure of the optimal risk neutral inventory and pricing policies these structural results are extended to models in which the decision maker has access to a partially complete financial market and can hedge its operational risk through trading financial securities computational results demonstrate that the optimal policy is relatively insensitive to small changes in the decision maker s level of risk aversion

application of fuzzy q learning for electricity market modeling by considering renewable power penetration abstract by increasing renewable resource penetration the need for developing fast and reliable market modeling approaches in the presence of these resources has gained greater attention in this paper fuzzy q learning approach is proposed for hour ahead electricity market modeling in presence of renewable resources the proposed approach is implemented on ieee 30 bus test system the effectiveness of the proposed approach is evaluated and compared with q learning approach for both normal and stressful cases simulation results indicate that the proposed approach is able to model electricity market for a range of continuous multidimensional renewable power penetration in considerably less iterations compared with q learning approach moreover the probability of finding nash equilibrium is becoming higher by using fuzzy q learning approach while the other indices such as average social welfare average of locational marginal prices lmps and average standard of deviation of lmps do not change considerably

risk preferences of a newsvendor with service and loss constraints abstract using the newsvendor framework we present an approach to determine an order quantity which is relevant for the observed ordering behavior of an inventory manager whereas in literature just one constraint has been used we suggest two conflicting constraints the service constraint specified by a target value for the cycle service level is fulfilled by high order quantities the loss constraint is characterized by a target resulting in losses is met by low order quantities choosing as objective function a mean deviation rule where risk attitudes are measured by the conditional value at risk the optimal order quantity is determined depending on the risk parameters if the newsvendor is not able to specify the risk preferences we use the constraints to describe the risk attitudes of the decision maker in dependence of the profitability of the product and its demand distribution including those products where no admissible order quantity exists if there are admissible solutions we identify conditions such that the service constraint is dominating i e the prescribed service level is high and necessarily risk taking behavior is implied contrary if the loss constraint dominates i e the probability of loss is low the decision maker in any case is a risk averter but if both the service target and the loss target are not too challenging then for products with high profitability all risk preferences are possible

inflation tax rules and investment some econometric evidence this paper presents econometric evidence on the effect of tax incentives on business investment in the united states in the period from 1953 through1978 the analysis emphasizes that the interaction of inflation and existing tax rules has contributed substantially to the decline of business investment since the late 1960 s because the investment process is far too complex for any simple econometric model to be convincing i have estimated three quite different models of investment behavior the strength of the empirical evidence rests on the fact that all three specifications support the same conclusion more generally the analysis and evidence show that theoretical models of macroeconomic equilibrium should specify explicitly the role of distortionary taxes especially taxes on capital income the failure to include such tax rules can have dramatic and misleading effects on the qualitative as well as the quantitative properties of macroeconomic theories this paper was presented as the fisher shultz lecture at the fourth world congress of the econometric society 29 august 1980 in aix en province this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this abstract was borrowed from another version of this item

generator bidding in oligopolistic electricity markets using optimal control fundamentals and application in this paper optimal control is applied to study generator bidding in an oligopolistic electricity market the repeated bidding process in hourly based real time electricity markets is modeled as a dynamic feedback system an optimal control problem is then formulated to explore individual generator s long term multiperiod optimization behavior particularly in our formulation the periodic property of the system demand is considered several lemmas are included for concerning system stability based on the necessary conditions for optimality from the pontryagin maximum principle a sweeping method is proposed and an optimal state feedback control rule is then obtained via backward induction numerical results suggest that the generator who unilaterally applies optimal control for generation decisions will obtain more profits a sensitivity analysis is also performed identifying these market factors that affect the performance of optimal control

strategic behavior and equilibrium in experimental oligopolistic electricity markets the method of experimental economics is applied to research of oligopolistic electricity markets the design of experimental platform principles of experimental economics and experimental design are introduced the experiments are organized on base of the cournot model of oligopolistic electricity markets a set of experiments are conducted on the experimental oligopolistic markets with three generating companies gencos and the experimental results are analyzed with strict statistics approaches the results show that the market competition will converge to the results between perfect competition equilibrium and nash equilibrium in oligopolistic electricity markets with asymmetric production cost functions and repeated play among the gencos the decision support tools of gencos have significant influences on experimental results the markets converge to static cournot nash equilibrium when the bounded rational subjects repeatedly play equipped with the tools that can give best response strategies the experimental method provides a complement to the theoretical research and computer simulation and has many merits in modeling realistic electricity markets

the impact of market clearing time and price signal delay on the stability of electric power markets we generalize a model proposed by alvarado of the electric power market by including the effects of control and communication to simulate realistic markets our model issues control signals only at given times and those signals are delayed during transmission these two effects transform alvarado s continuous system into a hybrid system with consequential effects the stability analysis of the new system reveals two important properties first there is an upper limit on the market clearing time and the delay of the price signal beyond which the system becomes unstable second there is a counter intuitive relationship between the market clearing time and price signal delay when the market clearing time is relatively long delaying the price signal can improve the market s stability while reducing the communication delay can destabilize the market this counter intuitive effect shows that the full impact of information technology on power markets can be significant and difficult to anticipate therefore as markets are designed and regulated careful attention should be paid to the effects of information technology on the market s dynamic behavior

management of multiple congested conditions in unbundled operation of a power system this paper studies congestion management based on congestion pricing as may be done by an independent power system operator four main concepts are discussed congestion pricing can lead to the same solution as an optimal power flow pricing need not have cost information available good estimates of nonlinear cost coefficients are necessary and pricing for congestion management is separable from pricing for the purpose of transmission network revenue reconciliation emphasis is on the determination of sufficient information by observation of the behavior of the market to permit optimum pricing without explicit communication among parties and without generators ever being explicitly concerned about the relief of flow congestion results from simulated experiments are presented

volatility of power grids under real time pricing the paper proposes a framework for modeling and analysis of the dynamics of supply demand and clearing prices in power systems with real time retail pricing and information asymmetry characterized by passing on the real time wholesale electricity prices to the end consumers real time pricing creates a closed loop feedback system between the physical layer and the market layer of the system in the absence of a carefully designed control law such direct feedback can increase sensitivity and lower the system s robustness to uncertainty in demand and generation it is shown that price volatility can be characterized in terms of the system s maximal relative price elasticity defined as the maximal ratio of the generalized price elasticity of consumers to that of the producers as this ratio increases the system may become more volatile since new demand response technologies increase the price elasticity of demand and since increased penetration of distributed generation can also increase the uncertainty in price based demand response the theoretical findings suggest that the architecture under examination can potentially lead to increased volatility this study highlights the need for assessing architecture systematically and in advance in order to optimally strike the trade offs between volatility robustness and performance metrics such as economic efficiency and environmental efficiency

robust inventory management with stock out substitution abstract stock out substitution is a well documented phenomenon that occurs when customers seek a different product as a substitute for their first choice item if it runs out of stock we consider a single period inventory model with limited information regarding the external demands i e mean variance and covariance and focus on identifying the inventory levels that maximize the worst case expected profit we formulate a two stage optimization model the second stage characterizes the worst case joint demand distribution by treating the inventory levels as input parameters and the first stage identifies the optimal inventory levels based on the results of the second stage the closed form solution of the second stage problem is analytically intractable except for two special cases we develop closed form solutions for these two special cases and use them to develop a heuristic for the general case an extensive numerical study over a wide range of parameters indicates that the performance of the heuristic that we develop is nearly optimal we also provide insights into the effects of demand correlation substitution rate and other parameters on the optimal worst case expected profit of the system

robust optimal policies of production and inventory with uncertain returns and demand abstract we consider an inventory and production planning problem with uncertain demand and returns in which the product return process is integrated into the manufacturing process over a finite planning horizon we first propose an inventory control model for the return and remanufacturing processes with consideration of the uncertainty of the demand and returns then a robust optimization approach is applied to deal with the uncertainty of the problem through formulating a robust linear programming model moreover properties on the robust optimization model are studied and an equivalent robust optimization model based on duality theory is obtained which allows the solutions to be derived more efficiently finally we provide a set of numerical examples to verify the effectiveness of the approach and analyze the effects of the key parameters on the solutions

studies of bilateral contracts with respect to steady state security in a deregulated environment under a deregulated environment electricity consumers and suppliers will be permitted to establish various bilateral service contracts the transmission company however will only have to honour and execute these bilateral contracts as far as the system design and operating conditions permit a fundamental question is to what extent the system security could affect these contracts and what kinds of system reinforcements will be required to meet the future contract needs this paper describes a series of studies modelling the bilateral contracts by using a transaction matrix t the concept of the transaction matrix is to expand the conventional load flow variables such as generations pg and loads pd into a 2 dimensional matrix t each element of t namely t sub ij corresponds to a bilateral contract between a supplier pg sub i and consumer pd sub j a generalized linear programming formulation is then proposed to solve various system operation and planning problems under a deregulated environment subjected to the steady state security constraints e g generation and line flow limits examples are presented to illustrate how to use this formulation to maximize any bilateral contract individual generation or groups of generations or to minimize the necessary correction needed for a proposed transaction matrix t sup 0 in order to comply with the security requirements other studies such as the use of monte carlo methods to study the behaviour of random bilateral contracts are also presented and discussed

a robust optimization approach to inventory theory we propose a general methodology based on robust optimization to address the problem of optimally controlling a supply chain subject to stochastic demand in discrete time this problem has been studied in the past using dynamic programming which suffers from dimensionality problems and assumes full knowledge of the demand distribution the proposed approach takes into account the uncertainty of the demand in the supply chain without assuming a specific distribution while remaining highly tractable and providing insight into the corresponding optimal policy it also allows adjustment of the level of robustness of the solution to trade off performance and protection against uncertainty an attractive feature of the proposed approach is its numerical tractability especially when compared to multidimensional dynamic programming problems in complex supply chains as the robust problem is of the same difficulty as the nominal problem that is a linear programming problem when there are no fixed costs and a mixed integer programming problem when fixed costs are present furthermore we show that the optimal policy obtained in the robust approach is identical to the optimal policy obtained in the nominal case for a modified and explicitly computable demand sequence in this way we show that the structure of the optimal robust policy is of the same base stock character as the optimal stochastic policy for a wide range of inventory problems in single installations series systems and general supply chains preliminary computational results are very promising

coping with risk management and fill rate in the loss averse newsvendor model abstract in this paper we introduce the cvar conditional value at risk measure to hedge against the risks for the loss averse newsvendor we derive the optimal order quantities for the loss averse newsvendor to maximize the cvar objective of utility with and without the shortage cost respectively it is shown that when shortage cost is not considered an increase in the degree of loss aversion leads to a decrease in the fill rate therefore the newsvendor should strike a balance between the two conflicting targets in selecting the optimal order quantity when the shortage cost is taken into account and sufficiently large it is proved that an increase in the degree of loss aversion leads to an increase in the fill rate to manage both of the two targets the newsvendor should order more items in this case our sensitivity analysis further verifies that high risk implies high return and low risk comes with low return based on the analysis some management insights for the risk management of the loss averse newsvendor are presented

optimal decisions for the loss averse newsvendor problem under cvar abstract most of the existing literature about the newsvendor problem mainly focused on choosing an optimal order quantity to maximize the expected profit of a risk neutral newsvendor however some studies pointed out that in practice managers decisions as to order quantities always deviate from the profit maximization order quantity which is referred to as decision bias in the newsvendor problem then many studies introduced other preferences rather than risk neutrality of the newsvendor to explain such a decision bias this paper thus introduces loss aversion to the research of the newsvendor decision bias we propose a new definition to the loss averse newsvendor problem legacy loss which is defined either as the loss for excess order or the shortage penalty for lost sales when sales time is due the optimal decisions of a loss averse newsvendor are obtained through the following three ways i minimizing the expected legacy loss ii minimizing cvar of legacy loss by combining the cvar measure in risk management iii minimizing the combination of expected legacy loss and cvar of legacy loss and are compared with other existing results besides we present some properties of the optimal decisions as well as relations among them some numerical examples are given to illustrate the obtained results

cost of wheeling methodologies the cost of wheeling and the methodology by which it is computed is a high priority problem throughout the power industry due to the growth in transmission facilities the cost differentials between utility companies and the dramatic growth in nonutility generation capacity this paper contains descriptions and summaries of computational procedures and data requirements of four embedded cost methodologies two long run incremental cost methods and the short run marginal cost method four methodologies are also presented for allocating the wheeling costs among a number of wheels when simultaneously present on a company s system as required for the standard long run incremental cost method

minimax distribution free procedure with backorder price discount abstract the inventory models analyzed in this paper explore the problem in which the lead time and ordering cost reductions are inter dependent in the continuous review inventory model with backorder price discount the objective is to minimize total related cost by simultaneously optimizing the order quantity reorder point lead time and backorder price discount moreover we assume that the mean and variance of the lead time demand are known but its probability distribution is unknown we apply a minimax distribution free procedure to find the optimal solution and three numerical examples are given to illustrate the results

handle with care a primer on incentive regulation regulators increasingly rely upon incentive regulation as a substitute or refinement of traditional cost of service regulation focusing on incentive regulation in the us utility industry this article first identifies four desirable attributes for incentive mechanisms it develops a taxonomy of the types of mechanisms that are available identifies the issues that arise in the design and evaluation of these mechanisms and then closes with a discussion of the risks associated with various mechanisms

the study of the impacts of potential coalitions on bidding strategies of gencos the paper studies the impacts of potential coalitions on bidding strategies of gencos in a pool based power market the generator under consideration can form any potential coalition with other generators subgroups are then formed and each of these subgroups consists of some members which coordinate their bidding strategies to achieve a common goal noncooperative gaming applies among all the subgroups while cooperative gaming applies among the members in each subgroup by implementation of bids sensitivities the paper presents an algorithm for the members in each coalition subgroup to obtain optimal bids which essentially is based on interior point optimal power flow ipopf model a priority list produced after optimal bids are found for all the potential combinations of coalition is used by the generator under consideration to bargain with members on the list the algorithm and model are tested by the ieee 30 bus system and numerical results are presented

the incentive subsidy for government support of private r d abstract an incentive subsidy policy for subsidizing private rd in addition the firm receives a small fraction of the resulting invention s social value this mechanism comes close to being perfectly incentive compatible the firm chooses itself whether it wants to be covered under the incentive subsidy generally the firm s choice coincides with three social aims first a project that the firm would conduct in any case should not be subsidized second a project should not be subsidized if its social value is negative third the subsidy should provide an incentive to maximize a project s social value using a simulation over a range of hypothetical research projects it is shown that the efficiency of conditional loans and normal grants declines drastically as the government s information about project parameters becomes poorer while the incentive subsidy performs consistently well

electricity tariffs under imperfect knowledge of participant benefits the authors consider the problem of establishing tariffs for electrical energy under uncertainty about the value of the energy to the participants a tariff update that achieves welfare maximization asymptotically through successive approximations to the ideal tariff is proposed the successive update of the tariff avoids the need for accurate a priori knowledge of electricity system demand and generation as a function of price the key results are a tariff update algorithm and a proof of local convergence two necessary steps for implementation of practical responsive pricing

agent based modeling in electrical energy markets using dynamic bayesian networks due to uncertainties in generation and load optimal decision making in electrical energy markets is a complicated and challenging task participating agents in the market have to estimate optimal bidding strategies based on incomplete public information and private assessment of the future state of the market to maximize their expected profit at different time scales in this paper we present an agent based model to address the problem of short term strategic bidding of conventional generation companies gencos in a power pool based on the proposed model each genco agent develops a private probabilistic model of the market using dynamic bayesian networks employs an online learning algorithm to train the model sparse bayesian learning and infers the future state of the market to estimate the optimal bidding function we show that by using this multiagent framework the agents will be able to predict and adapt to approximate nash equilibrium of the market through time using local reasoning and incomplete publicly available data the model is implemented in matlab and is tested on four test case systems two generic systems with 5 and 15 genco agents and two ieee benchmarks 9 bus and 30 bus systems both the day ahead da and hour ahead ha bidding schemes are implemented the results show a drop in market power in the 15 agent system compared to 5 agent system along with a pareto superior equilibrium in the ha scheme compared to the da scheme which corroborates the validity of the proposed decision making model also the simulations show that introduction of an ha decision making stage as an uncertainty containment tool leads to a more stable and less volatile price signal in the market which consequently results in flatter and improved profit curves for the gencos

convergence of volatile power markets with price based demand response price based demand response dr program is a mechanism for encouraging electricity consumers to dynamically manage their energy consumptions in response to time varying electricity prices and thereby reduce peak electricity demands and alleviate the pressure to power systems however it brings additional dynamics and new challenges to the real time supply and demand balance specifically if real time price based dr programs are widely deployed in the future price sensitive dr load levels would constantly change in response to dynamic real time prices which will impact the economic dispatch ed schedule and in turn affect electricity market clearing prices this paper adopts two methods for examining the impacts of different dr price elasticity characteristics and dr participation levels on the convergence of volatile power market a closed loop iterative simulation method and a non iterative method based on the contraction mapping theorem in this paper convergence refers to the fact that load and or price values will finally converge to a fixed point after a finite number of iterations between the ed problem and the price sensitive dr load adjustment five price sensitive dr performance function categories are used to simulate different nonlinear price elasticity characteristics of dr loads numerical studies illustrate how the convergence status of power markets will be affected by the nonlinear price elasticity dr curves the dr penetration levels and the capacity limits of generating units

combined pool bilateral dispatch part ii curtailment of firm and nonfirm contracts this paper deals with the dispatch of power networks under mixed pool bilateral trading the major questions that are examined are the following 1 to what degree does the relative level of pool versus bilateral trading influence performance in terms of individual power levels costs prices and revenues 2 what is the comparative performance of mixed trading with firm and nonfirm bilateral contracts under various curtailment strategies 3 is the revenue derived from the pool and bilateral trading consistent with the corresponding unbundled costs the above questions are sequentially addressed in separate parts of this three part paper the eventual goal of these results is to help generator and load serving entities choose appropriate relative levels of pool versus bilateral trades while considering risk economic performance and physical constraints in part ii two types of bilateral contracts firm and nonfirm are introduced together with their respective curtailment and noncurtailment bids the optimal power flow problem from part i is now modified to accommodate this new type of operation technical and economical performance measures defined in part i namely generation revenues from bilateral and pool sales pool demand payments plus generation and load expenditures to cover transmission loss and congestion management attributed to bilateral exchanges are also used here together with revenues from contract curtailment and expenditures due to noncurtailment bidding simulation results illustrate the effects of firm and nonfirm contracts and their bidding strategies on the relative levels of pool bilateral trading as well as on economic performance of market participants

the distribution free newsboy problem extensions to the shortage penalty case abstract in the classical newsboy problem no cost is assumed if the ordered quantity is less than the demand however in reality failure to meet demand is always associated with a penalty the aim of this work is to extend the analysis of the distribution free newsboy problem to the case when shortage cost is taken into consideration the analysis is based on the assumption that only the mean and variance of demand are known but its particular probability distribution is not a model is presented for determining both an optimal order quantity and a lower bound on the profit under the worst possible distribution of the demand the following cases are considered the single product case the fixed ordering cost case the random yield case and the resource constrained multi product case

transmission analysis by nash game method this paper describes an open access transmission method for maximizing profits in a power system the proposed method is based on the nash bargaining game for power flow analysis in which each transaction and its optimal price are determined to optimize the interests of individual parties transmission losses are considered by the proposed method and test cases and results are discussed to present the merits of the proposed method

the newsvendor problem review and directions for future research in this paper we review the contributions to date for analyzing the newsvendor problem our focus is on examining the specific extensions for analyzing this problem in the context of modeling customer demand supplier costs and the buyer risk profile more specifically we analyze the impact of market price marketing effort and stocking quantity on customer demand how supplier prices can serve as a coordination mechanism in a supply chain setting integrating alternative supplier pricing policies within the newsvendor framework and how the buyer s risk profile moderates the newsvendor order quantity decision for each of these areas we summarize the current literature and develop extensions finally we also propose directions for future research

expected value of distribution information for the newsvendor problem this paper extends previous work on the distribution free newsvendor problem where only partial information about the demand distribution is available more specifically the analysis assumes that the demand distribution f belongs to a class of probability distribution functions pdf f with mean and standard deviation while previous work has examined the expected value of distribution information evdi for a particular order quantity and a particular pdf f this paper aims at computing the maximum evdi over all f f for any order quantity in addition an optimization procedure is provided to calculate the order quantity that minimizes the maximum evdi

decision bias in the newsvendor problem with a known demand distribution experimental evidence in the newsvendor problem a decision maker orders inventory before a one period selling season with stochastic demand if too much is ordered stock is left over at the end of the period whereas if too little is ordered sales are lost the expected profit maximizing order quantity is well known but little is known about how managers actually make these decisions we describe two experiments that investigate newsvendor decisions across different profit conditions results from these studies demonstrate that choices systematically deviate from those that maximize expected profit subjects order too few of high profit products and too many of low profit products these results are not consistent with risk aversion risk seeking preferences prospect theory preferences waste aversion stockout aversion or the consequences of underestimating opportunity costs two explanations are consistent with the data one subjects behave as if their utility function incorporates a preference to reduce ex post inventory error the absolute difference between the chosen quantity and realized demand two subjects suffer from the anchoring and insufficient adjustment bias feedback and training did not mitigate inventory order errors we suggest techniques to improve decision making

large scale integration of deferrable demand and renewable energy sources we present a stochastic unit commitment model for assessing the impacts of the large scale integration of renewable energy sources and deferrable demand in power systems in terms of reserve requirements we analyze three demand response paradigms for assessing the benefits of demand flexibility the centralized co optimization of generation and demand by the system operator demand bids and the coupling of renewable resources with deferrable loads we motivate coupling as an alternative for overcoming the drawbacks of the two alternative demand response options and we present a dynamic programming algorithm for coordinating deferrable demand with renewable supply we present simulation results for a model of the western electricity coordinating council

bidding strategies in oligopolistic dynamic electricity double sided auctions in this paper the problem of developing bidding strategies in oligopolistic dynamic electricity double sided auctions is studied we model electricity double sided auctions as dynamic systems and use nash cournot strategies for the market participants generating firms and load serving entities through simulation studies we compare the efficiency and competitiveness of electricity double sided auctions to those of electricity supplier only auctions using the developed bidding strategies

multi product newsvendor problem with value at risk considerations abstract we consider the single period stochastic inventory newsvendor problem with downside risk constraints the aim in the classical newsvendor problem is maximizing the expected profit this formulation does not take into account the risk of earning less than a desired target profit or losing more than an acceptable level due to the randomness of demand we utilize value at risk var as the risk measure in a newsvendor framework and investigate the multi product newsvendor problem under a var constraint to this end we first derive the exact distribution function for the two product newsvendor problem and develop an approximation method for the profit distribution of the n product case n 2 a mathematical programming approach is used to determine the solution of the newsvendor problem with a var constraint this approach allows us to handle a wide range of cases including the correlated demand case that yields new results and insights the accuracy of the approximation method and the effects of the system parameters on the solution are investigated numerically

linear complementarity models of nash cournot competition in bilateral and poolco power markets two cournot models of imperfect competition among electricity producers are formulated as mixed linear complementarity problems lcps and a simple example is presented to illustrate their application the two models simulate bilateral markets the models include a congestion pricing scheme for transmission but other transmission pricing approaches can also be represented in this framework the two models differ from each other in that one has no arbitrage between nodes of the network while in the other model arbitragers erase any noncost based differences in price the latter bilateral model turns out to be equivalent to a cournot model of a poolco the models differ from other cournot market models in that they include both of kirchhoff s laws via a dc approximation can include arbitragers possess unique solutions and are readily solved by efficient lcp algorithms the key assumption that permits their formulation as lcps is that each producer naively assumes that its output will not affect transmission prices

studies of bilateral contracts with respect to steady state security in a deregulated environment of electricity supply under a deregulated environment electricity consumers and suppliers will be permitted to establish various bilateral service contracts the transmission company however will only have to honour and execute these bilateral contracts as far as the system design and operating conditions permit a fundamental question is to what extent the system security could affect these contracts and what kinds of system reinforcements will be required to meet the future contract needs this paper describes a series of studies modelling the bilateral contracts by using a transaction matrix t the concept of the transaction matrix is to expand the conventional load flow variables such as generations pg and loads pd into a 2 dimensional matrix t each element of t namely t sub ij corresponds to a bilateral contract between a supplier pg sub 1 and consumer pd sub j a generalized linear programming formulation is then proposed to solve various system operation and planning problems under a deregulated environment subjected to the steady state security constraints e g generation and line flow limits examples are presented to illustrate how to use this formulation to maximize any bilateral contract individual generation or groups of generations or to minimize the necessary correction needed for a proposed transaction matrix t spl deg in order to comply with the security requirements other studies such as the use of monte carlo methods to study the behaviour of random bilateral contracts are also presented and discussed it was concluded that the proposed methodology will be an effective tool to study the intricate relationships between the bilateral contracts and system security

effects of energy performance certificates on investment a quasi natural experiment approach incomplete information may be one reason why some households do not invest in energy efficiency even though it would benefit them to do so energy performance certificates epcs have been promoted

evaluation of market rules using a multi agent system method the california energy crisis in 2000 2001 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation due to the complexity of the market structure strategic interaction between the participants and the underlying physics it is difficult to fully evaluate the implications of potential changes to market rules this paper presents a flexible and integrative method to assess market designs through agent based modeling realistic simulation scenarios are constructed for evaluation of the proposed pjm like market power mitigation rules of the california electricity market simulation results show that in the absence of market power mitigation generation company genco agents facilitated by q learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark the incorporation of pjm like local market power mitigation rules is shown to be effective in suppressing the exercise of market power