on the solution of revenue and network constrained day ahead market clearing under marginal pricing part ii case studies this paper presents the numerical analysis of the bilevel programming approach for revenue and network constrained market clearing developed in its companion paper the impact of minimum revenue conditions and minimum declared profits on generation and consumption levels as well as on locational marginal prices for energy is examined in detail through three case studies first the results from an illustrative example including minimum revenue conditions are comprehensively analyzed the second case study is based on the ieee reliability test system and considers minimum declared profits in the third case study a modified version of the ieee 118 bus system is tested while accounting for minimum revenue conditions in addition the computational behavior of the proposed approach is illustrated with several case studies including the ieee 300 bus system numerical results show the effectiveness of the proposed approach to handle revenue constraints as well as its superiority over the heuristic currently implemented in the iberian electricity market moreover simulations reveal that unlike previous works in the literature generation revenue constraints can be precisely incorporated in day ahead market clearing while explicitly considering the standard economic dispatch based marginal pricing scheme and without requiring price uplifts

bidding strategies for electricity producers in a competitive electricity marketplace this paper presents a methodology for the development of bidding strategies for electricity producers in a competitive electricity marketplace initially the problem is modeled as a two level optimization problem where at the first level a market participant tries to maximize his expected profit under the constraint that at the second level an independent system operator dispatches power solving an optimal power flow problem that minimizes total system cost it is assumed that each supplier bids a linear supply function and chooses his bidding strategy based on probabilistic estimates of demand and rival behavior monte carlo simulation is used to calculate the expected profit and genetic algorithms are employed to find the optimal strategy subsequently the formulation is expanded to account for different market participants risk profiles it is shown that risk aversion may influence the optimal bidding strategy of an individual

agricultural land relations in the developing world in this paper we draw on a number of methodological approaches which have been used to explain land relations tenancy sharecropping and interlinking distress sales dualistic land ownership distributions classes and land reform and their variations over space and time we indicate that the explanatory power of theories on land relations hinges on the complexity market imperfections and distortions admitted in the analysis

revenue adequate bidding strategies in competitive electricity markets energy trading in a competitive electricity market can be modeled as a two level optimization at the top level a centralized economic dispatch ced uses a priority list method to solve the fundamental problem of reliable market clearing with price discovery the lower level consists of a set of decentralized bidding db subproblems the db model uses a self unit scheduling simulator based on parametric dynamic programming to produce hourly bid curves for the central dispatch coordinator unit operating constraints and costs such as the unit minimum up and minimum down times ramp rates and the unit start up no load and sunk capital costs are internalized in the bid curves through the simulator a special algorithm is presented to solve the revenue adequacy problem for marginal units both ced and db models are based on the revenue maximization in contrast with the cost minimization criteria used in the conventional unit commitment uc the proposed method has been tested in a study case and some interesting results have been demonstrated

risk based electricity procurement for large consumers in a competitive electricity market consumers seek strategies to procure their energy needs from different resources pool bilateral contracts and their own generation facilities at minimum cost while controlling the risk in this paper a novel method is proposed to address the electricity procurement problem of large consumers using the concept of information gap decision theory the method can be used as a tool for assessing the risk levels considering whether a large consumer is risk taking or risk averse regarding its midterm procurement strategies in the proposed method procurement decisions are evaluated by means of two criteria the first criterion is the robustness of the decision against experiencing high procurement costs and the second one is the opportunity of taking advantage of low procurement costs the pool price is considered an uncertain variable and it is assumed that the large consumer has an estimate of the prices in this study two models of uncertainty are addressed for the pool price based on the concept of weighted mean squared error using a variance covariance matrix and the expected procurement cost is modeled using a joint normal probability distribution function a case study illustrates the working of the proposed technique

offering strategies and simulation of multi item iterative auctions of energy contracts the objective of this work is threefold we firstly present an optimization model for a price taker hydrothermal generation company genco to devise bidding strategies in multi item iterative auctions of long term contracts the bidding model calculates a bidder s best response function which takes into account the key issues on the auctioned contracts such as its time horizon the risk factors that affect the future contract outcomes interdependence between auctioned products and the agents risk profile the risk profile of the gencos are represented as piecewise linear utility functions and a practical specification approach is proposed we finally present a simulator of a uniform pricing and iterative multi item contract auction where the set of auction rules is implemented and the optimization model developed is used to determine the gencos s best responses at each auction round the simulator enables auctioneers and generators to estimate the auction s competitive equilibrium price and to study the auction dynamics a real multiproduct descending clock auction is simulated for the brazilian power system under the proposed bidding scheme

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

an ordinal optimization based bidding strategy for electric power suppliers in the daily energy market the deregulation and reconstruction of the electric power industry worldwide raises many challenging issues related to the economic and reliable operation of electric power systems traditional unit commitment or hydrothermal scheduling problems have been integrated with generation resource bidding but the development of optimization based bidding strategies is only at a very preliminary stage this paper presents a bidding strategy based on the theory of ordinal optimization that the ordinal comparisons of performance measures are robust with respect to noise and modeling error and the problems become much easier if the optimization goal is softened from asking for the best to good enough solution the basic idea is to use an approximate model that describes the influence of bidding strategies on the market clearing prices mcp a nominal bid curve is obtained by solving optimal power generation for a given set of mcps via lagrangian relaxation then n bids are generated by perturbing the nominal bid curve the ordinal optimization method is applied to isolate a good enough set s that contains some good bids with high probability by performing rough evaluation the best bid is then selected by solving full hydrothermal scheduling or unit commitment problems for each of the bids in s using ordinal optimization approach we are able to obtain a good enough bidding strategy with reasonable computational effort numerical results using historical mcps from the california market and a generation company with 10 units show that the ordinal optimization based method is efficient

price taker offering strategy in electricity pay as bid markets the recent increase in the deployment of renewable energy sources may affect the offering strategy of conventional producers mainly in the balancing market the topics of optimal offering strategy and self scheduling of thermal units have been extensively addressed in the literature the feasible operating region of such units can be modeled using a mixed integer linear programming approach and the trading problem as a linear programming problem however the existing models mostly assume a uniform pricing scheme in all market stages while several european balancing markets e g in germany and italy are settled under a pay as bid pricing scheme the existing tools for solving the trading problem in pay as bid electricity markets rely on nonlinear optimization models which combined with the unit commitment constraints result in a mixed integer nonlinear programming problem in contrast we provide a linear formulation for that trading problem then we extend the proposed approach by formulating a two stage stochastic problem for optimal offering in a two settlement electricity market with a pay as bid pricing scheme at the balancing stage the resulting model is mixed integer and linear the proposed model is tested on a realistic case study against a sequential offering approach showing the capability of increasing profits in expectation

genetic algorithm evolution of utility bidding strategies for the competitive marketplace this paper describes an environment in which distribution companies discos and generation companies gencos buy and sell power via double auctions implemented in a regional commodity exchange the electric utilities profits depend on the implementation of a successful bidding strategy in this research a genetic algorithm evolves bidding strategies as gencos and discos trade power a framework in which bidding strategies may be tested and modified is presented this simulated electric commodity exchange can be used offline to predict whether bid strategies will be profitable and successful it can also be used to experimentally verify how bidding behavior affects the competitive electric marketplace

property rights and the political organization of agriculture we propose a general equilibrium model where the economic organization of agriculture and the political equilibrium determining the security of property rights are jointly determined in particular because the form of organization may affect the probability and distribution of benefits from future property challenges it may be shaped in anticipation of this impact property rights security may then be secured at the expense of economic efficiency the model provides a framework for understanding why in some contexts land is redistributed primarily via land sales and tenancy markets but via politics and conflict in others we test some implications of the theory using a five decade panel dataset that traces changes in the extent of tenancy and tenancy reform across 15 indian states

history institutions and economic performance the legacy of colonial land tenure systems in india we analyze the colonial land revenue institutions set up by the british in india and show that differences in historical property rights institutions lead to sustained differences in economic outcomes areas in which proprietary rights in land were historically given to landlords have significantly lower agricultural investments and productivity in the post independence period than areas in which these rights were given to the cultivators these areas also have significantly lower investments in health and education these differences are not driven by omitted variables or endogeneity problems they probably arise because differences in historical institutions lead to very different policy choices

wealth weather risk and the composition and profitability of agricultural investments despite the growing evidence that farmers in low income environments are risk averse there has been little empirical evidence on the importance of risk in shaping the actual allocation of production resources among farmers differentiated by wealth the authors use panel data on investments in rural india to examine how the composition of productive and nonproductive asset holdings varies across farmers with different levels of total wealth and across farmers facing different degrees of weather risk income variability is a prominent feature of the experience of rural agents in low income countries the authors report evidence based on measures of rainfall variability that the agricultural investment portfolio behavior of farmers in such settings reflects risk aversion due evidently to limitations on consumption soothing mechanisms such as crop insurance or credit markets the authors results suggest that uninsured weather risk is a significant cause of lower efficiency and lower average incomes a one standard deviation decrease in weather risk measured by the standard deviation of the timing of the rainy season would raise average profits by up to 35 percent among farmers in the lowest wealth quartile moreover rainfall variability induces a more unequal distribution of average incomes for a given distribution of wealth wealthier farmers are willing to absorb significant risk without giving up profits to reduce production risk smaller farmers have to invest their limited wealth in ways that reduce their exposure to risk at the cost of lower profit rates the authors found that at high levels of rainfall variability differences in rates of profit per unit of agricultural assets were similar across classes of wealth but over the sample range of rainfall variability these rates of profit were always higher for the poorer farmers than for the wealthier ones suggesting that the disadvantages of small farmers in risk diffusion are more than offset by their labor cost advantage

self scheduling of large consumers with second order stochastic dominance constraints this paper develops a decision making framework for mid term scheduling problems of the large industrial consumers the proposed approach is based upon the recently introduced class of stochastic programming problems established by the concept of second order stochastic dominance ssd in this paper it is assumed that the electricity price and the rate of availability unavailability of the generating unit forced outage rate are the sources of uncertainty in the decision making problem in the developed ssd constrained stochastic programming problem the consumer risk is managed by minimization of the pool procurement as the objective function and economic issues e g cost minimization are considered in the sd constraint furthermore while most approaches optimize the cost subject to an assumed demand profile our method enforces the electricity consumption to follow an optimum profile for mid term time scheduling i e three months 12 weeks so that the total production will remain constant simulation results for a typical cement factory as an industrial consumer and comparison to a mean risk approach with cvar risk measure revealed the interesting results and benefits of the proposed approach

price maker economic bidding in two settlement pool based markets the case of time shiftable loads in this paper a new scenario based stochastic optimization framework is proposed for price maker economic bidding in day ahead and real time markets the presented methodology is general and can be applied to both demand and supply bids that is no restrictive assumptions are made on the characteristics of the pool and its agents however our focus is on the operation of time shiftable loads with deadlines because they play a central role in creating load flexibility and enhancing demand response and peak load shaving programs both basic and complex time shiftable load types are addressed where the latter includes time shiftable loads that are uninterruptible have per time slot consumption limits or ramp constraints or comprise several smaller time shiftable subloads four innovative analytical steps are presented in order to transform the originally nonlinear and hard to solve price maker economic bidding optimization problem into a tractable mixed integer linear program accordingly the global optimal solutions are found for the price and energy bids within a relatively short amount of computational time a detailed illustrative case study along with multiple case studies based on the california energy market data are presented it is observed that the proposed optimal price maker economic bidding approach outperforms optimal price maker self scheduling as well as even load distribution

long run impacts of land regulation evidence from tenancy reform in india agricultural tenancy reforms have been widely enacted but evidence on their long run impact remains limited in this paper we provide such evidence by exploiting the quasi random assignment of linguistically similar areas to different south indian states that subsequently varied in tenancy regulation policies given imperfect credit markets the impact of tenancy reform should vary by household wealth status allowing us to exploit historic caste based variation in landownership thirty years after the reforms land inequality is lower in areas that saw greater intensity of tenancy reform but the impact differs across caste groups tenancy reforms increase own cultivation among middle caste households but render low caste households more likely to work as daily agricultural laborers at the same time agricultural wages increase these results are consistent with tenancy regulations increasing land sales to relatively richer and more productive middle caste tenants but reducing land access for poorer low caste tenants

are the poor less well insured evidence on vulnerability to income risk in rural china the authors test how well consumption is insured against income risk in a panel of sampled households in rural china they estimate the risk insurance models by generalized method of moments treating income and household size as endogenous insurance exists for all wealth groups although the hypothesis of perfect insurance is universally rejected those in the poorest wealth decile are the least well insured with 40 percent of an income shock being passed on to current consumption by contrast consumption by the richest third of households is protected from almost 90 percent of an income shock the extent of insurance in a given wealth stratum varies little between poor and nonpoor areas

strategic bidding under uncertainty a binary expansion approach this work presents a binary expansion be solution approach to the problem of strategic bidding under uncertainty in short term electricity markets the be scheme is used to transform the products of variables in the nonlinear bidding problem into a mixed integer linear programming formulation which can be solved by commercially available computational systems the be scheme is applicable to pure price pure quantity or joint price quantity bidding models it is also possible to represent transmission networks uncertainties scenarios for price quantity plant availability and load financial instruments capacity reinforcement decisions and unit commitment the application of the methodology is illustrated in case studies with configurations derived from the 80 gw brazilian system

empowerment and efficiency tenancy reform in west bengal the paper analyzes the effect of agricultural tenancy laws offering security of tenure to tenants and regulating the share of output that is paid as rent on farm productivity theoretically the net impact of tenancy reform is shown to be a combination of two effects a bargaining power effect and a security of tenure effect analysis of evidence on how contracts and productivity changed after a tenancy reform program was implemented in the indian state of west bengal in the late 1970s suggests that tenancy reform had a positive effect on agricultural productivity there

a robust linear approach for offering strategy of a hybrid electric energy company this paper presents a new approach for determining the day ahead bidding strategies of a large scale hybrid electric energy company the company has both energy generation and energy retailing businesses in a competitive electricity market demand response programs are also considered in the retail side of the company in order to hedge the risk of participation in wholesale market this paper introduces a max min bilevel mathematical programming with equilibrium constraint model for offering a strategy that manages the risk of uncertain forecasted rivals bids by robust optimization the max min bilevel model is converted to its equivalent single level optimization using karush kuhn tucker optimality conditions the duality theory is utilized to find the equivalent ordinary maximization model of the max min problem strong duality theory and big m method are also used to linearize the final model of offering strategy applicability of the proposed approach is shown by implementing it on the ieee 118 bus test system

testing market integration a model of spatial price differentials for a tradable good is proposed which avoids the inferential dangers of received methods using static price correlations the proposed method also extracts more information on the causes of price differentials from the same data the method is illustrated using monthly rice price data for postindependence bangladesh including the very substantial regional price shocks during the 1974 famine impediments to market integration are indicated

multimarket optimal bidding for a power producer this paper considers a profit maximizing thermal producer that participates in a sequence of spot markets namely day ahead automatic generation control agc and balancing markets the producer behaves as a price taker in both the day ahead market and the agc market but as a potential price maker in the volatile balancing market the paper provides a stochastic programming methodology to determine the optimal bidding strategies for the day ahead market uncertainty sources include prices for the day ahead and agc markets and balancing market linear price variations with the production of the thermal producer results from a realistic case study are reported and analyzed conclusions are duly drawn

distinguishing between equilibrium and integration in spatial price analysis this article introduces a new spatial price analysis methodology based on maximum likelihood estimation of a mixture distribution model incorporating price transfer cost and trade flow data this method permits differentiation between market integration and competitive market equilibrium and derivation of intuitive measures of intermarket tradability competitive market equilibrium perfect integration segmented equilibrium and segmented disequilibrium one can also use these estimates to derive semiparametric measures of time varying regime probabilities to track changing market conditions an application to trade in soybean meal among pacific rim economies demonstrates the usefulness of the method copyright 2002 oxford university press

environment technology and the social articulation of risk in west african agriculture two preoccupations are not mutually exclusive superficially they share the common concern that liberalization is insufficient to resolve the subsaharan food crisis at a deeper level the two preoccupations are more intimately interrelated via the correspondence that links initial wealth to risk exposure and to behavior in both production and asset accumulation a number of recent empirical studies of risk in low income countries find that households are able to employ their accumulated assets to smooth consumption in the face of adverse agricultural production shocks 3 missing from these studies is explicit attention to the fact that the effective risk from which households insulate consumption is not that of production shocks directly but of those shocks as socially articulated by institutions and property rights this article explores the creation and distribution of effective risk estimating how environment technology and social factors interact to construct it endogenously 4 put differently this article develops the notion that the risk from which households ex post try to insulate consumption is not an immutable natural or technical feature of the landscape as michael watt s contrast between precolonial and colonial nigeria forcefully demonstrates the effective risk presented by an unchanged set of environmental and technical circumstances can

exact welfare measurement for producers under uncertainty many useful results have been derived for different characterizations of uncertainty in the theory of the firm for example sandmo batra and ullah pope and kramer blair however the limited literature available on producer welfare measurement under uncertainty pope chavas and just pope and chavas just hueth and schmitz is pessimistic about the possibilities for deriving exact welfare measures from ex ante supply functions the only exception is pope and chavas who derive error bounds for the use of producer s surplus as an approximation for true welfare change that are analogous to willig s bounds for consumer s surplus as an approximation of compensating or equivalent variation however these results are presumably subject to the same shortcomings noted by hausman and amended by haveman gabay and andreoni for willig s error bounds even though compensating or equivalent variation is approximated well a poor approximation of deadweight loss may result pope chavas and just show that the ex ante supply function derived from an uncertainty model is generally not sufficient for determining true welfare change except in the special case of constant absolute risk aversion because decisions depend on the firm s wealth for nonneutral risk preferences a parameter price change induces a wealth effect in addition to an ordinary output effect thus for exact welfare measurement under price uncertainty the unobservable compensated constant expected utility supply function is needed newbery and stiglitz among others have shown that the area above an expected supply function is generally not a valid welfare measure

acreage decisions under risk the case of corn and soybeans an acreage supply response model is developed under expected utility maximization the resulting framework is used to specify and estimate a system of risk responsive acreage equations for corn and soybeans in the united states particular attention is given to the truncation effects of government price supports on the distribution of corn and soybean prices also a wealth variable is included in the acreage equations the empirical results indicate that risk and wealth variables play an important role in cornsoybean acreage decisions the analysis also shows that cross commodity risk reduction is important in acreage allocation decisions

optimal response of a power generator to energy agc and reserve pool based markets the electric power industry all over the world is undertaking major regulatory and operational changes the understanding of power supply as a public service is being replaced by the notion that competitive markets constitute a more appropriate framework to supply reliable and cheap electric energy to consumers as mandated by ferc orders 888 and 889 this paper considers simultaneously energy agc and reserve markets in a pool framework it provides a tool to enable a power generator to determine optimally its degree of involvement in each one of these markets a real world case study is analyzed and results are presented

application of games with incomplete information for pricing electricity in deregulated power pools the authors present a game theory approach to the problem of pricing electricity in deregulated marketplaces they assume that an independent operator receives bids by pool participants and defines transactions among participants by looking for the minimum price that satisfies the demand in the pool the competition among pool participants is modeled as a noncooperative game with incomplete information they assume that each pool participant knows its own operation costs but does not know his opponents operation costs the game with incomplete information is transformed into a game with complete but imperfect information and solved using the nash equilibrium idea the approach presented in this paper is geared towards providing support for pricing electricity in deregulated pools

nash equilibrium bidding strategies in a bilateral electricity market this paper examines bidding strategies in a bilateral market in which generating companies submit bids to loads a load accepts electricity delivery from the generator with the lowest bid at its bid price as long as this price is not higher than the load s willingness to pay necessary and sufficient conditions of nash equilibrium ne bidding strategy are derived based on a generic generating cost matrix and the loads willingness to pay vector the study shows that in any ne efficient allocation is achieved furthermore all nash equilibria are revenue equivalent for the generators based on the necessary and sufficient conditions this problem is formulated as an optimal assignment problem network optimization techniques are applied to calculate ne bid prices for the generators

insurance market efficiency and crop choices in pakistan this paper tests the efficiency of insurance markets in the pakistan punjab by examining how crop choices are affected by the presence of price and yield risk we estimate reduced form and structural models of crop choices although we cannot reject the hypothesis that village members efficiently share risk among themselves production choices are shown to depend on risk existing risk sharing and selfinsurance mechanisms thus imperfectly protect punjab farmers against village level shocks results also indicate that households respond to consumption price risk thereby suggesting that empirical and theoretical work on risk should avoid putting an exclusive emphasis on yield and output price risk

asset smoothing consumption smoothing and the reproduction of inequality under risk and subsistence constraints abstract a growing literature asks whether low wealth agents can accumulate assets over time or whether they are trapped in poverty this paper develops a stochastic dynamic programming model with endogenous asset price risk to explore savings and portfolio decisions in a resource poor environment characterized by risk and subsistence constraints optimal portfolio strategies are found to bifurcate despite divisible assets and fully rational agents wealthier agents acquire a higher yielding portfolio and pursue conventional consumption smoothing poorer agents acquire a less remunerative portfolio and pursue asset smoothing rather than consumption smoothing asset based risk coping thus results in positive correlation between initial wealth and portfolio rate of return

land acquisition for industrialization and compensation of displaced farmers this paper addresses the question of how farmers displaced by acquisition of agricultural land for the purpose of industrialization ought to be compensated prior to acquisition the farmers are leasing in land from a private owner or local government with a legally mandated sharecropping contract compensation rules affect the decision of the landlord to sell the land ex post to an industrial developer and ex ante incentives of tenants and landlord to make specific investments in agricultural productivity efficiency considerations are shown to require farmers be over compensated in the event of conversion

impact of optimal storage allocation on price volatility in energy only electricity markets recent studies show that the fast growing expansion of wind power generation may lead to extremely high levels of price volatility in wholesale electricity markets storage technologies regardless of their specific forms e g pump storage hydro large scale or distributed batteries are capable of alleviating the extreme price volatility levels due to their energy usage time shifting fast ramping and price arbitrage capabilities in this paper we propose a stochastic bilevel optimization model to find the optimal nodal storage capacities required to achieve a certain price volatility level in a highly volatile energy only electricity market the decision on storage capacities is made in the upper level problem and the operation of strategic regulated generation storage and transmission players is modeled in the lower level problem using an extended stochastic bayesian cournot based game the south australia sa electricity market which has recently experienced high levels of price volatility and a 30 bus ieee system are considered as the case studies our numerical results indicate that 50 price volatility reduction in the sa electricity market can be achieved by installing either 430 mwh regulated storage or 530 mwh strategic storage in other words regulated storage firms are more efficient in reducing the price volatility than strategic storage firms

weekly self scheduling forward contracting and pool involvement for an electricity producer an adaptive robust optimization approach abstract this paper addresses the optimization under uncertainty of the self scheduling forward contracting and pool involvement of an electricity producer operating a mixed power generation station which combines thermal hydro and wind sources and uses a two stage adaptive robust optimization approach in this problem the wind power production and the electricity pool price are considered to be uncertain and are described by uncertainty convex sets to solve this problem two variants of a constraint generation algorithm are proposed and their application and characteristics discussed both algorithms are used to solve two case studies based on two producers each operating equivalent generation units differing only in the thermal units characteristics their market strategies are investigated for three different scenarios corresponding to as many instances of electricity price forecasts the effect of the producers approach whether conservative or more risk prone is also investigated by solving each instance for multiple values of the so called budget parameter it was possible to conclude that this parameter influences markedly the producers strategy in terms of scheduling profit forward contracting and pool involvement these findings are presented and analyzed in detail and an attempted rationale is proposed to explain the less intuitive outcomes regarding the computational results these show that for some instances the two variants of the algorithms have a similar performance while for a particular subset of them one variant has a clear superiority

modeling strategic investment decisions in spatial markets abstract markets for natural resources and commodities are often oligopolistic in these markets production capacities are key for strategic interaction between the oligopolists we analyze how different market structures influence oligopolistic capacity investments and thereby affect supply prices and rents in spatial natural resource markets using mathematical programming models the models comprise an investment stage and a supply stage in which players compete in quantities we compare three models a perfect competition and two cournot models in which the product is either traded through long term contracts or on spot markets in the supply stage tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market results may vary substantially between the different models the metallurgical coal market has recently made progress in moving away from long term contracts and more towards spot market based trade based on our results we conclude that this regime switch is likely to raise consumer rents but lower producer rents while the effect on total welfare is negligible

optimization based bidding strategies in the deregulated market with the deregulation of electric power systems market participants are facing an important task of bidding energy to an independent system operator iso this paper presents a model and a method for optimization based bidding and self scheduling where a utility bids part of its energy and self schedules the rest as in new england the model considers iso bid selections and uncertain bidding information of other market participants with appropriately simplified bidding and iso models closed form iso solutions are first obtained these solutions are then plugged into the utility s bidding and self scheduling model which is solved by using lagrangian relaxation testing results show that the method effectively solves the problem with reasonable amount of cpu time

energy storage arbitrage under day ahead and real time price uncertainty electricity markets must match real time supply and demand of electricity with increasing penetration of renewable resources it is important that this balancing is done effectively considering the high uncertainty of wind and solar energy storing electrical energy can make the grid more reliable and efficient and energy storage is proposed as a complement to highly variable renewable energy sources however for investments in energy storage to increase participating in the market must become economically viable for owners this paper proposes a stochastic formulation of a storage owner s arbitrage profit maximization problem under uncertainty in day ahead and real time market prices the proposed model helps storage owners in market bidding and operational decisions and in estimation of the economic viability of energy storage case study results on realistic market price data show that the novel stochastic bidding approach does significantly better than the deterministic benchmark

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

impact of unit failure on forward contracting a generating unit can sell its production in the pool facing the financial risk inherent to volatile pool prices alternatively it can sell its production through the futures market at comparatively stable but smaller average prices unlike the pool forward contracts involve an obligation to sell during a specified time period and if the unit fails it should buy energy from the pool to meet its futures market commitments hence taking into account its forced outage rate the unit should determine the appropriate mix of pool and futures market involvement so that its expected profit is maximized for a prespecified risk level on profit variability within this context this paper analyzes the impact of the degree of unavailability of the generating unit on its forward contracting decisions a detailed case study illustrates the analysis performed

market integration efficiency of arbitrage and imperfect competition methodology and application to u s celery this paper develops and applies a methodology to test for efficiency of interregional commodity arbitrage application of the methodology requires only time series data on prices for alternative cities regions countries or product forms yet the approach is capable of generating evidence on a number of market parameters including market integration arbitrage efficiency the magnitude of marketing margins product substitutability and competitiveness of markets estimation is based on a switching regression model with three regimes efficient arbitrage relative shortage and relative glut results from application of the model to u s celery marketing indicated significant departures from efficient arbitrage for both california and florida celery

does the law of one price really hold for commodity prices in spite of the empirical failure of the law of one price it is usually assumed that commodity prices are perfectly arbitraged at least in the long run this paper argues that this assumption is counterfactual and that much of the empirical evidence provided to support it is flawed and affected by econometric shortcomings spurious regressions nonstationarity in the data inappropriate use of first differences an alternative methodology co integration by which a long run relationship between nonstationary series can be tested is proposed tests of nonstationarity and co integration for a group of commodities show quite uniformly that the law of one price as a long run relationship fails and that deviations from the pattern are permanent

land reform and agricultural productivity in india a review of the evidence in this paper we review as well as contribute to the empirical literature on the impact of land reform on agricultural productivity in india we find that overall for all states land reform legislation had a negative and significant effect on agricultural productivity however this hides considerable variation across types of land reform as well as variation across states decomposing by type of land reform the main driver for this negative effect seems to be land ceiling legislation in contrast the effect of tenancy reform averaged across all states is insignificant there seems to be a wide range of state specific effects which suggests that focusing on average treatment effects can hide a considerable amount of heterogeneity in particular allowing a separate slope for west bengal one of the few states that implemented tenancy laws rigorously we find that land reform had a marginal positive effect relative to the rest of india

a game theoretic approach for optimal time of use electricity pricing demand for electricity varies throughout the day increasing the average cost of power supply time of use tou pricing has been proposed as a demand side management dsm method to influence user demands in this paper we describe a game theoretic approach to optimize tou pricing strategies gt tou we propose models of costs to utility companies arising from user demand fluctuations and models of user satisfaction with the difference between the nominal demand and the actual consumption we design utility functions for the company and the users and obtain a nash equilibrium using backward induction in addition to a single user type scenario we also consider a scenario with multiple types of users each of whom responds differently to time dependent prices numerical examples show that our method is effective in leveling the user demand by setting optimal tou prices potentially decreasing costs for the utility companies and increasing user benefits an increase in social welfare measure indicates improved market efficiency through tou pricing

optimal bidding scheduling and deployment of battery systems in california day ahead energy market an optimal supply and demand bidding scheduling and deployment design framework is proposed for battery systems it takes into account various design factors such as the day ahead and real time market prices and their statistical dependency as well as the location size efficiency lifetime and charge and discharge rates of the batteries utilizing second life used batteries is also considered without loss of generality our focus is on the california independent system operator iso energy market and its two available bidding options namely self schedule bidding and economic bidding while the formulated stochastic optimization problems are originally nonlinear and difficult to solve we propose a methodology to decompose them into inner and outer subproblems accordingly we find the global optimal solutions within a short amount of computational time all case studies in this paper are based on real market data

credit market constraints consumption smoothing and the accumulation of durable production assets in low income countries investments in bullocks in india in this paper we formulate and estimate a finite horizon structural dynamic model of agricultural investment behavior that incorporates the major features of low income agricultural environments income uncertainty constraints on borrowing and rental markets and the use of investment assets to generate income and smooth consumption the model is fit to longitudinal indian household data on farm profits bullock stocks and pump sets the estimated structural parameters are used to assess the effects on the life cycle accumulation of bullocks agricultural profits and welfare associated with complete markets and bullock liquidity and with second best policies that provide assured sources of income to farmers and weather insurance

optimal bidding strategies and modeling of imperfect information among competitive generators the emerging electricity market behaves more like an oligopoly than a perfectly competitive market due to special features such as a limited number of producers large investment size barrier to entry transmission constraints and transmission losses which discourage purchase from distant suppliers this makes it practicable for only a few independent power suppliers to service a given geographic region and in this imperfect market each power supplier can increase its own profit through strategic bidding the profit of each supplier is influenced to varying extents by differences in the degree of imperfection of knowledge of rival suppliers a new framework to build bidding strategies for power suppliers in an electricity market is presented in this paper it is assumed that each supplier bids a linear supply function and that the system is dispatched to minimize customer payments each supplier chooses the coefficients in the linear supply function to maximize benefits subject to expectations about how rival suppliers will bid a stochastic optimization formulation is developed and two methods proposed for describing and solving this problem a numerical example serves to illustrate the essential features of the approach and the results are used to investigate the potential market power

determinants of redistributive politics an empirical analysis of land reforms in west bengal india we investigate political determinants of land reform implementation in the indian state of west bengal using a village panel spanning 1974 1998 we do not find evidence supporting the hypothesis that land reforms were positively and monotonically related to control of local governments by a left front coalition vis vis the right centrist congress party combined with lack of commitment to policy platforms instead the evidence is consistent with a quasi downsian theory stressing the role of opportunism reelection concerns and electoral competition jel d72 013 017 q15

optimal demand bidding for time shiftable loads time shiftable loads have recently received an increasing attention due to their role in creating load flexibility and enhancing demand response and peak load shaving programs in this paper we seek to answer the following question how can a time shiftable load that itself may comprise of several smaller time shiftable subloads submit its demand bids to the day ahead and real time markets so as to minimize its energy procurement cost answering this question is challenging because of the inter temporal dependencies in choosing the demand bids for time shiftable loads and due to the coupling between demand bid selection and time shiftable load scheduling problems nevertheless we answer the above question for different practical bidding scenarios and based on different statistical characteristics of practical market prices in all cases closed form solutions are obtained for the optimal choices of the price and energy bids the bidding performance is then evaluated in details by examining several case studies and analyzing actual market price data

price maker bidding in day ahead electricity market for a retailer with flexible demands this study develops a short term planning model to determine the bidding curves on a day ahead market for a price maker retailer with flexible power demand it concerns the interactions between the spot price and the flexible demand both conditional value at risk and volume deviation risk are taken into account a numerical study using the data from the nordic electricity market is performed to investigate the influence of risk factors on the retailer s profit risk levels average spot price and total consumption three types of price elasticity are compared to show that the retailer can benefit from the flexibility in demand side in some cases the flexibility also leads to lower spot prices so that the customers in real time price based demand response can face a lower electricity price for per unit power consumption

risk constrained generation asset arbitrage in power systems a competitive generating company genco can maximize its payoff by optimizing its generation assets this paper considers the genco s arbitrage problem using stochastic price based unit commitment while considering the associated risks the genco may consider arbitrage opportunities in purchases from qualifying facilities qfs as well as simultaneous trades with spot markets for energy ancillary services fuel and emission allowance the tradeoff between maximizing expected payoffs and minimizing risks due to market price uncertainties is modeled explicitly by including the expected downside risk as a constraint the downside risk is defined as the unfulfilled profit the monte carlo simulation is applied to generate scenarios and scenario reduction techniques are applied to reduce the number of scenarios while maintaining a good approximation of the exact solution the proposed case studies illustrate the significance of arbitrage in multi commodity markets and the importance of considering the uncertainty of market prices

comprehensive bidding strategies with genetic programming finite state automata this research is an extension of the authors previous work in double auctions aimed at developing bidding strategies for electric utilities which trade electricity competitively the improvements detailed in this paper come from using data structures which combine genetic programming and finite state automata termed gp automata the strategies developed by the method described here are adaptive reacting to inputs whereas the previously developed strategies were only suitable in the particular scenario for which they had been designed the strategies encoded in the gp automata are tested in an auction simulator the simulator pits them against other distribution companies distcos and generation companies gencos buying and selling power via double auctions implemented in regional commodity exchanges the gp automata are evolved with a genetic algorithm so that they possess certain characteristics in addition to designing successful bidding strategies whose usage would result in higher profits the resulting strategies can also be designed to imitate certain types of trading behaviors the resulting strategies can be implemented directly in online trading or can be used as realistic competitors in an off line trading simulator

optimal electricity supply bidding by markov decision process the bidding decision making problem is studied from a supplier s viewpoint in a spot market environment the decision making problem is formulated as a markov decision process a discrete stochastic optimization method all other suppliers are modeled by their bidding parameters with corresponding probabilities a systematic method is developed to calculate transition probabilities and rewards a simplified market clearing system is also included in the implementation a risk neutral decision maker is assumed the optimal strategy is calculated to maximize the expected reward over a planning horizon simulation cases are used to illustrate the proposed method

testing market integration new approaches with case material from the west bengal food economy given the inferential dangers of received methods a new methodology is introduced to provide a sequence of tests using weekly spot prices to examine the dynamic relationship of market commodity prices in three locations in west bengal tests suggest that the markets are integrated but a lower degree of integration of paddy and rice prices is identified the hypothesis of full market integration is rejected structural and institutional factors which affect the specifics of performance are identified physical isolation the institutional complexity of marketing systems and contractual forms the polarisation of assets assets specificity the institutional control of information and price formation the underdevelopment of linked markets and the idiosyncratic implementation of state regulatory policy and auto regulatory responses enter the explanation

property rights and water access evidence from land titling in rural peru summary insecure land tenure and property rights are an impediment to infrastructure access and services for households in many developing countries this paper explores whether alleviating this impediment through a land titling program in rural peru is associated with improvements in household water sources as well as sanitation and electricity services the economics literature on the links between property rights and investment decisions has amassed yet due to the necessity of water for life the high fixed costs associated with water infrastructure construction and the positive externalities that can result from water provision it is not obvious how water services might respond to land tenure improvements utilizing the phased in program timing in a quasi experimental design we exploit the differences in implementation timing across space in conjunction with the differences in program impact across households that held property titles prior to the project and those that did not results from this modified difference in differences method indicate that land titling is associated with small in magnitude but statistically significant increases in water access larger gains in sanitation and electricity services are found we investigate the channels through which this improved access occurs and find evidence of investments in all three services via either government or water utilities we find evidence of individual household investment only in the case of sanitation taken together these results indicate that land titles are important but not sufficient to increase access to water and other services

a continuous strategy game for power transactions analysis in competitive electricity markets this article presents a game theory application for analyzing power transactions in a deregulated energy marketplace such as poolco where participants especially generating entities maximize their net profits through optimal bidding strategies i e bidding prices and bidding generations in this article the electricity market for power transactions is modeled as a noncooperative game with complete information where the solution is determined in a continuous strategy domain having recourse to the nash equilibrium idea in order to provide more apprehensible analysis we suggest a new hybrid solution approach employing a two dimensional graphical approach as well as an analytical method finally the proposed approach is demonstrated on a sample power system

optimal energy management of an industrial consumer in liberalized markets this paper presents an optimization model for mid term management of a thermal and electricity supply system of an industrial consumer under liberalized energy markets electricity is supplied from the electric grid or from a gas engine while thermal energy is satisfied through a boiler or the mentioned gas engine the objective is to minimize the overall annual energy supply costs in order to make optimal contracting decisions mixed integer linear programming is applied to solve the problem since binary decision and operation variables have been employed a realistic case is presented to illustrate the model capabilities

risk constrained profit maximization in day ahead electricity market the deregulation of the electricity industry has caused for the generation company genco the need of tools for measuring and managing the risk beyond the classical problem of generating unit scheduling in this paper a probabilistic framework for the problem of managing risk faced by gencos trading in day ahead energy market is proposed in particular a stochastic forecast of electricity price and the technical features of hydrothermal units are considered the approach is based on an optimization procedure for maximizing expected profits in the presence of risk constraints conditional value at risk for the distribution of daily profit is used as risk measure

spatial price transmission and asymmetry in the ghanaian maize market abstract this paper utilizes recently developed threshold cointegration tests that allow for asymmetric adjustment toward a long run equilibrium relationship to examine price linkages between principal maize markets in ghana unlike previous studies the approach employed here assumes that economic agents only act to move the system back to equilibrium when the deviation from equilibrium exceeds a critical threshold whereby the benefits of this adjustment exceed the costs the findings indicate that major maize markets in ghana are well integrated both the threshold cointegration and asymmetric error correction models reveal that wholesale maize prices in local markets accra and bolgatanga respond more swiftly to increases than to decreases in central market techiman prices accra prices are found to react faster than bolgatanga prices to changes in techiman market prices

a simple procedure to evaluate ex ante producer welfare under price uncertainty a simple procedure is proposed for evaluating producer welfare under price uncertainty the method is derived under the assumption of constant absolute risk aversion in which risk preferences depend on the stock of wealth but not on the flow of income numerical examples corroborate the procedure s properties

risk constrained scheduling and offering strategies of a price maker hydro producer under uncertainty this paper presents a stochastic mixed integer linear programming smilp approach to maximize total expected profit of one price maker hydro producer in a pool based electricity market head dependence commitment decisions discharge ramping startup costs and forbidden zones are all effectively handled in our approach uncertainty about the competitors offers is adequately represented by residual demand curves rdcs scenarios the management of risk is suitably addressed by conditional value at risk cvar to provide the efficient frontier i e the solutions set for which the expected profit may not be augmented without enlarging the variance of profit appropriate offering strategies to the pool are also developed consisting of supply functions built for different risk levels a representative cascaded hydro system with 7 reservoirs is considered to analyze and compare risk neutral versus risk averse results

strategic bidding in an energy brokerage this focus of this paper is to present a framework in which strategies may developed for the individual participants in an energy brokerage such a framework is expected to be important with the increasing interest in electricity market structures such as the energy brokerage that deregulation has produced to illustrate the process of strategic bidding a simple suboptimal bidding strategy is presented with the aid of a numerical example the bidding strategy must be suboptimal because of the amount of unknown information about the other bidders further tuning of this strategy will be required before application to realistic scenarios

optimal bidding strategies for hydro electric producers a literature survey in a competitive environment with bid based markets power generation companies desire to develop bidding strategies that maximize their revenue in this paper we ask what approaches and methodologies have been used to model the bidding problem for hydro electric producers we present the problem s developments over time and through reviewing different variants of the problem progressively build to the case in which the agent is a price maker hydro electric producer in each variant of the bidding problem we examine how the approaches used to solve it may or may not be applicable to other variants last for the price maker hydro electric producer s bidding problem we recognize the most recent developments and illuminate a path for future efforts

coordinated price maker operation of large energy storage units in nodal energy markets in this paper a new optimization framework is proposed to coordinate the operation of large price maker and geographically dispersed energy storage battery systems in a nodal transmission constrained energy market the energy storage units are assumed to be investor owned and independently operated seeking to maximize their total profit various design factors are taken into consideration such as the location size efficiency and charge and discharge rates of the energy storage units as well as the joint impact of the energy storage operations on the locational marginal prices while the formulated optimization problem is originally nonlinear and hard to solve nonlinearities are tackled both in the objective function and in the constraints and the problem is transformed into a tractable mixed integer linear program for which the global optimal solutions are found for the charge and discharge schedules of each energy storage unit both deterministic and stochastic design scenarios are addressed various case studies are presented it is observed that transmission line congestion is often but not always desirable for the coordinated storage systems locational diversity practice of arbitrage robust design self scheduling versus economic bidding and the overall power system performance are also investigated

profit efficiency among basmati rice producers in pakistan punjab farm specific profit inefficiency among basmati rice producers was estimated from a variable coefficient profit frontier the mean level of inefficiency at farm resources and price levels was 28 with a wide range 5 87 average loss of profit was rs 1 222 per hectare socioeconomic factors related to profit loss were the farm household s education nonagricultural employment and a credit constraint institutional determinants of profit loss were a water constraint and the late application of fertilizer punjab wide benefits of increasing farmer s profit efficiency are large a 25 reduction in profit loss among basmati rice producers may generate over rs 240 million in extra profits each rice season rice is a major export commodity for pakistan generating about 2 5 billion pakistan rupees rs annually or 20 of foreign exchange earnings from commodity trade in the early 1980s two varieties dominate in pakistan s international trade in rice basmati 370 a high quality long grained aromatic variety and the medium long grained irri 6 distinct export markets exist for these rices over 90 of the basmati is exported to oil rich middle eastern nations while the mediumlong varieties are mainly marketed in southeast asia in 1983 the export price of basmati was about rs 7 900 per ton while the price of medium long grained varieties averaged rs 2 700 per ton pakistan has a comparative advantage in the international market for basmati but probably not for medium long grained rices azhar and mamhud historically pakistan had a near monopoly in international trade in basmati but now faces increased competition from thailand and the united states efferson therefore pakistan must strive to increase the efficiency of basmati production to retain its comparative advantage and competitive edge in foreign rice markets basmati 370 is a pure line selection made in

market integration and uncertainty the impact of domestic and international commodity price variability on rural household income and welfare in ghana and peru abstract we estimate rural household income uncertainties and welfare changes due to commodity price and production variability in ghana and peru under different scenarios for international and domestic market shocks uncertainties significantly affect the variability of household income especially for households that are specialised in the production of few commodities wider exposure to international markets would increase the income variability for producers of commodities that are subjected to stabilisation policies in ghana but would reduce the variability that rural households in peru face in terms of welfare rural households in both countries are expected to gain if fully exposed to international markets

distributional effects of maize price increases in malawi abstractin the wake of highly volatile world prices of staple commodities we examine the impacts of increases in maize prices on various categories of households in malawi using household level data changes in household income are calculated taking into account the net maize production status of the household and food price elasticities estimated from a censored demand system while maize price increases have unequivocal deleterious effects on the incomes of urban households rural households experience differential impacts net producing households in rural areas benefit from price increases with households above the poverty line obtaining proportionally higher incomes

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

on the solution of revenue and network constrained day ahead market clearing under marginal pricing part i an exact bilevel programming approach the first of this two paper series addresses a practical day ahead auction model where generation revenue constraints are explicitly incorporated in the problem formulation as routinely done in several national electricity markets across europe the revenue constrained market clearing procedure includes the effect of the transmission network inter temporal constraints associated with generation scheduling demand side bidding and marginal pricing this auction design is an instance of price based market clearing which features two major complicating factors first locational marginal prices become decision variables of the optimization process in addition producer revenues are formulated as bilinear and highly nonconvex products of power outputs and market clearing prices the resulting problem is formulated as a mixed integer nonlinear bilevel program with bilinear terms for which available solution techniques rely on heuristics approximations or modeling simplifications this paper presents a novel and exact methodology whereby the original problem is recast as an equivalent single level mixed integer linear program as a consequence finite convergence to optimality is guaranteed and the use of standard commercial software is allowed the proposed transformation is based on duality theory of linear programming karush kuhn tucker optimality conditions and integer algebra results in the second part of this two paper series numerical results from several case studies illustrate the effective performance of the proposed solution approach

assessing market structures in resource markets an empirical analysis of the market for metallurgical coal using various equilibrium models abstract the prevalent market structures found in many resource markets consist of high concentration on the supply side and low demand elasticity market results are therefore frequently assumed to be an outcome of strategic interaction between producers common models to investigate the market outcomes and underlying market structures are games representing competitive markets strategic cournot competition and stackelberg structures that take into account a dominant player acting first followed by one or more players we add to the literature by expanding the application of mathematical models and applying an equilibrium problem with equilibrium constraints epec which is used to model multi leader follower games to a spatial market using our model we investigate the prevalent market setting in the international market for metallurgical coal between 2008 and 2010 whose market characteristics provide arguments for a wide variety of market structures using different statistical measures to compare model results with actual market outcomes we find that two previously neglected settings perform best first a setting in which the four largest metallurgical coal exporting firms compete against each other as stackelberg leaders while the remainders act as cournot followers second a setting with bhpb acting as sole stackelberg leader

an individual welfare maximization algorithm for electricity markets an algorithm that allows a market participant to maximize its individual welfare in electricity spot markets is presented the use of the algorithm in determining market equilibrium points called nash equilibria is demonstrated the start of the algorithm is a spot market model that uses the optimal power flow opf with a full representation of the transmission system and inclusion of consumer bidding the algorithm utilizes price and dispatch sensitivities available from the hessian matrix and gradient of the opf to help determine an optimal change in an individual s bid the algorithm is shown to be successful in determining local welfare maxima and the prospects for scaling the algorithm up to realistically sized systems are very good nash equilibria are investigated assuming all participants attempt to maximize their individual welfare this is done by iteratively solving the individual welfare maximization algorithm until all individuals stop modifying their bids

rising food prices and coping strategies household level evidence from afghanistan this paper investigates the impact of rising wheat prices on household food security in afghanistan exploiting a unique nationally representative household survey the authors find evidence of large declines in the real value of per capita food consumption smaller price elasticities with respect to calories than with respect to food consumption suggest that households trade off quality for quantity as they move away from nutrient rich foods such as meat and vegetables toward staple foods the authors work improves upon country level simulation studies by providing estimates of actual household food security during a price shock in one of the world s poorest most food insecure countries

purchase allocation and demand bidding in electric power markets the purchase allocation problem is one of the most important problems faced by an electric energy service provider under new market environments the optimal purchase allocation problem for dual electric power markets and demand bid generation are discussed in this paper the price volatility is explicitly considered in purchase allocation problems and the sequential nature is modeled by conditional stochastic characteristics an analytical solution for the optimal allocation is derived with given demand and statistical characteristics of the market prices the method for generating demand bids for purchaser based on market allocation and price forecasting is then developed the numerical simulations for market allocation and bid generation are demonstrated based on the actual data of the u s california power market

a closer look at demand bids in california iso energy market one year of demand bids in the california energy market are analyzed and observations are reported on type size shape and other characteristics of the bids the implications of these observations the underlying causes and the potentials to improve demand bids by exploiting load flexibility are discussed

forecasting next day electricity prices by time series models in the framework of competitive electricity markets power producers and consumers need accurate price forecasting tools price forecasts embody crucial information for producers and consumers when planning bidding strategies in order to maximize their benefits and utilities respectively this paper provides two highly accurate yet efficient price forecasting tools based on time series analysis dynamic regression and transfer function models these techniques are explained and checked against each other results and discussions from real world case studies based on the electricity markets of mainland spain and california are presented

price maker self scheduling in a pool based electricity market a mixed integer lp approach this paper addresses the self scheduling problem faced by a price maker to achieve maximum profit in a pool based electricity market an exact and computationally efficient mixed integer linear programming milp formulation of this problem is presented this formulation models precisely the price maker capability of altering market clearing prices to its own benefits through price quota curves no assumptions are made on the characteristics of the pool and its agents a realistic case study is presented and the results obtained are analyzed in detail

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

testing for food market integration revisited this article considers the statistical performance of four commonly used econometric tests for market integration the law of one price the ravallion model cointegration and granger causality a spatial price equilibrium spe model that is subject to both production shocks and general price inflation and mimics many of the key characteristics of integrated food markets is constructed the model is used to generate food price time series of lengths that are typical of the short sample sizes available in most developing countries for both instantaneously integrated and independent markets a series of monte carlo experiments on these artificial food price time series are performed which show that all four of the conventional tests for market integration are statistically flawed

market power assessment and mitigation in hydrothermal systems the objective of this paper is to investigate market power issues in bid based hydrothermal scheduling initially market power is simulated with a single stage nash cournot equilibrium model market power assessment for multiple stages is then carried through a stochastic dynamic programming scheme the decision in each stage and state is the equilibrium of a multi agent game thereafter mitigation measures specially bilateral contracts are investigated case studies with data taken from the brazilian system are presented and discussed