tax exempt investors and the asset allocation puzzle abstract investors frequently hold equity in pensions and other tax exempt savings plans despite the prediction of the standard model that they hold only bonds we provide a new explanation for this empirical puzzle based on differences between tax exempt and taxable assets in the tax treatment of capital losses we show how limits on refundability of losses on taxable equities leads to diversity of investors preferences for corporate leverage on the basis of tax rates in the simplest equilibrium of the model tax exempt savers hold risky highly levered equities while low bracket taxable savers hold bonds and high bracket taxpayers hold relatively safe unlevered equities we discuss the implications of tax exempts for risk taking and agency costs within the firm

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

the pricing of durable exhaustible resources partial or total durability characterizes a large class of exhaustible resources hotelling s r percent rule will apply to a durable resource produced in a competitive market but will not apply if the resource is produced in a monopolistic market however the r percent rule does not mean that price is steadily rising it is shown that in general the competitive market price will fall initially as the stock in circulation increases and later will rise as the stock decreases and eventually depreciates toward zero after production ceases accounting for durability may thus help explain the u shaped long term price profiles observed for many resources 11 references 3 figures

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

demand side bidding agents modeling and simulation problems such as price volatility have been observed in electric power markets demand side participation is frequently offered as a potential solution by promising to increase market efficiency when hockey stick type offer curves are present however the individual end consumer will surely value electricity differently which makes demand side participation difficult as a group and at a bus in this paper demand is categorized into two groups one that highly values reliability and one that does not the two types are modeled separately and a new optimal bidding function is developed and tested based on this model

oil pricing policies and macroeconomy for an oil based economy abstract this paper analyses the oil pricing policies for an oil based economy within a national planning framework it contains a total asset maximization problem in the non oil sector and a macroeconomic model the main conclusion is that hotelling s r percent rule fails to apply for an oil based nation if the minimum import constraint becomes binding therefore the difference between the marginal revenue growth rate and the yield on domestic investment turns down when the import constraint is binding and then it goes through several cycles before it turns up as the constraint is non binding over the planning horizon

evaluation of alternatives for power system coordination and pooling in a competitive environment the paper defines and classifies essential issues that relate the need for electric power system coordination with the increasing development of competition principles are formulated and a coordination model and a market structure are proposed emphasizing the need for economic dispatch in the wholesale market a detailed comparison is made of the market and pooling implementations developed in argentina and chile countries that have pioneered the creation of competitive markets in the electric energy sector an evaluation of strengths and weaknesses of those two implementations is included

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

gaming and price spikes in electric power markets many challenging issues arise under the newly deregulated competitive electric power markets instead of centralized decision making in a vertically integrated environment as in the past decision making is now decentralized and driven by market forces gaming and price spikes have been observed in almost every electricity market but explicit analysis of these phenomena is rare in this paper the authors study historical bidding behavior to see how power suppliers and demand service providers were actually bidding in the california day ahead energy market based on their observations they formulate a prisoner s dilemma matrix game and introduce the notion of opportunistic tacit collision to explain strategic bidding behaviors in which suppliers withhold generation capacity from the market to drive up prices this explanation is applicable with or without market power transmission constraints and insufficient supply and is only enhanced by these factors their analysis is generally applicable to any uniform price electricity market in which there is significant insensitivity to price on the demand side

screening in a matching market contract design under incomplete information is often analysed in a bilaterally monopolistic setting if the informed party s reservation value does not depend on its private information its type it is a standard result that the uninformed side offers low types distorted contracts to reduce the information rent left to high types we challenge this result by embedding contract design in a matching market environment we consider a market where players meet pairwise and where in each match either side may be chosen to make a take it or leave it offer as frictions become sufficiently low we find that the set of equilibria is independent of whether there is complete or incomplete information in particular all contracts are free of distortions

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

electricity procurement for large consumers based on information gap decision theory in the competitive electricity market consumers seek strategies to meet their electricity needs at minimum cost and risk this paper provides a technique based on information gap decision theory igdt to assess different procurement strategies for large consumers supply sources include bilateral contracts a limited self generating facility and the pool it is considered that the pool price is uncertain and its volatility around the estimated value is modeled using an igdt model the proposed method does not minimize the procurement cost but assesses the risk aversion or risk taking nature of some procurement strategies with regard to the minimum cost using this method the robustness of experiencing costs higher than the expected one is optimized and the related strategy is determined the proposed method deals with optimizing the opportunities to take advantage of low procurement costs or low pool prices a case study is used to illustrate the proposed technique

application of mechanism design to electric power markets republished as competition is introduced across the electric power industry around the world market design for the industry is urgently needed to shape its future structure and performance when generator companies compete with one another in a deregulated market they may not be willing to share the information needed to perform an economic dispatch of the generation using game theory this paper designs a new mechanism that achieves efficiency economic dispatch in spite of this information problem in this mechanism when each company acts in the best of its own interest the outcome is efficient the paper demonstrates the merits of the mechanism by simulations including the ieee 14 bus case this paper contained an incorrect graphic when it originally appeared in the ieee transactions on power systems vol 16 no 1 p 1 8 2001 it is republished here with the correct graphic

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

using game theory to analyze electric transmission pricing policies in the united states abstract us public policy towards the private electric power industry is moving away from restrictive regulation and towards promotion of competition alternative policies concerning access to and pricing of transmission are now being discussed similar issues may arise in europe as trade barriers fall our purpose is to show how game theory can help illuminate that debate and identify desirable policies game theory models are used to estimate the possible effects of various policies upon productive efficiency and the distribution of gains among sellers transmitters and buyers of power static cooperative models are used to calculate the possible outcomes of short run transmission games long run games in which the amount of transmission capacity is a decisition variable are modeled as dynamic noncooperative stackelberg games one conclusion is that under some conditions price regulation and mandatory access could hurt power buyers by removing incentives for building transmission capacity another conclusion is that under a system of voluntary access and price regulation it may be better to allow wheeling prices to exceed the marginal cost of transport rather than to risk losing the benefits of cooperation

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

optimal allocation of energy storage system for risk mitigation of discos with high renewable penetrations along with the increasing penetration of renewable energy distribution system power flow may be significantly altered in terms of direction and magnitude this will make delivering reliable power on demand a major challenge in this paper a novel battery energy storage system bess based energy acquisition model is proposed for the operation of distribution companies discos in regulating price or locational marginal price lmp mechanisms while considering energy provision options within disco controlled areas based on this new model a new battery operation strategy is proposed for better utilization of energy storage system ess and mitigation operational risk from price volatility meanwhile optimal sizing and siting decisions for bess is obtained through a cost benefit analysis method which aims at maximizing the disco s profit from energy transactions system planning and operation cost savings the proposed energy acquisition model and ess control strategy are verified on a modified ieee 15 bus distribution network and risk mitigation is also quantified in two different markets the promising results show that the capacity requirement for ess can be reduced and the operational risk can also be mitigated

optimization based generation asset allocation for forward and spot markets one of the most important daily decisions that a genco has to make is to allocate generation assets between the forward and spot markets that is how much capacity should be contracted in the forward market and how much should be kept to bid in spot market this paper focuses on generation asset allocation between monthly forward contracts such as bilateral contracts futures contracts options contracts and daily spot markets considering operating costs and constraints of generating units as well as spot price risk the problem is to find the optimal hedging position based on the known forward price and the forecasted hourly spot prices and is formulated based on the model of pjm market the double dynamic programming method is applied to solve this optimal asset allocation problem with all the short term operating constraints of the generating unit satisfied three types of forward contracts that are commonly used in practice are considered and their impact on generation asset allocation are analyzed and compared the analytic relationship between the optimal contract quantity of a particular type and spot generation is established based on this relationship the applicability and characteristics of a particular type of contract are discussed furthermore with the solution to the generation asset allocation problem as a basis the pricing strategy in the forward market is analyzed a nash game model is established and an iterative process is developed to determine the equilibrium pricing of futures contracts numerical testing shows that the method for the generation asset allocation is effective various factors influencing the decision of generation asset allocation and the relationship between futures contract price and spot price are tested and analyzed

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

pricing regulation under bypass competition we analyze optimal pricing policies in local telecommunications subject to bypass for the access of long distance carriers we first consider the case of a regulated monopoly that operates the local network and has access to an additional technology bypass more efficient for large customers we then study how competition in bypass affects the optimal nonlinear pricing policy and the resulting allocation when transfers are allowed between the regulator and the network operator bypass competition benefits consumers at the expense of the taxpayer otherwise it benefits large consumers but hurts small ones

a security constrained bid clearing system for the new zealand wholesale electricity market this paper reports upon the mathematical models and implementation of the scheduling pricing and dispatch spd application for the new zealand electricity market nzem spd analyzes bids for energy offers reserve offers and energy demands and recognizes explicitly the effects on bid clearing due to transmission congestion network losses reserve requirements and ramp rate limits advanced lp solution methods are utilized to solve the large scale constrained optimization problem results on a 67 bus test system and the nzem are included

participation constraints in adverse selection models abstract this paper characterizes the optimal contract offered by an uninformed principal to an informed agent when the latter s reservation utility depends on his type the informational rent is nonmonotonic so that interior types may have a vanishing rent or be excluded from trade the paper identifies conditions for the optimal contract to be separating to be nonstochastic and to induce full participation it also discusses the nature of the solution when bunching occurs the results are applied to nonlinear pricing under price cap regulation and bypass competition and to competition in nonlinear pricing journal of economic literature classification numbers d82 d42 d23 d78 l51 l15

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

transaction analysis in deregulated power systems using game theory the electric power industry is in transition to a deregulated marketplace for power transactions in this environment all power transactions are made based on price rather than cost a regional power pool is noted as the most straightforward path to a deregulated electricity marketplace however many questions remain unanswered regarding the economics of power pool participation in a deregulated energy marketplace participants are interested in maximizing their own profits regardless of the system wide profits it is perceived that competition will reduce the price of electricity for retail customers however the key issue for participants is related with the price definition to remain competitive in this paper the authors use game theory to simulate the decision making process for defining offered prices in a deregulated environment the outcome of this study may be used by power pool coordinators to discourage unfair coalitions a modified ieee 30 bus power system is used as a deregulated power pool to illustrate the main features of the proposed method

contractual distortions in a market with frictions abstract this paper analyses contract design in a decentralized market environment with frictions while principals e g firms have all contractual power their market power is constrained as agents e g workers can choose to wait and search for better offers we find that results depend crucially on how market frictions affect agents utilities with type independent costs of search and waiting equilibrium contracts are always first best if agents are impatient and discount future payoffs however distortions vanish only gradually in the latter case we also characterize equilibrium offers and show that the market exhibits two types of externalities both of which are absent in the case of type independent costs of search

a study of basic bidding strategy in clearing pricing auctions this paper models bidding behaviors of suppliers in electricity auction markets under clearing pricing rule and with some simplified bidding assumptions optimal bidding strategy of suppliers is derived by solving a set of differential equations that specify the necessary conditions for bidders to maximize their expected payoffs the derived result indicates that bidders have incentives to mark up their bids above their costs of production the amount of markup depends on the probability of winning below and on the margin that are computed from the cost distribution of all suppliers market demand and the number of suppliers participating in the auction

on the extraction of an exhaustible resource by a monopoly hotelling s r percent rule does not hold for monopoly extractors of durable exhaustible resources an example with a nondurable resource in which the rule also fails to hold is presented an economy with a fixed average propensity to save is modelled the monopoly extractor recognizes that resource extraction by affecting output and hence capital accumulation affects future demand the firm exploits this effect by causing the marginal profitability of extraction to grow faster or slower than the rate of interest depending upon initial conditions conditions are developed under which the growth rate will be less than the interest rate

optional forward contracts for electric power markets this paper extends the idea of callable forward contracts which are potentially useful as demand side interruptible load contracts to their supply side analogues together these contracts allow market participants to take advantage of flexibility in generation or consumption to obtain a monetary benefit while simultaneously removing the risk of market price fluctuations this paper also considers the effects of strategic behavior on the part of market participants in their contract sales purchase decisions

a medium term decision model for discos forward contracting and tou pricing time varying prices by motivating customers to reduce their consumption in peak periods propel the electricity industry towards a higher efficiency compared to that of common flat prices focusing on time of use tou sale prices this paper establishes a stochastic model for the medium term decision making problem faced by a distribution company disco the developed model deals with the disco s decisions on the level of involvement in forward contracts and in the pool as well as the sale prices offered to customers the demand response to tou prices is captured using a price elasticity matrix pem the objective is to maximize the disco s profit while the exposure risk imposed by uncertainties is limited to a given level the model is formulated as a mixed integer linear programming milp problem that can be effectively solved via commercial software packages a typical finnish 20 kv urban distribution network is used to demonstrate the effectiveness of the developed model

regulation competition and liberalization in many countries throughout the world regulators are struggling to determine whether and how to introduce competition into regulated industries this essay examines the complexities involved in the liberalization process while stressing the importance of case specific analyses this essay distinguishes liberalization policies that generally are procompetitive from corresponding anticompetitive liberalization policies

priced based operation in an auction market structure open transmission access is a new legal requirement within the electric power industry interchange will require evaluation of the existing conditions to determine if the product can be delivered at the time required and at the level awarded through the bidding or negotiation process this paper seeks to identify the likely deregulation details for a full market implementation when native load is considered equal to any other third party load comparability this paper seeks to identify the technical issues such as standards and algorithms necessary for changing the national infrastructure from a vertically integrated industry to a horizontally integrated industry

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 bid solicitation and selection method for developing a competitive spot priced electric market the electric utility industry is in the beginning throes of a transformation from a cost based regulated structure to a more market based less regulated system traditional unit commitment and economic dispatch methodologies can continue to provide reliable least cost solutions providing they are modified to accommodate a larger sphere of market participants this paper offers a method for an entity such as an independent system operator iso to solicit and evaluate bids for developing a spot priced electric market by replicating existing utility practices that are effective and efficient while creating an open and equitable competitive marketplace for electricity

application of mechanism design to electric power markets as competition is introduced across the electric power industry around the world market design for the industry is urgently needed to shape its future structure and performance when generator companies compete with one another in a deregulated market they may not be willing to share the information needed to perform an economic dispatch of the generation using game theory this paper designs a new mechanism that achieves efficiency economic dispatch in spite of this information problem in this mechanism when each company acts in the best of its own interests the outcome is efficient the paper demonstrates the merits of the mechanism by simulations including the ieee 14 bus case

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 taker bidding strategy under price uncertainty this paper provides a framework to obtain the optimal bidding strategy of a price taker producer an appropriate forecasting tool is used to estimate the probability density functions of next day hourly market clearing prices this probabilistic information is used to formulate a self scheduling profit maximization problem that is solved taking advantage of its particular structure the solution of this problem allows deriving a simple yet informed bidding rule results from a realistic case study are discussed in detail

electricity price short term forecasting using artificial neural networks this paper presents the system marginal price smp short term forecasting implementation using the artificial neural networks ann computing technique the described approach uses the three layered ann paradigm with backpropagation the retrospective smp real world data acquired from the deregulated victorian power system was used for training and testing the ann the results presented in this paper confirm considerable value of the ann based approach in forecasting the smp

managing price risk in a multimarket environment in a competitive electricity market a generation company genco can manage its trading risk through trading electricity among multiple markets such as spot markets and contract markets the question is how to decide the trading proportion of each market in order to maximize the genco s profit and minimize the associated risk based on the mean variance portfolio theory this paper proposes a sequential optimization approach to electric energy allocation between spot and contract markets taking into consideration the risks of electricity price congestion charge and fuel price especially the impact of the fuel market on electric energy allocation is analyzed and simulated with historical data in respect of the electricity market and other fuel markets in the u s simulation results confirm that the proposed analytic approach is consistent with intuition and therefore reasonable and feasible for a genco to make a trading plan involving risks in an electricity market

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