role of distribution factors in congestion revenue rights applications in the locational marginal price lmp based congestion management scheme transmission customers face uncertainty in the congestion charges they incur in order to bring certainty to customers congestion revenue rights crr such as the fixed transmission rights ftr used in the pjm interconnection and flowgate rights fgr are introduced these crr are financial tools that provide the holder reimbursement of the congestion charges incurred in the day ahead market the implementation of crr requires appropriate modeling of the transmission network in which the distribution factors are extensively used these factors the injection shift factors isfs and the power transfer distribution factors ptdfs are linear approximations of the sensitivities of the active power line flows with respect to various variables the factors are computed for a specified network topology and parameter values in practice the ptdfs used for the crr issuance may be different from those used in the day ahead market due to changes in the forecasted network conditions the ptdf errors may impact the ftr issuance quantities the revenue adequacy of the ftr issuer and the hedging ability of the fgr in this paper we explore analytical characteristics of these distribution factors and investigate their role in crr applications we study the nature of the ptdf errors and examine their impacts in these applications both analytically and experimentally our results indicate that the impacts of the ptdf errors in crr applications stay in an acceptable range under a broad spectrum of conditions including contingencies used to establish n 1 security

clearing and pricing for coordinated gas and electricity day ahead markets considering wind power uncertainty natural gas and electricity systems are becoming increasingly strongly coupled gas fired units gfus are replacing retired coal plants and the power systems are more dependent on the flexibilities provided by gfus the gfus power generation capability relies on the availability of gas resources which is jointly determined by the capacity of gas suppliers and pipeline networks however the gas and electricity markets are operated separately consequently the gfus are forced to represent the entire power system to bid on the gas market they must make forecasts regarding future gas consumption and bear the risk of improper contracts or being unable to meet generation schedules due to occasional insufficient gas supply when facing larger shares of renewable energies and more frequent gas network congestions the current market framework is particularly unreliable and inefficient as well as economically unfriendly to the investors of the gfu assets in this paper we try to develop a framework that can combine the two markets by properly pricing the scarce resources e g gas transmission capacity the joint market can help us to allocate the resources more efficiently while satisfying the demands moreover a more forward looking day ahead market clearing framework is presented by considering the uncertainty brought by renewable energies the formulation and algorithm of the proposed joint market model will be presented as are some case studies

efficient mechanisms for bilateral trading we consider bargaining problems between one buyer and one seller for a single object the seller s valuation and the buyer s valuation for the object are assumed to be independent random variables and each individual s valuation is unknown to the other we characterize the set of allocation mechanisms that are bayesian incentive compatible and individually rational and show the general impossibility of ex post efficient mechanisms without outside subsidies for a wide class of problems we show how to compute mechanisms that maximize expected total gains from trade and mechanisms that can maximize a broker s expected profit journal of economic literature classification number 026

pricing for system security power tariffs security in power systems refers to the ability of the system to withstand imminent disturbances contingencies maintaining security is an issue which must be addressed at the system level it is shown in this paper however that it is possible to maintain power system security in an operating environment with many participants power companies independent power producers co generators consumers each attempting to optimize their own benefit through pricing incentives and appropriate information exchange rates for power generation consumption and for an offer to use during a contingency as well as information on the probability distribution of contingency need for each participant are derived so that individual optimization will lead to the socially optimal solution in which power system security is optimized and the aggregate benefit is maximized

market clearing with stochastic security part i formulation the first of this two paper series formulates a stochastic security constrained multi period electricity market clearing problem with unit commitment the stochastic security criterion accounts for a pre selected set of random generator and line outages with known historical failure rates and involuntary load shedding as optimization variables unlike the classical deterministic reserve constrained unit commitment here the reserve services are determined by economically penalizing the operation of the market by the expected load not served the proposed formulation is a stochastic programming problem that optimizes concurrently with the pre contingency social welfare the expected operating costs associated with the deployment of the reserves following the contingencies this stochastic programming formulation is solved in the second companion paper using mixed integer linear programming methods two cases are presented a small transmission constrained three bus network scheduled over a horizon of four hours and the ieee reliability test system scheduled over 24 h the impact on the resulting generation and reserve schedules of transmission constraints and generation ramp limits of demand side reserve of the value of load not served and of the constitution of the pre selected set of contingencies are assessed

the proper scope of government theory and an application to prisons when should a government provide a service in house and when should it contract out provision we develop a model in which the provider can invest in improving the quality of service or reducing cost if contracts are incomplete the private provider has a stronger incentive to engage in both quality improvement and cost reduction than a government employee has however the private contractor s incentive to engage in cost reduction is typically too strong because he ignores the adverse effect on noncontractible quality the model is applied to understanding the costs and benefits of prison privatization

simple contracts renegotiation under asymmetric information and the hold up problem abstract in this article it is demonstrated that voluntary bargaining over a collective decision under asymmetric information may well lead to ex post efficiency if the default decision is non trivial it is argued that the default decision may be interpreted as a simple contract that the parties have written ex ante this result is used in order to show that simple unconditional contracts which are renegotiated may allow the hold up problem to be solved even if the parties valuations are private information

contractual solutions to the hold up problem this paper considers a general version of the hold up problem where n agents first make relation specific investments and then must agree on some collective action it is shown that first best solutions exist under a variety of different assumptions about the nature of information asymmetries

distributed stochastic market clearing with high penetration wind power integrating renewable energy into the modern power grid requires risk cognizant dispatch of resources to account for the stochastic availability of renewables toward this goal day ahead stochastic market clearing with high penetration wind energy is pursued in this paper based on the dc optimal power flow opf the objective is to minimize the social cost which consists of conventional generation costs end user disutility as well as a risk measure of the system re dispatching cost capitalizing on the conditional value at risk cvar the novel model is able to mitigate the potentially high risk of the recourse actions to compensate wind forecast errors the resulting convex optimization task is tackled via a distribution free sample average based approximation to bypass the prohibitively complex high dimensional integration furthermore to cope with possibly large scale dispatchable loads a fast distributed solver is developed with guaranteed convergence using the alternating direction method of multipliers admm numerical results tested on a modified benchmark system are reported to corroborate the merits of the novel framework and proposed approaches

a stochastic electricity market clearing formulation with consistent pricing properties we argue that deterministic market clearing formulations introduce arbitrary distortions between day ahead and expected real time prices that bias economic incentives we extend and analyze a previously proposed stochastic clearing formulation in which the social surplus function induces penalties between day ahead and real time quantities we prove that the formulation yields price bounded price distortions and we show that adding a similar penalty term to transmission flows and phase angles ensures boundedness throughout the network we prove that when the price distortions are zero day ahead quantities equal a quantile of their real time counterparts the undesired effects of price distortions suggest that stochastic settings provide significant benefits over deterministic ones that go beyond social surplus improvements we propose additional metrics to evaluate these benefits

reserve requirements to efficiently manage intra zonal congestion the security constrained unit commitment problem schedules power generators to minimize cost subject to operating constraints reserve requirements ensure that reserve is available to re balance the system following a contingency but do not guarantee reliability in congested systems where reserve activation is limited by transmission constraints operators improve reserve deliverability by limiting power flows and controlling the location of reserves zones are used to address inter zonal congestion but operators lack efficient ways to handle intra zonal congestion we propose dynamically relating minimum reserve levels to transmission stress in a computationally efficient approach that complements existing reserve models from the literature analysis on the ieee rts 96 test case demonstrates the approach can mitigate intra zonal congestion more economically than traditional reserve policies

stochastic security for operations planning with significant wind power generation in their attempt to cut down on greenhouse gas emissions from electricity generation several countries are committed to install wind power generation up to and beyond the 10 20 penetration mark however the large scale integration of wind power represents a challenge for power system operations planning because wind power 1 cannot be dispatched in the classical sense and 2 its output varies as weather conditions change this warrants the investigation of alternative short term power system operations planning methods capable of better coping with the nature of wind generation while maintaining or even improving the current reliability and economic performance of power systems to this end this paper formulates a short term forward electricity market clearing problem with stochastic security capable of accounting for nondispatchable and variable wind power generation sources the principal benefit of this stochastic operation planning approach is that when compared to a deterministic worst case scenario planning philosophy it allows greater wind power penetration without sacrificing security

paying not to go to the gym how do consumers choose from a menu of contracts we analyze a novel dataset from three u s health clubs with information on both the contractual choice and the day to day attendance decisions of 7 752 members over three years the observed consumer behavior is difficult to reconcile with standard preferences and beliefs first members who choose a contract with a flat monthly fee of over 70 attend on average 4 3 times per month they pay a price per expected visit of more than 17 even though they could pay 10 per visit using a 10 visit pass on average these users forgo savings of 600 during their membership second consumers who choose a monthly contract are 17 percent more likely to stay enrolled beyond one year than users committing for a year this is surprising because monthly members pay higher fees for the option to cancel each month we also document cancellation delays and attendance expectations among other findings leading explanations for our findings are overconfidence about future self control or about future efficiency overconfident agents overestimate attendance as well as the cancellation probability of automatically renewed contracts our results suggest that making inferences from observed contract choice under the rational expectation hypothesis can lead to biases in the estimation of consumer preferences

uncertainty management in the unit commitment problem uncertainty in power systems operations has been traditionally managed by multistage decision making and operating reserve requirements a familiar example of multistage decisions is day ahead unit commitment and real time economic dispatch an alternate approach for managing uncertainty is a stochastic formulation which allows the explicit modeling of the sources of uncertainty this paper compares stochastic and reserve methods and evaluates the benefits of a combined approach for the efficient management of uncertainty in the unit commitment problem numerical studies show that unit commitment solutions obtained for the combined approach are robust and superior with respect to the traditional approach in terms of both economics and reliability metrics

market clearing with stochastic security part ii case studies this paper analyzes the market clearing formulation with stochastic security developed in its companion paper through two case studies solved using mixed integer linear programming techniques the generation and reserve schedules as well as the nodal prices of energy and security are assessed under various conditions such as a line flow limits b when nonspinning reserve is excluded from the formulation c demand side valuation of energy not served d generator ramping limits and e the set of pre selected contingencies

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

information gathering transaction costs and the property rights approach the property rights approach to the theory of the firm suggests that ownership structures are chosen in order to provide ex ante investment incentives while bargaining is ex post efficient in contrast transaction cost economics emphasizes ex post inefficiencies in the present paper a party may invest and acquire private information about the default payoff that it can realize on its own inefficient rent seeking can overturn prominent implications of the property rights theory in particular ownership by party b may be optimal even though only the indispensable party a makes an investment decision

two stage stochastic programming model for market clearing with contingencies planning for contingencies typically results in the use of more expensive facilities before disruptions it leads to different prices and energy availability at various network locations depending on how the contingency analysis is performed in this paper we present a two stage stochastic programming model for incorporating contingencies the model is computationally demanding and made tractable by using an interior point log barrier method coupled with benders decomposition the second stage optimal recourse function rf defines the most economically efficient actions in the post contingency state for returning the system back to normal operating conditions the approach is illustrated with for two examples small with 8 buses 11 branches and ieee medium scale with 300 buses 411 branches

discussion of scheduling of spinning reserve considering customer choice on reliability the authors proposed a market model in which the energy and spinning reserve are cleared sequentially the experience has shown that this kind of market model can lead to quite undesirable situations such as price reversal problem the case of the pre 2001 california electricity market is the best example moreover by using sequential market clearing enough capacity may not be brought into the reserve market as a result post clearing market ad hoc manipulations would be required to turn on enough extra units to meet reliability targets lastly ignoring the coupling that exists between the energy and the reserve scheduling can lead to suboptimal or infeasible results

risk constrained self scheduling of hydro wind units for short term electricity markets considering intermittency and uncertainty abstract in view of the intermittency and uncertainty associated with both the electricity production sector of restructured power system and their competitive markets it is necessary to develop an appropriate risk managing scheme so that it is desirable to trade off between optimum utilization of intermittent generation resources i e renewable energy resources uncertain market prices and related risks in order to maximize participants benefits and minimize the corresponding risks in the multi product market environment the main goal of this paper is to investigate risk management by introducing a novel multi risk index to quantify expected downside risk edr which is caused by both the wind power and market price uncertainties value at risk var method is used to assess the mentioned risk issue by the proposed weighted edr so that an optimal trade off between the profit and risk is made for the system operations also the roulette wheel mechanism is employed for random market price scenario generation wherein the stochastic procedure is converted into its respective deterministic equivalents moreover the autoregressive integrated moving average arima model is employed to characterize the stochastic wind farm wf generation by predetermined mean level and standard deviation of wind behavior as well as temporal correlation the problem is formulated as a mixed integer stochastic framework for a hydro wind power system scheduling and tested on a generation company genco

we like to see you in the gym a field experiment on financial incentives for short and long term gym attendance abstract this paper presents a field experiment to analyze whether financial incentives conditional on attending the gym can increase gym attendance of members of an off campus gym both in the short run two quarters of a year and in the long run the next two quarters of the year the incentivized subjects received a rebate of approximately 10 of the average membership fee conditional on attending the gym at least once per week in 11 of the 13 weeks of the first quarter of 2010 in the second quarter of 2010 the incentive was repeated allowing subjects a second chance to earn a rebate in both quarters they received a rebate of 25 instead of 15 conditional on attending the gym at least twice a week in 11 of the 13 weeks gym attendance was recorded both during the intervention period and during the two quarters after we compared the conditional incentive to attend the gym with an unconditional incentive where subjects would receive the 10 rebate per quarter merely for staying a member of the gym the conditional incentive to attend the gym had a positive yet non persistent impact on gym attendance we conclude that gym attendance can be improved through incentives but that smarter non financial incentives and nudges need to be explored as well to obtain more persistent improvements in gym attendance

can coasean bargaining justify pigouvian taxation the fact that according to the celebrated coase theorem rational parties always try to exploit all gains from trade is usually taken as an argument against the necessity of government intervention through pigouvian taxation in order to correct externalities however we show that the hold up problem which occurs if non verifiable investments have external effects and parties cannot be prevented from always exploiting ex post gains from trade through coasean bargaining may be solved by government intervention in this sense the impossibility of ruling out coasean bargaining after investments are sunk may in fact justify pigouvian taxation

benefits and challenges of electrical demand response a critical review advances in it control and forecasting capabilities have made demand response a viable and potentially attractive option to increase power system flexibility this paper presents a critical review of the literature in the field of demand response providing an overview of the benefits and challenges of demand response these benefits include the ability to balance fluctuations in renewable generation and consequently facilitate higher penetrations of renewable resources on the power system an increase in economic efficiency through the implementation of real time pricing and a reduction in generation capacity requirements nevertheless demand response is not without its challenges the key challenges for demand response centre around establishing reliable control strategies and market frameworks so that the demand response resource can be used optimally one of the greatest challenges for demand response is the lack of experience and the consequent need to employ extensive assumptions when modelling and evaluating this resource this paper concludes with an examination of these assumptions which range from assuming a fixed linear price demand relationship for price responsive demand to modelling the highly diverse distributed and uncertain demand response resource as a single centralised negative generator adopting fixed characteristics and constraints

a probabilistic reserve market incorporating interruptible load a probabilistic method for a pool based combined energy and reserve market which considers both generators and interruptible loads ils is proposed in this paper we minimize generation production cost together with the cost associated with expected energy not supplied eens due to outages of generating units and failures of ils to supply the reserve when required the proposed settlement scheme allocates equitably cost of reserve among generators and ils given that the method takes into account reliability of individual generators and ils the proposed scheme provides incentives for all market participants to improve their performance a number of case studies are carried out to illustrate the impact of participant s characteristics on the reserve cost allocation

cooperative investments and the value of contracting recent articles have shown that contracts can support the efficient outcome for bilateral trade even in the face of specific investments and incomplete contracting these studies typically considered selfish investments that benefit the investor e g the seller s investment reduces her production costs the authors find very different results for cooperative investments that directly benefit the investor s partner e g the seller s investment improves the buyer s value of the good most importantly if committing not to renegotiate the contract is impossible then contracting has no value i e the parties cannot do better than to abandon contracting altogether in favor of ex post negotiation

three or two stage stochastic market clearing algorithm as the power industry considers moving from a deterministic paradigm to a stochastic one to clear the day ahead market in systems with significant stochastic production the following question arises how should a stochastic clearing algorithm be formulated our analyses indicate that a three stage stochastic approach is clearly superior to a two stage one to show this we propose a model that includes three stages the first one represents the day ahead market the second stage the intraday market and the third one the real time operation the objective is to clear the day ahead market but with a prognosis of the future the intraday market and the real time operation to assess the impact of the intraday market on the day ahead outcomes we compare the results obtained from the proposed model with those of a simpler but more common two stage model which represents the day ahead market and the real time operation

asset ownership and contractibility of interaction in a property rights framework i study how organizational form and quantity contracts interact in generating investment incentives the model nests standard property rights and hold up models as special cases i admit general message dependent contracts but provide conditions under which noncontingent contracts are optimal first the article contributes to the foundation of the property rights theory i characterize under which circumstances its predictions are correct when trade is contractible second i study how the optimal use of the incentive instruments depends on the environment finally the model offers a new perspective on the classic fisher body case and produces implications that are empirically testable

is being flexible advantageous for demands this paper analyzes the impacts of flexible demands on day ahead market outcomes in a system with significant wind power production we use a two stage stochastic market clearing model where the first stage represents the day ahead market and the second stage represents the real time operation on one hand flexibility of demands is beneficial to the system as a whole since such flexibility reduces the operation cost but on the other hand shifts in demands from peak periods to off peak periods may influence prices in such a way that demands may not be willing to provide flexibility specifically we investigate the impacts of different degree of demand flexibility on day ahead prices a number of scenarios modeling the uncertainty associated with wind production at the operation stage and nonconvexities due to start up costs of generators and their minimum power outputs are taken into account

connecting the intraday energy and reserve markets by an optimal redispatch electricity markets based on simple bids provide a very high degree of transparency and simplicity however simple bids fail to capture many well known characteristics of generating units and therefore the responsibility for obtaining feasible schedules is transferred to market participants the purpose of this paper is to help the generating utility to automatically analyze the last energy program cleared in the market and in case this program is technically unfeasible to provide an alternative schedule by re dispatching the generating units this is achieved by formulating an optimization problem where the objective is to find the cheapest and feasible instantaneous power trajectory of each generator trying to minimize the differences between its hourly average values and the last energy program as the objectives of the utility can vary during the day three different models are presented two of them are formulated as a joint energy and reserve dispatch in order to take into account possible commitments acquired in the ancillary services market of agc regulation in this sense a novel approach for considering discontinuous ancillary regulation curves is proposed some numerical examples are included to illustrate the essential features of the models

optimal scheduling of spinning reserve effective control of spinning reserve can provide substantial cost reductions in large power systems this paper suggests that this goal can he achieved by tightly integrating a probabilistic reserve assessment with the unit commitment uc function this enables the reliability of individual units and the uncertainty of the load forecast to be considered for short term scheduling the generation can then be scheduled to meet a given risk index it is further argued that the optimal value of this risk index should be selected on the basis of a tradeoff between the total schedule cost obtained from the uc solution and the expected cost of energy not served which can be derived from the probabilistic reserve assessment finally the problem of over commitment of reserve in lagrangian relaxation based uc is reduced by means of a new unit decommitment technique incorporating a look ahead feature

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

holdups standard breach remedies and optimal investment in bilateral trading problems the parties may be hesitant to make relationship specific investments without adequate contractual protection we postulate that the parties can sign noncontingent contracts prior to investing and can freely renegotiate them after information about the desirability of trade is revealed we find that such contracts can induce one party to invest efficiently when courts impose either a breach remedy of specific performance or expectation damages moreover specific performance can induce both parties to invest efficiently if a separability condition holds expectation damages on the other hand is poorly suited to solve bilateral investment problems forthcoming the american economic review please contact the program in law and economics at boalt hall school of law uc berkeley berkeley ca 94720 for a copy of this paper

the effect of contingency analysis on the nodal prices in the day ahead market we look at the effect of modeling branch outage contingencies on locational marginal prices to model contingencies in the day ahead auction we formulate a two stage stochastic program rather than follow the current practice of including a list of possible contingencies that must be satisfied we incorporate a larger set of contingencies in the model and allow contingencies to result in load reductions outages at a cost the model can be used and interpreted in two ways one is to look at the tradeoff between reliability and outage costs another is to consider the load losses resulting from a contingency to be consumer offers of load reductions in response to line outages as part of the day ahead auction in analyzing the model structure we find that the prices in the model closer in definition to those currently used in the day ahead auction do not maximize expected surplus because the day ahead auction produces prices that assume shortages will never occur this raises issues with the design of auctions with important stochastic elements in the market we present results for a 68 node grid with 86 branches lines and transformers to illustrate how prices and expected values change as the costs of outages are varied

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

a single settlement energy only electric power market for unpredictable and intermittent participants we discuss a stochastic programming based method for scheduling electric power generation subject to uncertainty such uncertainty may arise from either imperfect forecasting or moment to moment fluctuations and on either the supply or the demand side the method gives a system of locational marginal prices that reflect the uncertainty and these may be used in a market settlement scheme in which payment is for energy only we show that this scheme is revenue adequate in expectation

economic dispatch under uncertainty the probabilistic envelopes approach with fast paced renewable energy integration stochastic methods are emerging as a viable alternative to traditional power system operations planning under uncertainty the value of stochastic planning lies in its effectiveness at reducing operational costs while allowing higher penetration levels of renewable sources and without much sacrifice to system security this is under the premise that the decision maker may not need to fully hedge against more extreme and costlier events that exhibit lower probabilities of occurrence on the other hand stochastic methods do suffer from the curse of dimensionality which renders them computationally intractable for practical application here we propose a novel hybrid robust stochastic approach based on the flexibility envelopes concept it circumvents the curse of dimensionality by using probability weighted envelopes to enclose the evolution of the net load uncertainty over the planning horizon the new approach is illustrated by a receding horizon economic dispatch example to compare its effectiveness to robust planning and stochastic planning with a scenario tree

energy and reserve pricing in security and network constrained electricity markets this paper analyzes some unresolved pricing issues in security constrained electricity markets subject to transmission flow limits although the notion of separate reserve types as proposed by ferc can be precisely and unambiguously defined when transmission constraints are active the very existence of separate reserve prices and markets is open to question when the prices are based on marginal costs instead we submit here that the only products whose marginal costs can be separately and uniquely defined and calculated are those of energy and security at each node thus under marginal pricing at any given network bus all scheduled reserve types should be priced not at separate rates but at a common rate equal to the marginal cost of security at that bus furthermore we argue that nodal or area reserves cannot be prespecified but must be obtained as by products of the market clearing process simulations back up these conclusions

towards full integration of demand side resources in joint forward energy reserve electricity markets this paper proposes a security constrained forward market clearing algorithm within which the inherent characteristics of demand flexibility are acknowledged when the provision of reserve from the demand side is considered in the proposed formulation we co optimize the cost of scheduling the appropriate resources to guarantee the security of the system and the expected cost of operating under any credible system state in addition we consider that consumers can offer to provide spinning reserve capacity deployable by voluntary load reductions in response to contingencies due to the load recovery effect i e since energy usage is essentially postponed when demand side reserve is deployed in post contingency states any voluntary reduction in the load has to be accompanied by a subsequent increase in demand from the initial forecast we demonstrate that the marginal value of the reserve provided by the demand can only be calculated taking into account the cost of supplying the recovery consumption flexible consumers can reduce their payments on average if energy is settled through real time prices

multi area energy and reserve dispatch under wind uncertainty and equipment failures the cross border trading among electricity markets in an interconnected multi area system e g in central europe and the integration of renewable resources e g wind energy have remarkably increased in recent years to efficiently operate such system a proper coordination among different areas is required within this context a decentralized algorithm for market clearing is proposed in this paper to dispatch simultaneously energy and reserve under wind generation uncertainty and equipment failures the proposed technique does not require a central operator but just a moderate interchange of information among neighboring areas additionally the benefit of cross border trading is studied

value based transmission expansion planning of hydrothermal systems under uncertainty transmission planning studies in hydrothermal systems deal with complex issues two include 1 the need for a robust grid that can accommodate a large number of economic dispatch patterns caused by differing hydrological conditions in the river basins and 2 the high cost of grid reinforcements due to the large distance from hydro plants to load centers and the required n l security criterion it is thus necessary to consider the tradeoff between supply reliability and reinforcement cost the resulting planning problem is formulated as a large scale mixed integer nonlinear optimization model the objective function is to minimize the sum of investment costs and expected load shedding costs the constraints include linearized power flow equations limits on circuit flows for all combinations of economic dispatch points which capture hydrological variation and circuit contingencies which capture supply reliability this paper describes a new solution scheme for this problem that is based on two techniques 1 the extension of a binary disjunctive technique which transforms the integer nonlinear problem into a linear one and 2 screening strategies which allow a judicious choice of contingencies and candidate circuits planning studies for brazil and bolivia are presented and discussed

market implications and pricing of dynamic reserve policies for systems with renewables static reserve policies are used within security constrained unit commitment scuc and security constrained economic dispatch sced to ensure reliability a common policy is that 10 min reserve must exceed the largest contingency however this condition does not guarantee reliability because voltage and thermal limits can hinder reserve deliverability many operators use zonal reserve markets to ensure reserves are dispersed across the grid such zonal models attempt to anticipate transmission bottlenecks which is a difficult task when the future system state is uncertain this paper examines the market implications of dynamic reserve policies used to mitigate uncertainty from renewable resources and contingencies we study the market implications of policies recently proposed in the literature such as hourly zones within day ahead scuc and an algorithm that formally disqualifies reserves that are expected to be undeliverable a locational reserve pricing scheme is also proposed in connection with scenario based reserve disqualification analysis on the rts 96 test case shows that dynamic zones and reserve disqualification along with the proposed compensation scheme help direct reserve payments toward resources that more effectively respond to contingencies

the value of intra day markets in power systems with high wind power penetration in this paper the value of intra day markets in managing wind power uncertainty in competitive electricity markets is analyzed a competitive electricity market model consisting of a day ahead market and a number of intra day markets is considered real time operation adjustment is also taken into account stochastic programming is used to model decision making under wind power uncertainty numerical simulations based on two test systems are presented

continuous time marginal pricing of electricity the current practice of discrete time electricity pricing starts to fall short in providing an accurate economic signal reflecting the continuous time variations of load and generation schedule in power systems this paper introduces the fundamental mathematical theory of continuous time marginal electricity pricing we first formulate the continuous time unit commitment problem as a constrained variational problem and subsequently define the continuous time economic dispatch ed problem where the binary commitment variables are fixed to their optimal values we then prove that the continuous time marginal electricity price equals to the lagrange multiplier of the variational power balance constraint in the continuous time ed problem the proposed continuous time marginal price is not only dependent to the incremental generation cost rate but also to the incremental ramping cost rate of the units thus embedding the ramping costs in calculation of the marginal electricity price the numerical results demonstrate that the continuous time marginal price manifests the behavior of the constantly varying load and generation schedule in power systems

a security constrained energy and spinning reserve markets clearing system using an interior point method a model and solution approach to a daily energy and spinning reserve electricity markets clearing system is presented in this paper the model considers offers for energy supply and spinning reserve bids for demand of energy and re schedulable bilateral contracts system security is taken into account by using a direct current model the model represents the clearing system used by an iso in charge of both the market and system security the clearing system is formulated as an optimization problem which is solved using an interior point method ipm taking advantage of the problem s special structure

optimal dispatch of a system based on offers and bids a mixed integer lp formulation the federal energy regulatory commission s ferc orders 888 and 889 will have far reaching consequences on the operation and dispatch of electric power systems a common element of the change is that of dispatching the system based on offers and bids to sell and buy unbundled commodities this paper formulates and solves the optimal dispatch problem as a mixed integer linear program such a formulation allows the acceptance of offers with minimum takes arising from generator characteristics

after you sir hold up direct externalities and sequential investment we propose a solution to the hold up problem the parties in a contract can avoid the inefficiencies caused by the possibility of opportunistic behaviour and implement the first best level of investment if they make their investment decision sequentially one party observing the choice made by the other party before making his own choice unlike the existing literature the proposed solution leads to the efficient choice of investment even when there are two sided direct externalities journal of economic literatureclassification numbers d23 d82

can financial incentives help people trying to establish new habits experimental evidence with new gym members can financial incentives aid habit formation in people attempting to establish a positive health behavior we provide evidence on this question from a randomized controlled trial of modest sized incentives to attend the gym among new members of a fitness facility our experiment randomized 690 participants into a control group that received a 30 payment unconditionally or one of 3 incentive groups that received a payment for attending the gym at least 9 times over the first 6 weeks of membership two incentive treatment arms offered monetary payments of 30 and 60 the third incentive treatment motivated by the endowment effect offered a physical item worth 30 all three incentives had only small impacts on attendance during members first 6 weeks and no effect on their post incentive visit trajectories we document substantial overconfidence among new members about their likely visits and discuss how overconfidence may undermine the effectiveness of incentive programs

differential evolution algorithm for security constrained energy and reserve optimization considering credible contingencies reserve services are an essential part of a standard market design and are under development in major electricity markets this paper presents the development of differential evolution algorithm for optimal allocation of energy and spinning reserve the optimization is performed in an integrated market with biddable spinning reserve and sectional price offer curves while considering all security and power systems constraints in steady state and system credible contingencies the effectiveness of the proposed method is examined by application of the proposed algorithm on the ieee 30 bus test system some comparisons are made with analytical and evolutionary methods in various cases

pricing energy and reserves using stochastic optimization in an alternative electricity market this paper presents a stochastic linear programming model that can be used for pricing in electrical energy and reserve markets it addresses capacity energy and reserve dispatch problems that may arise from n 1 contingency scenarios possible market solutions focusing on generator compensation using real time day ahead and hybrid schemes are enumerated along with opportunities for consumer pricing and transmission costing this model is illustrated on a 6 bus test system as well as a larger 66 bus system representing the ontario network a key difference among schemes is the degree of risk to the generators measured by variance in profit

pricing electricity in pools with wind producers this paper considers an electricity pool that includes a significant number of wind producers and is cleared through a network constrained auction one day in advance and on an hourly basis the hourly auction is formulated as a two stage stochastic programming problem where the first stage represents the clearing of the market and the second stage models the system operation under a number of plausible wind production realizations this formulation co optimizes energy and reserve and allows deriving both pool energy prices and balancing energy prices these prices result in both cost recovery for producers and revenue reconciliation a case study of realistic size is used to illustrate the functioning of the proposed pricing scheme

bargaining without commitment a fundamental assumption in all sequential bargaining models is that when an offer is accepted the bargaining terminates with the implementation of that proposal the proposer cannot change his mind he is in effect committed to his proposal in this short paper we explore the consequence of relaxing this rather strong commitment assumption our main result indicates that this commitment assumption is a fundamental reason for the uniqueness of the subgame perfect equilibrium partition in the rubinstein bargaining model this main result states that if the common discount factor of each bargainer is greater than l d 0 7 then any partition of the unit size cake can be supported as a subgame perfect equilibrium of the modified rubinstein bargaining model modified in that the commitment assumption is dropped the multiplicity of equilibria is generated by constructing supergame type punishment strategies journal ofeconomic literature classification number 026

unobservable investment and the hold up problem we study a two person bargaining problem in which the buyer may invest and increase his valuation of the object before bargaining we show that if all offers are made by the seller and the time between offers is small then the buyer invests efficiently and the seller extracts all of the surplus hence bargaining with frequently repeated offers remedies the hold up problem even when the agent who makes the relation specific investment has no bargaining power and contracting is not possible we consider alternative formulations with uncertain gains from trade or two sided investment

renegotiation proof implementation and time preferences this paper explores how the requirement that the implementation of contracts be renegotiation proof affects the set of contracts that can be implemented in a seller buyer scenario in which the information regarding the agents valuations is nonverifiable this paper explicitly adds a time dimension to an implementa tion problem and introduces a natural criterion of renegotiation proofness for the case of time consuming renegotiation the main insight gained is that the addition of the time dimension enlarges significantly the set of contracts that can be implemented in a renegotiation proof manner jel c70 d23 this paper explores how the requirement that the implementation of contracts be renegotiation proof affects the set of con tracts that can be implemented in a seller buyer scenario in which the informa tion regarding the agents valuations is non verifiable the paper s main contributions are that first it explicitly adds a time di mension to an implementation problem and second it introduces a natural criterion of renegotiation proofness for the case of time consuming renegotiation for concreteness the discussion will be conducted in the context of the following example there are two agents a seller and a buyer who sign a contract for the sale of one unit in the future their valuations for the unit denoted by s and b respectively are not known when they sign the contract they become known to both parties after the contract is signed and before it is imple mented thus when it comes to implement ing the contract the parties information is complete but it is assumed to be nonverifi able i e not observable to third parties such as a court 1 when they sign the con tract the parties want to specify for any possible realization of the valuations s b whether or not there will be trade and the price p s b at which it will take place the contract describes the procedure that will be followed after the valuations are real ized the purpose of this procedure is to make sure that the original intentions of the parties are indeed carried out the idea is that the steps laid out in the contract are independent of s b and hence are en forceable by a third party or by a social convention in game theoretic terms a contract specifies a game form that imple ments the function p in the sense that for all s and b p s b is the resulting game s unique subgame perfect equilibrium out come in the context of this scenario we shall investigate the set of price functions p s b that can be so implemented by a contract and examine how this set is affected by the requirement that the contract be renegotia

economic valuation of reserves in power systems with high penetration of wind power this paper proposes a methodology to determine the required level of spinning and nonspinning reserves in a power system with a high penetration of wind power the computation of the required reserve levels and their costs is achieved through a stochastic programming market clearing model spanning a daily time horizon this model considers the network constraints and takes into account the cost of both the load shedding and the wind spillage the methodology proposed is illustrated using an example and a realistic case study some conclusions are finally drawn

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

coasean bargaining in the presence of pigouvian taxation coasean arguments against the pigouvian perspective are well established a central tenet in this criticism argues that a pigouvian tax may be a source of inefficiency if parties were to bargain in the presence of a pigouvian tax allocative inefficiencies would occur the so called buchanan stubblebine turvey theorem by analyzing a coasean environment where the appropriation of property rights is costly we show coasean bargaining in the presence of a pre existing pigouvian tax may be superior this has implications for policy where dual regulatory environments exist such as regulation at the state and federal level as well as environmental liability and litigation

the impacts of transmission topology control on the european electricity network the european union is targeting a 20 share of energy from renewable resources by 2020 and this increase is in turn expected to lead to operational challenges that will require various congestion management actions by system operators in this paper we deal with topology control of the transmission network as a congestion management resource and evaluate the impacts of topology control on the european electricity network to do this we co optimize unit commitment and transmission switching over 24 h and we use a decomposition scheme to tackle the resulting large scale problem our analysis is conducted on different scenarios of load and renewable power generation we find that topology control results in significant cost savings within europe which tend to be inversely related to net load the robustness of our results is supported by an extensive sensitivity analysis

the theory of the firm as governance structure from choice to contract the propositions that organization matters and that it is susceptible to analysis were long greeted by skepticism by economists one reason why this message took a long time to register is that it is much easier to say that organization matters than it is to show how and why the prevalence of the science of choice approach to economics has also been an obstacle as developed herein the lessons of organization theory for economics are both different and more consequential when examined through the lens of contract this paper examines economic organization from a science of contract perspective with special emphasis on the theory of the firm

reliability and reserve in competitive electricity market scheduling power systems are typically scheduled at least cost subject to operational and security constraints generally no account is taken of generator reliability when scheduling units also the security criteria which include reserve are usually deterministic in nature this paper proposes a method to consider generator reliability explicitly in the scheduling problem a competitive structure is proposed which includes a market for reserve this is formulated as an augmented lagrangian dual function and is solved using a new recurrent neural network the price for reserve is used along with the unit reliability to find a balance between the cost of reserve and the risk of not providing it

the swiss reserve market stochastic programming in practice this paper presents the evolution and design of the swiss reserve market and describes its two stage stochastic market clearing model in switzerland the reserve market comprises weekly and daily auctions the decision making problem is to determine the amount of reserves that should be procured in each market stage the stochasticity stems from daily offers which are not available at the beginning of the week when the first stage decisions are made the new market clearing model minimizes expected procurement costs of reserves while taking reserve dimensioning criteria and market properties into consideration since the last week of january 2014 this model has been clearing the reserve market in switzerland to our knowledge this is the first real world implementation of a stochastic market clearing model in electricity markets

a stochastic programming model for a day ahead electricity market with real time reserve shortage pricing we present a multi period stochastic mixed integer programming model for power generation scheduling in a day ahead electricity market the model considers various scenarios and integrates the idea of reserve shortage pricing in real time instead of including all the possible scenarios we parsimoniously select a certain number of scenarios to limit the size of the model as realistic size models are still intractable for exact methods we propose a heuristic solution methodology based on scenario rolling that is capable of finding good quality feasible solutions within reasonable computation time

the mirrlees approach to mechanism design with renegotiation with applications to hold up and risk sharing the paper studies the implementation problem first analyzed by maskin and moore 1999 in which two agents observe an unverifiable state of nature and may renegotiate inefficient outcomes following play of the mechanism we develop a first order approach to characterizing the set of implementable utility mappings in this problem paralleling mirrlees s 1971 first order analysis of standard mechanism design problems we use this characterization to study optimal contracting in hold up and risk sharing models in particular we examine when the contracting parties can optimally restrict attention to simple contracts such as noncontingent contracts and option contracts where only one agent sends a message

multi area unit scheduling and reserve allocation under wind power uncertainty this paper proposes a decentralized methodology to optimally schedule generating units while simultaneously determining the geographical allocation of the required reserve we consider an interconnected multi area power system with cross border trading in the presence of wind power uncertainty the multi area market clearing model is represented as a two stage stochastic programming model the proposed decentralized procedure relies on an augmented lagrangian algorithm that requires no central operator intervention but just moderate interchanges of information among neighboring regions the methodology proposed is illustrated using an example and a realistic case study

using a system model to decompose the effects of influential factors on locational marginal prices locational marginal prices lmps are influenced by various factors such as load uncertainty thermal limit capacity reserve and market power we build a system model to quantitatively analyze the effects of these individual factors and their interactions on the mean and standard deviation of the lmps assuming that the factors are either active or inactive according to the sensitivity analysis results from convex quadratic programming lmps are piecewise linear functions of demand variation which is a key property used in the computation this paper attempts to answer the following types of questions 1 to what extent does market power raise the lmps above the marginal cost 2 what effects will generation or transmission capacity expansion have on relieving high lmps under high demand scenarios an ieee 30 bus test system is used as an example to demonstrate our approach

security constrained unit commitment for simultaneous clearing of energy and ancillary services markets this paper introduces a security constrained unit commitment scuc model with emphases on the simultaneous optimization of energy and ancillary services markets benders decomposition is used to decouple the scuc into a unit commitment uc master problem and hourly network security checking subproblems lagrangian relaxation is used to decouple the uc problem into individual single unit commitment problems dynamic programming is used to find the optimal commitment decision a simultaneous marginal curve algorithm is proposed to find the optimal values of energy and ancillary services a six bus system with three units and the ieee 118 bus system with 54 units are analyzed to illustrate the proposed model

spot pricing of capacities for generation and transmission of reserve in an extended poolco model the poolco model is emerging as one of the most acceptable options for organizing the spot market of electricity although the model represents a reasonable and safe transition from present industry practices to what is required in a competitive electricity market many important issues remain to be resolved in particular issues regarding reliability related services are of a special concern to the industry this paper is devoted to the issue of reserve service delivery and pricing the poolco model is extended in this paper to include spot pricing of reserve generation and transmission capacities as well as demand side bidding in the authors extended model suppliers submit bids for power as well as for reserve capacities a new formulation of the extended security constrained economic dispatch which allocates both power and reserve generation resources is presented in this paper the dispatch of the resources is constrained by limitations of system transmission capacities the proposed formulation is considered to be relevant not only in the poolco but in a more general setup an illustrative example is used to introduce concepts and present results finally some general issues regarding formats of proposals balance of payments and uniqueness of the prices that apply equally to both the original and extended poolco models are discussed

stochastic multiobjective market clearing of joint energy and reserves auctions ensuring power system security in this paper a stochastic multiobjective framework is proposed for day ahead joint market clearing the proposed multiobjective framework can concurrently optimize competing objective functions including augmented generation offer cost and security indices overload index voltage drop index and voltage stability margin besides system uncertainties including generating units and branches contingencies and load uncertainty are explicitly considered in the stochastic market clearing scheme the solution methodology consists of two stages which firstly employs roulette wheel mechanism and monte carlo simulation mcs for random adaptive 24 h scenario generation wherein the stochastic multiobjective market clearing procedure is converted into its respective deterministic equivalents scenarios in the second stage for each deterministic scenario a multiobjective mathematical programming mmp formulation based on the epsiv constrained approach is implemented for provision of spinning reserve sr and nonspinning reserve nsr as well as energy the mmp formulation of the market clearing process is optimized while meeting ac power flow constraints and expected interruption cost eic the ieee 24 bus reliability test system rts 24 bus is used to demonstrate the performance of the proposed method

incomplete contracts specific investments and risk sharing an optimal contract design problem is considered contracts which are incomplete and simple are used to investigate the extent to which constrained revisions can mitigate inefficiencies resulting from contractual incompleteness an optimal contract is characterized in two cases first when a contract is being used to facilitate trade between two risk neutral parties who must make relationship specific investments it is possible to implement the first best by a simple contract second when a contract is being used to share risk it is generally not possible to implement the first best when one party is risk neutral however it is possible to implement the first best by assigning all the ex post decision rights to that party

economic consequences of alternative solution methods for centralized unit commitment in day ahead electricity markets many wholesale electricity markets call on the independent system operator iso to determine day ahead schedules for generators based on a centralized unit commitment up until recently the lagrangian relaxation lr algorithm was the only practical means of solving an iso scale unit commitment problem and it was the solution technique used by most isos johnson et al 1 demonstrate however that equity incentive and efficiency issues will arise from use of lr solutions because different commitments that are similar in terms of total system costs can result in different surpluses to individual units recent advances in computing capabilities and optimization algorithms now make solution of the mixed integer programming mip formulation by means of branch and bound b b tractable often with optimality gaps smaller than those of lr algorithms which has led some isos to adopt b b algorithms and others proposing to do so with the move towards b b one obvious question is whether the use of mip will eliminate or reduce the issues with lr raised by johnson et al using actual market data from an iso we demonstrate that both lr and mip solutions will suffer the same equity issues unless the iso unit commitment problems can be solved to complete optimality within the allotted timeframe which is beyond current computational capabilities our results further demonstrate that the size of the payoff deviations are not monotone in the size of the optimality gap meaning smaller optimality gaps from b b will not necessarily mitigate the issues johnson et al raise we show that the use of make whole payments which ensure units recover any startup and no load costs not recovered by inframarginal energy rents can help to reduce surplus volatility and differences to some extent

sunk costs and the inefficiency of relationship specific investment it is well known that relationship specific investment will be inefficient when the parties are unable to write binding long term contracts in this note i exploit some of the recent developments in strategic bargaining theory in order to explore the relationship between the degree of inefficiency in the level of such relationship specific investment and the degree of sunkness in the cost of investment one result obtained is that the underinvestment result is not sensitive to the degree of sunkness in the cost of investment another result is that each player may actually overinvest when the cost of investment is not sunk

economic and environmental implications of different approaches to hedge against wind production uncertainty in two settlement electricity markets a pjm case study abstract this paper examines the economic and environmental outcomes of four two settlement electricity market clearing designs the first design corresponds to a deterministic market clearing dmc similar to the mechanism currently used in organized wholesale electricity markets in the united states the other three designs account for the day ahead da wind power production uncertainty into the da market mechanisms either implicitly or explicitly an augmented deterministic market clearing admc design introduces da ramp capability products these products ensure adequate and ramp feasible electricity generation capacity commitments in the da stage to cope with the real time realization of wind power generation a hybrid deterministic market clearing hdmc design augments admc by explicitly integrating a characterization of wind power production uncertainty into the residual unit commitment ruc process which is run after the da market is closed using stochastic programming the last design referred to as stochastic market clearing smc uses stochastic optimization to explicitly account for wind power production uncertainty in the da market clearing mechanisms i e da unit commitment and economic dispatch the four market clearing designs are assessed by simulating the electricity market operations of a test system and comparing their results in terms of operating costs prices costs and revenues of different types of producers consumer s payments integration of wind power and air emissions the test system has 12 of the capacity of pjm s fossil fired power generation fleet and uses data on coincident demand and wind power production from the bonneville power administration bpa system during years 2010 2014 the simulations are performed hourly for a whole year results show that smc is superior as its costs reductions are more than two times the improvements attained by admc and hdmc also smc results in electricity prices that are better aligned with operation costs cuts the spread between the day ahead and real time prices by 40 reduces out of market short term revenue sufficiency payments by 58 reduces co2 emissions by 3 52 and decreases power plants cycling hdmc is a distant second best market design relative to dmc it achieves a reduction in total costs that is less than half the reduction achieved by smc a reduction in out of market payments that is 80 of the reduction attained by smc and an increase in wind power integration that is

demand side reserve offers in joint energy reserve electricity markets we propose a market model that includes demand side reserve offers and where energy and reserve are jointly dispatched generators and consumers can submit offers and bids on five distinct products energy upspinning reserve downspinning reserve and two kinds of standby reserve the resources are scheduled and dispatched in a joint auction through a mixed integer optimization program the extra scheduling flexibility introduced by demand side reserve offers can lead to significant gains in economic efficiency thus the results suggest that not only do the consumers increase their profits but in addition the market power of the generators is reduced