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

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

comparing consumption based asset pricing models we make use of a recently developed method to estimate the intertemporal mar ginal rate of substitution consistent with the fluctuations of asset return data from the toronto stock exchange these estimates are then used to evaluate various parametric specifications for preferences often used in empirical studies of consumption and asset returns in contrast to existing studies we are able to perform a formal statistical comparison of these models we consider six extensions of the usual power utility model and we find that none can be said to be a demonstrable improvement on the standard model

reducing greenhouse gas emissions lessons from state climate action plans we examine how state level factors affect greenhouse gas ghg reduction policy preference across the united states by analyzing climate action plans caps developed in 11 states and surveying the cap advisory group members this research offers insights into how states approach the problem of choosing emissions abatement options that maximize benefits and minimize costs given their unique circumstances and the constellation of interest groups with power to influence state policy the state caps recommended ten popular ghg reduction strategies to accomplish approximately 90 of emissions reductions but they recommended these popular strategies in different proportions a strategy that is heavily relied on in one state s overall portfolio may play a negligible role in another state this suggests that any national policy to limit ghg emissions should encompass these key strategies but with flexibility to allow states to balance their implementation for the state s unique geographic economic and political circumstances survey results strongly support the conclusion that decisions regarding ghg reductions are influenced by the mix of actors at the table risk perception is associated with job type for all strategies and physical and or geographic factors may underlie the varying reliance on certain ghg reduction strategies across states

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

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

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

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

evolution toward standardized market design the evolution toward the standardized market design smd is presented in this paper with references to the market developments in new zealand australia pjm iso ne and ercot in the development of market designs two main objectives market liquidity facilitating bilateral trading and pricing efficiency facilitating congestion management have been pursued the efforts to balance the seemingly conflicting objectives led to most markets designed with a uniform or zonal pricing model introduction of locational marginal pricing and evolution of transmission rights from physical to financial form made it possible to harmonize the potentially conflicting goals in a market design the close coupling between energy and ancillary services requires that markets for these commodities be carefully coordinated different operational practices and reliability standard requirements have led to major differences in ancillary service market designs

swing contracts with dynamic reserves for flexible service management the increasing penetration of variable energy resources in modern electric power systems requires additional flexibility in reserve provision to maintain reliable and efficient grid operations however full recognition and appropriate compensation of this flexibility is difficult to ensure within current power market designs due to rigidity in reserve definitions and requirements this paper proposes a new mixed integer linear programming formulation for the optimal clearing of a day ahead market based on swing contracts with dynamically updated regulation reserve zones five bus and 30 bus test cases are used to illustrate the effectiveness of the proposed new market design

understanding carbon lock in abstract this paper narrative argues that industrial economies have been locked into fossil fuel based energy systems through a process of technological and institutional co evolution driven by path dependent increasing returns to scale it is asserted that this condition termed carbon lock in creates persistent market and policy failures that can inhibit the diffusion of carbon saving technologies despite their apparent environmental and economic advantages the notion of a techno institutional complex is introduced to capture the idea that lock in occurs through combined interactions among technological systems and governing institutions while carbon lock in provides a conceptual basis for understanding macro level barriers to the diffusion of carbon saving technologies it also generates questions for standard economic modeling approaches that abstract away technological and institutional evolution in their elaboration the question of escaping carbon lock in is left for a future paper

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

carbon geography the political economy of congressional support for legislation intended to mitigate greenhouse gas production over the last 5 years the u s congress has voted on several pieces of legislation intended to sharply reduce the nation s greenhouse gas emissions given that climate change is a world public bad standard economic logic would predict that the united states would free ride and wait for other nations to reduce their emissions within the congress there are clear patterns to who votes in favor of mitigating greenhouse gas emissions this paper presents a political economy analysis of the determinants of pro green votes on such legislation conservatives consistently vote against such legislation controlling for a representative s ideology representatives from richer districts and districts with a lower per capita carbon dioxide footprint are more likely to vote in favor of climate change mitigation legislation representatives from districts where industrial emissions represent a larger share of greenhouse gas emissions are more likely to vote no jel q54 q58 r50

canadian consumption and portfolio shares in this paper we gauge consumption and portfolio shares rather than the traditional pricing implications we study both aggregated financial tangible and human and disaggregated deposits stocks insurance and pensions assets the empirical shares are computed from recent aggregate canadian data the theoretical shares are constructed from a flexible specification of both investors preferences and investment opportunities our results reveal that the theoretical shares statistically match observed consumption and aggregated assets but not disaggregated assets also our findings for corporate stocks are consistent with the empirical asset returns literature finally our findings for other assets highlight several new striking features jel classification g11 consommation et parts de porte feuille au canada cette recherche analyse la consommation et les parts de portefeuille plutot que les prix des actifs nous etudions les actifs agreges i e financiers tangibles et humains ainsi que desagreges i e depots actions et caisses de retraite et assurance les parts empiriques sont calculees pour des donnees agregees canadiennes recentes les parts theoriques sont construites a partir d un modele flexible en ce qui a trait aux preferences et aux possibilites d investissement nos resultats demontrent que les parts theoriques reproduisent la consommation et les parts agregees mais pas les parts desagregees aussi nos resultats sont coherents avec ceux de la litterature empirique sur les rendements nos resultats concernant les autres actifs identifient d autres aspects caracteristiques

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

a zonal congestion management approach using real and reactive power rescheduling in a deregulated electricity market it may always not be possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors system operators try to manage congestion which otherwise increases the cost of the electricity and also threatens the system security and stability in this paper a new zonal cluster based congestion management approach has been proposed the zones have been determined based on lines real and reactive power flow sensitivity indexes also called as real and reactive transmission congestion distribution factors the generators in the most sensitive zones with strongest and nonuniform distribution of sensitivity indexes are identified for rescheduling their real power output for congestion management in addition the impact of optimal rescheduling of reactive power output by generators and capacitors in the most sensitive zones has also been studied the proposed new zonal concept has been tested on 39 bus new england system and a 75 bus indian system

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

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

foreword for the special section on wind and solar energy uncovering and accommodating their impacts on electricity markets the articles in this special section focus on wind and solar energy and the impact these energy technologies and services will have the utility markets the aim is to give particular focus on some of the areas of investigation that may allow to 1 uncover the impact of renewables on electricity market e g on market clearing outcomes need for ancillary services and investment and to 2 propose methodological innovations being theoretically sound and of practical relevance in order to accommodate substantial shares of renewables in power systems electricity network and markets were designed based on a long history of dealing with various forms of dispatchable generation as well as a fairly predictable inelastic electricity consumption pattern in a centralized top down manner little uncertainty was involved on both generation and demand sides hence allowing for a design of electricity markets accounting for the necessity of a forward optimal allocation with a real time mechanism supporting actual power system operation

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

pricing energy and ancillary services in integrated market systems by an optimal power flow a detailed ac opf based formulation for procuring pricing and settling energy and ancillary service in simultaneous auctions by integrated market systems is presented the paper provides clear definitions of locational marginal prices for energy and ancillary service marginal prices in terms of lagrange multipliers the characteristics of the prices are analyzed especially when economic substitution among ancillary services is required the paper also evaluates the conditions under which opportunity costs are incurred to units that provide ancillary services it is particularly shown that the intuitive belief that the provision of regulation down service does not incur opportunity cost to the provider in general is not true

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

dc power flow revisited linear mw only ldquodcrdquo network power flow models are in widespread and even increasing use particularly in congestion constrained market applications many versions of these approximate models are possible when their mw flows are reasonably correct and this is by no means assured they can often offer compelling advantages given their considerable importance in today s electric power industry dc models merit closer scrutiny this paper attempts such a re examination

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

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

aggregate wealth in canada this paper describes a comprehensive measure of aggregate private sector wealth in canada that includes both human and nonhuman wealth wealth and its components are measured at a quarterly frequency from 1963 to 1994 human wealth is computed as the expected present value of aggregate labor income net of government expenditures using a finite state markov approximation to an estimated bivariate var for the real interest rate and net income growth nonhuman wealth is constructed by consolidating the assets and liabilities of the various sectors of the economy to the extent possible assets and liabilities are measured at market value

escaping carbon lock in this article explores the climate policy implications of the arguments made in understanding carbon lock in unruh 2000 which posited that industrial countries have become locked into fossil fuel based energy systems through path dependent processes driven by increasing returns to scale carbon lock in arises through technological organizational social and institutional co evolution culminating in what was termed as techno institutional complex tic in order to resolve the climate problem an escape from the lock in condition is required however due to the self referential nature of tic escape conditions are unlikely to be generated internally and it is argued here that exogenous forces are probably required

the role of out of market corrections in day ahead scheduling in order to ensure a reliable and continuous supply of electric energy operators must manage hundreds to thousands of generators with complex operating requirements maintain synchronism and manage thousands of transmission assets further complications arise due to stringent reliability standards resource uncertainty and limited economical energy storage with advances in algorithmic performance and hardware such optimization problems still require an engineered and simplified market structure market operators must therefore adjust the proposed market solution in order to obtain a valid solution an overview of existing industry practices related to such market adjustments referred to as out of market corrections is presented this paper also analyzes the market implications and required out of market corrections for the day ahead scheduling process multiple out of market correction algorithms are created and used to analyze the potential impacts on market solutions and settlements finally such solutions are compared against an extensive form stochastic unit commitment solution

stochastic optimization of sub hourly economic dispatch with wind energy we present a stochastic programming framework for a multiple timescale economic dispatch problem to address integration of renewable energy resources into power systems this framework allows certain slow response energy resources to be controlled at an hourly timescale while fast response resources including renewable resources and related network decisions can be controlled at a sub hourly timescale to this end we study two models motivated by actual scheduling practices of system operators using an external simulator as driver for sub hourly wind generation we optimize these economic dispatch models using stochastic decomposition a sample based approach for stochastic programming computational experiments conducted on the ieee rts96 system and the illinois system reveal that optimization with sub hourly dispatch not only results in lower expected operational costs but also predicts these costs with far greater accuracy than with models allowing only hourly dispatch our results also demonstrate that when compared with standard approaches using the extensive formulation of stochastic programming the sequential sampling approach of stochastic decomposition provides better predictions with much less computational time

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

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

load following reserves procurement considering flexible demand side resources under high wind power penetration the variable and uncertain nature of the leading renewable energy resources such as wind power generation imposes the development of a sophisticated balance mechanism between supply and demand to maintain the consistency of a power system in this study a two stage stochastic programming model is proposed to procure the required load following reserves from both generation and demand side resources under high wind power penetration besides a novel load model is introduced to procure flexible reserves from industrial clients load following reserves from load serving entities lse are also taken into account as well as network constraints load shedding and wind spillage the proposed methodology is applied to an illustrative test system as well as to a 24 node system

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

cost effectiveness of renewable electricity policies we analyze policies to promote renewable sources of electricity a portfolio standard rps raises electricity prices and primarily reduces gas fired generation a knee of the cost curve exists between 15 and 20 goals for 2020 in our central case and higher natural gas prices lower the cost of greater reliance on renewables a renewable energy production tax credit lowers electricity price at the expense of taxpayers which limits its effectiveness in reducing carbon emissions and it is less cost effective at increasing renewables than a portfolio standard neither policy is as cost effective as a cap and trade policy for achieving carbon emission reductions

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

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

incorporating post zonal reserve deployment transmission constraints into energy and ancillary service co optimization this paper presents a new approach implemented in miso day ahead and real time energy and ancillary service market clearing processes to address the reserve deliverability issue in this approach miso enhanced the co optimization process to incorporate post zonal reserve deployment transmission constraints reserves are procured within the co optimization to meet both market wide reserve requirements and ensure their deliverability on a zonal basis as a result zonal market clearing prices mcps for reserves can properly reflect the effects of zonal reserve deployment on transmission constraints under consideration

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

electricity market clearing with improved scheduling of stochastic production abstract in this paper we consider an electricity market that consists of a day ahead and a balancing settlement and includes a number of stochastic producers we first introduce two reference procedures for scheduling and pricing energy in the day ahead market on the one hand a conventional network constrained auction purely based on the least cost merit order where stochastic generation enters with its expected production and a low marginal cost on the other a counterfactual auction that also accounts for the projected balancing costs using stochastic programming although the stochastic clearing procedure attains higher market efficiency in expectation than the conventional day ahead auction it suffers from fundamental drawbacks with a view to its practical implementation in particular it requires flexible producers those that make up for the lack or surplus of stochastic generation to accept losses in some scenarios using a bilevel programming framework we then show that the conventional auction if combined with a suitable day ahead dispatch of stochastic producers generally different from their expected production can substantially increase market efficiency and emulate the advantageous features of the stochastic optimization ideal while avoiding its major pitfalls a two node power system serves as both an illustrative example and a proof of concept finally a more realistic case study highlights the main advantages of a smart day ahead dispatch of stochastic producers

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

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