medium term power planning with bilateral contracts this paper addresses the optimal management of hydropower resources on medium term the objective is to maximize the expected revenue of a producer and the decision variables are generation and forward contracts in each period for each scenario stochastic linear and nonlinear programming has been used as a framework for modeling and solution results are exposited for a norwegian power producer participating in nord pool the nordic power exchange

financial risk management in a competitive electricity market this paper proposes solutions for electricity producers in the field of financial risk management for electric energy contract evaluation the efficient frontier is used as a tool to identify the preferred portfolio of contracts each portfolio has a probability density function for the profit for important scheduling policies closed form solutions are found for the amount of futures contracts that correspond to the efficient frontier production scheduling must consider resource constraints it is found that without resource constraints the portfolio with the highest expected profit can be preferred even for a risk averse decision maker when resource constraints are present portfolios not corresponding to the maximum expected profit criteria will more frequently be preferred

forward contracts for the operation of an electricity industry under spot pricing a study is reported of the use of forward contracts as risk instruments for electricity industries operating under spot pricing forward contracts involve financial transactions or commitments which relate to a physical trade at a later time instance price setting and appropriate participant responses are discussed simulation studies are used to demonstrate that forward contracts offer participants an opportunity to reduce their risk exposure without removing the incentive to respond to higher spot prices

distortionary taxes and the provision of public goods economists have long been concerned with finding an efficient level of public expenditure the classic statement of the problem was given by paul samuelson 1954 an optimal level of expenditure is where the sum of the marginal rates of substitution between the public good and a reference good equals the marginal rate of transformation between the public good and the reference good mrs mrt however samuelson s formula assumes that all of the revenue needed to finance public goods can be raised with lump sum taxes since this is not generally possible the formula must be modified to account for the distortionary effects of the tax system an appropriate modification is to multiply the cost side of the equation by a term that is commonly called the marginal cost of public funds mcf in the case of samuelson s formula where government is entirely financed with lump sum taxes the mcf would be exactly 1 0 in the traditional view of economists distortionary taxes cause the mcf to be greater than one thus raising the cost of providing public goods in this paper we discuss some cases where the mcf may be less than one we will illustrate this possibility using numerical examples for labor taxes

structure cooperation and the flow of market information this article explores the potential impact of individual consumer decisions to transmit or withhold word of mouth information on the flow of information in a market information flow is examined in networks composed of graphs and nodes where graphs represent channels that foster information flow and nodes represent sentient decision makers who can potentially impede or foster information flow we assert that actors in embedded markets first judge the moral hazards imposed by the information they consider for transmission and the social context of transmission and then moderate their decisions to transmit the information in light of these judgements we analyze this process using a modified version of marshall sahlins s social exchange theory examine the plausibility of this analysis using two laboratory experiments and explore the consequences of this behavior at the aggregate level using a computer simulation our view highlights the importance of the interplay of individuals and their social context for understanding word of mouth processes

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

the marginal welfare cost of public funds theory and estimates abstract we derive a general analytic formula for the marginal welfare cost mwc of public funds without imposing restrictive assumptions on preferences or technologies the framework encompasses the various special cases previously considered and reconciles the disparities among the reported estimates of mwc unresolved differences in existing estimates are fully explained by appropriate interpretations of intended thought experiments and alternative assumptions about the elasticity of labor supply with respect to public spending further progress in measuring mwc requires empirical estimation of labor supply functions that include government spending as an explanatory variable

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

forward contracting and selling price determination for a retailer to procure the electric energy to be sold to its clients a retailer has to face two major difficulties while buying electric energy it must cope with uncertain pool prices or sign forward contracts at higher average prices while selling electricity it should handle the uncertainty of the end user demand and the fact that customers might choose a different retailer if the selling price is not competitive enough we propose a risk constrained stochastic programming framework to decide which forward contracts the retailer should sign and at which price it must sell electricity so that its expected profit is maximized at a given risk level the developed model takes into account the elastic behavior of end users with respect to the selling price offered by the retailer a realistic case study illustrates the methodology proposed

optimal involvement in futures markets of a power producer this paper addresses the optimal involvement in a futures electricity market of a power producer to hedge against the risk of pool price volatility the considered trading horizon spans one whole year recognizing the highly uncertain nature of future pool prices a stochastic programming framework with recourse is used to model this decision making problem the resulting problem is a large scale mixed integer linear programming problem scenario reduction techniques are used to make this problem tractable risk is properly modeled using the cvar methodology results from a realistic case study are provided and analyzed some conclusions are finally drawn

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

optimal referral bonuses with asymmetric information firm offered and interpersonal incentives referral bonuses in which an existing customer gets an in kind or cash reward for referring a new customer are a popular way to stimulate word of mouth in this paper we examine key firm decisions about such bonuses others have studied referral bonus programs a key difference is that we study the role of recommendations not just in spreading awareness as they do but also in providing assessments we start with the idea that people have a variety of reasons for making product recommendations including placing a value on a friend s outcome with a product they recommend we apply that idea in a context of asymmetric information a customer combines his knowledge about the product and his familiarity with friends tastes making him more informed than the friends thus the recommendation is a signal about the value of the product to the friend in this setting we consistently find that the greater the concern for others outcomes the higher the referral bonus should be as long as the firm cannot more efficiently motivate recommendations with a lower price moreover if price is the more efficient lever the optimal bonus is zero and the optimal price is low we also show that greater concern tends to reduce firm profit and in some cases actually reduces consumer welfare as well

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

scenario reduction for futures market trading in electricity markets to make informed decisions in futures markets of electric energy stochastic programming models are commonly used such models treat stochastic processes via a set of scenarios which are plausible realizations throughout the decision making horizon of the stochastic processes the number of scenarios needed to accurately represent the uncertainty involved is generally large which may render the associated stochastic programming problem intractable hence scenario reduction techniques are needed to trim down the number of scenarios while keeping most of the stochastic information embedded in such scenarios this paper proposes a novel scenario reduction procedure that advantageously compares with existing ones for electricity market problems tackled via two stage stochastic programming

markets and pricing for interruptible electric power a market is proposed for interruptible or callable forward contracts for electric power in which the consumer grants the power supplier the right to interrupt a given unit of load in return for a price discount the callable forward contracts are traded continuously until the time of use this allows recourse for those customers with uncertain demand while risk averse consumers can minimize their price risk by purchasing early callable forward contracts are simple in form and can be directly incorporated into the utility s economic dispatch procedure

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

a marginal cost of funds approach to multi period public project evaluation implications for the social discount rate abstract although the use of marginal cost of funds mcf has been widely appreciated in public finance literature discussions of mcf have been confined to a static setting this paper develops a multi period project evaluation rule that is based on mcf unlike previous approaches the parameters required for implementing the mcf rule are independent of projects under consideration a lesson from this paper is that the government discount rate policies that are largely based on the concepts of social discount rate and shadow price of capital should be rewritten with the use of parameters representing mcf

on the marginal welfare cost of taxation this paper develops a rigorous partial equilibrium analysis of the determinants of margin al welfare cost mwc of taxes on labor earnings it shows that four key parameters interact to determine the magnitude of mwc using aggregate data and plausible ranges of values for the parameters mwc can vary from under 10 percent to more than 300 percent of marginal tax revenue intermediate parameter values sugge st mwc is in the 25 50 percent range however the more extreme estimates cannot be ruled out on the basis of available evidence suggesting that mwc cannot yet be copyright 1987 by american economic association

optimal public good provision with limited lump sum taxation it is often argued that the use of distortionary taxation lowers the optimal provision of public goods below its optimal level in a first best economy which contains no restrictions on lump sum taxation however this issue is usually investigated using commodity tax models that contain no lump sum taxes this paper examines a many consumer economy in which the only tax instruments are commodity taxes and a poll tax subsidies are negative taxes the optimal level of public good provision in this economy typically exceeds the first best level at least for distributionally neutral public goods copyright 1991 by american economic association

a review on risk constrained hydropower scheduling in deregulated power market in deregulated power market hydro producer has in principle no other objective than to produce electricity and sell with maximum profit with lower market risk attention must focus on profit uncertainty caused by uncertainty in spot prices and reservoir inflow the purpose of this review is to assess the state of the art in hydropower operations considering profit risk under uncertainty and consider future directions for additional research and application physical and financial tools to hedge risk in bilateral market and risk assessment methods are all discussed in detail furthermore production resources can also be used to manage risk to a certain extent this concept when be integrated with variety of risk management methods under stochastic optimal framework has operational significance for hydro producer participating in electricity market

the impact of investors risk aversion on the performances of capacity remuneration mechanisms abstract this paper analyses the impact of risk aversion on the performances of capacity remuneration mechanisms with investors facing an uncertain peak load three market designs are studied for this purpose a competitive energy only market a capacity market and a strategic reserve mechanism a simulation model based on system dynamics is developed in order to represent investment decisions and analyse the behaviour of each market design risk aversion is modelled through the computation of conditional value at risk the results are discussed in terms of impact on the reliability ability to limit shortages and cost total generation costs of the studied market designs when comparing the three market designs the capacity market seems to be the least affected by the introduction of risk aversion both in terms of cost and reliability this result suggests that implementing a capacity market is preferable in order to deal with the adverse effects of risk aversion given the simulations and parameters that were used

discounting according to output type federal discount rate policies advocate both a high rate representing the marginal productivity of capital and a low rate representing the government borrowing rate these differential discount rate policies could be inconsistent and biased in favor of projects on which the lower discount rate is applied this paper shows that the coexistence of different discount rates may be appropriate depending on the type of project output when a project s outputs are perfect substitutes for private consumption both its costs and benefits should be discounted using the marginal productivity of capital however if the project s outputs are separable in the utility function the benefits should be discounted using the net of tax rate of return

electricity markets volatility estimates regularities and risk management applications the recent deregulation of the market for electric power in many parts of the us and canada has expanded the set of potential tools for managing the types of risks faced by both generators and consumers of electric power in particular manufacturing and other firms whose operations are powered by electricity now face on a continuing basis the engineering management decisions concerning whether they should buy or produce electricity and if they are to buy or sell electricity what types of contracts are optimum these types of risk management decisions typically involve futures forwards options and other financial derivatives the price and volatility of electric power are known to play an essential role in determining which of these instruments should be used however electricity as a commodity possesses certain special features not shared by other commodities and hence its risk properties are not yet well understood in this paper we consider and test certain hypotheses about the properties of electricity price using recent market data we find that electricity prices possess certain volatility and other systematic properties that can be characterized by the type and method of delivery of electricity these properties can be used by firms in formulating their optimal demand and supply schedules of electric power

optimality with hydropower system this paper studies an electricity producer s long term optimality in the case of a multireservoir hydropower system the model solves the optimal production process and trading strategy of electricity and weather derivatives by maximizing the utility from production and terminal water reservoir level the optimal trading strategy hedges the rainfall and electricity price uncertainties

the numeraire matters in cost benefit analysis abstract the choice of numeraire is shown to be important in cost benefit analysis when a public good is involved individual consumers marginal rates of substitution will generally differ thus the less valuable the numeraire is to a person the higher the number required to express his net benefit and the more will his interest weigh in the total sum the choice of money as numeraire is systemetically favourable to those who value money the least relative to alternative numeraires

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

how can a competitive market for electricity be made compatible with the reduction of greenhouse gas emissions abstract under what conditions can the creation of a competitive market for electricity allow the efficient use of energy to compete on an equal basis with electricity supply thus providing both economic benefits to consumers and reductions in greenhouse gas emissions in this paper the current micro economic reforms to the australian electricity industry are taken as a case study to investigate this question it is found that the proposed competitive market for electricity contains barriers to the wider implementation of efficient energy use and renewable energy which are additional to those already existing in a highly regulated market in order to allow efficient energy use to compete on an equal basis with electricity supply it is necessary to create a market for energy services not electricity at the retail level to do this requires institutional changes correct pricing is not sufficient

optimization of electricity retailer s contract portfolio subject to risk preferences when an electricity retailer faces volume risk in meeting load and spot price risk in purchasing from the wholesale market conventional risk management optimization methods can be quite inefficient for the management of an electricity contract portfolio in this context we develop a multistage stochastic optimization approach which accounts for the uncertainties of both electricity prices and loads and which permits the specification of conditional value at risk requirements to optimize hedging across intermediate stages in the planning horizons our experimental results based on real data from nordpool suggest that the modeling of price and load correlations is particularly important the sensitivity analysis is extended to characterize the behavior of retailers with different risk attitudes thus we observe that a risk neutral retailer is more susceptible to price related than load related uncertainties in terms of the expected cost of satisfying the load and that a risk averse retailer is especially sensitive to the drivers of the forward risk premium

federal discount rate policy the shadow price of capital and challenges for reforms abstract this paper addresses the problem of determining discount rate policies that are both consistent with basic economic principles and implementable given real world constraints the paper first examines the discounting policies of the three federal oversight and budget agencies as they apply to public investment regulation lease purchase and asset divestiture decisions one prominent technique that has been suggested as a means of improving discounting policy the shadow price of capital approach is then considered in detail key aspects of its implementation are considered including the determination of program cost incidence rates of saving and reinvestment and proper aggregation of capital costs the analysis suggests that there are significant empirical challenges associated with this approach

financial optimization in the turkish electricity market markowitz s mean variance approach abstract electricity constitutes the input into many products that produced by industry and used by people hence it can be considered as a product or service that has vital importance in human life and economy since it has such special properties of instantaneous production and consumption obligation and unfeasible storage electricity market is not like other markets in a competitive electricity market generation company faces price risks and delivery risks so that risk management is an important part of a generation company and can deeply effect companies profitability this paper focuses on electricity generation asset allocation between bilateral contracts such as forward contracts and daily spot market considering constraints of generating units and spot price risks the problem is to find the optimal portfolio based on known electricity generation total costs bilateral contract prices it employed turkish historical balanced market hourly system marginal and day ahead hourly market prices between of 2006 and 2011 there are limited studies about portfolio optimization in electricity markets in literature and this paper should be considered frontier study taking spot market s hourly prices separately as risky assets markowitz mean variance optimization which is claimed to be the beginning of modern portfolio theory in financial sector is used to demonstrate this approach mean variance optimization has been successfully applied to all cases that modeled for electricity market some suggestions for future work are also listed in this paper

a gravity based multidimensional scaling model for deriving spatial structures underlying consumer preference choice judgments in multidimensional unfolding multidimensional scaling mds procedures the predicted utility of a brand for a consumer is inversely related to the distance between that consumer s ideal point and the brand position in the derived space most mds models treat all brands the same regardless of their respective market share in many product categories however consumer preferences are heavily influenced by the size of the existing market share i e the brand mass this article presents two versions of a new spatial methodology that incorporates the effects of brand as well as consumer mass via a spatial gravity model of consumer utility that is the attraction of a brand for a consumer depends not only on the distance of the brand from a consumer s ideal point but also on the current market size of the brand as well as the consumer purchase pattern and volume one version of the proposed model estimates brand positions and individual ideal points with two way or three way pick any n binary choice data the second version we develop provides the same spatial decomposition for two way or three way metric preference dominance data we also develop a series of nested mds models to estimate test and compare four different model structures with respect to any common data set we illustrate the proposed methodology using an actual commercial application involving physician prescription behavior and examine competing model fits

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

a generalized approach to multigeneration project evaluation 1 introductionit is well known that the choice of discount rate plays a significant role in the ranking of projects with varying time paths of costs and benefits for public projects the choice of the appropriate social discount rate sdr is not clear cut even in the context of short lived projects in which costs and benefits occur within a single generation in particular when capital taxes produce a wedge between gross and net rates of return should one discount at the economy s rate of return the before tax rate or the individual s rate of return the after tax rate in the single generation context the literature falls in two camps 1 one camp argues that the appropriate sdr is a weighted average of the gross and net rates of return with weights typically determined by the fractions of resources drawn from consumption and private investment respectively 2 a second camp argues that future benefits should be discounted at the net rate of return but that the initial investment should be multiplied by a scale factor so that the direct costs of the project can be expressed in terms of consumption units 3both approaches suffer from severe implementation problems for the first approach there is no general formula for the weights needed to calculate the sdr as a weighted average of two market rates of return dreze 1974 indeed the appropriate sdr to use is project specific stiglitz 1982 without a systematic methodology to derive project specific sdrs the weighted average approach is hard to implement for the second approach which equalizes the sdr to the net rate of return the scale factor the opportunity cost of public investment must be quantified the opportunity cost of public investment depends on whether resources come from private investment or consumption and on the calculation of the present value of the future consumption yielded by a unit of capital discounted at the net rate of return that is the shadow price of capital as lind 1997 points out however there is no general agreement on a specific procedure for calculating the shadow price of capital indeed the concept of the opportunity cost of public investment suffers the same project dependence problem as the first view of the sdr diamond 1968 multigeneration projects such as nuclear waste disposal natural resource conservation or even social security reform further complicate discount rate choice specifically intergenerational equity in addition to intertemporal efficiency plays a role in determining the appropriate social discount rate for multigeneration public project evaluation 4 as in the single generation context there are two competing views on the appropriate discount rate when evaluating multigeneration projects the descriptive and the prescriptive approaches 5the descriptive approach to discounting is a market based approach it does not rely on an explicit social welfare function swf or the pure time preference rate embedded in the swf however the descriptive approach works under the assumption that intergenerational compensation through changes in the tax debt policy is available 6 it is argued that under appropriate intergenerational compensation the market rates of return are still relevant for calculating the sdr for multigeneration project evaluation and in general the sdr should be a weighted average of the gross and net rates of return this descriptive view of setting the sdr equal to the market return appears to underlie the office of management and budget s omb adoption of 7 as the appropriate discount rate for federal programs 7the intent of the prescriptive approach is to use the social discount rate as an expression of ethical judgment on how consumption of future generations should be compared to consumption of current generations

managing the financial risks of electricity producers using options abstract electricity producers participating in electricity markets face risks pertaining to both selling prices and the availability of the production units among electricity derivatives options represent an adequate instrument to manage these risks in this paper we propose a multi stage stochastic model to determine the optimal selling strategy of a risk averse electricity producer including options forward contracts and pool trading a detailed case study highlights the advantages of an option vs a forward contract to hedge against the financial risks related to pool prices and unexpected unit failures

hedging with futures contracts in a deregulated electricity industry this paper is a statistical study of direct and cross hedging strategies using futures contracts in an electricity market a comparison of the strategies is based on the standard deviation or risk of the values of the hedging positions results indicate that the use of electricity futures contracts is superior to using other related futures contracts such as crude oil

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

hedging strategies in energy markets the case of electricity retailers as market intermediaries electricity retailers buy electricity from the wholesale market or self generate for re sale on the retail market electricity retailers are uncertain about how much electricity their residential customers will use at any time of the day until they actually turn switches on while demand uncertainty is a common feature of all commodity markets retailers generally rely on storage to manage demand uncertainty on electricity markets retailers are exposed to joint quantity and price risk on an hourly basis given the physical singularity of electricity as a commodity in the literature on electricity markets few articles deal on intra day hedging portfolios to manage joint price and quantity risk whereas electricity markets are hourly markets the contributions of the article are twofold first we define through a var and cvar model optimal portfolios for specific hours 3 am 6 am 12 pm based on electricity market data from 2001 to 2011 for the french market we prove that the optimal hedging strategy differs depending on the cluster hour secondly we demonstrate the significantly superior efficiency of intra day hedging portfolios over daily therefore weekly and yearly portfolios over a decade 2001 2011 our results clearly show that the losses of an optimal daily portfolio are at least nine times higher than the losses of optimal intra day portfolios

portfolio optimization under lower partial moments in emerging electricity markets evidence from turkey abstract optimization of the electricity markets under modern portfolio theory has a crucial role for financial decision makers power suppliers in deregulated electricity markets need to optimize their generation capacities and bidding strategies so as to effectively participate in bilateral contract and spot markets market players have to deal with continuously changing electricity prices in competitive electricity market environment during their daily routine system operations electricity not like the others is a unique product service and cannot be stored economically however it should be generated and consumed simultaneously in addition to all power suppliers face with fuel price water regime delivery and network risks in view of the scene described above prudent decision making methodologies are of critical importance to maximize profit while minimizing managing risks this paper presents a comprehensive comparison of mean variance down side and semi variance methods for optimization in electricity markets and the corresponding methodologies to maximize the return while minimizing risk real turkish day ahead market data set between december 2009 and december 2012 is used in numerical calculations generation cost data of hydraulic plants lignite coal fired thermal power plants and natural gas combined cycle power plants are taken into consideration in the course of optimization evaluations in the present of real data these methods can also be applied to renewable energy generation types these three methods were able to be applied to all case scenarios effectively and produced efficient frontiers optimal minimal portfolios and utility functions successfully the results have revealed that the methods significantly provide decisions for power suppliers with different risk aversion levels and for various instruments to maximize the profit while minimizing the associated market risks and to meet generation obligations consequently financial optimization under lower partial moments constraints would give notable results in analyzing the efficient frontiers for electricity markets in turkey

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

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

reconciling alternative views about the appropriate social discount rate abstract this paper shows that in an economy with an exogenous rate of return and a given capital income tax distortion and with lump sum taxes as the marginal tax instrument the soc and mcf criteria both correctly identify all worthwhile projects if the criteria are properly applied the equivalence between the soc and mcf criteria continues to hold i if distortionary taxes are used to balance the budget and ii if the rate of return to capital is endogenous apparent differences between the soc and mcf criteria arise from different definitions of a project s indirect revenue effect neither criterion has an implementation advantage because the information requirements for each are identical

new product diffusion with influentials and imitators we model the diffusion of innovations in markets with two segments influentials who are more in touch with new developments and who affect another segment of imitators whose own adoptions do not affect the influentials this two segment structure with asymmetric influence is consistent with several theories in sociology and diffusion research as well as many viral or network marketing strategies we have four main results 1 diffusion in a mixture of influentials and imitators can exhibit a dip or chasm between the early and later parts of the diffusion curve 2 the proportion of adoptions stemming from influentials need not decrease monotonically but may first decrease and then increase 3 erroneously specifying a mixed influence model to a mixture process where influentials act independently from each other can generate systematic changes in the parameter values reported in earlier research 4 empirical analysis of 33 different data series indicates that the two segment model fits better than the standard mixed influence the gamma shifted gompertz and the weibull gamma models especially in cases where a two segment structure is likely to exist also the two segment model fits about as well as the karmeshu goswami mixed influence model in which the coefficients of innovation and imitation vary across potential adopters in a continuous fashion

risk based assessment of the cost efficiency and the effectivity of renewable energy support schemes certificate markets versus feed in tariffs the introduction of renewable energy sources in the electricity generation mix has the potential to reduce power sector s emissions and countries dependence on imported oil climate change concerns and highly volatile oil prices have attracted governments interest and support to sustain investments in renewable energy capacity and different support policies have been implemented in many countries around the world this paper analyzes the effects of investors risk aversion on the performance of support schemes the analysis compares two policy options a feed in tariff mechanism with a certificate market system results show that while a tariff mechanism could obtain better results than a certificate market its performance is strictly dependent on regulator choices a certificate market instead permits to obtain the desired level of renewable energy market share with good cost efficiency as long as investors risk aversion is moderate moreover discounting future cash flows with higher social discount rates further benefits a certificate system making it preferable to feed in tariffs

a theory of electricity tariff design for optimal operation and investment this study addresses the problem of balancing supply and demand side operation and investment activities existing theory is extended to cover electricity industry models with uncertainty in future conditions and intertemporal linking such as storage and investment an optimal pricing structure which takes these into account is presented it would induce participants suppliers and consumers to make profit maximizing investment and operation decisions which are socially optimal the structure contains two terms a short run marginal cost pricing as well as a new incentive term to account for the interaction of participants at different time points a probabilistic forecast of pricing structures at future time is required a justification of the result and three simple illustrative examples are given

purchasing behavior in embedded markets this article explores the concept of market embeddedness and its impact on purchasing behavior in a consumer market embeddedness exists when consumers derive utility from two sources simultaneously from attributes of the product and from social capital found in preexisting ties between buyers and sellers this framework is applied to the home party method of direct sales we find that the degree of social capital present as measured by the strength of the buyer seller tie and buyer indebtedness to the seller significantly affects the likelihood of purchase we cannot tell the precise moment when friendship is formed as in filling a vessel drop by drop there is at last a drop which makes it run over so in a series of kindnesses there is at last one which makes the heart run over boswell 1777 1835

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

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

pricing flexible electricity contracts this paper is concerned with pricing of electricity contracts that allow flexible scheduling of the supply or demand of electric energy the contracts are priced based on the principle of no arbitrage variables of the contracts are used to determine arbitrage opportunities and the price of contracts pricing of flexible contracts involves a scheduling policy by representing the spot price with an appropriate stochastic process the scheduling policy can be found using stochastic dynamic programming simulation examples illustrate the tradeoffs between prices and scheduling flexibility