Modeling Electricity Markets as Two-Stage Capacity Constrained Price Competition Games under Uncertainty

The last decade has seen an increasing application of game theoretic tools in the analysis of electricity markets and the strategic behavior of market players. This paper focuses on the model examined by Fabra et al. (2008), where the market is described by a two-stage game with the firms choosing their capacity in the first stage and then competing in prices in the second stage. By allowing the firms to endogenously determine their capacity, through the capacity investment stage of the game, they can greatly affect competition in the subsequent pricing stage. Extending this model to the demand uncertainty case gives a very good candidate for modeling the strategic aspect of the investment decisions in an electricity market. After investigating the required assumptions for applying the model in electricity markets, we present some numerical examples of the model on the resulting equilibrium capacities, prices and profits of the firms. We then proceed with two results on the minimum value of price caps and the minimum required revenue from capacity mechanisms in order to induce adequate investments

Market Power Assessment and Mitigation in Hydrothermal Systems

The objective of this work is to investigate market power issues in bid- based hydrothermal scheduling. Initially, market power is simulated with a single stage Nash-Cournot equilibrium model. Market power assessment for multiple stages is then carried through a stochastic dynamic programming scheme. The decision in each stage and state is the equilibrium of a multi-agent game. Thereafter, mitigation measures, specially bilateral contracts, are investigated. Case studies with data taken from the Brazilian system are presented and discussed.Game theory, Hydroelectric-thermal power generation, Power generation economics

A looming revolution: Implications of self-generation for the risk exposure of retailers. ESRI WP597, September 2018

Managing the risk associated with uncertain load has always been a challenge for retailers in electricity markets. Yet the load variability has been largely predictable in the past, especially when aggregating a large number of consumers. In contrast, the increasing penetration of unpredictable, small-scale electricity generation by consumers, i.e. self-generation, constitutes a new and yet greater volume risk. Using value-at-risk metrics and Monte Carlo simulations based on German historical loads and prices, the contribution of decentralized solar PV self-generation to retailers’ load and revenue risks is assessed. This analysis has implications for the consumers’ welfare and the overall efficiency of electricity markets

Equilibrium Predictions in Wholesale Electricity Markets

We review supply function equilibrium models and their predictions on market outcomes in the wholesale electricity auctions. We discuss how observable market characteristics such as capacity constraints, number of power suppliers, load distribution and auction format affect the behavior of suppliers and performance of the market. We specifically focus on the possible market power exerted by pivotal suppliers and the comparison between discriminatory and uniform-price auctions. We also describe capacity investment behavior of electricity producers in the restructured industry.Electricity markets; Supply function equilibrium; Markov perfect equilibrium; electricity auctions; pivotal suppliers; capacity investment.

Modeling Electricity Markets as Two-Stage Capacity Constrained Price Competition Games under Uncertainty

The last decade has seen an increasing application of game theoretic tools in the analysis of electricity markets and the strategic behavior of market players. This paper focuses on the model examined by Fabra et al. (2008), where the market is described by a two-stage game with the firms choosing their capacity in the first stage and then competing in prices in the second stage. By allowing the firms to endogenously determine their capacity, through the capacity investment stage of the game, they can greatly affect competition in the subsequent pricing stage. Extending this model to the demand uncertainty case gives a very good candidate for modeling the strategic aspect of the investment decisions in an electricity market. After investigating the required assumptions for applying the model in electricity markets, we present some numerical examples of the model on the resulting equilibrium capacities, prices and profits of the firms. We then proceed with two results on the minimum value of price caps and the minimum required revenue from capacity mechanisms in order to induce adequate investments.Capacity Constraints; Electricity Markets; Regulatory Policy; Strategic Behaviour;

Electricity Pricing and Market Power - Evidence from Germany

The aim of this paper is to develop a methodology for measuring the exercise of potential market power in liberalized electricity markets. We therefore investigate producer behavior in the context of electricity pricing with respect to fundamental time-dependent marginal cost (TMC), i.e. CO2- and fuel cost. In doing so, we do not - in contrast to most current approaches to market power investigation - rely on an estimate of the entire generation cost, which inevitably suffers from the lack of appropriate available data. Applying an analytical model of a day-ahead electricity market, we derive work-on rates, which provide information about the impact of TMC variations on electricity prices in the market constellations of perfect competition, quasi-monopoly and monopoly. Comparing these model-based work-on rates with actual work-on rates, estimated by an adjusted first-differences regression model of German power prices on the cost for hard coal, natural gas and emission allowances, we find evidence of the exercise of market power in the period 2006 to 2008. However, our results reveal that German market competitiveness increases marginally. We confirm our results by simulating a TMC-driven diffusion model of futures power prices estimated by maximum-likelihood.energy; electricity; market power analysis; spot-futuresprice relation

Electricity pricing and market power: Evidence from Germany

The aim of this paper is to develop a methodology for measuring the exercise of potential market power in liberalized electricity markets. We therefore investigate producer behavior in the context of electricity pricing with respect to fundamental time-dependent marginal cost (TMC), i.e. CO2- and fuel cost. In doing so, we do not - in contrast to most current approaches to market power investigation - rely on an estimate of the entire generation cost, which inevitably suffers from the lack of appropriate available data. Applying an analytical model of a day-ahead electricity market, we derive work-on rates, which provide information about the impact of TMC variations on electricity prices in the market constellations of perfect competition, quasi-monopoly and monopoly. Comparing these model-based work-on rates with actual work-on rates, estimated by an adjusted first-differences regression model of German power prices on the cost for hard coal, natural gas and emission allowances, we find evidence of the exercise of market power in the period 2006 to 2008. However, our results reveal that German market competitiveness increases marginally. We confirm our results by simulating a TMC-driven diffusion model of futures power prices estimated by maximum-likelihood. --

An Empirically Based Model of the Supply Schedule in Day-Ahead Electricity Markets

The first part of this paper establishes some new pieces of evidence on the dynamics of prices and volumes in wholesale electricity day-ahead markets (NordPool, APX, Powernext). The growth of prices is more strongly autocorrelated than the growth of volumes; it is more more heavy-tailed; and its conditional standard deviation decays like the reciprocal of the price level (1/P scaling). In the second part of the paper, it is shown that a linear supply function with stochastic intercept and constant slope suffices to explain the 1/P scaling. Furthermore, this model allows to decompose price fluctuations in an exogenous demand effect and a strategically-driven supply effect. In light of this model, the heavier tails of price growth and its stronger autocorrelation structure are due to persistent and intermittent strategic moves by suppliers, related to expected demand growth.Electricity Markets, Supply Curve, Subbotin Distribution, Fat Tails, Scaling, Demand Effect, Supply Effect.

Market Design, Bidding Rules, and Long Memory in Electricity Prices

In uniform price, sealed-bid day-ahead electricity auctions, the market price is set at the intersection between aggregate demand and supply functions built by a market operator. Each day, just one agent - the marginal generator - owns the market-clearing plant. Day-ahead auctions are moreover embedded in multi-segment systems, wherein diverse protocols coexist and change over time. Such a complex environment leads to adoption of simple, adaptive bidding rules. Specifically, such a market design lets two different types of routines emerge, depending on whether the agent is a likely marginal or inframarginal generator. However, because of the uniform price mechanism, only the bidding behavior of the former can be reflected into market prices. Depending on the specific way marginal generators process past information to set their bids - 'hyperbolic' or 'exponential' - electricity prices are likely to display long- or short-memory. Experimental evidence on hyperbolic discounting - a quite robust behavioral bias in humans - supports a long-memory view of electricity prices. This insight is broadly confirmed by spectral analysis of daily data from NordPool and CalPX markets, in sharp contrast with most previous empirical studies. This paper underlines the importance of institutional settings in determining market outcomes, and an interesting mapping of bidding rules and models of information processing into the time series properties of market prices.Market Design, Electricity Markets, Hyperbolic Discounting, Long Memory, Fractional Processes