Network-constrained models of liberalized electricity markets: the devil is in the details

Numerical models for electricity markets are frequently used to inform and support decisions. How robust are the results? Three research groups used the same, realistic data set for generators, demand and transmission network as input for their numerical models. The results coincide when predicting competitive market results. In the strategic case in which large generators can exercise market power, the predicted prices differed significantly. The results are highly sensitive to assumptions about market design, timing of the market and assumptions about constraints on the rationality of generators. Given the same assumptions the results coincide. We provide a checklist for users to understand the implications of different modelling assumptions

Combining Top-Down and Bottom-up in Energy Policy Analysis: A Decomposition Approach

The formulation of market equilibrium problems as mixed complementarity problems (MCP) permits integration of bottom-up programming models of the energy system into top-down general equilibrium models of the overall economy. Despite the coherence and logical appeal of the integrated MCP approach, implementation cost and dimensionality both impose limitations on its practical application. A complementarity representation involves both primal and dual relationships, often doubling the number of equations and the scope for error. When an underlying optimization model of the energy system includes upper and lower bounds on many decision variables the MCP formulation may suffer in robustness and efficiency. While bounds can be included in the MCP framework, the treatment of associated income effects is awkward. We present a decomposition of the integrated MCP formulation that permits a convenient combination of top-down general equilibrium models and bottom-up energy system models for energy policy analysis. We advocate the use of complementarity methods to solve the top-down economic equilibrium model and quadratic programming to solve the underlying bottom-up energy supply model. A simple iterative procedure reconciles the equilibrium prices and quantities between both models. We illustrate this approach using a simple stylized model. --Mathematical Programming,Mixed Complementarity,Top-Down/Bottom-Up

Network-constrained models of liberalized electricity markets: the devil is in the details

Numerical models for electricity markets are frequently used to inform and support decisions. How robust are the results? Three research groups used the same, realistic data set for generators, demand and transmission network as input for their numerical models. The results coincide when predicting competitive market results. In the strategic case in which large generators can exercise market power, the predicted prices differed significantly. The results are highly sensitive to assumptions about market design, timing of the market and assumptions about constraints on the rationality of generators. Given the same assumptions the results coincide. We provide a checklist for users to understand the implications of different modelling assumptions.Market power, Electricity, Networks, Numeric models, Model comparison

Evaluating the impact of average cost based contracts on the industrial sector in the European emission trading scheme

The inception of the Emission Trading System in Europe (EU-ETS) has made power price more expensive. This affects the competitiveness of electricity intensive industrial consumers and may force them to leave Europe. Taking up of a proposal of the industrial sector, we explore the possible application of special contracts, based on the average cost pricing system, which would mitigate the impact of CO2 cost on their electricity price. The model supposes fixed generation capacities. A companion paper treats the case with capacity expansion. We first consider a reference model representing a perfectly competitive market where all consumers (households and industries) are price-takers and buy electricity at the short-run marginal cost. We then change the market design assuming that large industrial consumers pay power either at a single or at a nodal average cost price. The analysis of these problems is conducted with simulation models applied to the Northwestern European market. The equilibrium models developed are implemented in the GAMS environment.average cost pricing, complementarity conditions, EU-ETS, Northwestern Europe market.

The More Cooperation, the More Competition? A Cournot Analysis of the Benefits of Electric Market Coupling

Market coupling in Belgian and Dutch markets would permit more efficient use of intercountry transmission, 1) by counting only net flows against transmission limits, 2) by improving access to the Belgian market, and 3) by eliminating the mismatch in timing between interface auctions and the energy spot market. A Cournot market model that accounts for the region’s transmission pricing rules and limitations is used to simulate market outcomes with and without market coupling. This accounts for 1) and 2). Market coupling improves social surplus in the order of 108 €/year, unless it encourages the largest producer in the region to switch from a price-taking strategy in Belgium to a Cournot strategy due to a perceived diminishment of the threat of regulatory intervention. Benefit to Dutch consumers depends on the behavior of this company. The results illustrate how large-scale oligopoly models can be useful for assessing market integration

Strategic Action in the Liberalised German Electricity Market

Nowadays, a process can be observed in Germany where electricity producing and trading firms react to the electricity market liberalisation by merging market shares, since the year 2000, which reduces the number of suppliers and influences production and consumer prices. This paper discusses whether the liberalisation process will have positive or negative impacts on the environmental situation and whether this process together with a phase out of nuclear power can guarantee the intended improvement of environmental conditions without governmental regulation in Germany. This is done by modelling different strategic options of energy suppliers and their impacts on the economic and environmental situation in the liberalised German electricity market by a computational game theoretic model. Calculations with this model show that when German firms act strategically (e.g. a change in action of one firm affects the electricity price and, hence, the payoffs of other firms), the environment is better off at the cost of higher electricity prices. This result is robust to perturbations as shows by performing a sensitivity analysis.Electricity market liberalisation, game theoretic model, environmental effectiveness

The More Cooperation, the More Competition? A Cournot Analysis of the Benefits of Electric Market Coupling

Market coupling in Belgian and Dutch markets would permit more efficient use of intercountry transmission, 1) by counting only net flows against transmission limits, 2) by improving access to the Belgian market, and 3) by eliminating the mismatch in timing between interface auctions and the energy spot market. A Cournot market model that accounts for the region’s transmission pricing rules and limitations is used to simulate market outcomes with and without market coupling. This accounts for 1) and 2). Market coupling improves social surplus in the order of 108 €/year, unless it encourages the largest producer in the region to switch from a price-taking strategy in Belgium to a Cournot strategy due to a perceived diminishment of the threat of regulatory intervention. Benefit to Dutch consumers depends on the behavior of this company. The results illustrate how large-scale oligopoly models can be useful for assessing market integration.Electric power, Electric transmission, Liberalization, Oligopoly, Complementarity models, Computational models, Netherlands, Belgium, France, Germany, Market Coupling

Combining Top-Down and Bottom-up in Energy Policy Analysis: A Decomposition Approach

The formulation of market equilibrium problems as mixed complementarity problems (MCP) permits integration of bottom-up programming models of the energy system into top-down general equilibrium models of the overall economy. Despite the coherence and logical appeal of the integrated MCP approach, implementation cost and dimensionality both impose limitations on its practical application. A complementarity representation involves both primal and dual relationships, often doubling the number of equations and the scope for error. When an underlying optimization model of the energy system includes upper and lower bounds on many decision variables the MCP formulation may suffer in robustness and efficiency. While bounds can be included in the MCP framework, the treatment of associated income effects is awkward. We present a decomposition of the integrated MCP formulation that permits a convenient combination of top-down general equilibrium models and bottom-up energy system models for energy policy analysis. We advocate the use of complementarity methods to solve the top-down economic equilibrium model and quadratic programming to solve the underlying bottom-up energy supply model. A simple iterative procedure reconciles the equilibrium prices and quantities between both models. We illustrate this approach using a simple stylized model

Ramsey Pricing in a Congested Network with Market Power in Generation: A Numerical Illustration for Belgium.

This paper derives the socially optimal transmission prices in a congested electricity network when there is imperfect competition in generation, and when the budget constraint of the network operator is binding. The results which we derive are a generalization of the standard Ramsey prices and also of the locational marginal prices (LMP). The model is illustrated with a numerical model based on the Belgian electricity data.

Integrating short-term demand response into long-term investment planning

Planning models have been used for many years to optimize generation investments in electric power systems. More recently, these models have been extended in order to treat demand-side management on an equal footing. This paper stresses the importance of integrating short-term demand response to time-varying prices into those investment models. Three different methodologies are suggested to integrate short-term responsiveness into a long-term model assuming that consumer response can be modelled using price-elastic demand and that generators behave competitively. First, numerical results show that considering operational constraints in an investment model results in less inflexible base load capacity and more mid-range capacity that has higher ramp rates. Then, own-price and cross-price elasticities are included in order to incorporate consumers’ willingness to adjust the demand profile in response to price changes. Whereas own-price elasticities account for immediate response to price signals, cross-price elasticities account for shifting loads to other periods. As energy efficiency programs sponsored by governments or utilities also influence the load profile, the interaction of energy efficiency expenditures and demand response is also modelled. In particular, reduced responsiveness to prices can be a side effect when consumers have become more energy efficient. Comparison of model results for a single year optimization with and without demand response shows the peak reduction and valley filling effects of response to real-time prices for an illustrative example with a large amount of wind power injections. Additionally, increasing demand elasticity increases the optimal amount of installed wind power capacity. This suggests that demand-side management can result in environmental benefits not only through reducing energy use, but also by facilitating integration of renewable energy