Derek W. Bunn

Forecasting loads and prices in competitive power markets

This paper provides a review of some of the main methodological issues and techniques which have become innovative in addressing the problem of forecasting daily loads and prices in the new competitive power markets. Particular emphasis is placed upon computationally intensive methods, including variable segmentation, multiple modeling, combinations, and neural networks for forecasting the demand side, and strategic simulation using artificial agents for the supply side.

Agent-based simulation-an application to the new electricity trading arrangements of England and Wales

This paper presents a large-scale application of multiagent evolutionary modeling to the proposed new electricity trading arrangements (NETA) in the UK. This is a detailed plant-by-plant model with an active specification of the demand side of the market. NETA involves a bilateral forward market followed by a balancing mechanism and then an imbalance settlement process. This agent-based simulation model was able to provide pricing and strategic insights, ahead of NETAs actual introduction.

Review of guidelines for the use of combined forecasts

Abstract A large literature has evolved in the thirty years since the seminal work on combining forecasts. Despite this, when evaluating performance we only look at measures of accuracy and thus ignore most of the rigour of time series analysis. Furthermore, the output from a combination of forecasts is just a single point estimate which is insufficient for business planning models that take explicit account of risk and uncertainty. In this paper, we review evidence on the performance of different combining methods with the aim of providing practical guidelines based on three properties of the forecast errors: variance, asymmetry and serial correlation. The evidence indicates that using different criteria leads to distinct preferences, and that the properties of the individual forecast errors can strongly influence the characteristics of the combinations errors. We show that a practical approach to combining also requires a degree of judgement on the attributes of error specification.

Experimental analysis of the efficiency of uniform-price versus discriminatory auctions in the England and Wales electricity market

Abstract The question of whether the uniform price or discriminatory auction format is the better multi-unit auction mechanism is addressed in the context of the 1999 debate on reforming the England & Wales electricity market. Each generator is modelled as an autonomous adaptive agent capable of endogenously developing its own bidding strategies using a naive reinforcement learning algorithm. The discriminatory auction results in higher market prices than the uniform-price auction. This is because market prices are not publicly available and agents with a large market share gain a significant informational advantage in a discriminatory auction, thereby facing less competitive pressure.

Forecasting with scenarios

Abstract It is often argued that scenario development is different from forecasting, but the analysis presented here reevaluates how it is converging with contemporary forecasting practice. The most common aspects of scenario analysis are discussed, with an emphasis on their support for strategic modelling and in the light of relevant research on human cognition and judgemental forecasting. The paper also offers some practical guidelines and a more integrative perspective on using scenarios to support strategic planning.

Sensitivity of reserve margin to factors influencing investment behaviour in the electricity market of England and Wales

Abstract The electricity generation and distribution industries of England and Wales have recently undergone major re-structuring as part of the privatization process of taking them out of the public sector. On the generation side, three major companies have been created which compete both with each other and with the new independent companies who are expected to enter the market. Trading between generators and distributors is controlled centrally by a pool system which attempts to ensure the optimal operation of the system in the short-term and gives a pricing signal for longer-term investment. This pricing signal depends upon an a priori loss of load probability. This paper is intended to provide insights into how the investment in capacity for generation could evolve according to various regulatory conditions, economic assumptions, degrees of competition and the strategic behaviour of the separate companies. Using a system dynamics approach, a simulation model of investment is developed to generate insights into the volatility of the reserve margin, variations in the loss of load probability and the various market share scenarios. The degree of uncertainty in the demand, the amount of information exchange between competitors and the degree of foresight in planning are considered as well as different financial or market-share objectives for companies.

Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation

We use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices. The research contributions of this paper are both in the areas of market power and market design policy issues for electricity markets, and in the methodological use of large industry-wide evolutionary simulation models.

Interaction of European Carbon Trading and Energy Prices

This paper addresses the economic impact of the EU Emission Trading Scheme for carbon on wholesale electricity and gas prices. Specifically, we analyse the mutual relationships between electricity, gas and carbon prices in the daily spot markets in the United Kingdom. Using a structural co-integrated VAR model, we show how the prices of carbon and gas jointly influence the equilibrium price of electricity. Furthermore, we derive the dynamic pass-trough of carbon into electricity price and the response of electricity and carbon prices to shocks in the gas price.

Divestiture of Generation Assets in the Electricity Pool of England and Wales: A Computational Approach to Analyzing Market Power

The task of developing an adequate modeling approach to understanding strategic behavior in competitive electricity markets is still a major open research question. In this paper, we develop an based on computational modeling and simulation. We apply the new approach to analyzing the second round (1999) of capacity divestiture proposals, which the government and regulatory authorities in England and Wales required in order to improve the efficiency of the wholesale power market. In this context, we suggest that, for a second time, the level of market power may be underestimated and that although the proposed amount of divestiture is substantial, it may still be insufficient to avoid the need for further regulatory controls in the short term.

Statistical efficiency in the linear combination of forecasts

Abstract In seeking an efficient combination of forecasts which minimises the forecast error variance, many methods have been suggested. Through analysis, simulation and case studies, this paper seeks to develop insights into the statistical circumstances which influence the relative accuracy of six of these methods. The six methods chosen have all been advocated in various publications and consist of ‘equal weighting’ (i.e., pooled average), ‘optimal’ (i.e., error variance minimising), ‘optimal with independence assumption’ (i.e., error variance minimising assuming zero correlation between individual forecast errors) and three variations on the formulation of a Bayesian combination based upon posterior probabilities. The statistical circumstances reflected varying conditions of relative forecast errors, error correlations and outliers.