Spot Markets in Electric Power Network: Theory

IEEE Power Engineering Review, 1999

In order to form the loop impedance matrix, the required self and mutual impedance between various conductors are identified in equations 1 and 2. By solving equation 10, the loop currents can be calculated. Knowing the loop currents, the branch currents can be calculated.

A liberalised market is a market where customers can freely choose their supplier. This market model came with the introduction of competition into non-competitive regulated markets. In a non-competitive environment, supply and prices are regulated, while in a liberalized market regulation aims at avoiding the abuse of market power. In the case of electricity, the starting point was the rigorous analysis of the sectors of the industry which were natural monopolies and the identification of the activities where the barriers to entry were such that no competition will develop naturally. It had been assumed in former market organization that the whole of the electricity industry was a natural monopoly which led to the acceptance of vertically integrated monopoly supply utilities. On a closer inspection it was found that only certain activities were natural monopolies, in particular the transmission and distribution networks. This discovery led reformers to search for mechanisms of introducing competition wherever this seemed possible. Bearing in mind the upcoming Iberian Electricity Market -MIBEL, we studied the sensitivity of the Market Clearing Price to changes in the production inputs, such as coal, natural gas and fuel.

Momoh/Economic Market Design Planning, 2009

This chapter provides a comprehensive overview of the economic structure of present and future electricity markets from the combined perspectives of economics and electrical engineering. It describes the basic structure of an electricity market and defines concepts such as consumer surplus, congestion rents, and market power. Furthermore, it outlines the mechanisms resulting in strategic bidding by generators and provides definitions and applications of the different equilibrium models to effectively analyze associated outcomes (prices and quantities). Examples from different equilibrium models (e.g. Cournot, auction-based) are presented. LMP calculations are then described via examples and economic dispatch formulation. Finally, their possible extension in stochastic and dynamic markets is highlighted via adaptive dynamic programming.

ECMS 2006 Proceedings edited by: W. Borutzky, A. Orsoni, R. Zobel, 2006

After the liberalization of the electricity generation industry, capacity expansion decisions are made by multiple selforiented power companies. Unlike the regulated environment, decision-making of market participants is now guided by price signal feedbacks and by an imperfect foresight of the future market conditions that they will face. In such an environment, decision makers need to understand long-term dynamics of the supply and demand side of the power market. To visualize the competitive electricity power market dynamics, a simulation model based on system dynamic philosophy is developed in this study. The developed model includes the demand module, the capacity expansion module, the power generation sector, an accounting and financial module, various competitors and a bidding mechanism (power pooling system). By means of such a decision tool, companies and regulators have a better opportunity to understand possible consequences of different decisions that they may make under different policies and market conditions. The main part of the paper is devoted to a detailed presentation of the model. At the end, some findings of the preliminary scenario analysis are discussed.

Journal of Policy Modeling, 2000

The technical characteristics of electricity generation and transmission have implications for the way in which economic principles are adapted to evaluate pricing and regulation issues in electricity markets. In particular, there is an externality associated with the way in which electricity flows in networks because of Kirchoff's laws. In this paper, a mathematical programming model is presented that simulates a competitive electricity market, based on the spatial-intertemporal equilibrium models pioneered by . The model is used to simulate the operation of a hypothetical electricity market, illustrating some of the issues arising from the network externality.

2011

An electrical transmission network consists of producers, consumers and the power lines connecting them. We build an ideal (lossless) DC load flow model as a cooperative game over a graph with the producers and consumers located at the nodes, each described by a maximum supply or desired demand and the power lines represented by the edges, each with a given power transmission capacity and admittance value describing its ability to transmit electricity. Today's transmission networks are highly interconnected, but organisationally partitioned into several subnetworks, the so-called balancing groups with balanced production and consumption. We study the game of balancing group formation and show that the game contains widespread externalities that can be both negative and positive.

1999

Romanian journal of economic forecasting

The reform of a single player power sector (i.e. a natural monopoly) into a multipleplayers power market brings to the clients not only the benefits of competition but also the costs of complexity. In between the two, an optimal number of players is found, corresponding to the minimum price of power to the clients. Considering time as the third dimension, the optimum curve becomes a potential surface on which the evolution of the market entities is seen as oscillations (mergers and unbundling) along the valley of the minimum price. Every oscillation triggers a price burst, which is detrimental to the clients. To avoid this, the role of the regulator is better defined in the sense of smoothing the transition from monopoly to market. The example of the US and of the EU power sectors evolution is relevant here. In the above approach, long range competition resulting from the future opening of power markets in Europe, or from the penetration, 70 years ago, of the interconnection technology in USA, is compared with the short range (local) competition. Finally, the price limits are determined, which ensure that (i) the new entrants on the market are not eliminated and (ii) the market avoids oscillations (chaotic behavior), which may drastically shock a non-resilient economy. A case study calculation is made for a transition economy (Romania).

2009

The research presented in this Thesis investigates the strategic behaviour of generating firms in bid-based electricity pool markets and the effects of control methods and network features on the electricity market outcome by utilising the AC network model to represent the electric grid. A market equilibrium algorithm has been implemented to represent the bi-level market problem for social welfare maximization from the system operator and utility assets optimisation from the strategic market participants, based on the primal-dual interior point method. The strategic interactions in the market are modelled using supply function equilibrium theory and the optimum strategies are determined by parameterization of the marginal cost functions of the generating units. The AC power network model explicitly represents the active and reactive power flows and various network components and control functions. The market analysis examines ii 2.12 Existence and multiplicity of pure equilibria in linear SFE models 60 2.13 Stochastic optimisation with linear supply function bidding 64 2.14 Numerical methods for SFE solutions 66 Chapter 3: Methodology and implementation of the electricity market SFE algorithm 3.1 The work in this Thesis 71 3.2 The primal-dual interior point method 76 3.3 Applications of the primal-dual interior point method 81 3.4 Introduction to the implemented market equilibrium algorithm 83 3.5 Modelling of the electricity network 84 3.5.1 Representation of the transmission line branch 84 3.5.2 Representation of the transformer 86 3.5.3 Formulation of the power flow and power mismatch equations 89 3.6 Electricity market assumptions and ISO obligations 90 3.7 The optimisation problem of the ISO 94 3.8 The optimisation problem of the generating firms 95 3.9 The solution for the SFE market problem 95 3.9.1 Reformulation of the ISO optimisation problem 96 3.9.2 Introduction of the complementarity constraint 98 3.9.3 Formulation of the combined optimisation problem for the SFE solution 99 3.9.4 Linearization of the market problem's KKT system 102 3.9.5 Formulation of the Newton matrix equation 105 3.10 Implementation issues for the primal-dual interior point algorithm 109 3.11 Conclusions for Chapter 3 112 Chapter 4: The impact of transformer tap-ratio control on the electricity market equilibrium 157 6.2.1 The interactions between the new firm and the existing firms 160 6.2.2 The choice for the best location for the new generating unit 161 6.2.3 The effects of the new entry on the nodal prices and the social welfare 162 6.3 Conclusions for Chapter 6 163 iv Chapter 7: Modelling of grid-connected photovoltaic systems in the electricity market equilibrium algorithm 7.1 Introduction to photovoltaic (PV) technology 165 7.2 Modelling the economic aspects of grid-connected PV systems in the electricity market model 167 7.3 Numerical results using the PV systems economic model 168 7.4 Discussions on the PV economic model 172 7.5 Modelling the operational aspects of grid-connected PV systems in the electricity market model, in terms of active and reactive PV power output 173 7.5.1 Experimental PV equipment 174 7.5.2 Processing the data collected from the experimental PV park 174 7.5.3 Modelling the PV output performance in the electricity market algorithm 176 7.6 Numerical results using the economic-operational PV systems model: the effect of the solar irradiance-dependent PV active and reactive power generation on the electricity market 177 7.6.1 Numerical results on the 5-bus system 178 7.6.2 Numerical results on the IEEE 57-bus system 183 7.6.3 Discussion on the impact of solar irradiance on the electricity market equilibrium and the significance of PV reactive power modelling 185 7.7 Conclusions for Chapter 7 186 Chapter 8: Parameterization of supply functions in AC electricity market equilibrium models References 226

Computational Mathematics and Modeling, 2019

An energy transmission system is usually a part of every energy market. The problem of optimizing transmission system to maximize the social welfare is the subject of the present paper. For energy markets with tree-type network structures, an approach to optimizing their transmission systems is developed based upon the concept of competitive and complementary network lines. Also, a method for the supply-demand balances transfer to the root node of the network is discussed. Finally, the problem of optimally developing an energy transmission system up to a given planning horizon is discussed.