Market-based transmission congestion management using extended optimal power flow techniques

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 5/9/2001This thesis describes research into the problem of transmission congestion management. The causes, remedies, pricing methods, and other issues of transmission congestion are briefly reviewed. This research is to develop market-based approaches to cope with transmission congestion in real-time, short-run and long-run efficiently, economically and fairly. Extended OPF techniques have been playing key roles in many aspects of electricity markets. The Primal-Dual Interior Point Linear Programming and Quadratic Programming are applied to solve various optimization problems of congestion management proposed in the thesis. A coordinated real-time optimal dispatch method for unbundled electricity markets is proposed for system balancing and congestion management. With this method, almost all the possible resources in different electricity markets, including operating reserves and bilateral transactions, can be used to eliminate the real-time congestion according to their bids into the balancing market. Spot pricing theory is applied to real-time congestion pricing. Under the same framework, a Lagrangian Relaxation based region decomposition OPF algorithm is presented to deal with the problems of real-time active power congestion management across multiple regions. The inter/intra-regional congestion can be relieved without exchanging any information between regional ISOs but the Lagrangian Multipliers. In day-ahead spot market, a new optimal dispatch method is proposed for congestion and price risk management, particularly for bilateral transaction curtailment. Individual revenue adequacy constraints, which include payments from financial instruments, are involved in the original dispatch problem. An iterative procedure is applied to solve this special optimization problem with both primal and dual variables involved in its constraints. An optimal Financial Transmission Rights (FTR) auction model is presented as an approach to the long-term congestion management. Two types of series F ACTS devices are incorporated into this auction problem using the Power Injection Model to maximize the auction revenue. Some new treatment has been done on TCSC's operating limits to keep the auction problem linear

Financial risk management and market performance in restructured electric power markets: Theoretical and agent-based test bed studies

Electric power systems have traditionally been operated as natural monopolies. Restructuring has entailed un-bundling of hitherto vertically integrated organizations into independently managed generation, transmission and distribution systems. As a result, electric power markets can be divided into wholesale and retail layers. The wholesale power market design proposed by the U.S. Federal Energy Regulatory Commission (FERC) in an April 2003 white paper FERC (2003) encompasses the following core features: central oversight by an independent system operator (ISO); a two-settlement system consisting of a day-ahead market supported by a parallel real-time market to ensure continual balancing of electric power supply and demand. In this new environment electricity is traded like other commodities in ISO organized power pools. However, power systems must be in instantaneous power balance, i.e. demand must equal supply at all times. Moreover, at present, electric power cannot be stored economically in substantial amounts. The power flows on transmission systems are governed by physical laws of power flow such as the Kirchoff\u27s law, and are constrained by the overall capacity of transmission lines. During the peak hours of electric power demand, the above mentioned constraints become binding affecting outcomes throughout the grid. Transmission constraints in particular create congestion, which can impede the generation and/or injection of electric power into the grid in merit-order , i.e., from least-cost generator to high-cost generators. Electric power prices can be very volatile and hence, new forms of risk have arisen due to the restructuring. As part of restructuring, congestion on electricity transmission grids is now handled in many energy regions by means of locational marginal pricing (LMP), i.e., the pricing of electric energy in accordance with the location of its injection or withdrawal from the grid. The LMP so calculated at a node k measures the least cost to supply an additional unit of load at that location from the resources of the system. The difference in LMPs at any two buses is known as congestion rent, which is collected by the ISO. In the case of grid congestion, LMPs can vary widely across the grid, which creates price risk for all market participants. Using existing market design features, this thesis investigates the risk management issues of market participants and overall efficiency of the wholesale power markets. Additionally, I also study the market rules dealing with renewable energy sources

Multi-agent system for modelling the restructured energy market

Master'sMASTER OF ENGINEERIN

FINANCIAL TRANSMISSION AND STORAGE RIGHTS

The paper presents concepts of Financial Transmission Rights (FTRs) and Financial Storage Rights (FSRs) as key market concepts for alleviating congestion issues in transmission networks. These instruments are in place in markets where prices differ depending on the location/node due to congestions. They serve as a tool for transmission system operators TSO (or independent system operators; ISOs) for eliminating congestions by remunerating entities who make it possible. The paper further discusses different aspects of FTRs, which are traditional financial instruments used to hedge the risk of high cost occurrence associated with transmission congestion. By owning and trading with FTRs, through auction or via bilateral contracts, market participants can gain additional profit. More variable and uncertain power system environment, characterized by high penetration of renewable energy sources (RES), creates potential for storage units to assist TSO/ISO in maximizing social welfare through FSR. As storage has the capability to move energy in time, it can alleviate transmission lines congestion and create profit through intertemporal arbitrage (by load shifting and peak shaving) improving return rate of its investment. These concepts are additionally explained by intuitive examples showing how, when congestion occurs and TSO/ISO awards market participants who own transmission and storage rights, price volatility is reduced

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of one week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. © 2011 Elsevier Ltd. All rights reserved