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Hesamzadeh M.R.,KTH Royal Institute of Technology | Biggar D.R.,The Australian Competition and Consumer Commission | Hosseinzadeh N.,Swinburne University of Technology | Wolfs P.J.,Curtin University Australia
IEEE Transactions on Power Systems | Year: 2011

This paper describes a numerical approach to solving the mathematical structure proposed in the first part of this paper. The numerical approach employs a standard genetic algorithm (GA) embedded with an island parallel genetic algorithm (IPGA). The GA handles the decision variables of the transmission network service provider, (TNSP) while the IPGA module finds the equilibrium of the electricity market. The IPGA module uses the concept of parallel islands with limited communication. The islands evolve in parallel and communicate with each other at a specific rate and frequency. The communication pattern helps the IPGA module to spread the best-found genes across all isolated islands. The isolated evolution removes the fitness pressure of the already-found optima from the chromosomes in other islands. A stability operator has been developed which detects stabilized islands and through a strong mutation process re-employs them in exploring the search space. To improve the efficiency of the proposed numerical solution, two high performance computing (HPC) techniques are used - shared-memory architecture and distributed-memory architecture. The application of the proposed approach to the assessment of transmission augmentation is illustrated using an IEEE 14-bus example system. © 2006 IEEE. Source


Hesamzadeh M.R.,KTH Royal Institute of Technology | Biggar D.R.,The Australian Competition and Consumer Commission | Hosseinzadeh N.,Swinburne University of Technology | Wolfs P.J.,Curtin University Australia
IEEE Transactions on Power Systems | Year: 2011

This paper proposes a new mathematical structure for evaluating the economic efficiency of transmission investment in a liberalized electricity market. The problem faced by a transmission planner is modeled using the concept of social welfare from economics. The behavior of generators is modeled as the Nash equilibrium of a strategic game. The Nash solution concept is reformulated as an optimization problem and a new concept - the Stackelberg-Worst Nash equilibrium - is introduced to resolve the problem of multiple equilibria. The proposed structure can take into account the effects of a transmission augmentation on both market power and strategic generation investment. Accordingly, the optimal solution to the transmission planner's problem may allow additional transmission capacity both to reduce market power and to defer investment in the generation sector. A methodology is proposed to decompose the benefits of a transmission augmentation policy into the efficiency benefit, competition benefit, and the deferral benefit. The outcomes of the proposed approach to transmission augmentation are compared with the outcomes of two other approaches to transmission augmentation using a simple three-bus network example. © 2006 IEEE. Source


Hesamzadeh M.R.,KTH Royal Institute of Technology | Biggar D.R.,The Australian Competition and Consumer Commission | Hosseinzadeh N.,Swinburne University of Technology
Energy Policy | Year: 2011

Wholesale electricity market regulators have long sought a simple, reliable, transparent indicator of the likely impact of wholesale market developments on the exercise of market power. Conventional indicators, such as the Pivotal Supplier Indicator (PSI) and the Residual Supply Index (RSI) cannot be extended to apply to meshed transmission networks, especially when generating companies hold a portfolio of generating units at different locations on the network. This paper proposes a generalisation of these standard measures termed the "Transmission-Constrained Pivotal Supplier Indicator (TC-PSI)". The TC-PSI of a generating company is defined as the maximum must-run generation for any subset of generating plant while allowing for strategic operation of other plant in the portfolio. We illustrate the use of the TC-PSI using a five-node model of the Australian NEM. © 2011 Elsevier Ltd. Source


Hesamzadeh M.R.,KTH Royal Institute of Technology | Biggar D.R.,The Australian Competition and Consumer Commission
IEEE Transactions on Power Systems | Year: 2013

Around the world, electricity market regulators and competition authorities are struggling to find ways to reliably assess the likely market impact of mergers of generators. Conventional indicators of market power fail to capture key aspects of the exercise of market power in wholesale electricity markets. On the other hand, full-scale computation of Nash equilibria has historically been time consuming, non-transparent, and typically results in multiple Nash equilibria. In this paper we propose two methodological advances: an efficient approach to computing ex-tremal- Nash equilibria in a wholesale power market with market power and the application of this approach in the assessment of wholesale market mergers. The extremal-Nash equilibria are those equilibria which have the highest or the lowest social cost to the society. The resulting formulation is a Mixed Integer Linear Program which efficiently finds the full set of extremal-Nash equilibria. The continuum of these extremal-Nash equilibria over a range of demand conditions describes the upper and lower envelopes of the Equilibria Band. To illustrate the advantages of the proposed approach, two case studies are explored, involving the New South Wales region of the Australian National Electricity Market, on the one hand, and the IEEE 14-Bus Test System, on the other. © 2012 IEEE. Source


Hesamzadeh M.R.,KTH Royal Institute of Technology | Biggar D.R.,The Australian Competition and Consumer Commission
IEEE Transactions on Power Systems | Year: 2012

This letter proposes a new approach to the computation of extremal-Nash equilibria in a wholesale power market with transmission constraints. The approach uses linearization techniques to formulate the extremal-Nash equilibrium problem as a single-stage mixed-integer linear programming problem which can be solved with standard software. Through the introduced concept of extremal-Nash equilibria, the derived structure can efficiently locate all Nash equilibria of the game. We show that this approach offers significant performance improvements over existing approaches to computing Nash equilibria. © 2012 IEEE. Source

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