Modelling and Analysis of Deregulated Electricity Market Operations
D.Prasad1, M.Gopila2, S.Purushotham3
1D.Prasad, Department of EEE, Sona College of Technology, Salem, India.
2Dr M.Gopila, Department of EEE, Sona College of Technology, Salem, India.
3S.Purushotham, Department of EEE, Sona College of Technology, Salem, India.

Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5581-5585 | Volume-8 Issue-4, November 2019. | Retrieval Number: B2517078219/2019©BEIESP | DOI: 10.35940/ijrte.B2517.118419

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Abstract: Deregulation in power industry is restructuring of the rules and economic incentives that government set up to control and drive the electrical power industry. Restructuring in electricity industry will create new business opportunities where new firms selling new products and services will appear, consumers will have alternatives in buying electricity services, and new technologies such as metering and telecommunication devices will develop. Bidding by participants is one of the major challenges. To overcome this issue, strategic bidding models are being developed based on market structure, auction rules and bidding protocols. This paper proposes to formulate an optimal bidding strategy algorithm for DisCos and analyze its impact in the market operations. The bidding optimization is aimed at developing bids that get selected in the market operations and simultaneously maximizing the total profit of DisCos and minimizing power imbalances. Power Exchange market, which is simple yet enables competition, will be considered. This is proposed to be done using MATLAB coding and Genetic Algorithm tool box. Multiple simple bids are modeled. Power imbalance for each of the possible cases is computed. Decision variables (L1,L2,L3) and (C1,C2,C3) are used in order to compute objective functions i.e. Minimization of Power imbalances and maximization of profit, using MATLAB coding and GA tool box.
Keywords: Distribution company, Market Clearing Price, Power Exchange, Genetic Algorithm.
Scope of the Article: E-Governance.