Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty

Abstract

In deregulated electricity markets, an electricity consumer should distribute his required electricity optimally between different markets including spots markets with instantaneous price and bilateral contract markets. The present study aimed to design a model for selecting the optimal electricity market portfolio so that purchase costs can be minimized by considering a risk level. For this purpose, an optimization approach based on random planning was proposed to minimize costs and reduce power supply risk. The proposed approach is able to provide the conditions for changing the optimal allocation of a portfolio for a consumer on a daily basis. Purchases from the energy pool and the energy exchange are associated with uncertainty due to the market price of electricity. These uncertainties complicate the purchase of electrical energy and also create unfavorable situations in the cost of providing energy carriers. Conditional value at risk was used as an appropriate and well-known factor for reducing unfavorable situations in decision-making under uncertain conditions. For simulations, the real information of Iran in 2018 was used as much as possible. Due to the small number of industrial subscribers, the whole population was studied. In addition, MATLAB software was used for implementing the proposed model. The efficiency of the proposed model was proved by analyzing different sensitivities and the best components of the risk-averse decision-making purchasing portfolio in included 34% purchase from the energy exchange, 39% from the energy pool, and 27% in bilateral contracts.