Optimization of a Green Energy Portfolio in a Retail Electricity Market Considering Consumer's Elasticity
In this paper, a novel approach is proposed to optimize a green energy portfolio in a retail electricity market. To achieve this goal, uncertainties associated with the electricity price and energy extracted from wind and solar generating units are considered as random variables through a bi-level stochastic programming. From retailers prospective, different kinds of contracts, including forward contracts and contracts based on block-index pricing methods, are proposed to enable consumers and retailers to manage risk and profit in a competitive electricity market. To optimize green energy portfolio, uncertainties associated with the problem are modeled by using a time series, Auto Regressive Integrated Moving Average (ARIMA) approach and a Monte-Carlo simulation scheme. Risk and elasticity analysis make a golden opportunity for retailers and consumers to strike a right balance between risk and profit through their participation in electricity market. At the end, numerical examples and simulation results show the applicability of the proposed approach in an electricity retail market.