Optimization of green energy portfolio in retail market using stochastic programming

In this paper, a mathematical optimization approach for green energy portfolio is presented to strike a right balance between risk and profit associated with retailing in power market. This approach emphasizes on the increasing use of renewable resources to overcome conservation concerns to some degrees. Three different uncertainties are considered for electricity price and energy output of wind and solar distributed generation units. In order to model the uncertainties properly, scenario construction schemes, namely Monte Carlo and time series with ARIMA (Auto regressive integrated moving average) are implemented in this paper. Moreover, risk and elasticity analysis are considered simultaneously to enable consumers and retailers to manage their risk and incomes. Two-stage stochastic programming with fixed recourse is used to model the probabilistic space of decision making process in this paper. At the end, numerical results and simulations are presented which demonstrate the applicability of the proposed approach in a retail electricity market.