Optimal energy portfolio method for regulable hydropower plants under the spot market

Abstract

The energy allocation method for regulable hydropower plants under the spot market significantly impacts their income. The available studies generally draw on the Conditional Value-at-Risk (CVaR) approach, which typically assumes a fixed risk aversion coefficient for generators. This assumption is based on the assumption that the total energy the power plant can allocate is constant during the decision period. However, the amount of energy that the regulable hydropower plant can generate will be affected by inflow and water level during the decision period, and the assumption of the fixed risk aversion coefficient is only partially consistent with the actual decision behavior of the hydropower plant. In this regard, the time-varying relative risk aversion (TVRRA) based method is proposed for the energy allocation of regulable hydropower plants. That method takes the change value of the hydropower plant’s energy generation as the basis for adjusting the time-varying relative risk aversion coefficient to make the energy allocation results more consistent with the actual decision-making needs of the hydropower plant. A two-layer optimal method is proposed to obtain the income-maximizing energy portfolio based on regulable hydropower plants’ time-varying relative risk aversion coefficient. The inner point method solves the optimal energy portfolio of income and risk in the upper layer. The time-varying relative risk aversion coefficient in the lower layer accurately describes the dynamic risk preference of hydropower plants for each period. The results and comparison show that the proposed method increases the income of the energy portfolio by 31%, and water disposal of regulated hydropower plants is reduced by 2%. The energy portfolio optimization method for regulable hydropower plants proposed in this paper not only improves the economic income of hydropower plants but also improves the utilization rate of hydro energy resources and enhances the market competitiveness of regulable hydropower plants.

Two-Stage Stochastic Scheduling of Cascaded Hydropower–Wind–Photovoltaic Hybrid Systems Considering Contract Decomposition and Spot Market

“…As can be seen from Equation (18), the output of a hydropower unit is a nonlinear expression related to the generation coefficient, generation flow, and net water head. In this paper, assuming that the generation efficiency of each unit is constant [37,38], the output characteristics of the hydropower unit can be linearized by the McCormick convex envelope relaxation method as expressed in Equations ( 33)- (36).…”

“…In recent years, some studies have been conducted on the operation of hydropower participating in the electricity market. Lu et al [18] proposed a method based on time-varying relative risk aversion for the energy allocation of regulable hydropower plants and a two-layer optimal method for obtaining an income-maximizing energy portfolio; these methods can improve the economic income of hydropower plants and the utilization rate of hydropower energy resources. Yuan et al [19] established an optimized scheduling model for cascade hydropower plants simultaneously participating in the daily contract market, and the impact of the penalty coefficient for the contract electricity imbalance was analyzed; their results can provide an effective reference for market operators formulating electricity trading rules.…”