资源环境科技发展态势分析平台

The forecast-informed hydropower operation for mixed reservoir systems, which consist of parallel and cascade reservoirs, is of considerable importance in practice; however, this operation still lacks an analytical basis in theory. From the perspective of energy, this paper introduces the concept of "hydraulic potential energy" and mathematically derives the energy transformation formula for multi-reservoir hydropower operation. Based on this formula and the rolling single-period forecast, a maximum hydraulic potential energy model (E1 model) is proposed. The presented rigorous proofs demonstrate the deficiencies of the commonly considered objectives or principles of minimizing the outflow-induced energy-cost, while the objective function of the E1 model is demonstrated to be superior. If the constraints of power output and reservoir storage are nonbinding, the derived optimal spatial principle for hydropower operation is (1) to equalize the Relative Marginal Energy (RME) among reservoirs or (2) if this status is not feasible, to release water and generate hydropower first from the reservoirs that have the largest RME values. Considering the uncertainty of future inflow, the E1 model is extended to the two-stage hydraulic potential energy model (E2 model). A case study of a hypothetical mixed three-reservoir system demonstrates the superior performance of the E2 model compared with the conventional K-value principle and the minimum energy-cost model. This paper provides an innovative spatial principle and a practical model for the realization of forecast-informed hydropower operation, which contributes to the optimization of the large-scale energy market.

Key Points

The energy transformation formula for multi-reservoir hydropower operation is proved based on the concept of hydraulic potential energy The theoretical Relative Marginal Energy principle is mathematically derived for the optimal spatial allocation of reservoir storages The hydraulic potential energy model is an effective tool to improve the forecast-informed hydropower operation for mixed reservoir systems