Multi-time scale trading profit model of pumped storage power plant for electricity market

Abstract

Pumped storage power plant (PSPP) has the upper hand on economy and cleanness. It also has the functions of frequency regulation, phase regulation, and spare, which have been instrumental in maintaining the stability of power system operation. But now the mechanism for PSPP to become involved in electricity market transactions in China is imperfect. How to properly establish a multi-time scale trading profit model and reasonably allocate the capacity of PSPP has been instrumental in realizing the economic operation of the power system. So, this article analyzes the mechanism for PSPP to become involved in electricity market trading by providing combined electricity supply services and ancillary services, and establishes an optimization model with respect to economic optimization. At the same time, considering the volatility of electricity prices in the spot market, the risk of PSPP becoming involved in electricity market trading is measured by conditional Value at Risk (CVaR) to achieve economic optimization while minimizing the risk. The case studies demonstrate that the proposed profit model can enhance the revenue and decrease the risk of PPSP.

Regional electricity market price forecasting based on an adaptive spatial–temporal convolutional network

“…Tschora et al (2022) studied the effect of different machine learning methods in predicting electricity prices, considering the historical prices of neighboring countries to improve the prediction results. Because of the many influencing factors involved in electricity prices, traditional methods still cannot fully characterize them, so the predictive accuracy was limited (Luo et al, 2022).…”