A Planned Power Generation For Battery-Assisted Photovoltaic System Using Short-Term Forecast

IEEE ACCESS(2021)

引用 3|浏览4
暂无评分
摘要
The introduction of variable renewable energies, such as photovoltaic systems (PV), into electric power systems will increase the amount of resources necessary to balance supply and demand in terms of both quality and quantity. Thus, a planned power generation that matches the planned values submitted in advance with the actual values of PV power generation is required by installing battery energy storage systems (BESS). Currently, since the cost of BESS is still high, eliminating the imbalance which equals to the difference between planned and actual values of PV power generation by BESS is not economically feasible, and appropriate cooperation is required to share the role of balancing with regulating generators. However, variable renewable energies can cause steep imbalances which cannot be compensated by regulating generators due to their relatively slow response times. To address this problem, this paper proposes a planned power generation method that can reduce the burden on regulating generators by introducing a strategy to mitigate the changing rate of imbalance, (hereinafter called "imbalance leveling") by determining the optimal scheduling of BESS using the short-term forecast of PV power generation. Numerical simulations were conducted using a model based on Japanese frequency control to compare the proposed method with the conventional method without imbalance leveling. The results confirmed that the proposed method can improve the capacity value per unit of BESS in supply and demand adjustment owing to the effect of leveling the imbalance. Additionally, it can improve the performance of supply and demand adjustment with the same capacity.
更多
查看译文
关键词
Power generation, Generators, Batteries, Automatic generation control, Supply and demand, Renewable energy sources, Predictive models, Battery energy storage system, frequency control, photovoltaic system, planned power generation, short-term forecast
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要