Optimal power bidding of overseas PV plants in Singapore wholesale electricity market

Yan Xu
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Abstract

Singapore's power sector has set targets of net-zero emissions by 2050. Given the limited land space of the country, a key strategy to decarbonize the power grid is to import clean power from renewable energy resources such as photovoltaic (PV) plants installed at overseas locations. The present electricity market rules require such overseas PV plants to maintain constant power generation during each bidding period. To meet such requirements, energy storage systems (ESSs) are to be deployed in the PV plants to compensate for the PV power fluctuation. This paper proposes an optimal power bidding approach for maximizing the profit of the PV plant participating in the Singapore wholesale electricity market. The problem is formulated as a stochastic programming model, which takes the short-term PV power forecasting as the input, maximizes the expected profit considering the PV power selling revenue and the penalty cost for power shortfall during each bidding cycle (30 min), and satisfies constraints of the ESS. The proposed method can also be used for determining the optimal size of the ESS. Simulation results have verified the effectiveness of the proposed method.

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新加坡电力批发市场中海外光伏电站的最优电力竞标
新加坡电力部门设定了到 2050 年实现净零排放的目标。由于国土面积有限,电网去碳化的一个关键战略是从可再生能源资源(如安装在海外的光伏电站)进口清洁电力。目前的电力市场规则要求这些海外光伏电站在每个竞标期内保持稳定的发电量。为了满足这些要求,必须在光伏电站中部署储能系统 (ESS),以补偿光伏发电的波动。本文提出了一种最优电力竞标方法,以实现参与新加坡电力批发市场的光伏电站的利润最大化。该问题被表述为一个随机编程模型,它以短期光伏发电量预测为输入,在每个竞价周期(30 分钟)内考虑光伏发电量销售收入和电量不足的惩罚成本,并满足 ESS 的约束条件,实现预期利润最大化。所提出的方法还可用于确定 ESS 的最佳规模。仿真结果验证了所提方法的有效性。
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