考虑消纳水平的新能源配套储能和输电通道容量协调优化配置

随着以风光为代表的可再生能源发电比例迅速提升，风电场、光伏电站出力的不确定性和波动性给电力实时平衡带来了极大的挑战，配置合理规模的储能可以保障经济性并提高新能源利用率。为此，针对容量已知的新能源电站，提出了一种配套储能和传输线路容量协调优化配置的机会约束规划模型，以储能和传输线路建设成本最小化为目标，以年新能源弃电率不超过规定的指标为机会约束。由于机会约束非凸且缺乏显式表达，基于条件风险价值将机会约束对应的可行域保守转换为线性约束，得到易于求解的线性规划问题，并量化分析了规划方案对新能源场景概率分布的鲁棒性。算例分析结果表明，所提规划模型可以有效地解决考虑新能源消纳能力的储能和传输线路容量配置问题，通过合理配置储能可以降低传输线路的容量从而节约总投资成本。

Coordinated optimal capacity configuration of energy storage equipped by new energy and transmission lines considering consumption level

With the rapid increase of the proportion of renewable energy power generation represented by wind and photovoltaic power, the uncertainty and volatility of the output of wind farms and photovoltaic power plants pose great challenges to the real-time power balance. The configuration of energy storage with reasonable scale can guarantee the economy and improve the utilization rate of new energy. Therefore, aiming at the new energy power station with known capacity, a chance-constrained programming model for coordinated optimal capacity configuration of energy storage equipped by new energy and transmission lines is proposed, which aims to minimize the construction cost of energy storage and transmission lines, and takes the annual new energy abandonment rate not exceeding the specified index as the chance constraints. Since the chance constraints are usually non-convex and lack explicit expressions, the feasible domain corresponding to the chance constraints is conservatively converted into linear constraints based on conditional value at risk to obtain a linear programming problem which can be efficiently solved, and the robustness of the programming scheme to the probability distribution of new energy scenarios is quantitatively analyzed. The example analysis results show that the proposed programming model can effectively solve the capacity configuration problem of energy storage and transmission lines considering the consumption level of new energy, and the capacity of transmission lines can be reduced by rational configuration of energy storage, thus saving the total investment cost.