含小水电配电网重要负荷评估及其水光储优化配置方法

Assessment of Critical Load and Optimization Configuration Method for Small Hydropower Distribution Network with Integrated Hydro-PV-energy Storage

为保证含小水电配电网重要负荷的电能质量安全与稳定,发挥水光储系统互补作用,提出一种负荷重要程度评估方法和含小水电配电网重要负荷的水光储优化配置方法。首先,从用户角度出发,基于用电效益指标与用电体验指标2个维度建立负荷重要程度评估体系,采用G1熵权法量化用户节点的重要程度,确定重要负荷节点并将其作为光储接入备选节点,降低光储优化配置求解维度;其次,建立以水光储全寿命周期成本最小、电压偏差平方之和最小为目标的优化配置模型,引入规格化平面约束法求解两目标水光储优化配置问题,得到均匀的Pareto最优解集;然后,计算各解集综合偏移程度函数,得到最优折中解,作为优化配置最佳参考方案;最后,以改进的IEEE 33节点配电网为算例,证明所提的优化配置方法可以改善重要负荷的电压偏差,同时提高投资者的收益。

To ensure the safe and stable power quality of critical loads in the small hydropower distribution networks and give the hydro-PV-energy storage a complementary role,this paper proposes a method for assessing the importance of loads and an optimization configuration method for integrating hydro-PV-energy storage systems into the small hydropower distribution networks.Firstly,the paper establishes a system based on two dimensions for evaluating load importance from the perspective of users,one is electricity utilization index and the other is electricity experience index.The G1-entropy weight method is used to quantify the importance of user nodes to determine critical loads,which are then considered as alternative nodes for integrating energy storage,effectively reducing the dimensions of the optimization configuration.Secondly,an optimization configuration model is built with the objectives of minimizing the full life cycle cost of hydro-PV-energy storage and the sum of voltage deviations.The normalized normal constraint method is introduced to solve the bi-objective optimization problem,yielding a uniform Pareto optimal solution set.Then,by calculating the comprehensive deviation function of each solution set,the optimal compromise solution is obtained as the best reference for optimization configuration.Finally,using an improved IEEE 33 node distribution network as a case study,the paper demonstrates that the proposed optimization configuration method can improve the voltage deviations of critical loads while increasing investor returns.