考虑多重不确定性的含需求响应及电碳交易的虚拟电厂优化调度策略

为解决当前对虚拟电厂系统中多重不确定性源的表征考虑不全面且处理方法单一的问题，提出一种基于蒙特卡罗与曼哈顿概率距离的场景生成与削减法来对风光出力、电价进行建模，并利用区间法对碳价、需求响应进行建模；以虚拟电厂运行成本最小化为目标，综合考虑电碳交易及激励型需求响应机制，建立基于区间线性规划的虚拟电厂优化调度模型，采用强区间线性规划法中的两阶段分解算法对模型进行求解，针对不同不确定性源的特点，采用2种方法处理虚拟电厂系统中的多重不确定性。算例结果表明，该模型能够通过指标变化趋势有效地反映多重不确定性因素对系统调度结果的影响，在保证虚拟电厂系统安全运行的基础上提高经济性，区间形式的表示为决策者留出了一定的现实选择空间。

Optimal scheduling strategy of virtual power plant with demand response and electricity-carbon trading considering multiple uncertainties

In order to solve the problems of incomplete consideration for representation of multiple uncertain sources in virtual power plant system and the single dealing method, a scenario generation and reduction method based on Monte Carlo and Manhattan probability distance is proposed to model the wind and photovoltaic output and electricity price, and the interval method is used to model the carbon price and demand response. Comprehensively considering the electricity-carbon trading and incentive-based demand response mechanisms, an optimal scheduling model of virtual power plant based on interval linear programming is established, which takes the minimum operation cost of virtual power plant as its objective. The model is solved by the two-stage decomposition algorithm in the strong interval linear programming method. Aiming at the characteristics of different uncertain sources, two methods are adopted to deal with the multiple uncertainties in virtual power plant system. Example results show that the proposed model can effectively reflect the influence of multiple uncertain factors on the system scheduling results by the index variation trend, improve the economy on the basis of ensuring the safe operation of virtual power plant system, and a certain realistic choice space for the decision-makers is provided by the representation of interval form.