电力高峰负荷持续增长以及间歇式能源的迅猛发展对电力系统调节能力提出新的重大挑战,柔性负荷调度作为发电调度的补充,已成为国内外关注的热点。从柔性负荷参与电网调度运行的视角综述了近年来国内外在柔性负荷可调度潜力、调度模式、响应行为建模和调度架构等方面的研究成果,着重对比分析了不同调度模式和调度架构的适用场景和优缺点,从柔性负荷综合响应建模、多时间尺度互动交易模式、多时间尺度协调调度、集中＆分布式协调控制和互动效益评估5个方面探讨了柔性负荷调度领域需进一步研究的方向。并结合中国国情,提出了开展柔性负荷调度的建议设想。

Integration of flexible and controllable load resources into power system scheduling and operation will enrich scheduling modes and enhance the system regulating capability, which has become a worldwide research hotspot. This paper is intended to make a review of recent investigations on the adjustable potential, scheduling modes, response behavior modeling and scheduling frameworks of flexible loads considering demand response (DR). Then detailed light is shed on the advantages and problems of these scheduling modes and scheduling frameworks. By proceeding from five aspects including modeling of flexible load’s comprehensive response, multi-time scales interactive trading modes, multi-time scales coordinated scheduling, coordination of centralized control and decentralized control, interactive benefit assessment, further research directions for flexible load scheduling are discussed. In addition, in view of China’s actual situation, suggestions for and assumptions about developing flexible load scheduling are proposed.

提出了一种通过需求侧管理激励负荷侧的高载能企业参与调峰,提高系统风电消纳能力的错峰峰谷分时电价机制。考虑了高载能企业转移负荷能力差的特点及其对峰谷分时电价时段连续划分的诉求,建立了相应的峰谷时段连续划分的错峰用电模型,并以提高系统谷时风电消纳能力为目标建立了错峰峰谷电价决策模型。通过解耦时段划分与电价优化,设计了2步优化方法求解峰谷时段与电价综合优化模型。错峰峰谷电价避免了传统多峰时段峰谷电价对用户的频繁扰动,更加适合高载能企业等大用户的生产特点。通过协调各用户的峰谷时段划分,减少峰时段时长,减轻了高载能企业电力成本压力,提高了参与调峰的积极性。

A stagger peak-valley time-of-use (TOU) price mechanism, in which heavy energy-consuming enterprises are impelled to participate the peak load regulation under the demand side management (DSM), is proposed to improve the wind power accommodation capability of power grid. Considering the poor load transferring capability of heavy energy-consuming enterprises as well as their appeal to continually dividing the period of peak-valley TOU price, an stagger peak power consumption model with continuous division of peak-valley period is correspondingly established, and taking the improvement of wind power accommodation ability of power grid at valley period as the objective, a decision-making model for stagger peak-valley TOU price is built. Through decoupling time period division optimization and electricity price optimization, a two-step optimization method is designed to solve the synthetic optimization model of peak-valley period and electricity price. The frequent disturbance to power consumers due to the peak-valley price under traditional multi-peak load periods can be avoided by stagger peak-valley price mechanism, so it is more suitable for the production characteristics of big consumers such as heavy energy-consuming enterprises and so on. By means of coordinating the peak-load period division of various consumers and decreasing the length of peak-load period, the stress of heavy energy-consuming enterprises due to electric power cost can be relieved, thus the initiative of heavy energy-consuming enterprises to take part in the peak load regulation is enhanced.

随着风电并网容量的增加，调峰和电网输送能力已成为电力系统消纳风电的瓶颈。为直观表达省级系统消纳风电的能力，指导风电发展规划以及未来调度运行工作，结合中国电力系统运行特性，研究了综合考虑调峰约束和电网输送能力约束的风电电量消纳预测方法，并根据中国北方风电富集省份现有的电网条件、电源结构、实际运行方式等信息，对多种场景下两相邻省份水平年风电电量消纳情况进行了详细预测分析，最后根据电力系统实际运行情况，提出了提高风电消纳能力的措施和建议。

With the increasing of wind power installed capacity， peak load regulation and transmission capacity have become main restrictions for accommodation of wind power. In order to provide an intuitive demonstration on the accommodation of wind power and guidance for the planning and dispatching of wind power， this paper presents a method for predicting the accommodation of wind energy considering peak load and transmission regulation. Based on the present condition of the gird， construction of power source and the actual operational data of the northern provinces of China with rich wind power resource， this paper analyzes and predicts two provinces available capability of wind energy in the target year under different scenarios. At last， this paper gives advices to improve the capability to connect wind power.