基于自动需求响应的多能互补智能楼宇全直流微网动态优化

There is huge potential of electricity demand response in intelligent building, but a challenge is encountered that conflicts to the consistency of dispatch form power to supply and demand to the consistency of dispatch form power to supply and demand and the dynamic of building control load distribution, under the distributed multi-energy complementary mix power supply environment. Automatic Demand Response (ADR) can further enhance the participation initiative of electricity users to promote the optimal balance of power supply and demand. It’s project aims to study the dynamic adaptive fuzzy control strategy to realize multi-source complementary energy management for Wind-PV-FC hybrid power system in intelligent building full DC Microgrid. The nonlinear behavior of multiple input DC/DC converter (MIDDC) is analyzed to get its optimization design on stability, the switch states of MIDDC or island/grid and their transfer code can be described by finite state machine theory to solve the problem for discrete stochastic dynamic problems between its different mode. The ADR model of building power and multi-scale rolling optimization mechanisms of power supply and demand is studied in-depth. By establish supply business model and load forecasting model to analyze the power behavior of both supply and demand based on ADR; For electricity of building to maximize the benefits as the goal, a master-slave game power supply and demand optimization method is proposed. The day-ahead power purchase planning of supply enterprise planning is implemented, and coordinate the real time scheduling of building, the power optimization electricity price can be got. Considering the distributed multi-energy complementary mix power supply environment of dynamic electricity price, using the optimal day-ahead scheduling decisions as conditions, an elite multi-objective optimization algorithm based on molecular kinetic theory for controllable load dispatch in intelligent building is also proposed to for solving multi-objective dynamic optimization.Research for this project can enrich the theory and methods of smart grid demand response, and improve the adaptability of intelligent computing in distributed dynamic environment.

楼宇用电需求响应潜力巨大，但分布式多能互补环境下电力供需调度一致性与楼宇负荷分配动态性相矛盾, ADR通过用户主动参与提升响应水平，优化电力供需平衡。项目深入研究模糊动态自适应控制策略，实现智能楼宇全直流微网风光燃多源互补能量管理；分析MIDDC非线性行为进行稳定优化设计；采用有限状态机描述开关状态和转移编码，求解不同模式的离散随机动态问题。研究楼宇用电ADR及电力供需多尺度滚动优化机制；建立供电企业模型和楼宇负荷预测模型，分析ADR电力供需主体行为；以楼宇用电效益最大化等为目标，提出基于主从博弈的电力供需优化方法，通过供电企业购电日前计划和楼宇用电决策实时调度实现优化电价。考虑动态电价和分布式混合供电，提出精英多目标分子动理论优化算法进行楼宇直流负荷调度动态优化。丰富智能电网ADR理论和方法，改进分布式和动态环境下智能计算的适应性。

本项目主要研究多源互补能量汇集、智能楼宇用电需求响应建模、智能楼宇负荷分配实时动态优化控制。在多源互补能量汇集研究上，依据多种分布式能源的时空互补特性，用一个能够实现升/降压且输入/输出同极性的新型多输入直流变换器代替多个单输入直流变换器，实现风、光、沼/柴三种清洁能源汇集，采用基于模糊控制的动态自适应功率协调控制进行智能楼宇能量管理，为将来实现楼宇源、汽、热等多种能量动态管理。采用有限状态机理论描述开关状态和转移编码，求解不同模式的智能能楼宇直流微网供需平衡的离散随机动态问题，实现能源和负荷的动态自适应调整。在智能楼宇用电需求响应建模上，研究供电企业模型，分析供电企业经济效益、发电边际成本驱动下购电计划、售电计划之间的关系及电力定价影响，充分利用风光水等能源的时空互补特征，在不影响用户舒适的前提条件下，最大限度利用新能源、减少用户总费用；研究含多能互补分布式能源的智能楼宇负荷预测模型，研究能量系统建模，通过支持向量机学习模型，搭建分布式能源仿真平台和楼宇负荷控制仿真平台，实现需求响应下智能楼宇负荷控制。在智能楼宇负荷分配实时动态优化控制上，研究智能楼宇负荷模型，并面向3用户、5用户、10用户和多用户等实例对象，研究智能楼宇负荷分配优化调度算法，探索基于分子动理论精英策略算法，优化求解过程中的多目标协调机制，及算法对计算环境的动态检测机制与响应策略；动态智能算法性能评价，研究算法适应性动态改进策略。