基于时间隧道与虚拟狼群策略的大型互联发电生态系统的智能发电控制

The more importance to solve the haze problem is that large–scale renewable energy is adopted in power system in order to reduce carbon emission. However the main trouble to use the renewable energy increasingly in power network is stochastic disturbance. Therefore the urgent task is how to ensure the compatibility between renewable energy and power system. A hierarchical and distributed control (HDC) system is proposed, which solves the problem that using conventional centralized automatic generation control (AGC) can not deal with the trouble of stochastic disturbance when renewable and distributed energy are penetrated into the power network increasingly. A mixed homogeneous and heterogeneous multi-agent stochastic consensus game will be taken in the project, which is a thorny problem in the control theory. The final research target in applied theory will be to set up smart generation control method for distributed energy, integrating new win-lose judgement criteria and HDC structure. In this project research content includes that the HDC system is established between the control center and the distributed energy. Also a novel smart generation control based on virtual wolf pack control is proposed. Finally a novel PDWoLF-PHC(λ) method based on time tunnel is proposed to acquire the optimal equilibrium solution of HDC. Multi-solution of the problem may be solved in theory when the number of agent is large. In practical engineering it also can solve the problem that AGC power reference cannot be allocated dynamically and optimally as tracking the total power reference. Research results verify that the proposed scheme can reduce carbon emission, furthest increase the utilization rate of the renewable energy.

解决雾霾问题重要途径之一是大规模引入可再生能源，以减少碳排放。而新能源大规模接入会给电网带来随机扰动问题。如何保证新能源与电力系统兼容成为当务之急。本课题拟提出一种分层分布控制（HDC）系统，以解决传统集中式AGC难以解决新能源及分布式能源大规模接入电网所带来的随机扰动问题。以控制论的难点问题，即同构异构相混合的多智能体随机一致博弈理论为支点，以建立面向分布式能源、融入新赢输评判标准且具有HDC结构的智能发电控制方法作为最终的研究目标。研究内容包括：在控制中心和分布式能源之间建立HDC系统；提出基于虚拟狼群的智能发电控制策略；提出基于时间隧道的PDWoLF-PHC(λ)算法，以获得HDC系统的最优均衡解。从理论上解决了HDC系统中智能体个数大规模激增而出现多解问题；从工程角度解决了对总功率跟踪的同时，没有对功率进行动态优化分配问题。研究成果能够减少碳排放、最大程度提高新能源利用率。

为解决传统集中式AGC难以解决分布式能源大规模接入电网所带来的随机扰动问题，本课题不仅探索了一种基于MA-SCG原理，融入新赢输评判标准的PDWoLF-PHC(λ)算法，且提出了一类适应于分层分布式控制系统协同控制的多智能体算法，进而获取AGC的“控制”部分最优解。以具有HDC结构的智能发电控制为研究对象，不仅提出基于同构异构相混合的多智能体随机一致博弈的分层分布式虚拟狼群控制策略，同时提出了多种适用于复杂电网模式下的同构异构相混合的协同一致性策略，进而获取AGC全局最优解。通过搭建的IEEE两区域改进模型和华中电网、湖北电网、广东电网等大电网系统模型，以及融入了水、风、光、燃料电池、生物质储能、飞轮储能、小水电、电动汽车和冷热电联产系统的配电网模型，验证了所提算法和策略的有效性。