基于多人博弈的智能电网能量有效分配
Efficient Energy Distribution in a Smart Grid using Multi-Player Games
摘要：
基于博弈论的算法和模型如今已成为关键系统数字控制器设计的重要技术。事实上，这样的技术可以实现自动合成：给定一个环境模型和控制器必须执行的属性，这些技术可以自动生成一个正确的控制器。在本文中，我们考虑了一类并发的，加权的，多人游戏，非常适合建模和研究的相互作用的几个代理谁是竞争一些可测量的资源，如能源。我们证明，这些游戏的子类总是承认一个纳什均衡，即在这种情况下，所有的球员在这样一种方式，他们没有动机偏离。此外，产生这些纳什均衡的策略具有特殊的结构：当其中一个代理人偏离均衡时，所有其他代理人形成一个联盟，该联盟将实施报复机制，惩罚偏离的代理人。我们将这些结果应用于现实生活中的案例研究，其中几个智能房屋使用太阳能电池板产生自己的能源，并可以在微电网中共享这些能源，必须分配这些能源的使用，以避免消耗必须从全球电网购买的电力。我们证明，我们的理论允许一个合成一个有效的控制器，这些房子：使用罚款支付的水电费作为激励，我们迫使房子遵循预先计算的时间表，最大限度地提高本地生产的能源消耗的比例。
英文摘要：
Algorithms and models based on game theory have nowadays become prominent techniques for the design of digital controllers for critical systems. Indeed, such techniques enable automatic synthesis: given a model of the environment and a property that the controller must enforce, those techniques automatically produce a correct controller, when it exists. In the present paper, we consider a class of concurrent, weighted, multi-player games that are well-suited to model and study the interactions of several agents who are competing for some measurable resources like energy. We prove that a subclass of those games always admit a Nash equilibrium, i.e. a situation in which all players play in such a way that they have no incentive to deviate. Moreover, the strategies yielding those Nash equilibria have a special structure: when one of the agents deviate from the equilibrium, all the others form a coalition that will enforce a retaliation mechanism that punishes the deviant agent. We apply those results to a real-life case study in which several smart houses that produce their own energy with solar panels, and can share this energy among them in micro-grid, must distribute the use of this energy along the day in order to avoid consuming electricity that must be bought from the global grid. We demonstrate that our theory allows one to synthesise an efficient controller for these houses: using penalties to be paid in the utility bill as an incentive, we force the houses to follow a pre-computed schedule that maximises the proportion of the locally produced energy that is consumed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
