A A Tutorial on Event-Based Optimization with Application in Energy Internet

In many practical systems, the control or decision-making is usually triggered by certain events. These systems are classified as discrete event dynamic systems (DEDSs). Considering the performance optimization of these systems, a new optimization framework called event-based optimization (EBO) is introduced in this paper. Compared with Markov decision process (MDP), one of the main characteristics of EBO is that decisions are made based on“events”rather than states. In this regard, there exist a number of advantages for EBO. First, an event usually corresponds to a set of state transitions with some common properties. Generally, the number of events of a system requiring decisions is much smaller than that of states. Therefore, the EBO approach can utilize the special structure of systems characterized by events to aggregate the potentials, thus alleviating the curses of dimensionality. Second, the EBO approach applies to many practical problems where actions are required only when certain events happen. Such problems do not fit well the standard MDP formulation in which the decisions made based on different states are independent. However, for that cases, the same action may be taken for the same event, which may correspond to many different states. Based on the basic theory of MDP, this paper is addressed around three aspects. First, we briefly review the basic ideas of EBO and the development for its theory and applications. Second, we introduce the simulation-based policy iteration methods for EBO based on the performance potentials or Q-factors; Third, a case study is conducted on the coordination of electric vehicle charging with the distributed wind power generation of a building, which aims to shed some lights on the application of EBO in energy Internet.