Using Intelligent System Approaches for Simulation of Electricity Markets

Abstract

Significances and approaches of applying intelligent systems to artificial electricity market is discussed. In recent years, with the moving into restructuring of electric system in Japan, the deregulation for the electric market is progressing. The most major change of the market is a founding of JEPX (Japan Electric Power eXchange.) which is expected to help lower power bills through effective use of surplus electricity. The electricity market designates exchange of electric power between electric power suppliers (supplier agents) themselves. In the market, the goal of each supplier agents is to maximize its revenue for the entire trading period, and shows complex behavior, which can model by a multiagent platform. Using the multiagent simulations which have been studied as "artificial market" helps to predict the spot prices, to plan investments, and to discuss the rules of market. Moreover, intelligent system approaches provide for constructing more reasonable policies of each agents. This article, first, makes a brief summary of the electricity market in Japan and the studies of artificial markets. Then, a survey of tipical studies of artificial electricity market is listed. Through these topics, the future vision is presented for the studies.

Multi‐agent‐based autonomous power distribution network restoration using contract net protocol

“…7, generation areas 1 and 20 act as network hubs. In addition, areas 4,5,8,9,11,12,17 connect two subnetworks centered on areas 1 and 20. These network functions were developed by negotiations among agents that possessed only local information.…”

“…Some solutions to this problem based on autonomous distributed approach have been proposed recently in many fields, such as an automated system composed of agents playing various roles as necessary for control and operation of power systems [2], multi-agent techniques for fault diagnosis [3,4], and so forth. There have also been power market analyses using multi-agent approaches [5,6].…”