Optimal electric power‐plant planning under uncertainty of demand by means of the scenario aggregation algorithm

作     者：Nishikawa, Yoshikazu Tezuka, Tetsuo Kita, Hajime Nakano, Shinichi 

作者机构：Kyoto University Japan Kawasaki Heavy Industries Ltd. Japan 

出 版 物：《Electrical Engineering in Japan》 (Electr Eng Jpn)

年 卷 期：1993年第113卷第7期

页      面：85-94页

学科分类：080801[工学-电机与电器] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0807[工学-动力工程及工程热物理] 

主　　题：decentralized power plants economics of scale Power plant planning stochastic programming problem uncertainty of demand 

摘      要：Recently, electric power systems have faced increasing uncertainties in demand, energy price and environmental constraints in the future. In such a situation, a plan for expansion of the system capacity must be made robust against the aforementioned uncertainties. Large‐scale power plants require a long time for construction so that the decision of construction must be made under much uncertainty in the future. On the other hand, small‐scale plants require less time for construction, i.e., the decision can be made under less uncertainty in spite of their relatively higher costs. This paper is concerned with an optimal combination of the large‐scale and the small‐scale plants having the aforementioned characteristics under uncertainty of future demand. First, the demand growth in the future is described by scenarios of demand growth branching like a tree. Then the optimization problem of the system expansion is formulated into a stochastic linear‐programming problem. An optimal solution of the problem is obtained by using the scenario‐aggregation algorithm proposed by Rockafellar and Wets. The simulation results, yielded by using a parallel computation on transputers, show that there is a possibility of constructing small‐scale power plants to cope with the uncertainty even if they are more expensive than the large‐scale plants. Copyright © 1993 Wiley Periodicals, Inc., A Wiley Company