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Calculation of the loss‐minimum configuration in the IEEJ local power system model
Authors:Yasuhiro Hayashi  Junya Matsuki  Ikuo Kurihara
Abstract:In Japan, local power systems (77 kV) are served from the 275‐ or 154‐kV substations. For enhancement of power supply reliability, the transmission lines are connected to several substations, and the operational configuration is radial. The local power system's configuration is determined by connecting and disconnecting transmission lines so as to keep the radial structure and satisfy the operation constraints. When a local power system has a number of transmission lines, many configuration candidates occur. Recently, an IEEJ committee made a practical scale local system model (IEEJ Local System Model). Since the IEEJ Local System Model has 76 transmission lines, the total number of configuration candidates is 276 (approximately 7.5 × 1022). In this paper, the authors try to strictly obtain the loss‐minimum configuration under constraints such as substation capacity, line capacity, and radial structure in the IEEJ Local System Model. In order to obtain the optimal configuration, a new computation algorithm is proposed. In the proposed algorithm, the configuration determination problem is replaced as two combinatorial optimization problems based on the operational constraints [(1) substation capacity, (2) line capacity, and (3) radial structure]. One combinatorial optimization problem (subproblem 1) is to pick up all partial configurations so as to minimize total line loss under the substation capacity constraint. By using the enumeration method, subproblem 1 is solved. Subproblem 2 is solved by using the reduced ordered binary decision diagram (ROBDD). Since the proposed method is based on enumeration and Boolean function, the optimality of obtained solution is guaranteed. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 146(4): 34–42, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10226
Keywords:IEEJ local power system model  loss‐minimum configuration  operational constraints  combinatorial optimization problem  global optimum  guarantee for optimal solution
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