Network Topology and Battery Size Exploration for Decentralized Energy Network with MIP Base Power Flow Optimization

• TANIGUCHI Ittetsu

  College of Science and Engineering, Ritsumeikan University

• SAKAKIBARA Kazutoshi

  College of Information Science and Engineering, Ritsumeikan University

• KATO Shinya

  Graduate School of Science and Engineering, Ritsumeikan University

• FUKUI Masahiro

  College of Science and Engineering, Ritsumeikan University

Abstract

Large-scale introduction of renewable energy such as photovoltaic energy and wind is a big motivation for renovating conventional grid systems. To be independent from existing power grids and to use renewable energy as much as possible, a decentralized energy network is proposed as a new grid system. The decentralized energy network is placed among houses to connect them with each other, and each house has a PV panel and a battery. A contribution of this paper is a network topology and battery size exploration for the decentralized energy network in order to make effective use of renewable energy. The proposed method for exploring the decentralized energy network design is inspired by the design methodology of VLSI systems, especially design space exploration in system-level design. The proposed method is based on mixed integer programming (MIP) base power flow optimization, and it was evaluated for all design instances. Experimental results show that the decentralized energy network has the following features. 1) The energy loss and energy purchased due to power shortage were not affected by each battery size but largely affected by the sum of all battery sizes in the network, and 2) the network topology did not largely affect the energy loss and the purchased energy. These results will become a useful guide to designing an optimal decentralized energy network for each region.

Journal

• IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E96.A (7), 1617-1624, 2013

  The Institute of Electronics, Information and Communication Engineers

Keywords

• design optimization
• mixed integer programming (MIP)
• combinatorial optimization problem
• smart grid

Details

• CRID: 1390001206310538240
• NII Article ID: 130003370690
• DOI: 10.1587/transfun.e96.a.1617
• ISSN: 17451337
• ISSN: 09168508
• Web Site: https://www.jstage.jst.go.jp/article/transfun/E96.A/7/E96.A_1617/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed