The Optimal Operation of Distributed Generation Possessed by Community Energy System Considering Low-Carbon Paradigm

저탄소 패러다임에 따른 구역전기사업자의 분산전원 최적 운영에 관한 연구

  • 김성열 (한양대 공대 전기공학과) ;
  • 심헌 (한양대 공대 전기공학과) ;
  • 배인수 (강원대 전기제어공학부) ;
  • 김진오 (한양대 공대 전기공학과)
  • Published : 2009.08.01

Abstract

By development of renewable energies and high-efficient facilities and deregulated electricity market, the operation cost of distributed generation(DG) becomes more competitive. The amount of distributed resource is considerably increasing in the distribution network consequently. Also, international environmental regulations of the leaking carbon become effective to keep pace with the global efforts for low-carbon paradigm. It contributes to spread out the business of DG. Therefore, the operator of DG is able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, community energy system(CES) having DGs is recently a new participant in the energy market. DG's purchase price from the market is different from the DG's sales price to the market due to the transmission service charges and etc. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize the profit. If there is no regulation for carbon emission(CE), the generators which get higher production than generation cost will hold a prominent position in a competitive price. However, considering the international environment regulation, CE newly will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and unit's efficiency. This paper will introduce the optimal operation of CES's DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES and Particle Swarm Optimization (PSO) will be used to solve this problem. The optimal operation of DG represented in this paper is to be resource to CES and system operator for determining the decision making criteria.

Keywords

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