DOI QR코드

DOI QR Code

The Optimal Operation for Community Energy System Using a Low-Carbon Paradigm with Phase-Type Particle Swarm Optimization

  • Kim, Sung-Yul (Dept. of Electrical Engineering, Hanyang Univ.) ;
  • Bae, In-Su (Dept. of Electrical Engineering, Kangwon National Univ.) ;
  • Kim, Jin-O (Dept. of Electrical Engineering, Hanyang Univ.)
  • 투고 : 2010.01.19
  • 심사 : 2010.04.21
  • 발행 : 2010.11.01

초록

By development of renewable energy and more efficient facilities in an increasingly deregulated electricity market, the operation cost of distributed generation (DG) is becoming more competitive. International environmental regulations of the leaking carbon become effective to reinforce global efforts for a low-carbon paradigm. Through increased DG, operators of DG are 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, a community energy system (CES) with DGs is 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 transmission service charges and other costs. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize profit. Considering the international environment regulations, CE 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 introduces 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. A Particle Swarm Optimization (PSO) will be used to solve this complicated problem. The optimal operation of DG represented in this paper would guide CES and system operators in determining the decision making criteria.

키워드

참고문헌

  1. P. A. Daly and J. Morrison, "Understanding the Potential Benefits of Distributed Generation on Power Delivery Systems", Rural Electric Power Conference, pp. 424-429, 1999
  2. Funabashi T., Yokoyama R., “Microgrid field test experiences in Japan”, Power Engineering Society General Meeting, IEEE, pp. 2, 18-22 June 2006
  3. Prodanovic M., Green T.C., "High-Quality Power Generation Through Distributed Control of a Power Park Microgrid", IEEE Trans. on Industrial Electronics, vol. 53, Issue 5, pp. 1471-1482, Oct. https://doi.org/10.1109/TIE.2006.882019
  4. In-Su Bae and Jin-O Kim, “Reliability Evaluation of Customers in a Microgrid”, IEEE Trans. on Power System, vol. 23, No. 3, August 2008, pp.1416-1422. https://doi.org/10.1109/TPWRS.2008.926710
  5. T.J. Hammons, "Impact of electric power generation on green house gas emissions in Europe: Russia, Greece, Italy and views of the EU power plant supply industry - A critical analysis", International Journal of Electrical Power & Energy Systems, vol. 28, Issue 8, pp 548-564, Oct. 2006 https://doi.org/10.1016/j.ijepes.2006.04.001
  6. Erik Delarue, William D’haeseleer, “Greenhouse gas emission reduction by means of fuel switching in electricity generation: Addressing the potentials”, ELSELVIER Energy Conversion and Management, vol. 49, pp 843-853, Aug. 2007
  7. Karki, S.; Mann, M.D.; Salehfar, H., “Substitution and Price Effects of Carbon Tax on CO2 Emissions Reduction from Distributed Energy Sources”, Power Systems Conference: Advanced Metering, Protection, Control, Communication, and Distributed Resources, 2006. PS '06, pp. 236 - 243, 14-17 March 2006
  8. J. Kennedy and R. C. Eberhart, “Particle Swarm Optimization”, Proceedings IEEE Int’l. Conf. on Neural Networks, IV, pp.1942-1948. 1995
  9. Yuchao Ma, Chuanwen Jiang, Zhijian Hou, Chenming Wang, "The Formulation of the Optimal Strategies for the Electricity Producers Based on the Particle Swarm Optimization Algorithm", IEEE Trans. on Power System, vol. 21, no. 4, pp. 1663-1671, 2006 https://doi.org/10.1109/TPWRS.2006.883676
  10. Belkacem Mahdad , Tarek Bouktir, Kamel Srair, Mohamed El Hachemi Benbouzid, “Economic Power Dispatch with Discontinuous Fuel Cost Functions using Improved Parallel PSO", Journal of Electrical Engineering & Technology, pp. 45-53, Mar. 2010

피인용 문헌

  1. Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm vol.9, pp.2, 2014, https://doi.org/10.5370/JEET.2014.9.2.433
  2. Transmission Network Expansion Planning for the Penetration of Renewable Energy Sources - Determining an Optimal Installed Capacity of Renewable Energy Sources vol.9, pp.4, 2014, https://doi.org/10.5370/JEET.2014.9.4.1163