Document Type : Review Article

Authors

1 Bahar Branch, Islamic Azad University, Hamedan, Iran

2 Department of Electrical Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran

Abstract

In this paper a hybrid and practical method is provided to allocation and capacity determination combined heat and power (CHP) generator at a bus. This method consists of  two stages. Firstly, Through the bus thermal coefficient, the suitable buses will be found  for CHP installation. This coefficient indicates the possibility of heat selling around each buses and will be calculated using the fuzzy method. Then, for the appropriate buses, considering the obtained heat capacity and electrical power to heat ratio of  CHPs on the market, several CHPs is recommended . Secondly, On the one hand, the amount of loss reduction and improve the voltage due to proposed CHPs installation  using nodal pricing method as financial benefit of distribution company  to be derived, and on the other hand, the financial benefit for investors by selling CHP heat output is determined Finally, using the Game Theory and consider the distribution company and investors as players, the suitable location and capacity for CHP installation based on the Game strategy set is obtained. The proposed method, is implemented to a sample distribution feeder in the Hamadan city and the results are shown.

Keywords

[1] M.H.Moradi, M. Abedini, A Combination of Genetic Algorithm and Particle Swarm Optimization for Optimal DG location and Sizing in Distribution Systems, Int. Journal of Electrical Power and Energy Systems (34) 2012, pp 66-74
[2] T. Ackermann, G. Andersson, L. Soder. (2001). Distributed generation : a definition, Electr. Power Syst. Res. 57 (3) 195–204.
[3] Mithulananthan N, Oo Than, Van Phu Le. (2004). Distributed generator placement in power distribution system using genetic algorithm to reduce losses. TIJSAT ;9(3):55–62.
[4] Griffin T, Tomosovic K, Secrest D, Law A. (2000). Placement of dispersed generations systems for reduced losses. In: Proceedings of the 33rd Hawaii international conference on sciences, Hawaii .
[5] M.H.Moradi, M. Abedini , A Combination of GA and PSO for Optimal DG location and Sizing in Distribution Systems with Fuzzy Optimal Theory, International Journal of Green Energy, 2011, In press.
[6] K. Nara, Y. Hayashi, K. Ikeda, and T. Ashizawa, (2001). Application of Tabu Search to optimal placement of distributed generators, Proceedings of the IEEE Power Engineering Society, vol. 2, pp. 918-923, February.
[7] G. Bidini, U. Desideri, S. Saetta, P. ProiettiBocchini, 1998 . Internal combustion engine combined heat and power plants: case study of the university of Perugia power plant, Appl. Therm. Eng. 18 (6) 401–412.
[8] A.C. Caputo, M. Palumbo, F. Scacchia, (2004). Perspectives of RDF use in decentralized areas: comparing power and co-generation solutions, Appl. Therm. Eng. 24 (14–15) 2171–2187.
[9] R.K. Singh, S.K. Goswami. (2010). Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction,and voltage improvement including voltage rise issue. Electrical Power and Energy Systems 32 . 637–644 .
[10] Viawan Ferry A, SanninoAmbra, DaalderJaap. (2007) . Voltage control with on-load tap changers in medium voltage feeders in presence of distributed generation.Electr Power Syst Res ;77:1314–22.
[11] Repo S, Laaksonen H, JarventaustaPertti, HuhtalaOsmo, Mickelsson Mikael. (2003) . A case study of a voltage rise problem due to a large amount of distributed generation on a weak distribution network. In: Proceedings of 2003 IEEE Bologna power tech conference, vol. 4. Bologna, Italy .
[12] Song Yiqun, HouZhijian, Wen Fushuan, Ni Yixin, Wu F.F. (2002). Analysis of marketpower in oligopolistic electricity market based on game theory”, power systems and communications infrastructures for the future, Beijing, September .
[13] Lance B.cunningham, Ross baldick, Martin L. Baughman. (2002) . Anempiricalstudy of applied game theory: Transmission constrained cournot behavior. IEEE transactions on power systems, Vol.17, No.1,February.
[14] V.Neimane ,A.Sauhats, G.Vempers, I.Tereskina, G.Bockarjova. (2010). Allocating Production Cost at CHP Plant to Heat and Power using Cooperative Game Theory “ IEEE Bucharest Power Tech Conference, June 28th – July 2nd, Bucharest, Romania.
[15] ASHREA handbook of fundamental. (2005). the American society of heating, refrigerating and air –conditioning engineers, inc.
[16] tabatabaie, seyed mojtaba. (2008). Computing facility construction .
[17] Mutale J, Strbac G, Crucis S, Jenkins N. (2000). Allocation of losses in distribution systems with embedded
generation. IEE Proc Gen TransmDistribut;147(1), 7–12.
[18] Viawan Ferry A, SanninoAmbra, DaalderJaap. (2007). Voltage control with on-load tap changers in medium voltage feeders in presence of distributed generation.Electr Power Syst Res;77:1314–22.
[19] D.W.Wu, R.Z. Wang. (2006). Combined cooling, heating and power: A review “. Progress in energy and Combustion Science 32, 459- 495.
[20] Catalog of CHP Technologies. (2008). U.S. Environmental Protection Agency(EPA), Combined Heat and Power Partnership, Arlington, Virginia 22209 .
[21] Osborne, M.J. and Rubinstein, A. (1994). A Course in Game Theory , MIT Press(Chapters 13, 14, 15) .
[22] A.Souri. (2008). Game Theory and Economic Applications “,Department of Economic Sience, Tehran, Iran, Nore Elm Entesharat .
[23] 19th section. (2009). National Building Regulations In Iran, Tehran, Iran .
[24] A.Jalali, H. zekri. (2011). Allocation of losses costs in distribution networks in the presence of distributed generation using nodal pricing method ,the second electrical energy saving conference,Ahvaz ,Iran .
[25] M.H.Moradi, F.Samaie. (2011). Optimal Allocation of Combined Heat and Power (CHP) in Hamedan City . Research Project, research committee of HAMADAN power distribution company.
[26] Sotkiewicz Paul M, Mario Vignolo J. (2006). Nodal pricing for distribution networks: efficient pricing for efficiency enhancing DG. IEEE Trans power Syst ;21:1013–4.