Modified PSO Based Optimal Control for Maximizing Benefits of Distributed Generation System
Deregulation in the power system industry and the invention of new technologies for producing electrical energy has led to innovations in power system planning. Distributed generation (DG) is one of the most attractive technologies that bring different kinds of advantages to a lot of entities, engaged in power systems. In this paper, a model for considering DGs in the power system planning problem is presented. Dynamic power system planning for reduction of maintenance and operational cost is presented in this paper. In addition to that, a modified particle swarm optimization (PSO) is used to find the optimal topology solution. Voltage Profile Improvement Index (VPII) and Line Loss Reduction Index (LLRI) are taken as benefit index of employing DG. The effectiveness of this method is demonstrated through examination of IEEE 30 bus test system.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1128959Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 588
 X. Luo, J. Wang, M. Dooner and J. Clarke, “Overview of current development in electrical energy storage technologies and the application potential in power system operation,” Applied Energy, Vol. 137, 2015, pp. 511-536.
 G. Pepermans, J. Driesen, D. Haeseldonckx, R. Belmans, W. D’haeseleer, “Distributed generation: definition, benefits and issues,” Energy Policy, Vol. 33, No. 6, 2005, pp. 787-798.
 T. Ackermann, G. Andersson, L. Soder, “Distributed generation: a definition,” Electric Power Systems Research, Vol. 57, No. 3, 2001, pp. 195-204.
 D. Singh, K. S. Verma, “Multiobjective optimization for DG planning with load models,” IEEE Trans. Power Syst., Vol. 24, No. 1, 2009, pp. 427-436.
 D. Q. Hung, N. Mithulananthan, R. C. Bansal, “Analytical expressions for DG allocation in primary distribution networks,” IEEE Trans. Energy Convers., Vol. 25, No. 3, 2010, pp. 814-820.
 E. Naderi, H. Seifi, M. S. Sepasian, “A dynamic approach for distribution system planning considering distributed generation,” IEEE Transactions on Power Delivery, Vol. 27, No. 3, 2012, pp. 1313-1322.
 M. R. Estabragh, M. Mohammadian, M. Shafiee, “A novel approach for optimal allocation of distributed generations based on static voltage stability margin,” Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 20, No. 1, 2012, pp. 1044-1061.
 K. Divya and S. Srinivasan, “Optimal siting and sizing of DG in radial distribution system and identifying fault location in distribution system integrated with distributed generation,” IEEE Conference on Advanced Computing and Communication Systems (ICACCS), 22-23 Jan, 2016.
 C. Yammani, S. Maheswarapu, S. Matam, “Optimal placement of multi DGs in distribution system with considering the DG bus available limits,” Scientific and Academic Publishing, Energy and Power, Vol. 2, No. 1, 2012, pp. 18-23.
 R. K. Singh and S. K. Goswami, “A genetic algorithm based approach for optimal allocation of distributed generations in power systems for voltage sensitive loads,” ARPN Journal of Engineering and Applied Sciences, Vol. 4, No. 2, 2009, pp. 78-87.
 A. Bosisio, D. Moneta, M. T. Vespucci and S. Zigrino, “A procedure for the optimal management of medium voltage AC networks with distributed generation and storage devices,” Procedia - Social and Behavioral Sciences, Vol. 108, No. 3, 2014, pp. 164 – 186
 P. Chiradeja and R. Ramakumar, “An approach to quantify the technical benefits of distributed generation,” IEEE Transaction on Energy Conv., Vol. 19, No. 4, 2004, pp. 764-773.
 R. K. Singh and S. K. Goswami, “Optimum siting and sizing of distributed generations in radial and networked systems,” Electric Power Components and Systems, Vol. 37, No. 2, 2009, pp.127–145.
 Y. Arora, “A review on power quality problems and its solution at distribution end using interfacing devices and DG,” International Journal of Emerging Trends in Engineering and Development, Vol. 4, No. 5, 2014, pp. 373-382.
 K. Nara, Y. Hayashi, K. Ikeda, T. Ashizawa, “Application of tabu search to optimal placement of distributed generators,” in Proc. IEEE Power Engineering Society Winter Meeting, Columbus, USA, 28th jan–1st feb 2001, pp. 918–923.
 S. N. Ravadanegh, “A multistage expansion planning method for optimal substation placement, Iranian Journal of Electrical & Electronic Engineering, 2014, Vol. 10, No. 1, 311-324.
 D. Q. Hung and N Mithulananthan, Multiple distributed generator placement in primary distribution networks for loss reduction, IEEE Transaction on Industrial Electronics, Vol. 60, No. 4, 2013, pp. 1433-1446.
 G. Celli, E. Ghiani, S. Mocci, and F. Pilo, “A multiobjective evolutionary algorithm for the sizing and siting of distributed generation,” IEEE Transactions On Power Systems, Vol. 20, No. 2, 2005, pp. 750-757.
 G. Carpinelli, G. Celli, S. Mocci, “Optimisation of embedded generation sizing and siting by using a double trade-off method,” IEE Proc., Gener. Trans. Distrib., Vol. 152, No. 4, 2005, pp. 503–513.
 R. P. Payasi, A. K. Singh and D. Singh, “Review of distributed generation planning: objectives, constraints, and algorithms, International Journal of Engineering, Science and Technology, Vol. 3, No. 3, 2011, pp. 823-836.
 J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proc. IEEE Int. Conf. Neural Networks, pp. 1942–1948.
 J. Kennedy, “The particle swarm: social adaptation of knowledge,” in: Proceedings of International Conference on Evolutionary Computation,” 1997, pp. 303–308.
 M. H. Moradi and M. Abedini, “A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems,” Electrical Power and Energy Systems, Vol. 34, No. 2, 2012, pp. 66–74.
 J. K. Charles and N. A. Odero, “A combined sensitivity factor based GA-IPSO approach for system loss reduction and voltage profile enhancement,” International Journal of Innovative Research in Engineering & Science, Vol. 2, No. 12, 2013, pp. 453-457.
 C. A. Coello, G. T. Pulido and M. S. Lechuga, “Handling multiple objectives with particle swarm optimization,” IEEE Transaction on Evolutionary Computation, Vol. 8, No. 3, 2004, pp. 256-259.
 M. B. Reddy, Y. P. Obulesh and S. S. Raju, “Particle swarm optimization based optimal power flow for volt-var control,” ARPN Journal of Engineering and Applied Sciences, Vol. 7, No. 1, 2012, pp. 20-25.
 A. I. Selvakumar and K. Thanushkodi, “A new particle swarm optimization solution to nonconvex economic dispatch problems,” IEEE Transaction on Power Systems, Vol. 22, No. 1, 2007, pp. 42-51.