DG Allocation Based on Reliability, Losses and Voltage Sag Considerations: an expert system approach
Expert System (ES) as a branch of Artificial Intelligence (AI) methodology can potentially help in solving complicated power system problems. This may be more appropriate methodology than conventional optimization techniques when contradiction between objectives appears in reaching the optimum solution. When this contradiction is the hindrance in reaching the required system operation through the application of traditional methods ES can give a hand in such case.
In this paper, the knowledge- based ES technique is proposed to reach near-optimum solution which is further directed to the optimum solution through particle swarm optimization (PSO) technique. This idea is known as Hybrid-Expert-System (HES). The proposed idea is used in getting the optimum allocation of a number of distributed generation (DG) units on Distribution System (DS) busbars taking into consideration three issues; reliability, voltage sag, and line losses. Optimality is assessed on the economic basis by calculating money benefits (or losses) resulting from DG addition considering the three aforementioned issues. The effectiveness of the proposed technique is ascertained through example.
Task Force on Distributed Generation Planning and Optimization, “State-of-the-art-techniques and challenges ahead for distribution generation planning and optimization,” IEEE Trans. Power Systems, vol. 28, no. 2, May 2013.
R. A. Walling, R. Saint, R. C. Dugan, J. Burke, and L.A. Kojovic, “Summary of distributed resources impact on power delivery systems,” IEEE Trans. Power Del., vol. 23, no. 3, pp.1636-1644, Jul. 2008.
IEEE Standard for Interconnecting Distributed Resources With Electric Power Systems., IEEE Std. 1547-2003, 2003.
R. Macdonald and G.W. Ault, “An optimisation model to integrate active network management into the distribution network investment planning task,” in Proc. 2011 Int. Conf. Electricity Distribution (CIRD).
V. Ravikumar Pandi, H.H. Zeineldein, and Weidong Xiao, “Determining optimal location and size od distributed generator resources considering harmonic and protection coordination limits,” IEEE Trans. Power Systems, vol. 28, no. 2, May 2013.
M. H. Bollen and F. Hassan, Integration of Distributed Generation in Power System. New York: Wiley-IEEE Press, 2011.
K. Abookazemi, M.Y. Hassan, and M. S. Majid, “A review on optimal placement methods of distribution generation sources,”2010 IEEE International Conference on Power and Energy (PECon2010).
Cesar Augusto Penuela Meneses and Jose Roberto Sanches Mantovani, “Improving the grid operation and reliability cost of distributed systems with dispersed generation,” IEEE Trans. Power systems, vol. 28, no. 3, August 2013.
Sahar A. Moussa, “Expert system aided power reinforcement with reliability and voltage sag consideration,”IEEE International Conference on Systems, Computing Sciences and Software Engineering (SCSS10), Bridgeport, CT 06604, USA, Dec 3-6, 2010.
Shang Gao and Zaiyue Zhang, “Multiplicate particle swarm optimization Algorithm,” Journal of Computers, vol. 5, no. 1, pp 150-157, Jan. 2010.
Sahar A. Moussa, “Distributed generation unit allocation utilizing expert system with reliability and voltage sag consideration,” 2015 IEEE LISAT Conference, May 1st , 2015.
J. Kennedy and R Eberhart, “Particle swarm optimization,” Proceedings of IEEE International Conference on Netral Networks (ICNN’95) , vol IV, pp 1942-1948, Perth, Australia, 1995.
Shawkat M. Hamdan, “ Modified particle swarm optimization techniques in electrical power system analysis,”Ph.D. Deseration, BUA,2014.
Power Systems test Case Archive [Online]. Available http://monaco.eee.starth.ac.uk/ukgds/.
- There are currently no refbacks.
Copyright (c) 2017 Sahar Abdel Moneim Moussa, Ayman Abdelwahed
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Renewable Energy and Sustainable Development
Academy Publishing Center (APC)
Arab Academy for Science, Technology and Maritime Transport (AASTMT)