Simultaneously Optimal Placement and Operation Scheduling of BESSs and DGs in Distribution Networks in order to minimizing net present value related to power losses

Year 2016, Volume: 16 Issue: 2, 2081 - 2089, 23.09.2016

Murtaza Farsadi Tohid Sattarpur Amin Yazdaninejadi

Abstract

In recent years, because of increasing interest to integrate energy storage devices as one of the main goals into the power system smart grid, penetration of battery energy storage and distribution generation in distribution networks is increased. The integration of battery energy storages and distribution generations are improve the reliability and satisfactory operation of power system. The deployment of distributed generations and battery energy storages has led to a revolution in the use of distribution systems to improve many concepts of smart grid. This paper prepared to optimal palacement and optimal operation of distributed generations and battery energy storages to improved net present value reduction related to power losses as one of the main factors in smart grids. This placement is evaluated based on genetic algorithm in order to achieve the best operation during faced different percentage of load levels with specific electricity price for each level. In this paper in spite of most of researches which are proposed in literatures in this fields, the placement problem is done simultaneously for distribution generation and battery energy storages, in addition, the load characteristic is considered multi-level to approach realty in optimal scheduling. In this paper to show the superiority of using distribution generation and battery energy storages, cost benefit of energy storage installation respected to the energy losses cost is calculated toward optimal costs. This is a while, in this paper, arbitrage benefits of this installation did not considered. By considering this, yet the results show that, the total benefit in presented scheduling is higher than homogeneous works. During this scheduling, a comprehensive investigation is done to describe of combination structure of distribution generation and battery energy storage systems. To evaluate this optimization challenge, IEEE 33 bus standard distribution network test is chosen to implement presented scheme. To validation of efficiency of presented scheme, results are compared with previous similar works.

Keywords

BESS, DGs, net present value, and power losses

References

• Anderson, Max D., and Dodd S. Carr. "Battery energy storage technologies"Proceedings of the IEEE 81.3 (1993): 475-479.
• Lachs, W. R., and D. Sutanto. "Application of battery energy storage in power systems" Power Electronics and Drive Systems, 1995., Proceedings of 1995 International Conference on. IEEE, 1995.
• Wade, Neal S., et al. "Evaluating the benefits of an electrical energy storage system in a future smart grid" Energy policy 38.11 (2010): 7180-7188.
• Amin, S. Massoud, and Bruce F. Wollenberg. "Toward a smart grid: power delivery for the 21st century" Power and Energy Magazine, IEEE 3.5 (2005): 34-41.
• Joseph, Ami, and Mohammad Shahidehpour. "Battery storage systems in electric power systems" Power Engineering Society General Meeting, IEEE, 2006.
• A. Zakariazadeh, S. Jadid, and P. Siano, "Smart Microgrid Energy and Reserve Scheduling with Demand Response Using Stochastic Optimization", Electrical Power and Energy Systems, vol. 63, pp. 523–533, 2014.
• T. Niknam, F. Golestaneh, and A. Malekpour, "Probabilistic Energy and Operation Management of a Microgrid Containing Wind/ Photovoltaic/ Fuel Cell Generation and Energy Storage Devices Based on Point Estimate Method and Self-adaptive Gravitational Search Algorithm", Energy, vol. 43, pp. 427-437, 2012.
• K. Kuroda, H. Magori, D. Kobayashi, T. Ichimura and R. Yokoyama, "An Evaluation Method for the Impact of PV Installations into Distribution Systems", IEEE Innovative Smart Grid Technologies-Asia (ISGT ASIA), Japan, 2014.
• A. Zakariazadeh, S. Jadid, and P. Siano, "Economic Environmental Energy and Reserve Scheduling of Smart Distribution Systems: A Multiobjective Mathematical Programming Approach", Energy Conversion and Management, vol. 78, pp. 151–164, 2014.
• Harrison, Gareth P., Antonio Piccolo, and Pierluigi Siano. "Exploring the tradeoffs between incentives for distributed generation developers and DNOs" IEEE Transactions on Power Systems, 22.2 (2007): 821-828.
• Zou, Kai, et al. "Distribution system planning with incorporating DG reactive capability and system uncertainties" IEEE Transactions on Sustainable Energy, 3.1 (2012): 112-123.
• Celli, Gianni, et al. "A multiobjective evolutionary algorithm for the sizing and siting of distributed generation" IEEE Transactions on Power Systems, 20.2 (2005): 750-757.
• Liu, Zhipeng, Fushuan Wen, and Gerard Ledwich. "Optimal siting and sizing of distributed generators in distribution systems considering uncertainties" IEEE Transactions on Power Delivery, 26.4 (2011): 2541-2551.
• Faria, Pedro, et al. "Modified particle swarm optimization applied to integrated demand response and DG resources scheduling." IEEE Transactions on Smart Grid, 4.1 (2013): 606-616.
• Fini, A. Sheikhi, M. Parsa Moghaddam, and M. K. Sheikh-El-Eslami. "An investigation on the impacts of regulatory support schemes on distributed energy resource expansion planning" Renewable Energy 53 (2013): 339-349.
• Naik, S. Gopiya, D. K. Khatod, and M. P. Sharma. "Optimal allocation of combined DG and capacitor for real power loss minimization in distribution networks" International Journal of Electrical Power & Energy Systems 53 (2013): 967-973.
• S. Golshannavaz, “Optimal Simultaneous Siting and Sizing of DGs and Capacitors Considering Reconfiguration in Smart Automated Distribution Systems” J Intelligent Fuzzy Syst, vol. 27, no. 4, pp. 1719-1729, 2014.
• Awad, Ahmed S., Tarek HM El-Fouly, and Magdy M. Salama. "Optimal ESS Allocation for Load Management Application." IEEE Transactions on Power Systems, 30.1 (2015): 327-336.
• Xiao, Jun, et al. "Method, implementation and application of energy storage system designing" International Transactions on Electrical Energy Systems, 24.3 (2014): 378-394.
• Exarchakos, Lazaros, Matthew Leach, and Georgios Exarchakos. "Modelling electricity storage systems management under the influence of demand‐side management programmes" International Journal of Energy Research 33.1 (2009): 62-76.
• Haessig, Pierre, et al. "Energy storage sizing for wind power: impact of the autocorrelation of day‐ahead forecast errors" Wind Energy 18.1 (2015): 43-57.
• M. Farsadi, T. Sattarpour, A. Yazdaninejadi "Optimal Placement and Operation of BESS in a Distribution Network Considering the Net Present Value of Energy Losses Cost" 9th International conference on ELECO, IEEE index. 2015, 1-6.
• Pregelj, Aleksandar, Miroslav Begović, and Ajeet Rohatgi. "Recloser allocation for improved reliability of DG-enhanced distribution networks" IEEE Transactions on Power Systems, 21.3 (2006): 1442-1449.
• Salehi, Javad, and Mahmood‐Reza Haghifam. "Determining the optimal reserve capacity margin of Sub‐Transmission (ST) substations using Genetic Algorithm" International Transactions on Electrical Energy Systems, 24.4 (2014): 492-503.
• Sattarpour, T., et al. "An Optimal Procedure for Sizing and Siting of DGs and Smart Meters in Active Distribution Networks Considering Loss Reduction" Journal of Electrical Engineering & Technology 10.3 (2015): 804-811.
• Sood, V. K., et al. "Developing a communication infrastructure for the smart gri." Electrical Power & Energy Conference (EPEC), 2009 IEEE. IEEE, 2009.
• BaranME, Wu FF. "Optimum sizing of capacitor placed on radial distribution systems" IEEE Trans PWRD 4 (1989): 735-74.