Abstract
In this work, a two-layer optimization framework to investigate the effect of responsive demand scheduling on distribution network in the presence of distribution feeder reconfiguration (DFR) is proposed. In the first layer, scheduling of responsive demand is carried out. For this purpose, two objectives: minimize customer energy payment and load variance of network is developed from perspective of customers and network operator respectively. These objectives are optimized both independently and jointly. In the second layer, the problem of DFR is solved with the modified load profile obtained from first layer to minimize energy losses. The joint optimization of customer energy payment and load variance of network in the first layer is formulated as a multi-objective model and solved using an augmented \(\epsilon \)-constraint method, and the trade-off solution is obtained using fuzzy min–max satisfying criteria. The DFR problem in second layer is solved using genetic algorithm. The efficacy of the proposed two-layer framework is assessed on 33-bus distribution system.
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References
Ajoulabadi, A., Ravadanegh, S.N., Mohammadi-Ivatloo, B.: Flexible scheduling of reconfigurable microgrid-based distribution networks considering demand response program. Energy 196, 117024 (2020)
Baran, M.E., Wu, F.F.: Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Power Eng. Rev. 9(4), 101–102 (1989)
Esmaeili, S., Anvari-Moghaddam, A., Jadid, S., Guerrero, J.M.: Optimal simultaneous day-ahead scheduling and hourly reconfiguration of distribution systems considering responsive loads. Int. J. Electr. Power Energy Syst. 104, 537–548 (2019)
Gazijahani, F.S., Salehi, J.: Integrated DR and reconfiguration scheduling for optimal operation of microgrids using Hong’s point estimate method. Int. J. Electr. Power Energy Syst. 99, 481–492 (2018)
Gutiérrez-Alcaraz, G., Tovar-Hernández, J., Lu, C.N.: Effects of demand response programs on distribution system operation. Int. J. Electr. Power Energy Syst. 74, 230–237 (2016)
Imani, M.H., Niknejad, P., Barzegaran, M.: The impact of customers’ participation level and various incentive values on implementing emergency demand response program in microgrid operation. Int. J. Electr. Power Energy Syst. 96, 114–125 (2018)
Jahani, M.T.G., Nazarian, P., Safari, A., Haghifam, M.: Multi-objective optimization model for optimal reconfiguration of distribution networks with demand response services. Sustain. Cities Soc. 47, 101514 (2019)
Mavrotas, G.: Effective implementation of the \(\varepsilon \)-constraint method in multi-objective mathematical programming problems. Appl. Math. Comput. 213(2), 455–465 (2009)
Panwar, L.K., Konda, S.R., Verma, A., Panigrahi, B.K., Kumar, R.: Demand response aggregator coordinated two-stage responsive load scheduling in distribution system considering customer behaviour. IET Gener. Transm. Distrib. 11(4), 1023–1032 (2017)
Rawat, T., Niazi, K.R., Gupta, N., Sharma, S.: Impact assessment of electric vehicle charging/discharging strategies on the operation management of grid accessible and remote microgrids. Int. J. Energy Res. 43(15), 9034–9048 (2019)
Rawat, T., Niazi, K.R.: Comparison of EV smart charging strategies from multiple stakeholders’ perception. J. Eng. 2017(13), 1356–1361 (2017)
Rawat, T., Niazi, K., Gupta, N., Sharma, S.: A two stage interactive framework for demand side management in smart grid. In: 2019 IEEE 16th India Council International Conference (INDICON), pp. 1–4. IEEE, New York (2019)
Sadati, S.M.B., Moshtagh, J., Shafie-khah, M., Catalão, J.P.: Smart distribution system operational scheduling considering electric vehicle parking lot and demand response programs. Electr. Power Syst. Res. 160, 404–418 (2018)
Safdarian, A., Degefa, M.Z., Lehtonen, M., Fotuhi-Firuzabad, M.: Distribution network reliability improvements in presence of demand response. IET Gener. Transm. Distrib. 8(12), 2027–2035 (2014)
Singh, J., Tiwari, R.: Cost benefit analysis for v2g implementation of electric vehicles in distribution system. IEEE Trans. Industry Appl. pp. 1–1 (2020)
Singh, J., Tiwari, R.: Real power loss minimisation of smart grid with electric vehicles using distribution feeder reconfiguration. IET Gener. Transm. Distrib. 13(18), 4249–4261 (2019)
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Rawat, T., Niazi, K.R., Gupta, N., Sharma, S. (2021). Impact of Responsive Demand Scheduling on Optimal Operation of Smart Reconfigurable Distribution System. In: Gupta, O.H., Sood, V.K. (eds) Recent Advances in Power Systems. Lecture Notes in Electrical Engineering, vol 699. Springer, Singapore. https://doi.org/10.1007/978-981-15-7994-3_11
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DOI: https://doi.org/10.1007/978-981-15-7994-3_11
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