Adetunji, KEHofsajer, IWAbu-Mahfouz, Adnan MICheng, L2023-05-082023-05-082022-11Adetunji, K., Hofsajer, I., Abu-Mahfouz, A.M. & Cheng, L. 2022. A novel dynamic planning mechanism for allocating electric vehicle charging stations considering distributed generation and electronic units. <i>Energy Reports, 8.</i> http://hdl.handle.net/10204/127602352-4847https://doi.org/10.1016/j.egyr.2022.10.379http://hdl.handle.net/10204/12760Achieving a sustainable and efficient power systems network and decarbonized environment involves the optimal allocation of multiple distributed energy resource (DERs) unit types and flexible alternating current transmission systems (FACTS) to distribution networks. However, while the most focus is on optimization algorithms and multi-objective techniques, little to no attention is paid to the underlying mechanisms in planning frameworks. This paper goes beyond existing literature by investigating the impact of planning mechanisms in smart grid planning frameworks when considering the allocation of PV distributed generation units, battery energy storage systems, capacitor banks, and electric vehicle charging station facilities. First, a single- and multi-objective planning problem is formulated. Then, we propose a novel adaptive-dynamic planning mechanism that uses a recombination technique to find optimal allocation variables of multiple DER and FACTS types. To cope with the additional complexity resulting from the expanded solution space, we develop a hybrid stochastic optimizer, named cooperative spiral genetic algorithm with differential evolution (CoSGADE) optimization scheme, to produce optimal allocation solution variables. Through numerical simulations, it is seen that the proposed adaptive planning mechanism improves achieves a 12% and 14% improvement to the conventional sequential (multi-stage) and simultaneous mechanisms, on small to large scale distribution networks.FulltextenBattery energy storage systemsComputational intelligenceDistributed generationElectric vehiclesElectric vehicle charging stationHybrid optimization algorithmPlanning mechanismsReinforcement learningArticleAdetunji, K., Hofsajer, I., Abu-Mahfouz, A. M., & Cheng, L. (2022). A novel dynamic planning mechanism for allocating electric vehicle charging stations considering distributed generation and electronic units. <i>Energy Reports, 8</i>, http://hdl.handle.net/10204/12760Adetunji, KE, IW Hofsajer, Adnan MI Abu-Mahfouz, and L Cheng "A novel dynamic planning mechanism for allocating electric vehicle charging stations considering distributed generation and electronic units." <i>Energy Reports, 8</i> (2022) http://hdl.handle.net/10204/12760Adetunji K, Hofsajer I, Abu-Mahfouz AM, Cheng L. A novel dynamic planning mechanism for allocating electric vehicle charging stations considering distributed generation and electronic units. Energy Reports, 8. 2022; http://hdl.handle.net/10204/12760.TY - Article AU - Adetunji, KE AU - Hofsajer, IW AU - Abu-Mahfouz, Adnan MI AU - Cheng, L AB - Achieving a sustainable and efficient power systems network and decarbonized environment involves the optimal allocation of multiple distributed energy resource (DERs) unit types and flexible alternating current transmission systems (FACTS) to distribution networks. However, while the most focus is on optimization algorithms and multi-objective techniques, little to no attention is paid to the underlying mechanisms in planning frameworks. This paper goes beyond existing literature by investigating the impact of planning mechanisms in smart grid planning frameworks when considering the allocation of PV distributed generation units, battery energy storage systems, capacitor banks, and electric vehicle charging station facilities. First, a single- and multi-objective planning problem is formulated. Then, we propose a novel adaptive-dynamic planning mechanism that uses a recombination technique to find optimal allocation variables of multiple DER and FACTS types. To cope with the additional complexity resulting from the expanded solution space, we develop a hybrid stochastic optimizer, named cooperative spiral genetic algorithm with differential evolution (CoSGADE) optimization scheme, to produce optimal allocation solution variables. Through numerical simulations, it is seen that the proposed adaptive planning mechanism improves achieves a 12% and 14% improvement to the conventional sequential (multi-stage) and simultaneous mechanisms, on small to large scale distribution networks. DA - 2022-11 DB - ResearchSpace DP - CSIR J1 - Energy Reports, 8 KW - Battery energy storage systems KW - Computational intelligence KW - Distributed generation KW - Electric vehicles KW - Electric vehicle charging station KW - Hybrid optimization algorithm KW - Planning mechanisms KW - Reinforcement learning LK - https://researchspace.csir.co.za PY - 2022 SM - 2352-4847 T1 - A novel dynamic planning mechanism for allocating electric vehicle charging stations considering distributed generation and electronic units TI - A novel dynamic planning mechanism for allocating electric vehicle charging stations considering distributed generation and electronic units UR - http://hdl.handle.net/10204/12760 ER -26515