Electric vehicles, which have both energy storage capability and mobility capability, can provide a new solution for electricity sharing between different building communities (i.e., a group of buildings connected with a microgrid). This comes to the community-to-community (C2C) energy sharing network. The C2C energy sharing networks have the potential to not only minimize the effects of electric vehicle integration into the energy grid, but also improve the electricity grid efficiency as a whole. In this thesis, a coordinated smart charging method of electric vehicles (EVs) is proposed for the C2C model. The proposed method considers the power regulation needs in both the present parking community and the next destination community. Then, based on the needs of both communities, the control method will decide the optimal amount of electricity that can be delivered by EV, so that the energy performances in both communities can be the best. The developed coordinated control has been compared with a base case (without any smart charging) and an uncoordinated control case under two control strategies: minimizing the peak energy exchanges with the grid and maximizing the renewable self-utilization. The genetic algorithm tools in MATLAB software are used for the optimization of the model. Meanwhile, to test the robustness of this C2C model, different combinations of building communities have been studied, namely residential-workplace, residential-university, and residential-workshop communities. The case study reveals that the C2C model is effective in improving energy performance under both control strategies. Peak reduction control strategies work most effectively for smaller systems with lower electricity demand and production. With C2C energy sharing, the annual mean peak reduction ranged from 39 % at the smallest community and 20 % at the largest community. Self-consumption maximization strategies work best for systems with a larger surplus of electricity production. With C2C energy sharing, the annual self-consumption increase ranged from 50 % at the community with the largest production surplus, to 7 % at the community with the smallest production surplus. The residential-workshop community studied in this thesis benefited the most from C2C charging control due to its production surplus and the relatively low electricity demands of the communities.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:du-47201 |
| Date | January 2023 |
| Creators | Board, Anthony |
| Publisher | Högskolan Dalarna, Institutionen för information och teknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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