Abstract
Micro-grids are known as a means of localization of renewable energy production and consumption. However, due to the intermittent nature of renewable energy sources, one of the main challenges in Micro-grid energy control and management is to handle any deviation from the prior forecasted power generation/consumption. Our proposed distributed multi-agent algorithm tries to handle power imbalance situations in a PV-based grid connected Micro-grid through optimizing a combination of storage usage, load curtailment, and main grid power purchase. In this model, the users’ consumption preferences are considered as an important factor in the decision making. We first devise a community of consumers with various energy usage preferences and then investigate the performance of our proposed algorithm over multiple scenarios having different users’ reactions to the energy conservation requests. The results obtained show the convergence and feasibility of the proposed algorithm. Moreover, the cost of imbalance handling is considerably reduced, preserving the level of satisfaction in the community, as the inconvenience effect of load curtailment is compensated by paying back to the consumers.
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Ghorbani, S., Morsali, R., Unland, R., Kowalczyk, R. (2018). Distributed Multi-agent Based Energy Management of Smart Micro-grids: Autonomous Participation of Agents in Power Imbalance Handling. In: Bajo, J., et al. Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection. PAAMS 2018. Communications in Computer and Information Science, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-319-94779-2_28
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