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An Energy Scheduling Strategy With Priority Within Islanded Microgrids

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To achieve self-healing in the smart grid, the microgrid can be switched to the islanded state for effective autonomy in the event of disasters or attacks. Based on the data… Click to show full abstract

To achieve self-healing in the smart grid, the microgrid can be switched to the islanded state for effective autonomy in the event of disasters or attacks. Based on the data collected by smart meters, the microgrid can support an efficient energy scheduling strategy to guide both energy suppliers and consumers so that electricity can be used efficiently. Significant research efforts have been carried out regarding energy scheduling. Nonetheless, the majority of existing strategies failed to prioritize consumers. In fact, the energy consumption order of different users should be distinguished from each other in islanded microgrids with limited energy supply, meaning that they have different priority. To address this issue, in this paper we propose an energy scheduling strategy with priority within islanded microgrids (E2SP) to ensure that consumers with higher priority can obtain energy supply in an earlier order. To be specific, we solve the problem of deriving the amount of power each energy supplier should supply to each consumer via using the Goal Programming Model with positive and negative deviation variables. To evaluate the validity of E2SP, we conduct comprehensive experiments in five cases. The results show that the E2SP strategy can effectively ensure that energy is supplied to consumers in order of priority. In addition, we introduce the dissatisfaction degree as a metric to measure the effectiveness of our strategy. Simulation results show that our E2SP strategy has a lower dissatisfaction degree compared with the scheduling strategy without considering priority, indicating that our E2SP strategy is more effective.

Keywords: strategy; priority; energy scheduling; energy; scheduling strategy; islanded microgrids

Journal Title: IEEE Access
Year Published: 2019

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