Abstract This paper proposes a novel methodology for redesigning a micro-grid characterized by a heavy reliance on diesel generators due to receiving power supply from an unreliable grid. The new design aims at phasing out the diesel generators and replacing them with a hybrid energy system composed of photovoltaics and a battery storage system. Two optimization approaches are adopted, a heuristic genetic algorithm approach is used to achieve sub-optimal sizing of the hybrid system sources and a rules-based dynamic programming approach to ensure optimal power flow. In order to reduce the computation time, a novel combinational approach employing genetic algorithm, dynamic programming and rules-based algorithm is proposed. The intervention of the dynamic programming for optimal power flow is restricted to certain active hours within a given day, while the rules-based power flow algorithm runs only outside those hours. The study demonstrates that the application of the hybrid system yields minimal operational cost by almost entirely phasing out the diesel generators and significantly reducing the energy purchased from the grid during peak hours. The micro-grid of a university campus is used as a case study where energy and economic indicators are derived to prove the superiority of the proposed techniques.

中文翻译：

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考虑光伏和蓄电池储能的大学校园微电网不可靠电网优化设计

摘要 本文提出了一种重新设计微电网的新方法，该微电网的特点是由于从不可靠的电网接收电力而严重依赖柴油发电机。新设计旨在逐步淘汰柴油发电机，代之以由光伏和电池存储系统组成的混合能源系统。采用了两种优化方法，一种是启发式遗传算法方法用于实现混合系统源的次优尺寸调整，另一种是基于规则的动态规划方法来确保最佳潮流。为了减少计算时间，提出了一种采用遗传算法、动态规划和基于规则的算法相结合的新方法。优化潮流的动态规划的干预仅限于给定一天内的某些活动时间，而基于规则的潮流算法只在这些时间之外运行。研究表明，混合动力系统的应用通过几乎完全淘汰柴油发电机并显着减少高峰时段从电网购买的能源，产生了最低的运营成本。大学校园的微电网被用作案例研究，从中得出能源和经济指标以证明所提出技术的优越性。