This paper investigates the operation of various optimised AC‐coupled hybrid power systems for an isolated community in South Australia. In addition to diesel generators, various combinations of distributed generators and storage technologies are considered to form different hybrid power systems. Optimal design of the hybrid power systems is implemented using particle swarm optimisation (PSO) algorithm. The performance of the PSO in optimizing the above hybrid systems is discussed in detail. Whilst meeting the power system operational constraints, the minimum levelised cost of electricity (LCOE) of all systems, with various combinations of system components, are calculated. Simulation results obtained for each optimized system are carefully described and analysed. The annual operations of various components in each system are then compared and discussed in detail. A sensitivity analysis by varying the cost of wind turbines and the photovoltaic is also conducted for all hybrid systems. It has been found that the inclusion of energy storage systems (battery and flywheel) can reduce the LCOE and CO₂ emission significantly compared to the inclusion of renewable generations (solar and wind) alone. The diesel‐wind‐solar‐battery system is the eco‐friendliest with an annual CO₂ emission of 451 t compared to the reference diesel system (1064 t). In addition, the hybrid system consisting of diesel, wind, solar, battery and flywheel is found to be the most economic with a LCOE of 58.94 ¢/kWh compared to the diesel system with a LCOE of 67.17 ¢/kWh.

中文翻译：

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针对澳大利亚偏远社区的交流耦合混合动力系统优化

本文针对南澳大利亚的一个孤立社区，研究了各种优化的交流耦合混合动力系统的运行情况。除了柴油发电机之外，分布式发电机和存储技术的各种组合也被认为构成了不同的混合动力系统。混合动力系统的优化设计是使用粒子群优化（PSO）算法实现的。详细讨论了PSO在优化上述混合系统中的性能。在满足电力系统运行约束的同时，计算了所有系统以及系统组件的各种组合的最低平准化电费（LCOE）。仔细描述和分析了每个优化系统获得的仿真结果。然后比较并详细讨论了每个系统中各个组件的年度操作。对于所有混合动力系统，还通过改变风力涡轮机和光伏发电的成本进行了灵敏度分析。已经发现，包括能量存储系统（电池和飞轮）可以降低LCOE和CO₂排放量与仅包含可再生能源（太阳能和风能）相比要显着。与参考柴油系统（1064吨）相比，柴油-风-太阳能-电池系统是最环保的，每年的CO ₂排放量为451 t。此外，由柴油，风能，太阳能，电池和飞轮组成的混合动力系统被发现是最经济的，其LCOE为58.94¢/ kWh，而柴油系统的LCOE为67.17¢/ kWh。