Abstract Independent investors can install distributed generations (DGs) in power networks as long as they follow the systems’ rules and frameworks. Logically, they try to maximize their profits, and network owners/operators usually cannot directly control their decisions regarding the DG location and size. However, there are inherent interactions between their decisions and the systems’ technical and economic characteristics. In this paper, a new approach is presented for optimal DG placement and sizing from the standpoint of independent investors, with specific consideration given to interactions with pool-based electricity markets. The proposed approach is founded on the innovative combination of the meta-heuristic optimization model and the reinforcement learning-based market simulation strategy. This approach is implemented using the particle swarm optimization algorithm and the Q-learning technique, and it is comprehensively examined in the IEEE 30-bus system with consideration for different pricing rules and DG types. The results confirm that there are significant interdependencies between the optimal decision of DG investors and the strategic bidding behavior of market players. Also, they indicate that the proposed approach is useful for independent investors in identifying the most valuable DG location and size as well as for the systems’ policy-makers in investigating the long-term effects of specific rules.

中文翻译：

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从投资者的角度考虑基于池的电力市场的分布式发电规划

摘要 独立投资者只要遵守系统的规则和框架，就可以在电网中安装分布式发电（DG）。从逻辑上讲，他们试图最大化他们的利润，而网络所有者/运营商通常无法直接控制他们关于 DG 位置和规模的决定。然而，他们的决策与系统的技术和经济特征之间存在内在的相互作用。在本文中，从独立投资者的角度出发，提出了一种优化 DG 配置和规模的新方法，并特别考虑了与基于池的电力市场的互动。所提出的方法建立在元启发式优化模型和基于强化学习的市场模拟策略的创新组合之上。这种方法是使用粒子群优化算法和 Q 学习技术实现的，并在 IEEE 30 总线系统中进行了全面检查，同时考虑了不同的定价规则和 DG 类型。结果证实，DG投资者的最优决策与市场参与者的战略投标行为之间存在显着的相互依赖关系。此外，他们指出，所提议的方法对于独立投资者确定最有价值的 DG 位置和规模以及系统决策者调查特定规则的长期影响非常有用。结果证实，DG投资者的最优决策与市场参与者的战略投标行为之间存在显着的相互依赖关系。此外，他们指出，所提议的方法对于独立投资者确定最有价值的 DG 位置和规模以及系统决策者调查特定规则的长期影响非常有用。结果证实，DG投资者的最优决策与市场参与者的战略投标行为之间存在显着的相互依赖关系。此外，他们指出，所提议的方法对于独立投资者确定最有价值的 DG 位置和规模以及系统决策者调查特定规则的长期影响非常有用。