The continuous proliferation of distributed generation is leading end users to look for new tools that help to design hybrid electrical energy systems (HEES). Thus, this work proposes a novel approach for optimal planning of HEES, which comprises the optimization of the type and capacity of distributed generation connected to the end user. The main objective is to minimize the project’s total cost, considering the net metering scheme. To this end, the bioinspired meta-heuristic artificial immune system is proposed to optimally determine the number and type of photovoltaic panels. In addition, a nonlinear programming model is proposed to optimize the diesel generator and BESS capacity, considering the energy supply to the consumer by the HEES and the main distribution grid. Case studies involving commercial and residential customers in Brazil are introduced considering the normative resolutions from ANEEL, the Brazilian Regulatory Agency. Comparative analyses are made concerning an exhaustive search procedure and the commercial software Homer Pro, designed to optimize the operation of HEES systems. An important conclusion is that the proposed approach is as effective as the cutting-edge tools, with reasonable computational effort.

分布式发电的不断发展促使最终用户寻找有助于设计混合电能系统 (HEES) 的新工具。因此，这项工作提出了一种优化 HEES 规划的新方法，包括优化连接到最终用户的分布式发电的类型和容量。考虑到净计量方案，主要目标是最小化项目的总成本。为此，提出了仿生元启发式人工免疫系统来优化确定光伏面板的数量和类型。此外，考虑到HEES和主配电网对消费者的能源供应，提出了一种非线性规划模型来优化柴油发电机和BESS容量。考虑到巴西监管机构 ANEEL 的规范性决议，介绍了涉及巴西商业和住宅客户的案例研究。对详尽的搜索程序和旨在优化 HEES 系统操作的商业软件 Homer Pro 进行了比较分析。一个重要的结论是，所提出的方法与尖端工具一样有效，并且具有合理的计算工作量。