Abstract An efficient approach to optimal energy management and determine daily optimal operation schedule of two interconnected micro-grids (MGs), isolated from the grid, is proposed. The proposed energy management system consists of day-ahead and hour-ahead scheduling, and economic dispatch during real-time operation. The optimal day-ahead unit commitment can be achieved through two stages, management of the power generated from sources in both MGs and controllable load management. The day-ahead energy scheduling of each unit with technical constraints, being a complex nonlinear problem with several inequality constraints, needs to be optimized to achieve high quality operation as well as minimum daily forecasted energy consumption cost. Meta-heuristic algorithms seem more suitable to handle the task of optimal scheduling compared to the conventional analytic methods for power system economic dispatch. Considering the technical constraints, an advanced state-of-the-art meta-heuristic optimization technique, a modified version of the basic Porcellio Scaber algorithm (PSA) that offers improved efficiency in minimizing the objective function, is applied to solve the optimization problem. Results obtained demonstrate that the developed Global PSA is more efficient than a number of other meta-heuristic techniques to determine the optimal economic dispatch of multi-micro-grids incorporating various types of distributed generators.

中文翻译：

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使用先进进化算法的两个孤岛互连微电网的能源管理系统

摘要 提出了一种优化能源管理和确定与电网隔离的两个互连微电网 (MG) 的每日最佳运行计划的有效方法。拟议的能源管理系统包括日前和小时前调度，以及实时运行期间的经济调度。最佳日前机组承诺可以通过两个阶段实现，管理两个 MG 中的电源产生的功率和可控负载管理。具有技术约束的各机组日前能源调度是一个具有多个不等式约束的复杂非线性问题，需要对其进行优化以实现高质量运行以及最小的每日预测能耗成本。与传统的电力系统经济调度分析方法相比，元启发式算法似乎更适合处理优化调度任务。考虑到技术限制，应用了一种先进的最先进的元启发式优化技术，即基本 Porcellio Scaber 算法 (PSA) 的修改版本，可提高最小化目标函数的效率，用于解决优化问题。获得的结果表明，开发的 Global PSA 比许多其他元启发式技术更有效，以确定包含各种类型分布式发电机的多微电网的最佳经济调度。一种先进的最先进的元启发式优化技术，是基本 Porcellio Scaber 算法 (PSA) 的修改版本，可提高最小化目标函数的效率，用于解决优化问题。获得的结果表明，开发的 Global PSA 比许多其他元启发式技术更有效，以确定包含各种类型分布式发电机的多微电网的最佳经济调度。一种先进的最先进的元启发式优化技术，是基本 Porcellio Scaber 算法 (PSA) 的修改版本，可提高最小化目标函数的效率，用于解决优化问题。获得的结果表明，开发的 Global PSA 比许多其他元启发式技术更有效，以确定包含各种类型分布式发电机的多微电网的最佳经济调度。