Solving high-dimensional multi-area economic dispatch problem by decoupled distributed crisscross optimization algorithm with population cross generation strategy

Multi-area economic dispatch (MAED) is a non-convex non-differentiable high-dimensional optimization problem, aiming to minimize the total fuel cost and meet the requirements of load balance. Current distributed mathematical programming methods are hard to solve the valve point effect in MAED. In addition, distributed meta-heuristic algorithms so far require a centralized controller. To address these issues, a decoupled distributed crisscross optimization with population cross generation (DDCSO-PCG) algorithm is proposed, which can 1) realize decentralization, 2) protect area data privacy, 3) reduce dimensions and improve convergence ability. First, the population cross generation (PCG) strategy is integrated into the crisscross optimization (CSO) algorithm to maintain population diversity and enhance exploitation ability. Second, the DDCSO-PCG algorithm is implemented to solve the MAED problem in a fully decentralized manner. Under the distributed framework, the proposed algorithm employs CSO-PCG independently to optimize the area dispatch in parallel. The total optimal cost is achieved by minimizing the cost of each area with no centralized controller required. The experimental results on multi-area static economic dispatch (MASED) and multi-area dynamic economic dispatch (MADED) problems show that the proposed DDCSO-PCG algorithm can not only provide a distributed solution, but also achieve the best economic cost compared with other state-of-the-art techniques.(c) 2022 Elsevier Ltd. All rights reserved.

多区域经济调度（MAED）是一个非凸、不可微的高维优化问题，旨在最小化总燃料成本并满足负荷平衡的要求。当前的分布式数学规划方法难以解决MAED中的阀点效应。此外，到目前为止，分布式元启发式算法需要一个集中控制器。为了解决这些问题，提出了一种具有种群交叉生成的解耦分布式交叉优化（DDCSO - PCG）算法，该算法能够：1）实现分散化；2）保护区域数据隐私；3）降低维度并提高收敛能力。首先，将种群交叉生成（PCG）策略集成到交叉优化（CSO）算法中，以保持种群多样性并增强开发能力。其次，实施DDCSO - PCG算法以完全分散的方式解决MAED问题。在分布式框架下，所提出的算法独立地采用CSO - PCG并行优化区域调度。通过最小化每个区域的成本来实现总最优成本，无需集中控制器。在多区域静态经济调度（MASED）和多区域动态经济调度（MADED）问题上的实验结果表明，所提出的DDCSO - PCG算法不仅能够提供分布式解决方案，而且与其他现有技术相比，还能实现最佳经济成本。（c）2022爱思唯尔有限公司。保留所有权利。