.png){kind=icon}
返回
Solving high-dimensional multi-area economic dispatch problem by decoupled distributed crisscross optimization algorithm with population cross generation strategy
.png){kind=icon}
PRE
AI
DOI：10.1016/j.energy.2022.124836.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Multi-area economic dispatch (MAED)
Crisscross optimization (CSO)
Population cross generation (PCG)
Decoupled distributed calculation
Data privacy
期刊
IF:
9.4
论文数:
4.3W
被引数:
20.2W
机构
引用论文
分享收藏Optimal dispatching strategy and real-time pricing for multi-regional integrated energy systems based on demand response基于需求响应的多区域综合能源系统优化调度策略与实时定价.png)
RENEWABLE ENERGY
RENEWABLE ENERGYIF9.1
PREAI
分享收藏
查看更多内容