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An initialization-free distributed algorithm for dynamic economic dispatch problems in microgrid: Modeling, optimization and analysis
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DOI：10.1016/j.segan.2023.101004.png)
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Abstract
En 中文
In this paper, a distributed optimization algorithm is designed for a hybrid microgrid network to minimize the total generation cost in a dynamic economic dispatch problem (DEDP). The hybrid microgrid model is constructed with different types of traditional power resources, renewable energy and energy storage batteries, which are subject to the supply-demand balance, capacity, and ramp-rate constraints of the generation facilities. Meantime, from the perspective of environment protection, the pollutant emissions from traditional generators are considered to reduce its impact on environment. Firstly, we transform the multi-objective optimization problem to a single objective optimization problem through the weight-sum method. Then, compared to the most existing centralized algorithms, we propose a fully distributed algorithm that does not depend on the initialization process to solve the dynamic dispatch problem. Moreover, we assume that the optimization objective functions are convex functions rather than a strictly standard quadratic function, and the convergence of the proposed algorithm is analyzed through convex analysis and a Lyapunov function method. Finally, some experiments with quadratic or non-quadratic cost functions and comparison examples are simulated, the experimental results verify that the optimal solution satisfies the constraints of the supply-demand constraints and capacity inequalities in each time slot.(c) 2023 Elsevier Ltd. All rights reserved.
Keywords:
Distributed optimization
Dynamic economic dispatch
Hybrid microgrid network
Initialization-free
Journal
IF:
5.6
Papers:
614
Citations:
5.1K