Picanço Alessandra F, de Souza Antônio C Zambroni, Oliveira Andressa Pereira
Department of Automation and System, Federal Institute of Bahia (IFBA), Salvador, Bahia, Brazil.
Federal University of Itajubá (UNIFEI), Inst. of Electrical System and Energy, Itajubá, Minas Gerais, Brazil.
MethodsX. 2024 Aug 20;13:102924. doi: 10.1016/j.mex.2024.102924. eCollection 2024 Dec.
In an island power system, optimizing energy management is fundamental since there are renewable sources with their limitations. This management includes the allocation and capacity of energy sources to supply the loads. In this context, optimizing losses in the system contributes to improve the efficiency of this management. This paper proposes the losses optimization and energy management in the island power system. The authors propose the Natural Logarithm Particle Swarm Optimization to solve the problem and compare it with the Attractor Point Algorithm and Evolutionary Particle Swarm Optimization. And with that, we also propose a particle initialization for the studied particle-based algorithms to guarantee convergence in radial power systems. This is because the system configuration influences the response of the algorithm convergence. These techniques were applied to the IEEE-34 unbalanced radial island system.•Natural Logarithm Particle Swarm Optimization differs from classical PSO in that it does not calculate the velocity of the particles. Therefore, the method considers a cloud of particles with a natural logarithmic trajectory to solve the reduction of losses in a power system with a radial topology.•Natural Logarithmic Particle Swarm Optimization uses an initialization equation to minimize the initial estimation process, which is relevant to the convergence process.
在岛屿电力系统中,由于存在具有局限性的可再生能源,优化能源管理至关重要。这种管理包括能源的分配和供应负荷的能力。在此背景下,优化系统中的损耗有助于提高这种管理的效率。本文提出了岛屿电力系统中的损耗优化和能源管理方法。作者提出了自然对数粒子群优化算法来解决该问题,并将其与吸引点算法和进化粒子群优化算法进行比较。此外,我们还为所研究的基于粒子的算法提出了一种粒子初始化方法,以保证在辐射状电力系统中的收敛性。这是因为系统配置会影响算法收敛的响应。这些技术应用于IEEE - 34不平衡辐射状岛屿系统。
自然对数粒子群优化算法与经典粒子群优化算法的不同之处在于它不计算粒子的速度。因此,该方法考虑具有自然对数轨迹的粒子群来解决辐射状拓扑电力系统中的损耗降低问题。
自然对数粒子群优化算法使用一个初始化方程来最小化初始估计过程,这与收敛过程相关。