Operation Planning of Standalone Maritime Power Systems Using Particle Swarm Optimization

M. Mehrzadi, C. Su, Y. Terriche, J. Vasquez, J. Guerrero
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引用次数: 4

Abstract

This paper presents the power management system (PMS) that relies on optimal power planning and maximum energy efficiency in dynamic positioning (DP) drilling vessel. Nowadays, it is becoming an improving demand for higher precision and decreases ship motion induced by environmental disturbance such as wind, waves, and sea current, which leads to the use of power generation more efficient. According to this, an efficient strategy solution and schedule have increased significantly for power management of diesel generator (DG) units on marine vessels as an independent microgrid to the utility grid. Thus, the power management system (PMS) of vessels is proposed to monitor and prevent the blackout by using the model predictive controller (MPC) based on optimal control method in order to estimate the future power demand in the hostile environment. Due to nonlinear characteristics of diesel generators, such as power ramp rate limits and non-smooth cost functions, a particle swarm optimization (PSO) is applied to solve the economic dispatch (ED) problem for a dynamic system. The simulation results demonstrate that the proposed method can improve ED operation problems more efficiently while meeting DGs constraints.
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基于粒子群算法的单机海上电力系统运行规划
提出了一种基于最优功率规划和最大能效的动力定位钻井船动力管理系统。如今,对更高精度的要求越来越高,并且减少了风、浪、海流等环境扰动引起的船舶运动,从而提高了发电的效率。因此,船舶柴油发电机组作为一个独立的微电网对公用事业电网的电力管理,一个有效的策略解决方案和时间表显著增加。为此,提出了船舶电力管理系统(PMS),利用基于最优控制方法的模型预测控制器(MPC)来监测和预防船舶在恶劣环境下的停电,以估计船舶未来的电力需求。针对柴油发电机组的非线性特性,如功率斜坡速率限制和非光滑的成本函数,将粒子群算法应用于求解动态系统的经济调度问题。仿真结果表明,该方法能在满足DGs约束的情况下,更有效地改善ED的运行问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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