采用多目标优化方法,改进了pareto-optimal解决方案,以提高电力系统的经济和环境调度
Muhammad Ilyas Khan Khalil1, Izaz Ur Rahman1, Muhammad Zakarya1,2
1Department of Computer Science, Abdul Wali Khan University, Mardan, Pakistan.
Scientific reports
|June 11, 2024
概括
非主导排序多目标粒子集群优化与本地最佳 (NS-MJPSOloc) 算法有效地解决了经济和环境的调度问题. 这种新的方法将燃料成本降低6.4%,计算时间降低9.1%,排放量降低9.4%.
科学领域:
- 电气工程 电气工程
- 优化算法 优化算法
- 计算智能是一种计算智能.
背景情况:
- 经济/环境调度 (EED) 问题需要平衡电力需求与运营成本和环境影响.
- 传统的优化方法与降低成本和控制电力系统中的排放的非可比性目标作斗争.
- 越来越多的环境法规需要先进的方法来实现可持续的能源管理.
研究的目的:
- 为EED问题实施和评估非主导排序多目标粒子集群优化与本地最佳 (NS-MJPSOloc) 算法.
- 通过重新定义本地最佳候选人来提高粒子群集优化 (PSO) 在多目标优化的性能.
- 在发电中实现经济成本和环境排放之间的最佳权衡.
主要方法:
- 利用了第n个状态的马科维亚跳跃粒子群优化 (PSO) 与本地搜索意识.
- 纳入了基于进化因素的机制来识别妥协解决方案.
- 采用马尔科夫链状态跳跃技术来控制帕雷托最佳集大小和邻域拓.
主要成果:
- 在一个代中,NS-MJPSOloc算法成功生成了一组多样化且分布良好的帕雷托最佳解决方案.
- 在解决方案的多样性和质量方面,与传统的公共服务组织相比,表现优越.
- 燃料成本降低了6.4%,计算时间降低了9.1%,排放量降低了9.4% (/小时).
结论:
- 拟议的NS-MJPSOloc方法有效地解决了多目标的EED问题,提供了高质量的权衡解决方案.
- 算法对本地最佳候选人的新方法和帕雷托最佳集管理提高了优化性能.
- 验证了NS-MJPSOloc在可持续电力系统运行中的实际适用性和效率.
相关概念视频
01:23Maximum Power Flow and Line Loadability
107
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
107
01:24Fast Decoupled and DC Powerflow
187
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
187
01:26The Power Flow Problem and Solution
200
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk, phase angle δk, real power Pk, and reactive power Qk. Two of these four variables are inputs, while the...
200
01:30Control of Power Flow
265
There are several methods to control power flow in power systems:
265
01:25Multimachine Stability
151
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
151
01:28Load-frequency control
155
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
155