基于凸透镜成像的多目标改进马群优化器,用于分布网络中风能资源的随机优化,考虑到可靠性和不确定性
Fude Duan1, Ali Basem2, Dheyaa J Jasim3
1School of Intelligent Transportation, Nanjing Vocational College of Information Technology, Nanjing, 210000, Jiangsu, China. fudeduan88@163.com.
Scientific reports
|November 28, 2024
概括
这项研究利用一种新的算法优化了风力轮机在电网中的放置,发现考虑到不确定性增加了成本,但提高了对电网性能的理解. 该研究引入了多目标改进马群优化器 (MOIHHO) 以更好地整合风能.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 优化算法 优化算法
背景情况:
- 辐射分布网络需要高效的风力轮机 (WT) 分配以获得最佳性能.
- 在WT发电和网络负载的不确定性显著影响电网稳定性和经济性.
- 现有的优化方法可能遭受过早的融合,限制其有效性.
研究的目的:
- 开发一种可靠的方法,用于辐射分布网络中风力轮机的随机多目标分配.
- 为了最大限度地减少功耗损失,提高可靠性,并降低与WT相关的成本.
- 评估不确定性对功率损失和可靠性的影响.
主要方法:
- 一个新的多目标改进马群优化器 (MOIHHO) 结合了镜像来增强融合.
- 无香转换 (UT) 方法用于模拟WT功率和网络负载的不确定性.
- 在33号和69号公共汽车配送网络上,确定性和随机性分配场景的比较.
主要成果:
- 与传统方法 (MOHHO,MOSPO,MOGWO,MOGOA) 相比,MOIHHO算法显示出更高的性能.
- 随机的WT分配,考虑到UT的不确定性,导致电力损失成本增加.
- 随机分配导致研究的分销网络的可靠性降低.
结论:
- 拟议的MOIHHO有效地处理不确定性下的多目标WT分配问题.
- 考虑到不确定性,可以更现实地评估功率损失和可靠性影响.
- 该研究强调了风能整合时成本和可靠性之间的权衡.
相关概念视频
Wind Turbine Machine Models
106
In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
106
Optimal Foraging
12.0K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
12.0K
Maxwell-Boltzmann Distribution: Problem Solving
1.4K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.4K
Distributed Loads: Problem Solving
624
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
624
Maximum Power Flow and Line Loadability
95
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.
95
Energy Conservation and Bernoulli's Equation
8.6K
Applying the conservation of energy principle or the work-energy theorem to an incompressible, inviscid fluid in laminar, steady, irrotational flow leads to Bernoulli's equation. It states that the sum of the fluid pressure, potential, and kinetic energy per unit volume is constant along a streamline.
All the terms in the equation have the dimension of energy per unit volume. The kinetic energy per unit volume is called the kinetic energy density, and the potential energy per unit volume is...
All the terms in the equation have the dimension of energy per unit volume. The kinetic energy per unit volume is called the kinetic energy density, and the potential energy per unit volume is...
8.6K


