Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

Maciel, Renan Silva; Rosa, Mauro; Miranda, Vladimiro; Padilha‐Feltrin, Antonio

doi:10.1016/j.epsr.2012.02.018

Cited by 49 publications

(23 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…DG could reduce environmental emissions, and a large scale DG embedded in a distribution system is beneficial to the operation of the power system [21][22][23][24][25]. Under the selected objectives, a SMG could be formulated, and the progress of OSA for the SMG can be described as in Table 6.…”

Section: The Osa Of Dg Optimization Planningmentioning

confidence: 99%

Game Optimization Theory and Application in Distribution System Expansion Planning, Including Distributed Generation

Wang

et al. 2013

Energies

View full text Add to dashboard Cite

Based on Game Theory and Multi-objective optimization problems (MOP), Game Optimization Theory (GOT) is discussed in this paper. Optimization Stability Analysis (OSA), Distance Entropy Multi-Objective Particle Swarm Optimization (DEMPSO) and Fuzzy Multi-weights Decision-making Method (FMW) are proposed as well. Game Optimization Theory, which is a comprehensive system, could not only handle multi-objective optimization problems effectively, but also could offset the disadvantages of traditional optimization theories, such as lack of framework and the insufficient consideration of relevant elements. In this paper GOT is used for the first time in solving the distribution systems planning (DSP) issue by implementing distributed generation. The proposed model integrates costs, losses, and voltage index to achieve optimal size and site of distributed generation. The model allows minimizing total system costs, system power losses and maximizing voltage improvement. A detailed DSP example is used for verifying the effectiveness and reasonableness of GOT in this context.

show abstract

Section: The Osa Of Dg Optimization Planningmentioning

confidence: 99%

Game Optimization Theory and Application in Distribution System Expansion Planning, Including Distributed Generation

Wang

et al. 2013

Energies

View full text Add to dashboard Cite

show abstract

“…The current references mostly use the heuristic algorithm to solve the station‐network planning of IES. Particle swarm optimization (PSO) is commonly used in power system planning, as its fast convergence speed and high optimization efficiency in Reference . The number of lines in each mesh set is different and may change in breaking loop operation, so the encoding/ decoding method of special PSO is used to map the lines to the contiguous space of [0, 1], and it can improve the convergence speed.…”

Section: Model Solving Methodsmentioning

confidence: 99%

Energy station and distribution network collaborative planning of integrated energy system based on operation optimization and demand response

Li¹

2020

Int J Energy Res

View full text Add to dashboard Cite

Summary In the energy station and distribution network collaborative planning of integrated energy system (IES), it is difficult to consider station and network interaction in IES operation at the same time. For resolving this problem, the model and solution of planning and operation alternative optimization are proposed considering multiagent interest balance. First, the three‐stage optimization framework and model of station and network planning of IES are proposed based on the operation scheduling of IES and the response of energy station and users as different subjects, aiming at optimization of station and network cost‐effectiveness, respectively. Second, the distribution network simplification method is proposed based on topological equivalence principle. The topological structure characteristics of distribution network is analyzed, the rapid generation strategy of single tie line network based on broken circle method is proposed, and then an encoding/decoding scheme is proposed based on particle swarm optimization algorithm. Third, considering the load characteristics and energy station demand response based on flexible comfort level of users, a dynamic spot price optimization method and operation strategy of IES are proposed. And then the station and network collaborative planning solution is presented based on the operation optimization of IES. Finally, an example is given to verify the practicability and effectiveness of the proposed method in this paper.

show abstract

“…S. Maciel [52] has proposed a multi-objective approach to a distribution network planning process, which handles the challenges of the DG integration. He has used the multi-objective version of the wellknown Evolutionary Particle Swarm Optimization method (MEPSO).…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Distributed generation deployment: State-of-the-art of distribution system planning in sustainable era

Jain

Kalambe

Agnihotri

et al. 2017

Renewable and Sustainable Energy Reviews

View full text Add to dashboard Cite

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

Cited by 49 publications

References 22 publications

Game Optimization Theory and Application in Distribution System Expansion Planning, Including Distributed Generation

Game Optimization Theory and Application in Distribution System Expansion Planning, Including Distributed Generation

Energy station and distribution network collaborative planning of integrated energy system based on operation optimization and demand response

Distributed generation deployment: State-of-the-art of distribution system planning in sustainable era

Contact Info

Product

Resources

About