Optimal distributed renewable generation planning: A review of different approaches

Tan, Wen; Hassan, Mohammad Yusri; Majid, Shah; Rahman, Hasimah Abdul

doi:10.1016/j.rser.2012.10.039

Cited by 232 publications

(116 citation statements)

References 96 publications

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“…where, 1 2 , f f and 3 f are the power loss, voltage deviation and load balancing respectively. The mathematical equation of the multi-objective function is described as follows:…”

Section: Problem Formulationmentioning

confidence: 99%

“…DGs tend to be small-scale bringing in devices between numbers of KWs for you to 100 MWs: micro, small, medium and huge DGs, which are fitted at the load facilities to attenuate power deficits along with inefficiencies [2]. Compared to huge main power plants based on fossil fuel, oil, along with gas-fired plants [3], DGs resources for instance wind generators, photovoltaic, fuel cells, biomass, micro generators, small hydroelectric plant, landfill gas, and so on. [4] get a reduced amount of funds expenditure along with maintenance and upkeep costs, the area is a lot easier to get and possess less unfavorable affect the surroundings [5].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Technique for Locating and Sizing of Renewable Energy Resources in Power System

Durairasan¹,

Kalaiselvan²,

Sait³

2017

Journal of Electrical Engineering and Technology

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-In the paper, a hybrid technique is proposed for detecting the location and capacity of distributed generation (DG) sources like wind and photovoltaic (PV) in power system. The novelty of the proposed method is the combined performance of both the Biography Based Optimization (BBO) and Particle Swarm Optimization (PSO) techniques. The mentioned techniques are the optimization techniques, which are used for optimizing the optimum location and capacity of the DG sources for radial distribution network. Initially, the Artificial Neural Network (ANN) is applied to obtain the available capacity of DG sources like wind and PV for 24 hours. The BBO algorithm requires radial distribution network voltage, real and power loss for determining the optimum location and capacity of the DG. Here, the BBO input parameters are classified into sub parameters and allowed as the PSO algorithm optimization process. The PSO synthesis the problem and develops the sub solution with the help of sub parameters. The BBO migration and mutation process is applied for the sub solution of PSO for identifying the optimum location and capacity of DG. For the analysis of the proposed method, the test case is considered. The IEEE standard bench mark 33 bus system is utilized for analyzing the effectiveness of the proposed method. Then the proposed technique is implemented in the MATLAB/simulink platform and the effectiveness is analyzed by comparing it with the BBO and PSO techniques. The comparison results demonstrate the superiority of the proposed approach and confirm its potential to solve the problem

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“…where, 1 2 , f f and 3 f are the power loss, voltage deviation and load balancing respectively. The mathematical equation of the multi-objective function is described as follows:…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid Technique for Locating and Sizing of Renewable Energy Resources in Power System

Durairasan¹,

Kalaiselvan²,

Sait³

2017

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

show abstract

“…The recent technology in distributed generation is not only helping in technical and economic mode but also nonpolluting and sustainable. The main advantages form DGs are it can be helpful in reducing peak demand, enhancing voltage stability, improving load factor and deferral the transmission cost [10]. The technical issue related to DG connection in distribution system depends on its rating.…”

Section: Distributed Generation (Dg)mentioning

confidence: 99%

Optimal Configuration of DG in Distribution System: An Overview

Kumar

Nallagownden

Elamvazuthi

2016

MATEC Web of Conferences

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Abstract. Distributed generation (DG) has increased ever attention in the distribution system from last few years. The main reason for DG in distribution system is increasing electric demand, deregulated power system and congested transmission network, which eventually declines the system performance. There is also increasing pressure of greenhouse gas emissions. For proper utilization of DG, the optimal placement and sizing is of main concern. Because improper DG location and size will increase the losses and decrease the system performance than existing. On the contrary, proper placement will maintain voltage profile, reduce power loss, and increase voltage stability in the distribution system. This paper presents overview of DG, the advances in DG technology and different optimization methods used for optimal placement and sizing problem. The key issues and challenges offered in the development of DG is also presented in this paper.

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“…In order to enhance the utilization of the renewable energy sources for power generation, energy storage solutions are indispensable. In fact, the interest in electrical energy storage systems is due to their ability in decoupling the electric power generation phase and the consumption phase [1,2].…”

Section: Introductionmentioning

confidence: 99%

A New Tri-Generation System: Thermodynamical Analysis of a Micro Compressed Air Energy Storage

Vallati¹,

Grignaffini²,

Quintino³

et al. 2016

JEPE

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There is a growing interest in the electrical energy storage system, especially for matching intermittent sources of renewable energy with customers' demand. Furthermore, it is possible, with these system, to level the absorption peak of the electric network (peak shaving) and the advantage of separating the production phase from the exertion phase (time shift). CAES (compressed air energy storage systems) are one of the most promising technologies of this field, because they are characterized by a high reliability, low environmental impact and a remarkable energy density. The main disadvantage of big systems is that they depend on geological formations which are necessary to the storage. The micro-CAES system, with a rigid storage vessel, guarantees a high portability of the system and a higher adaptability even with distributed or stand-alone energy productions. This article carries out a thermodynamical and energy analysis of the micro-CAES system, as a result of the mathematical model created in a Matlab/Simulink ® environment.New ideas will be discussed, as the one concerning the quasi-isothermal compression/expansion, through the exertion of a biphasic mixture, that will increase the total system efficiency and enable a combined production of electric, thermal and refrigeration energies. The exergy analysis of the results provided by the simulation of the model reports that more than one third of the exergy input to the system is lost. This is something promising for the development of an experimental device.

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Optimal distributed renewable generation planning: A review of different approaches

Cited by 232 publications

References 96 publications

Hybrid Technique for Locating and Sizing of Renewable Energy Resources in Power System

Hybrid Technique for Locating and Sizing of Renewable Energy Resources in Power System

Optimal Configuration of DG in Distribution System: An Overview

A New Tri-Generation System: Thermodynamical Analysis of a Micro Compressed Air Energy Storage

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