Probabilistic approach for optimal planning of distributed generators with controlling harmonic distortions

Abdelsalam, Abdelazeem A.; El-Saadany, Ehab F.

doi:10.1049/iet-gtd.2012.0769

Cited by 45 publications

(20 citation statements)

References 27 publications

(18 reference statements)

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“…There are some other family optimization algorithms that have been adopted in meta-heuristic as shown in Fig. 4 [4][5][6], [13,22], [25][26][27][28], [2,[33][34][35][36][37][38][39][40][41][42][43][44][45].…”

Section: Artificial Intelligent Techniquesmentioning

confidence: 99%

“…Integration of the DG in existing distribution network increases the short circuit capacity of the system by increasing the steady state current at fault. This depends on size, type and remoteness of the DG from the Genetic algorithm [18], [83], [4], [39] [41], [42] Artificial intelligent techniques Fuzzy logic [80], [34], [45] Non-dominated sorting GA-II [85], [46] Honey bees mating Particle swarm optimization [31], [13], [81], [82] [2] Plant growth simulation algorithm [86], [12] Artificial bee colony [45], [61] Invasive weed algorithm [89], [60], [80] Ant colony search [5], [45] Artificial neural network…”

Section: Short Circuit Capacitymentioning

confidence: 99%

“…Tabu Search Algorithm (TSA) [23] Clustering Algorithm (CA) [43], [86], [94] Monte Carlo Simulation (MCS) [7], [10], [24], [35] Modified Teaching Learning Based Optimization algorithm [31] Backtracking Search Optimization Algorithm [58] Brute Force Algorithm (BFA) [8], [86] Big Bang Big Crunch Algorithm (BBBCA) [13], [37], [95] Bat Algorithm (BA) [49][86]…”

Section: Electricity Pricing Issuesmentioning

confidence: 99%

“…The DG can improve system performance. Further, it can also mitigate harmonics, voltage sag and swell significantly along with reduced investment in transmission and distribution [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Distributed Energy Resources and Supportive Methodologies for their Optimal Planning under Modern Distribution Network: a Review

Agarwal¹,

Jain²

2019

Technol Econ Smart Grids Sustain Energy

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Rapid growth in electrical load demand with lack in generation of electrical power and transmission line congestion has set the trend for smart electrical system. In smart electrical system, need arises to deploy more non-conventional energy sources, which include Renewable Energy Sources (RES) as well as non-RES. Though, the RES are getting more encouragement due to several advantages over non-RES. In recent past, there is significant increase in the penetration of small units of local generation in existing distribution system. These small units (RES and non-RES), usually known as Distributed Generation (DG), may offer several technical, economic and environmental benefits like reduction in power loss, improvement in power quality, reliability, system security, reduction in capital cost investment at large level, reduction in emission of greenhouse gases and many more. However, these advantages are difficult to achieve due to some technical and non-technical barriers. To extract maximum potential benefits from the DG, the optimal planning of such sources in distribution network has always been a topic of great interest. Though, fresh researchers face many problems in carrying out research in this area due to lack of knowledge about suitable research software, standard test networks, types of renewable/non-renewable sources, appropriate literature, etc. This paper uses a systematic approach to discuss the DG and its technologies with advantages, disadvantages and effects on end users as well as on the utility. A comparative study of all optimization techniques for planning of DG in existing power system considering optimal size and location is also included. This paper also involves the details about some standard test systems along with details of useful software's (licensed & open source) for DG planning. The present study can add worthful information and serve as a base for the fellow working in this area.

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Section: Artificial Intelligent Techniquesmentioning

confidence: 99%

Section: Short Circuit Capacitymentioning

confidence: 99%

Section: Electricity Pricing Issuesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Distributed Energy Resources and Supportive Methodologies for their Optimal Planning under Modern Distribution Network: a Review

Agarwal¹,

Jain²

2019

Technol Econ Smart Grids Sustain Energy

View full text Add to dashboard Cite

show abstract

“…The limitations of both harmonic and protection coordination constraints are considered in [38] to obtain the system-hosted capacity. In [39], the authors introduce a probabilistic method to minimize annual energy losses and mitigate harmonic distortion in distorted networks, considering all possible operating conditions of the DG units. In [40], the authors propose a phase-shifting approach to mitigate harmonics, supplied with converter-connected DG units.…”

Section: An Overview Of Hosting Capacity and Harmonic Distortion Limitsmentioning

confidence: 99%

Integration of large- scale PV plants in non-sinusoidal environments: Considerations on hosting capacity and harmonic distortion limits

Sakar

Balcı

Aleem

et al. 2018

Renewable and Sustainable Energy Reviews

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Placement of Distributed Generation in Distribution Networks: A Survey on Different Heuristic Methods

Godha

Bapat

Korachagaon³

2019

Techno-Societal 2018

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Probabilistic approach for optimal planning of distributed generators with controlling harmonic distortions

Cited by 45 publications

References 27 publications

Distributed Energy Resources and Supportive Methodologies for their Optimal Planning under Modern Distribution Network: a Review

Distributed Energy Resources and Supportive Methodologies for their Optimal Planning under Modern Distribution Network: a Review

Integration of large- scale PV plants in non-sinusoidal environments: Considerations on hosting capacity and harmonic distortion limits

Placement of Distributed Generation in Distribution Networks: A Survey on Different Heuristic Methods

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