Transmission Expansion Planning for 133 Bus Tamil Nadu Test System Using Artificial Immune System Algorithm

Prakash, Satya; Henry, Joseph

doi:10.1007/978-981-13-1742-2_15

Cited by 1 publication

(3 citation statements)

References 6 publications

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“…The uncertainties in TNEP also result from inaccurate load forecast. More accurate load forecast enhances a stable and reliable TNEP [15].…”

Section: Uncertainty Issues In Tnepmentioning

confidence: 99%

“…A clonal selection principle and a population based algorithm known as Artificial Immune System (AIS), proposed by Dasgupta and Forrest [106], was recently applied in TNEP problem in [15]. The algorithm was formulated based on human immune system, which is a parallel, distributed and highly evolved adaptive system that exhibits certain traits, such as immune recognition, immune memory, reinforcement learning, diversity, robustness and feature extraction.…”

Section: Meta-heuristic Optimization Algorithms In Solving Tnep Prmentioning

confidence: 99%

“…Moreover, evacuation of power generated and the investment costs are becoming more of bigger problem than the generation expansions due to inadequate TNEP capacity and several uncertainties. [15].…”

Section: Introductionmentioning

confidence: 99%

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A Comprehensive State-of-the-Art Survey on the Transmission Network Expansion Planning Optimization Algorithms

2019

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Long term planning in power transmission network expansion provides a well ordered and profitable extension of power equipment and facilities to meet the expected electric energy demand with an allowable degree of reliability. However, high quality and improved reliability in energy supply have to be balanced with the available funds. The need to expand transmission network can never be over emphasized. Transmission Network Expansion Planning (TNEP) is a periodical measure that must be carried out due to dynamic societies that attract extra energy demands. It is highly important to minimize the network reinforcement and operational costs while satisfying the increase in demand imposed by technical and economic conditions over the planning horizon. Several optimization algorithms for TNEP problems have been developed and applied over the past decades. This paper presents a comprehensive state-of-the-art survey on the TNEP optimization algorithms. The approach of this paper is in the area of highlights of the various available TNEP algorithms, their applications, viability, computational complexities and drawbacks, which can aid in the identifications of the proper methods that can yield an optimal solution to TNEP problem. INDEX TERMS Algorithm, hybrid, meta-heuristics, optimization techniques, power network expansion planning, power system, transmission network expansion.

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“…The uncertainties in TNEP also result from inaccurate load forecast. More accurate load forecast enhances a stable and reliable TNEP [15].…”

Section: Uncertainty Issues In Tnepmentioning

confidence: 99%

Section: Meta-heuristic Optimization Algorithms In Solving Tnep Prmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive State-of-the-Art Survey on the Transmission Network Expansion Planning Optimization Algorithms

2019

View full text Add to dashboard Cite

show abstract

Transmission Expansion Planning for 133 Bus Tamil Nadu Test System Using Artificial Immune System Algorithm

Cited by 1 publication

References 6 publications

A Comprehensive State-of-the-Art Survey on the Transmission Network Expansion Planning Optimization Algorithms

A Comprehensive State-of-the-Art Survey on the Transmission Network Expansion Planning Optimization Algorithms

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