Transmission Expansion Planning in the presence of wind farms with a mixed AC and DC power flow model using an Imperialist Competitive Algorithm

Moradi, Mansour; Abdi, Hamdi; Lumbreras, Sara; Ramos, Andrés; Karimi, Shahram

doi:10.1016/j.epsr.2016.05.025

Cited by 45 publications

(60 citation statements)

References 53 publications

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“…Guerra et al [437] developed a combined energy model to resolve GEP and TEP problems. Moradi et al [438] developed an algorithm technique to resolve the TEP problems. A social-spider algorithm is used by [439] to solve TEP problems.…”

Section: Rajesh Et Al [349] Established a Multi-stage Mixedmentioning

confidence: 99%

Recent Updates on Energy Planning Models - A Review

Hafeez

Gulshan

Tahira

2020

Journal of Mechanical and Energy Engineering

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Energy is the most important part for community and financial growth of any country. Energy planning models play a vital role in strategy formulation and power sector progress. In this paper a systematic review and comparison of energy planning models developed and applied from 1977-2019 has been presented. The review indicates that most of the energy planning models has been presented and applied in developed nations. Only few numbers of energy planning models have been presented and applied in under developing countries. The review also shows the comparison of energy planning models applied in developed and under-developed countries. This review article will assistance the energy managers, scholars and strategy makers broadly.

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Section: Rajesh Et Al [349] Established a Multi-stage Mixedmentioning

confidence: 99%

Recent Updates on Energy Planning Models - A Review

Hafeez

Gulshan

Tahira

2020

Journal of Mechanical and Energy Engineering

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“…One of the most recent works is [63]. In this paper, they proposed to solve TEP problem using an imperialist competitive algorithm comparing the results with other evolutionary methods.…”

Section: 22mentioning

confidence: 99%

“…Given that optimality is not guaranteed, comparisons between different heuristic performances are frequently found in last decade's literature. Comparison in terms of time of performance and the quality of the solutions found is necessary in order to evaluate the suitability of certain proposed method [63].…”

Section: 22mentioning

confidence: 99%

“…(2) Metaheuristic approaches have proven to find highquality solutions at relatively low computational costs when addressing G&TEP problem, hence optimality cannot be guaranteed. Heuristic methods generally perform better than classical ones for large problems where classical optimization methods become unmanageable [63].…”

Section: Metaheuristics For Gandtep Problemmentioning

confidence: 99%

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Analysis of Constraint‐Handling in Metaheuristic Approaches for the Generation and Transmission Expansion Planning Problem with Renewable Energy

et al. 2018

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A multiperiod generation and transmission expansion planning (G&TEP) problem is considered. This model integrates conventional generation with renewable energy sources, assuming a stochastic approach. The proposed approach is based on a centralized planned transmission expansion. Due to the worldwide recent energy guidelines, it is necessary to generate expansion plans adequate to the forecast demand over the next years. Nowadays, in most energy systems, a public entity develops both the short and long of electricity-grid expansion planning. Due to the complexity of the problem, there are different strategies to find expansion plans that satisfy the uncertainty conditions addressed. We proposed to address the G&TEP problem with a pure genetic algorithm approach. Different constraint-handling techniques were applied to deal with two complex case studies presented. Numerical results are shown to compare the strategies used in the test systems, and key factors such as a prior initialization of population and the estimated minimum number of generations are discussed.

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“…Moradi et al presented a formulation for TEP based on a single‐objective optimization applied to different case studies including AC power flow and DC power flow to analyze the effect of electrical losses on the final solutions. This work applied an imperialist competitive algorithm to the problem to find the optimal plans in the IEEE 24‐bus and IEEE 118‐bus test systems.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective transmission expansion planning problem based on ACOPF considering load and wind power generation uncertainties

Abbasi

Abdi

2016

Int. Trans. Electr. Energ. Syst.

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SummaryThis article tackles the transmission expansion planning (TEP) problem in a deregulated environment with the objective functions of investment, congestion, and load curtailment costs. The proposed TEP approach is a mixed-integer nonlinear optimization problem with a nonconvex structure and noncommensurable objective function. Until now, the research efforts on this problem have been mostly based on the DC power flow, which has the disadvantage of neglecting reactive load, power losses, and voltage constraints. However, a realistic transmission network operates based on AC power flow conditions. Therefore, the obtained transmission expansion plans based on DC power flow may be unable to satisfy the real conditions of power systems. In this article, the effects of different transmission network models on the objective functions of TEP are analyzed. Furthermore, different uncertainties especially associated with load and wind power generation are considered as the major concerns in TEP studies for each of the previously mentioned models. The point estimation method that enjoys from proper accuracy and low computational efforts is used for modeling the uncertainties. The nondominated sorting genetic algorithm II (NSGA II) is performed to obtain the Pareto optimal solutions of the TEP objectives and the final optimal solution is searched by applying the fuzzy decision-making approach based on decision-maker preferences. The models are simulated on the case studies of IEEE 24-bus reliability test system as well as the Iranian 400 kV transmission grid. The obtained results show that the type of power flow and uncertainties can change the TEP optimal solutions and objectives significantly.

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Transmission Expansion Planning in the presence of wind farms with a mixed AC and DC power flow model using an Imperialist Competitive Algorithm

Cited by 45 publications

References 53 publications

Recent Updates on Energy Planning Models - A Review

Recent Updates on Energy Planning Models - A Review

Analysis of Constraint‐Handling in Metaheuristic Approaches for the Generation and Transmission Expansion Planning Problem with Renewable Energy

Multiobjective transmission expansion planning problem based on ACOPF considering load and wind power generation uncertainties

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