Generation Expansion Planning Including Biomass Energy Sources with Global Environmental Consideration Using Improved Tabu Search

Nualhong, D.; Chusanapiputt, S.; Jantarang, S.; Pungprasert, Vuthichai

doi:10.1109/tencon.2005.300990

Cited by 5 publications

(6 citation statements)

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“…Another way to mitigate this challenge is the adoption of storage units . Various authors have included the integration of RE sources in GEP problem . From the reviewed literature, the use of wind and solar PV in GEP studies has received considerable attention.…”

Section: Environmental Considerationsmentioning

confidence: 99%

“…1 Various authors have included the integration of RE sources in GEP problem. 44,[49][50][51]59,61,97,99,104,147,170,[208][209][210][211][212][213][214] From the reviewed literature, the use of wind and solar PV in GEP studies has received considerable attention. This is as a result of their widespread resource availability and state-of-the-art technological advancements.…”

Section: Intermittent Re Integration In Gepmentioning

confidence: 99%

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A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

2019

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Summary Generation expansion planning (GEP) is a power plant mix problem that identifies what, where, when, and how new generating facilities should be installed and when old units be retired over a specific planning horizon. GEP ensures that the quantity of electricity generated matches the electricity demand throughout the planning horizon. This kind of planning is of importance because most production and service delivery is dependent on availability of electricity. Over the years, the traditional GEP approaches have evolved to produce more realistic models and new solution algorithms. For example, with the agitation for green environment, the inclusion of renewable energy plants and energy storage in the traditional GEP model is gradually gaining attention. In this regards, a handful of research has been conducted to identify the optimal expansion plans based on various energy‐related perspectives. The appraisal and classification of studies under these topics are necessary to provide insights for further works in GEP studies. This article therefore presents a comprehensive up‐to‐date review of GEP studies. Result from the survey shows that the integration of demand side management, energy storage systems (ESSs), and short‐term operational characteristics of power plants in GEP models can significantly improve flexibility of power system networks and cause a change in energy production and the optimal capacity mix. Furthermore, this article was able to identify that to effectively integrate ESS into the generation expansion plan, a high temporal resolution dimension is essential. It also provides a policy discussion with regard to the implementation of GEP. This survey provides a broad background to explore new research areas in order to improve the presently available GEP models.

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Section: Environmental Considerationsmentioning

confidence: 99%

Section: Intermittent Re Integration In Gepmentioning

confidence: 99%

A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

2019

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“…The real-world GEP problem is described as the combinatorial optimization for a very large search space. Using (19), the decision search spaces of the test system [12] in each state are 6 × 5 × 4 × 4 × 4 = 1920. Accordingly, the overall search spaces of 10 time stages are 1920 10 = 6.81 × 10 32 combinations.…”

Section: Feasible Search Conceptmentioning

confidence: 99%

“…The decision variable u t = (GT, ST) is contained in the decision vector (u 1 , u 2 , u 3 ). Using (19), the decision spaces are 3 × 3 = 9 combinations. The overall search spaces of three time stages are 9 3 = 729 combinations.…”

Section: Example Of Hybrid Cs-dp For Solving the Gep Problemmentioning

confidence: 99%

“…In the past two decades, nature-inspired metaheuristic methods, such as evolutionary programming [11], genetics algorithm (GA) [12], particle swarm optimization [13], shuffled frog leaping algorithm [14], differential evolution [15], expert system [16], ant colony optimization [17], simulated annealing [18], tabu search [19], and hybrid approach [20,21], have been successfully used to solve the GEP problem. A cuckoo search (CS) algorithm, a population-based search algorithm with unique local search, was developed by X.S.…”

Section: Introductionmentioning

confidence: 99%

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An efficient hybrid CS‐DP application for generation expansion planning problem

Komasatid

Jiriwibhakorn

2019

IEEJ Transactions Elec Engng

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This article proposes a new hybrid approach for generation expansion planning (GEP) based on cuckoo search (CS) and dynamic programming (DP). Generally, the GEP problem is known as having very large search space and highly nonlinear complex combinatorial optimization. The global optimal solution is to solve with the full enumeration DP. However, the computation time grows exponentially when the planning horizon and candidate options increase, which is called ‘curse of dimensionality’. To solve this problem, a hybrid CS‐DP approach is proposed with three techniques for solution quality and convergence characteristic enhancement. First, the CS is integrated into the DP structure for the optimum solution of the very large search space problem. Second, the feasible search concept can eliminate infeasible solutions from the searching process. Finally, the memory exploration search is applied to prevent repeated searches. To measure its effectiveness, the proposed method is applied to 15 existing power plants, with 5 candidate options and 2 test cases: 14 year and 20 year study periods. The experimental results are compared with classical and metaheuristic optimizations. The test results indicate that the proposed hybrid CS‐DP achieves higher solution quality and superior convergence characteristics than other methods. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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