Transmission expansion planning via a constructive heuristic algorithm in restructured electricity industry

Khorasani, H.; Pourakbari‐Kasmaei, Mahdi; Romero, Rubén

doi:10.1109/epecs.2013.6712989

Cited by 10 publications

(4 citation statements)

References 19 publications

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“…The transmission system has a vital role in power systems, especially in deregulated environments, where it intervenes to make an adoption between generation and distribution sections [1]. The main objective of transmission expansion planning (TEP) problem is to determine where, how many, and when to construct new lines while satisfying several technoeconomic constraints, which allows the power system planners to spot the optimal facilities to be retrofitted in the transmission system aiming at enhancing the power transfer between the generation side and load points [2]. Since the electricity demand has a direct relationship with the development of countries, the faster a country is developed, the higher the demand becomes.…”

Section: Background Definitions and Motivationsmentioning

confidence: 99%

Transmission expansion planning integrated with wind farms: A review, comparative study, and a novel profound search approach

Naderi

Pourakbari‐Kasmaei²,

Lehtonen³

2020

International Journal of Electrical Power & Energy Systems

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This paper develops a novel hybrid algorithm for solving transmission expansion planning (TEP) problems in electric power networks. Raising the awareness about immense contaminants produced by fossil fuels as well as depleting these resources, have pushed energy companies toward considering more renewable energy resources (RERs). The RESs are beneficial for the society and the power system utility, however, taking into account the uncertainties, which are inherent in RERs, increase the complexity of the optimization problems. In this work, a Monte-Carlo simulation (MCS) is used to address the intermittent nature of wind energy. To handle the resulted model, by modifying and combining three wellknown evolutionary algorithms such as shuffled frog leaping algorithm (SFLA), particle swarm optimization (PSO), and teaching learning-based optimization (TLBO), a potent hybrid MSFLA-MPSO-MTLBO, namely combinatorial heuristic-based profound-search algorithm (CHPSA), is proposed. A self-adaptive probabilistic mutation operator (SAPMO) is employed to enhance the effectiveness and computational efficiency of the CHPSA. Ten commonly-used benchmark problems are introduced to corroborate the performance of the CHPSA, while the IEEE RTS 24-bus test system is used to validate the model. Results show that the proposed CHPSA is capable of obtaining better solutions than other algorithms, either implemented in this paper or borrowed from the literature.

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Section: Background Definitions and Motivationsmentioning

confidence: 99%

Transmission expansion planning integrated with wind farms: A review, comparative study, and a novel profound search approach

Naderi

Pourakbari‐Kasmaei²,

Lehtonen³

2020

International Journal of Electrical Power & Energy Systems

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“…A Constructive Heuristic Algorithm (CHA), an aspect of mathematical model for solving TNEP problem in a deregulated market was proposed in [71]. Multiple generation scenarios were considered in the proposed model in order to provide high quality solution with adequacy in power system operation.…”

Section: Mathematical Optimization Algorithms In Solving Tnep Promentioning

confidence: 99%

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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“…Once the expansion planning is implemented, it is difficult to change the grid structure substantially, and the research on it has always been one of the hot spots of power systems [1]. The main objective of the problem is to determine where, how many and when to build new lines while meeting the constraints and low‐cost requirements that enables power system planners to identify the best facilities in the transmission network to be modified to enhance power transmission between the generation side and the load point [2].…”

Section: Introductionmentioning

confidence: 99%

Hybrid‐adaptive differential evolution with decay function applied to transmission network expansion planning with renewable energy resources generation

Zhang

Wang

2021

IET Generation Trans & Dist

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As the country implements the reform of the electricity market and a large number of renewable energy resources (RES) are connected to the grid, the model and algorithm of traditional transmission network expansion planning (TNEP) are not suitable. A model of TNEP is built, in which the investment cost of new lines and the market‐based annual congestion surplus are selected as objective functions. A probabilistic DC power flow method is used to describe uncertainties of RES generation. A new algorithm, Hybrid‐Adaptive Differential Evolution with Decay Function (HyDE‐DF), is applied to solve the model of TNEP for the first time. Analysis and comparison in the IEEE 18‐bus system and the 52‐bus system in an area of Sichuan Province prove the feasibility, effectivity, and practicability of the model and solving algorithm. Some comparisons are performed using other variants of Differential Evolution (DE) and a swarm intelligence optimization algorithm to demonstrate the performance superiority of the new algorithm and new application. It is worth mentioning that in the 52‐bus system of an area of Sichuan Province, the investment cost obtained by the new algorithm is at least one or two orders of magnitude lower than other algorithms.

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Transmission expansion planning via a constructive heuristic algorithm in restructured electricity industry

Cited by 10 publications

References 19 publications

Transmission expansion planning integrated with wind farms: A review, comparative study, and a novel profound search approach

Transmission expansion planning integrated with wind farms: A review, comparative study, and a novel profound search approach

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

Hybrid‐adaptive differential evolution with decay function applied to transmission network expansion planning with renewable energy resources generation

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