Optimal scheduling of distributed energy resources in a distribution system based on imperialist competitive algorithm considering reliability worth

Bashiri, Masoud

doi:10.1007/s00521-014-1581-5

Cited by 16 publications

(19 citation statements)

References 19 publications

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“…Ant Colony Optimization [24] Approximate Q-Learning [35] Artificial Bee Colony [32] Artificial Neural Network [38] Differential Evolution [37] Expert System [28] Fuzzy Sets [17,27,44,47] Genetic Algorithm [16,22,25,34,36,39,43] Geometric Clustering with Unsupervised Learning [42] Heuristic Optimization [21] Imperialist Competitive Algorithm [18] Multi Agent Systems [10,14,23,41,48,49] Particle Swarm Optimization [11][12][13]15,26,29,30,33,37,40,46] Reinforcement Learning [50] Scatter Search [31] Simulated Annealing [19] Support Vector Machines [45] 4.…”

Section: Computational Intelligence Methods Referencementioning

confidence: 99%

“…(1) Single objective. The most common single objective is the minimization of the total operation cost [10,11,13,15,18,[23][24][25][26][27][28]30,31,34,46]. (2) Multiple objectives with weights [19,20,32,44].…”

Section: Objectivesmentioning

confidence: 99%

“…In [18], a local energy market at the distribution level is considered. In this market, the participants are distribution system operator, distributed generators (energy storage system, fuel cell, micro turbine, phototoltaics, and wind generators), and loads.…”

Section: Imperialist Competitive Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Georgilakis

2020

Energies

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The massive integration of distributed energy resources in power distribution systems in combination with the active network management that is implemented thanks to innovative information and communication technologies has created the smart distribution systems of the new era. This new environment introduces challenges for the optimal operation of the smart distribution network. Local energy markets at power distribution level are highly investigated in recent years. The aim of local energy markets is to optimize the objectives of market participants, e.g., to minimize the network operation cost for the distribution network operator, to maximize the profit of the private distributed energy resources, and to minimize the electricity cost for the consumers. Several models and methods have been suggested for the design and optimal operation of local energy markets. This paper introduces an overview of the state-of-the-art computational intelligence methods applied to the optimal operation of local energy markets, classifying and analyzing current and future research directions in this area.

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Section: Computational Intelligence Methods Referencementioning

confidence: 99%

Section: Objectivesmentioning

confidence: 99%

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Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Georgilakis

2020

Energies

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“…However, the research did not consider the switching process as a possible improvement technique. Bashiri introduced a technique to obtain the optimal output and status of DG in microgrid systems regarding the load profile and weather conditions that affect outputs of some DG types. The strategy in this research is effective in enhancing the operation depending on the weather condition without changing the location of DG units.…”

Section: Introductionmentioning

confidence: 99%

Switching strategy for DG optimal allocation during repairing fault periods on loop distribution networks

Hamad

el‐Ghany

Azmy

2017

Int Trans Electr Energ Syst

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Summary It is expected that the use of distributed generation (DG) will increase sharply in distribution systems, especially with the realization of smart grids. In spite of the benefits of DG in distribution systems, high penetration level of DGs could cause some challenges for the network. Therefore, the optimal sizing and siting of DGs should be identified carefully. In addition, different operating conditions have to be taken into account in this process. The DGs are usually installed depending on optimal siting and sizing techniques considering normal operating periods. During repairing fault periods, different locations and capacities of DGs may be preferable. In this paper, 2 scenarios of switching strategies are presented for attaining the optimal sizing and siting of DGs during repairing fault period starting from the optimal allocation obtained for normal operating period. Genetic algorithm is used for solving the optimization problem that is implemented for an actual loop distribution system in Egypt.

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“…The utilization of different alternative resources such as solar, hydro, wind, biomass, etc has resulted in a more reliable, more secure with high power quality service from the consumer power generation as well as the direct/indirect effects of power units on the utility and vice versa [3,4]. From the utility point of view, the MG can be considered as a controllable unit within the network which can be regarded as a single load to be supplied or even as a power source to supply the network [5].…”

Section: Introductionmentioning

confidence: 99%

A novel stochastic framework for energy management in renewable micro-grids considering uncertainty of measurement and forecasting

Taherpoor

Niknam

Kavousi‐Fard

2015

Journal of Intelligent &Amp; Fuzzy Systems

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This paper investigates the optimal operation management of Micro-Grids (MGs) considering different types of distributed generations such as Fuel Cell (FC), Photovoltaic's (PV), Micro Turbine (MT), Wind Turbine (WT) as well as the storage devices. A stochastic optimization method based on scenarios production is proposed to consider the non-deterministic characteristics of WT/PVs electrical power production, the utility price and the unpredictable load consumption. The utilization of renewable energy sources and storage devices can affect the total operation strategies of the MGs with increasing the complexity and nonlinearity aspects of the problem. Consequently, an efficient optimization technique based on Harmony Search (HS) algorithm is suggested. In order to see the feasibility and satisfying performance of the proposed stochastic method, a typical grid-connected MG is studied as test system. The simulation results show the proper ability of the proposed stochastic framework to capture the uncertainty of the problem. Also, the high search ability of the proposed HS in both local and global explorations is evident.

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Optimal scheduling of distributed energy resources in a distribution system based on imperialist competitive algorithm considering reliability worth

Cited by 16 publications

References 19 publications

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Switching strategy for DG optimal allocation during repairing fault periods on loop distribution networks

A novel stochastic framework for energy management in renewable micro-grids considering uncertainty of measurement and forecasting

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