Smart design and management of hybrid energy structures for isolated systems using biogeography- based optimization algorithm

Shahinzadeh, Hossein; Moazzami, Majid; Abbasi, Meisam; Masoudi, H.; Sheigani, Vahid

doi:10.1109/sgc.2016.7883458

Cited by 16 publications

(3 citation statements)

References 16 publications

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“…In [18], the authors have used the bacterial foraging algorithm to optimize FACTS devices. In recent years, new evolutionary algorithms such as bat algorithm (BA) [19], glowworm swarm optimization algorithm (GSO) [20], gravity search algorithm (GSA) [21], gray wolf algorithm (GWO) [22], Shuffled frog leaping algorithm (SFLA) [23], biogeography-based optimization (BBO) algorithm [24], and big bang-big crunch (BBBC) optimization algorithm [25] have been widely used to solve optimization problems in power system operation and market analysis. In the present article, a new method is proposed which is obtained by merging the ALO algorithm and optimal power flow, and this approach is employed to determine the optimal TCSC location.…”

Section: Introductionmentioning

confidence: 99%

“…Where P Gi and Q Gi are the active and reactive power in the node i, P Gj and Q Gj are the active and reactive power in the node j, P Di and Q Di are the active and reactive power consumed by the demand in the node i, P Dj and Q Dj are the active and reactive power of the loads in the node j, P i TCSC and Q i TCSC are the active and reactive injection power by TCSC to the node i, P j TCSC and Q j TCSC are the active and reactive injection power by TCSC to the node j. The constraints of the problem are also expressed in the following (22)(23)(24)(25)(26):…”

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confidence: 99%

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Optimal TCSC placement for congestion management in deregulated power systems using antlion optimization algorithm

Moazzami¹,

Shahinzadeh²,

Gharehpetian³

et al. 2019

IJRA

Self Cite

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Congestion management is one of the important issues in the deregulated power systems. There are several methods to eliminate congestion. Utilizing FACTS devices is an appropriate option for large-scale and quick control of flows of transmission lines. FACTS devices such as Thyristor Controlled Series Capacitor (TCSC) can help to mitigate the transmitting flow of power in the congested lines, which leads to an increase in the network loading ability as well as reduction of both losses and production costs. Due to the considerably high price of FACTS devices, it is important to determine their optimum location on the network. Accordingly, in this paper, the Antlion optimization algorithm (ALO) has been employed to conduct a congestion management analysis to determine the optimal location for the installation of TCSC, which is simulated on an IEEE 14-bus test system subject to satisfy the constraints of the market environment.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Optimal TCSC placement for congestion management in deregulated power systems using antlion optimization algorithm

Moazzami¹,

Shahinzadeh²,

Gharehpetian³

et al. 2019

IJRA

Self Cite

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“…HOMER is found to be most widely used tool in the research studies followed by RETSCREEN, IHOGA, HYBRID2 and TRNSYS specially in hybrid system analysis. Instead, analytical techniques including genetic algorithm (GA) and particle swarm optimization (PSO) , (BBO) and artificial bee colony (ABC) are artificial intelligence methods which are able to calculate sizing. However, the algorithm become inefficient to solve certain difficulties, such as increasing the number of variables, e.g., the number of PV modules, the number.…”

Section: Introductionmentioning

confidence: 99%

Techno‐economic Analysis of a Stand‐alone Hybrid Wind/Fuel Cell Microgrid System: A Case Study in Kouhin Region in Qazvin

Amirkhalili

Zahedi

2018

Fuel Cells

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The decrease of fossil energy resources and the increasing amount greenhouse gas necessitate the needs of clean sources of energy. One renewable energy source is wind power which has been developing in recent years. Unfortunately, it can happen that no wind power is available during peak hours. In this case, a storage system, charged with backup power, is required. In this study, a hybrid system is presented for a wind farm to provide a reliable power supply and offer, in addition, valuable by‐products. The presented hybrid system consists of four main components: a wind turbine, an electrolyzer, a hydrogen storage tank and a fuel cell. In this paper, the case study for the system was done in Kouhin area of Qazvin province. The technical and economic optimization of the system suggested that in the best scenario (consisting of 3 wind turbines), the annual energy production of the hybrid system would be 2,268,072 kWh, with 9.41% provided by the fuel cell. The results show that the hybrid system would lead to a 10.8% increase in wind power capacity factor. The calculated energy costs and the net present cost for the optimum hybrid system are 0.7599 cent per kilowatt‐hour and 5,235,066 USD.

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Exergy and environmental analysis of oscillating wave energy converter hybrid with other renewable energy resources: A case study

Jahangir

Salehi

Alimoradiyan

2023

Energy Sources, Part B: Economics, Planning, and Policy

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Smart design and management of hybrid energy structures for isolated systems using biogeography- based optimization algorithm

Cited by 16 publications

References 16 publications

Optimal TCSC placement for congestion management in deregulated power systems using antlion optimization algorithm

Optimal TCSC placement for congestion management in deregulated power systems using antlion optimization algorithm

Techno‐economic Analysis of a Stand‐alone Hybrid Wind/Fuel Cell Microgrid System: A Case Study in Kouhin Region in Qazvin

Exergy and environmental analysis of oscillating wave energy converter hybrid with other renewable energy resources: A case study

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