Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network

Kayal, Partha; Chanda, Chandan Kumar

doi:10.1016/j.renene.2014.10.003

Cited by 187 publications

(77 citation statements)

References 34 publications

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“…1) Only one DG is connected to the same bus at a time [19]. 2) Similarly, the system considered for the study is operated in balanced mode [19].…”

Section: Results Analysismentioning

confidence: 99%

“…Hybrid PSO (HPSO) is employed to minimize the system loadability for obtaining the optimal place and sizes of DGs for various radial test bus systems [18]. Weighted aggregation PSO (WAPSO) is employed to obtain the size, type and location of DG to be connected with the practical Indian distribution systems [19]. Many algorithms like fireworks optimization algorithm [20] and bacterial foraging algorithm (BFA) [21] are also implemented to obtain DGs placement and their capacities.…”

Section: Introductionmentioning

confidence: 99%

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Transmission congestion management considering multiple and optimal capacity DGs

Peesapati

Yadav

Kumar

2017

J. Mod. Power Syst. Clean Energy

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Transmission congestion management became a grievous issue with the increase of competitiveness in the power systems. Competitiveness arises due to restructuring of the utilities along with the penetration of auxiliary services. The present study depicts a multi objective technique for achieving the optimal capacities of distributed generators (DG) such as solar, wind and biomass in order to relieve congestion in the transmission lines. Objectives like transmission congestion, real power loss, voltages and investment costs are considered to improve the technical and economical performances of the network. Multi objective particle swarm optimization algorithm is utilized to achieve the optimal sizes of unity power factor DG units. The insisted methodology is practiced on IEEE-30 and IEEE-118 bus systems to check the practical feasibility. The results of the proposed approach are compared with the genetic algorithm for both single and multi-objective cases. Results revealed that the intimated method can aid independent system operator to remove the burden from lines in the contingency conditions in an optimal manner along with the improvement in voltages and a reduction in real power losses of the network.

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“…1) Only one DG is connected to the same bus at a time [19]. 2) Similarly, the system considered for the study is operated in balanced mode [19].…”

Section: Results Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Transmission congestion management considering multiple and optimal capacity DGs

Peesapati

Yadav

Kumar

2017

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

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“…where NOCT is nominal operating cell temperature, T amb is the ambient temperature which is assumed to be • C, and Sun is the intensity of the solar radiation. In order to generate the pattern of solar radiation, the beta probability distribution function is used [27] as follows:…”

Section: Solar Cellmentioning

confidence: 99%

A Bi-Layer Multi-Objective Techno-Economical Optimization Model for Optimal Integration of Distributed Energy Resources into Smart/Micro Grids

et al. 2020

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The energy management system is executed in microgrids for optimal integration of distributed energy resources (DERs) into the power distribution grids. To this end, various strategies have been more focused on cost reduction, whereas effectively both economic and technical indices/factors have to be considered simultaneously. Therefore, in this paper, a two-layer optimization model is proposed to minimize the operation costs, voltage fluctuations, and power losses of smart microgrids. In the outer-layer, the size and capacity of DERs including renewable energy sources (RES), electric vehicles (EV) charging stations and energy storage systems (ESS), are obtained simultaneously. The inner-layer corresponds to the scheduled operation of EVs and ESSs using an integrated coordination model (ICM). The ICM is a fuzzy interface that has been adopted to address the multi-objectivity of the cost function developed based on hourly demand response, state of charges of EVs and ESS, and electricity price. Demand response is implemented in the ICM to investigate the effect of time-of-use electricity prices on optimal energy management. To solve the optimization problem and load-flow equations, hybrid genetic algorithm (GA)-particle swarm optimization (PSO) and backward-forward sweep algorithms are deployed, respectively. One-day simulation results confirm that the proposed model can reduce the power loss, voltage fluctuations and electricity supply cost by 51%, 40.77%, and 55.21%, respectively, which can considerably improve power system stability and energy efficiency.Energies 2020, 13, 1706 2 of 25 microgrids is evolving quickly [1]. The advanced structure of the microgrids allows the distribution network operators (DSOs) to consider the EV battery, either as a load or distributed generator [2]. However, deployment of RESs and EVs creates some challenges, e.g., poor reliability and power quality problems. One of the most effective ways to mitigate these challenges is the deployment of energy storage systems (ESSs) in distribution grids. ESSs can alleviate the negative effects of uncertainties in RESs production [3]. On the other hand, despite the remarkable advantages of these units, there are some challenges in terms of adequate DERs capacity requirement, system configuration, and energy management and control. One of the most challenging issues is the optimal coordination of both supply and demand sides in microgrids with the main grid, while satisfying system constraints.Currently, extensive studies have been done on the impacts of the RESs, EVs, and ESSs on the network operation . In [4], a smart home energy management strategy is proposed to realize cost-effective energy systems for customers and provide reactive power compensation for home appliances using EV and ESS. In this paper, network-level studies are limited to investigating the power factor indicator, while the potential role of EVs and ESSs in distribution networks has not been considered. Researchers in [5] presented the centralized control strategy to manag...

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“…Here, u c (t) and u b (t) are the continuous and binary control variables vectors, respectively. w i is a weighting factor used to convert the multi-objective optimization problem to a singleobjective optimization problem [22]. C e.g is the cost of energy dispatched from the grid in $/kW h, C exp is the cost of the exported power to the grid in $/kW h, C f is the cost of diesel generator fuel in $/l, C up/d is the start up or shut down cost in $ and C o&m is the maintenance cost in $/h.…”

Section: Optimization Problem Formulationmentioning

confidence: 99%

Optimal Operation of PV-Diesel MicroGrid with Multiple Diesel Generators Under Grid Blackouts

Alramlawi

Timothy

Gabash

et al. 2018

2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Syst

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This paper addresses the optimal operation problem of a PV-diesel microgrid considering grid blackouts, which is a usual case of discontinuous power supply in developing countries. The model of a grid-connected PV-diesel microgrid is enhanced, and new practical constraints are added. In addition, a new mixed-integer nonlinear programming (MINLP) problem is formulated to optimize the power flow in the microgrid for covering the load while minimizing the power consumption cost as well as maximizing the dispatched power from the PV-array. To demonstrate the applicability of the developed model and the optimal operation strategy, a comparison between different system configurations is made. The results show that the proposed microgrid can reduce the dispatched power cost while decreasing the power curtailment from the PV-array. Moreover, installing multiple diesel generators (DGs) can significantly reduce the fuel consumption by the DGs in comparison to a single DG in the PV-diesel microgrid.

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Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network

Cited by 187 publications

References 34 publications

Transmission congestion management considering multiple and optimal capacity DGs

Transmission congestion management considering multiple and optimal capacity DGs

A Bi-Layer Multi-Objective Techno-Economical Optimization Model for Optimal Integration of Distributed Energy Resources into Smart/Micro Grids

Optimal Operation of PV-Diesel MicroGrid with Multiple Diesel Generators Under Grid Blackouts

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