Multi‐distributed generation planning using hybrid particle swarm optimisation‐ gravitational search algorithm including voltage rise issue

Tan, Wen; Hassan, Mohammad Yusri; Rahman, Hasimah Abdul; Abdullah, Pauzi; Hussin, Faridah

doi:10.1049/iet-gtd.2013.0050

Cited by 90 publications

(34 citation statements)

References 31 publications

(30 reference statements)

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“…An iterative method based on voltage sensitivity is used to identify the best storage location in [13], sensitivity analysis is used to find the optimal, gas-fired distributed generation capacity locations in the distribution system in [14], while Gravitational Search Algorithm (GSA) and PSOGSA are used to determine multiple distributed generation capacity and location in DS in [15] and [16] respectively. An OPF-based algorithm for siting the aggregated capacity of energy storage was developed to decrease the wind energy curtailment and cost of energy supply in [17].…”

Section: Resultsmentioning

confidence: 99%

Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder

Petinrin¹,

Sanusi²,

Tijani³

et al. 2017

IJMEA

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Abstract:Increasing demand on electrical energy coupled with lack of new distribution facilities create a potential threat that can eventually sprawl to jeopardize the distribution system reliability. The variability characteristics of wind energy sources present a fundamental problem to its smooth integration in the distribution feeders, in a large proportion. Energy storage (ES) systems and demand response (DR) technique have the potential to improve the flexibility of distribution network, by allowing two ways of freedom for the distribution network operator (DNO), to support mitigation of demand-supply balance issues, and thereby the share of renewable energy sources (RESs) or improve penetration levels of renewables. By shifting electricity supply and customer demand patterns, this paper applies real time pricing and energy storage not only to significantly increase the penetration of wind energy, but also to offer other important value to shifts demand to times of relatively high renewable energy resources and low load; and by storing energy during off-peak, with less line losses, and redispatching this energy when needed. The results show that real time pricing and energy storage can effectively provide demand-supply benefits to the distribution network and customers.

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Section: Resultsmentioning

confidence: 99%

Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder

Petinrin¹,

Sanusi²,

Tijani³

et al. 2017

IJMEA

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“…In [13], a hybrid algorithm was presented that improved stress profiles and reduced emissions using a particles' gravitational colony search to determine the proper location and sizing of the DG that minimized loss. The aim of this article is to contribute to the discussion on the effectiveness of heuristic and metaheuristic methods for optimal dimensioning and location of DG.…”

Section: Introductionmentioning

confidence: 99%

Electric Power Grids Distribution Generation System for Optimal Location and Sizing—A Case Study Investigation by Various Optimization Algorithms

Ali¹,

Padmanaban²,

Twala³

et al. 2017

Energies

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Abstract:In this paper, the approach focused on the variables involved in assessing the quality of a distributed generation system are reviewed in detail, for its investigation and research contribution. The aim to minimize the electric power losses (unused power consumption) and optimize the voltage profile for the power system under investigation. To provide this assessment, several experiments have been made to the IEEE 34-bus test case and various actual test cases with the respect of multiple Distribution Generation DG units. The possibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been verified. Finally, four algorithms were trailed: simulated annealing (SA), hybrid genetic algorithm (HGA), genetic algorithm (GA), and variable neighbourhood search. The HGA algorithm was found to produce the best solution at a cost of a longer processing time.

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“…For the improved reliability of hybrid systems, the optimal design of the size of each component is one of the most important issues in stand-alone hybrid system. In recent years, optimal sizing methods for hybrid systems based on probabilistic, analytical, and heuristic methods have been studied [1][2][3][4][5][6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…Heuristic algorithms, such as genetic algorithm (GA) [9,10], particle swarm optimization (PSO) [11], simulated annealing [12], harmony search [13], and hybrid optimization algorithms [14], are also gaining usage in the sizing problem for hybrid systems. Dufo-López, and Bernal-Agustín [15] used a triple multi-objective design of off-grid hybrid systems by simultaneously minimizing the total cost throughout the useful life of the installation, pollutant emissions (CO 2 ), and unmet load.…”

Section: Introductionmentioning

confidence: 99%

Structure Optimization of Stand-Alone Renewable Power Systems Based on Multi Object Function

2016

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This paper presents a methodology for the size optimization of a stand-alone hybrid PV/wind/diesel/battery system while considering the following factors: total annual cost (TAC), loss of power supply probability (LPSP), and the fuel cost of the diesel generator required by the user. A new optimization algorithm and an object function (including a penalty method) are also proposed; these assist with designing the best structure for a hybrid system satisfying the constraints. In hybrid energy system sources such as photovoltaic (PV), wind, diesel, and energy storage devices are connected as an electrical load supply. Because the power produced by PV and wind turbine sources is dependent on the variation of the resources (sun and wind) and the load demand fluctuates, such a hybrid system must be able to satisfy the load requirements at any time and store the excess energy for use in deficit conditions. Therefore, reliability and cost are the two main criteria when designing a stand-alone hybrid system. Moreover, the operation of a diesel generator is important to achieve greater reliability. In this paper, TAC, LPSP, and the fuel cost of the diesel generator are considered as the objective variables and a hybrid teaching-learning-based optimization algorithm is proposed and used to choose the best structure of a stand-alone hybrid PV/wind/diesel/battery system. Simulation results from MATLAB support the effectiveness of the proposed method and confirm that it is more efficient than conventional methods.

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Multi‐distributed generation planning using hybrid particle swarm optimisation‐ gravitational search algorithm including voltage rise issue

Cited by 90 publications

References 31 publications

Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder

Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder

Electric Power Grids Distribution Generation System for Optimal Location and Sizing—A Case Study Investigation by Various Optimization Algorithms

Structure Optimization of Stand-Alone Renewable Power Systems Based on Multi Object Function

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