Statistical Performances Evaluation of APSO and Improved APSO for Short Term Hydrothermal Scheduling Problem

Fakhar, Muhammad Salman; Kashif, Syed Abdul Rahman; Ain, Noor Ul; Hussain, Hafiz Zaheer; Rasool, Akhtar; Sajjad, Intisar Ali

doi:10.3390/app9122440

Cited by 16 publications

(17 citation statements)

References 33 publications

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“…The objective function of the conventional hydrothermal scheduling problem minimizes the total fuel cost of the thermal generation while preserving the reservoir and thermal constraints [47]- [49]. This sections describes the updated hydro-thermal-solar scheduling problem and presents the optimal power allocation of each energy source for different test cases while meeting the different system constraints.…”

Section: Methodology and Resultsmentioning

confidence: 99%

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Application of Dynamically Search Space Squeezed Modified Firefly Algorithm to a Novel Short Term Economic Dispatch of Multi-Generation Systems

et al. 2021

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Section: Methodology and Resultsmentioning

confidence: 99%

“…For simulating the different test cases, this section describes the essential system parameters of each energy source in the suggested hybrid system. The test cases are developed according to the parameters provided in [49].…”

Section: Simulation Parametersmentioning

confidence: 99%

Application of Dynamically Search Space Squeezed Modified Firefly Algorithm to a Novel Short Term Economic Dispatch of Multi-Generation Systems

et al. 2021

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“…Reference [135], has presented implementation of fully informed PSO (FIPSO), a variant of canonical PSO, to solve NCSTHTS problems.The paper discussed the local and global neighbourhood variants of FIPSO to solve the problem. References [136] and [137] discussed the implementation of metaheuristic optimization algorithms, i.e. two variants of Accelerated Particle Swarm Optimization algorithm and a variant of firefly algorithm on NCSTHTS problems.…”

Section: B Particle Swarm Optimization Algorithms Applied On Sthts Problemmentioning

confidence: 99%

“…two variants of Accelerated Particle Swarm Optimization algorithm and a variant of firefly algorithm on NCSTHTS problems. In reference [136], a comparison of simple APSO algorithm and dynamic search space squeezing based APSO was made statistically using independent sample t-test. Reference in solving NCSTHTS problem.…”

Section: B Particle Swarm Optimization Algorithms Applied On Sthts Problemmentioning

confidence: 99%

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

et al. 2021

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Short term hydrothermal scheduling (STHTS) is a non-linear, multi-modal and very complex constrained optimization problem which has been solved using several conventional and modern metaheuristic optimization algorithms. A number of research articles have been published addressing STHTS using different techniques. This article presents a comprehensive review of research published for solving the STHTS problem in the last four decades.INDEX TERMS Short term hydrothermal scheduling, conventional algorithms, meta-heuristic algorithms, no free lunch theorem

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“…For thermal and hydro units, discharge rate characteristics and the thermal cost equation with and without the valve point effect loading are required. For this, a test case is developed using the data in [46], which consists of one non-pumped hydel unit having the following discharge characteristics.…”

Section: Simulation Parametersmentioning

confidence: 99%

Performance Analysis of APSO and Firefly Algorithm for Short Term Optimal Scheduling of Multi-Generation Hybrid Energy System

et al. 2020

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This paper presents a modified and novel form of the conventional short-term hydrothermal scheduling problem by incorporating the effects of adding the photovoltaic energy source to the conventional grid. A photovoltaic energy source is intermittent in nature, therefore, to determine the optimal power contribution of the photovoltaic source towards the economic dispatch problem, a detailed strategy is presented in this paper. The proposed design method includes the forecasting of the photovoltaic system's parameters using the Auto-Regressive Integrated Moving Average (ARIMA) model. The analytical model is developed based on the fractional integral polynomials for studying the characteristics of the single photovoltaic module. The optimization of power allocation in the system consisting of conventional and non-conventional energy sources is highly non-linear and classical deterministic methods can not be guaranteed to determine the optimal solution for economic power dispatch. The global optima of such non-linear and non-convex problems can be determined using swarm-based intelligence techniques. This paper presents accelerated particle swarm optimization and the firefly algorithm to determine a solution for short-term non-linear scheduling problems. The multiple test cases have been presented to demonstrate the effectiveness of the proposed solution over classical methods. The overall generation cost of the selected hybrid system is reduced using the proposed methods while meeting the generation constraints of each energy source. Moreover, due to the stochastic nature of the meta-heuristic techniques, a comprehensive statistical comparison, based on the independent T-test results, is also presented to highlight the algorithm which performs better for selected scheduling problems. It has been demonstrated that accelerated particle swarm optimization gives lower mean generation cost of the system whereas the execution time of the firefly algorithm is better compared to its counterpart. INDEX TERMS Mathematical modeling, auto-regressive integrated moving average model, accelerated particle swarm optimization, firefly algorithm, short term hydrothermal scheduling, independent t-test.

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Statistical Performances Evaluation of APSO and Improved APSO for Short Term Hydrothermal Scheduling Problem

Cited by 16 publications

References 33 publications

Application of Dynamically Search Space Squeezed Modified Firefly Algorithm to a Novel Short Term Economic Dispatch of Multi-Generation Systems

Application of Dynamically Search Space Squeezed Modified Firefly Algorithm to a Novel Short Term Economic Dispatch of Multi-Generation Systems

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

Performance Analysis of APSO and Firefly Algorithm for Short Term Optimal Scheduling of Multi-Generation Hybrid Energy System

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