Modified Chaos Particle Swarm Optimization-Based Optimized Operation Model for Stand-Alone CCHP Microgrid

Wang, Fei; Zhou, Lidong; Wang, Bo; Wang, Zheng; Shafie‐khah, Miadreza; Catalào, João P. S.

doi:10.3390/app7080754

Cited by 27 publications

(11 citation statements)

References 35 publications

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“…But, the specific class of power generation value was ignored by the authors that is being discussed in the preceding discussions. The authors in [104] presented Chaos PSO based optimization method for standalone MGs to achieve economic dispatch and voltage compensation. The proposed mechanism controlled not just the electricity but the cooling and heating systems as well.…”

Section: Compensation For Load and Voltage Variationmentioning

confidence: 99%

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Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review

et al. 2019

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Renewable energy sources (RESs) are the replacement of fast depleting, environment polluting, costly, and unsustainable fossil fuels. RESs themselves have various issues such as variable supply towards the load during different periods, and mostly they are available at distant locations from load centers. This paper inspects forecasting techniques, employed to predict the RESs availability during different periods and considers the dispatch mechanisms for the supply, extracted from these resources. Firstly, we analyze the application of stochastic distributions especially the Weibull distribution (WD), for forecasting both wind and PV power potential, with and without incorporating neural networks (NN). Secondly, a review of the optimal economic dispatch (OED) of RES using particle swarm optimization (PSO) is presented. The reviewed techniques will be of great significance for system operators that require to gauge and pre-plan flexibility competence for their power systems to ensure practical and economical operation under high penetration of RESs.

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Section: Compensation For Load and Voltage Variationmentioning

confidence: 99%

“…Here P a D , P L , P s and P W are the load demand, transmission losses, solar and wind powers, respectively [103,104].…”

Section: Gimentioning

confidence: 99%

Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review

et al. 2019

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“…According to the above parts the optimal Energies 2018, 11, 1676 5 of 21 scheduling of IES is determined the optimization model below. The mathematical models of BESS, photovoltaic and CHP power generation are presented in [28,29].…”

Section: Model Of the Integrated Energy Systemmentioning

confidence: 99%

Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss

et al. 2018

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Integrated energy systems (IESs) are considered a trending solution for the energy crisis and environmental problems. However, the diversity of energy sources and the complexity of the IES have brought challenges to the economic operation of IESs. Aiming at achieving optimal scheduling of components, an IES operation optimization model including photovoltaic, combined heat and power generation system (CHP) and battery energy storage is developed in this paper. The goal of the optimization model is to minimize the operation cost under the system constraints. For the optimization process, an optimization principle is conducted, which achieves maximized utilization of photovoltaic by adjusting the controllable units such as energy storage and gas turbine, as well as taking into account the battery lifetime loss. In addition, an integrated energy system project is taken as a research case to validate the effectiveness of the model via the improved differential evolution algorithm (IDEA). The comparison between IDEA and a traditional differential evolution algorithm shows that IDEA could find the optimal solution faster, owing to the double variation differential strategy. The simulation results in three different battery states which show that the battery lifetime loss is an inevitable factor in the optimization model, and the optimized operation cost in 2016 drastically decreased compared with actual operation data.Energies 2018, 11, 1676 2 of 21 gas, and on the energy demand side, it supplies kinds of energy to users, such as heating and electricity. However, as a complex hybrid energy system, a couple of meaningful topic need to be considered integrally, firstly the inherent fluctuation of renewable energy (RE) sources has a severe influence on the overall operation of the IES, both technically and economically, as the inherent volatility and intermittency of RE leads to difficulties in the economic scheduling of IES while providing multiple load supply. The arguments are mainly about the fact that the renewable energy generation cannot be dispatched flexibly while maintaining a certain reliability. Thus it cannot be avoided that a large amount of spare capacity must be provided to ensure the system reliability, and booming techniques such as energy storage systems (ESSs) and gas turbines are widely utilized due to their characteristics of stable output as well as speedy response [6]. However, it is inevitable that the cost would increase with the addition of components in systems, which obviously impacts the overall economy of the IES. The integrated energy system generally consists of electric, thermal and other energy subsystems. Due to the distinct characteristics and utilization scale, the difficulty of research comparing different subsystems it greatly enhanced. Gas turbines (GTs) as a rising energy hub, can convert energy from different subsystems, and are considered to be a reliable integrated energy unit, since according to the different forms of energy demand, GTs could form a combined cooling, heating a...

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“…Particle Swarm Optimization (PSO) was proposed by Eberhart and Kennedy [23] in 1995, but the performance of the standard PSO algorithm is not high enough and shows some defects, such as parameter sensitivity, premature convergence, and slow local search. In recent years, a variant PSO called accelerated PSO (APSO) has attracted wide attention from scholars [24][25][26][27]. Although the APSO improves the convergence speed, the algorithm also may lead to premature convergence and omit some extreme values.…”

Section: Chaos-enhanced Accelerated Particle Swarm Optimization Algormentioning

confidence: 99%

A Quantitative Structure-activity Relationships Model Based on Hybrid Artificial Intelligence Methods and its Application

M¹,

Zhang²,

Liu³

et al. 2018

Preprint

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10Abstract: Quantitative structure-activity relationship (QSAR) model is adopted to study the 11 relationship between the chemical and physical properties of various substances and the structure. 12Through QSAR studies, the internal relationship between the invisible structure and the activity 13 can be obtained. In this paper, a novel chaos-enhanced accelerate particle swarm algorithm 14 (CAPSO) is proposed, which is used to molecular descriptors screening and optimization of the 25Keywords: quantitative structure-activity relationship; hybrid intelligence; artificial neural 26 network; particle swarm optimization 27 28

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Modified Chaos Particle Swarm Optimization-Based Optimized Operation Model for Stand-Alone CCHP Microgrid

Cited by 27 publications

References 35 publications

Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review

Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review

Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss

A Quantitative Structure-activity Relationships Model Based on Hybrid Artificial Intelligence Methods and its Application

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