A multi-objective optimization dispatching and adaptability analysis model for wind-PV-thermal-coordinated operations considering comprehensive forecasting error distribution

Tan, Qinliang; Mei, Shufan; Dai, Mei; Zhou, Liping; Wei, Yongmei; Ju, Liu

doi:10.1016/j.jclepro.2020.120407

Cited by 22 publications

(9 citation statements)

References 39 publications

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“…In 2020, Tan et al [13] proposed a dispatching model based on renewable energy forecasting mistakes with the goal of assessing the function of the present power supply. Tey supplied a complete forecasting error model that was created to propose wind and PV power forecasting mistakes into the dispatching system, according to the researchers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Te particle is indicated by equation ( 12), here, n is the generating units. To satisfy the constraints, the j th dimension of the I th particle is assigned a value of P IJ as shown in equation (13). In which, R ∈ [0, 1].…”

Section: 3mentioning

confidence: 99%

“…Economic load dispatch (ELD), a subset of the unit commitment issue, is a signifcant problem that deals with minimizing the operating cost of a power production facility, with power system engineers' primary duty being to examine the economics of power systems [4,[10][11][12]. Economic dispatch additionally aids throughout the reduction of global pollutants and fuel usages [13][14][15][16][17]. Furthermore, it is essential to address the ELD problems concerning the constraints to avoid unwanted mishaps such as power system breakdowns and also to enhance the security of an electric system [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System

Miracle

Viral

Tiwari

et al. 2023

International Transactions on Electrical Energy Systems

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Hybrid generating systems in power networks have emerged as a result of the rapid growth of renewable infrastructure and widespread support for green energy. One of the most significant problems in designing and operating an electric power generation system is the efficient scheduling of all power generation facilities to meet the rising power demand. Economic load dispatch (ELD) is a generic procedure in the electrical power system, and the ELD in power system problems involves scheduling the power generating units to reduce cost and satisfy system constraints. Metaheuristic algorithms are gaining popularity for solving constrained ELD issues because of their larger global solution capacity, flexibility, and derivative-free construction. In this research, the ELD problem of integrated renewable resources is solved using a unique solution model based on hybrid optimization. Furthermore, this work considers multiobjectives such as total wind generation cost, total cost function of thermal units, and penalty cost function. The hybrid optimization model optimizes the power generation of thermal power plants within the maximum and minimum limitations. Additionally, the turbines are selected optimally by the hybrid optimization model to ensure the power generation of wind turbines based on the demands. The proposed hybrid optimization is a combination of particle swarm optimization (PSO) and cat swarm optimization (CSO), and the new algorithm is referred to as the particle oriented cat swarm optimization model (POCSO). Finally, the performance of the proposed work is compared to other conventional models. In particular, the cost function of POCSO is 6.25%, 6%, 11.7%, 36%, 27%, and 46.42% better than the cost function of whale optimization algorithm (WOA), elephant herd optimization (EHO), moth-flame optimization (MFO), dragonfly algorithm (DA), sealion optimization (SLnO), CSO, and PSO methods, respectively. Also, for IEEE-30 bus system, the best value of the proposed work is 7.46%, 5.41%, 16.30%, 14.88%, 17.60%, 13.86%, 15.21%, 17.49%, and 4.27% better than that of the PSO, CSO, SLnO, DA, MFO, EHO, WOA, multiagent glowworm swarm optimization (MAGSO), and Harris hawks optimization-based feed-forward neural network (HHO-FNN) methods, respectively.

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Section: Literature Reviewmentioning

confidence: 99%

Section: 3mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System

Miracle

Viral

Tiwari

et al. 2023

International Transactions on Electrical Energy Systems

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“…The delivered power from the standby and storage units depends on the PDF of the solar irradiance (G). The PDF of G is fitted via the lognormal distribution [33,34], as illustrated in Figure 4b. Equation (15) describes the probability of G at lognormal fit parameters set as µ = 5.6 and σ = 0.6; thus:…”

Section: B Cost Calculation Of the Solar Plantmentioning

confidence: 99%

Multi-Objective Environmental Economic Dispatch of an Electricity System Considering Integrated Natural Gas Units and Variable Renewable Energy Sources

et al. 2020

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This paper presents a multi-objective economic-environmental dispatch (MOEED) model for integrated thermal, natural gas, and renewable energy systems considering both pollutant emission levels and total fuel or generation cost aspects. Two cases are carried out with the IEEE 30-bus system by replacing thermal generation units into natural gas units to minimize the amount of toxin emission and fuel cost. Equality, inequality like active, reactive powers, prohibited operating zones (POZs) which represents poor operation in the generation cost function, and security constraints are considered as system constraints. Natural gas units (NGUs) are modeled in detail. Therefore, the flow velocity of gas and pressure pipelines are also considered as system constraints. Multi-objective optimization algorithms, namely multi-objective Harris hawks optimization (MOHHO) and multi-objective flower pollination algorithm (MOFPA) are employed to find Pareto optimal solutions of fuel or generation cost and emission together. Furthermore, the technique for order preference by similarity to ideal solution (TOPSIS) is proposed to obtain the best value of Pareto optimal solutions. Three scenarios are investigated to validate the effectiveness of the proposed model applied to the IEEE 30-bus system with the integration of variable renewable energy sources (VRESs) and natural gas units. The results obtained from Scenario III with NGUs installed instead of two thermal units reveal that the economic dispatching approach presented in this work can greatly minimize emission levels as 0.421 t/h and achieve lower fuel cost as 796.35 $/h. Finally, the results obtained show that the MOHHO outperforms the MOFPA in solving the MOEED problem.

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“…To improve the accuracy of power generation calculation, illumination and wind speed are predicted in [9,10]. In [11][12][13], wind power and PV power plants are jointly dispatched, and economic dispatch is carried out considering the objectives of the maximum wind-solar joint benefit. In summary, the utilization rate and output characteristics of wind power and photovoltaic power generation can directly describe the uncertainty of their behavior.…”

Section: Introductionmentioning

confidence: 99%

Day-Ahead Economic Dispatch of Renewable Energy System considering Wind and Photovoltaic Predicted Output

Liu

Tian

et al. 2022

International Transactions on Electrical Energy Systems

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To alleviate the issues of global warming and energy crisis, countries are vigorously developing renewable energy technology. The integration of large-scale renewable energy, including wind energy, hydropower, and photovoltaic (PV), has a great impact on system operation scheduling and economic dispatch. This paper presents an economic dispatching method of wind-PV-CSP-hydro-battery system with wind and photovoltaic power generation as the main energy sources. The long short-term memory (LSTM) neural network is applied to predict wind and PV power, besides, the Latin Hypercube Sampling (LHS) method and the synchronous reduction algorithm are used to obtain 10 typical wind and PV power scenarios. A day-ahead economic dispatch model of wind-PV-CSP-hydro-battery mathematical model is established, and relevant constraints are considered. Concentrated solar power (CSP), hydropower stations, batteries, and transferable loads are used as flexible resources to increase the penetration rate of wind and photovoltaic power generation. Finally, three cases are tested to demonstrate the feasibility of the proposed model. The results show that: (1) LSTM neural network can well predict the output power of wind and photovoltaic power generation with a small root mean square error (RMSE). (2) The introduction of transferable loads and CSP power station into the renewable energy power system can effectively reduce the fluctuation and curtailment rates of wind power and PV power generation.

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A multi-objective optimization dispatching and adaptability analysis model for wind-PV-thermal-coordinated operations considering comprehensive forecasting error distribution

Cited by 22 publications

References 39 publications

Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System

Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System

Multi-Objective Environmental Economic Dispatch of an Electricity System Considering Integrated Natural Gas Units and Variable Renewable Energy Sources

Day-Ahead Economic Dispatch of Renewable Energy System considering Wind and Photovoltaic Predicted Output

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