Multiple-Cut Benders Decomposition for Wind-Hydro-Thermal Optimal Scheduling With Quantifying Various Types of Reserves

Ge, Xiaolin; Jin, Yan; Fu, Yang; Ma, Yue; Xia, Shu

doi:10.1109/tste.2019.2925213

Cited by 15 publications

(10 citation statements)

References 33 publications

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“…The learning algorithm usually uses the gradient method to train and learn the parameters. However, the gradient method has the defects of slow learning speed and low accuracy, whereas the conjugate direction method has the characteristics of secondary termination, small memory requirement, simple calculation and easy realization [18][19][20][21] .Therefore, this paper presents an improved RBF neural network learning algorithm based on conjugate gradient. The specific steps are as follows.…”

Section: B Load Forecasting Methods Based On Rbf Neural Network Algorithmmentioning

confidence: 99%

Hierarchical Evaluation of Distribution Network Access Capacity Taking Into Various Prosumer Group Load Forecasts

Chen

Huang

et al. 2020

IEEE Access

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Now the measurement means of access capacity at all levels of distribution network are insufficient and it is difficult to calculate effectively based on limited data. This paper proposes a hierarchical evaluation method of access capacity of distribution network with multiple prosumer group load forecasting. Firstly, a load dynamic prediction model is constructed. According to the typical load model of historical data mining, a unit prediction model of typical users is established by using the conjugate gradient RBF neural network learning algorithm. Then, according to the charge-discharge dynamic model of the energy storage power station and the load dynamic prediction results, an assessment model of access capacity at the 10kV side was constructed. By analyzing the known load type, load type ratio and transformer capacity on the low-voltage side, the conversion coefficient of 10kV side load to 0.4kV side transformer capacity is obtained by weighting different types of loads proportionally. Then, access distribution capacity of different prosumer group can be obtained based on conversion coefficient. It can ensure the effective measurement of access capacity at all levels of distribution network under the premise of meeting N-1 safety criteria. Finally, an example is given to demonstrate the effectiveness of the proposed method.INDEX TERMS User accessible capacity (UAC), energy storage power station (ESS), load forecasting, RBF neural network, conversion coefficient

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Section: B Load Forecasting Methods Based On Rbf Neural Network Algorithmmentioning

confidence: 99%

Hierarchical Evaluation of Distribution Network Access Capacity Taking Into Various Prosumer Group Load Forecasts

Chen

Huang

et al. 2020

IEEE Access

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show abstract

“…According to the response time and frequency band, the reserve can be divided into 30s real-time response reserve, AGC reserve, 10min spinning reserve, 30 min operating reserve, 60 min operating reserve and cold reserve. In order to realize the reasonable allocation of resources, the discrete Fourier transform method in [26] is employed to quantify the demand of various types of reserves. , , , , , 1 1…”

Section: B Constraintsmentioning

confidence: 99%

A Short-Term Optimal Scheduling Model for Wind-Solar-Hydro-Thermal Complementary Generation System Considering Dynamic Frequency Response

et al. 2021

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This paper proposes a model to realize the coordinated optimal dispatch of wind-solar-hydrothermal hybrid power generation system, aiming at minimizing the power generation cost of thermal generators and maximizing the water storage value of hydropower stations at the end of the scheduling periods, while considering the dynamic frequency response of wind/solar/hydro/thermal generators. Considering the virtual inertia and droop control of wind farms and PV stations, the dynamic frequency response model of wind-solar-hydro-thermal multi-energy complementary system is derived and the metrics that evaluate the frequency dynamic characteristics of the generation system are presented. Then the dynamic frequency response constraints are incorporated into the traditional optimal scheduling model and the Mixed Integer Linear Programming (MILP) method is used to solve it. Finally, the validity and applicability of the proposed model are verified by simulation examples.INDEX TERMS Dynamic frequency response of generators, virtual inertia control, droop control, windsolar-hydro-thermal multi-energy complementary system, Mixed Integer Linear Programming (MILP). NOMENCLATURE A. SETSc mt P Active injection power of node m at period t in scenario c. , c ht Q Water discharge volume of hydro generator h at period t in scenario c. , p c ht h Water head of hydro station p h at period t in scenario c.

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“…Nevertheless, intelligent optimization algorithms have some advantages over the mathematical optimization methods in the aspect of convergence. A coordinated optimization scheduling model of wind-hydro-thermal power system was solved using multiple-cut Benders decomposition algorithm with Jensen's inequality [19]. Ref.…”

Section: Tppmentioning

confidence: 99%

Stochastic Economic Dispatch of Hydro-Thermal-Wind-Photovoltaic Power System Considering Mixed Coal-Blending Combustion

Huang

Han

et al. 2020

IEEE Access

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Multiple-Cut Benders Decomposition for Wind-Hydro-Thermal Optimal Scheduling With Quantifying Various Types of Reserves

Cited by 15 publications

References 33 publications

Hierarchical Evaluation of Distribution Network Access Capacity Taking Into Various Prosumer Group Load Forecasts

Hierarchical Evaluation of Distribution Network Access Capacity Taking Into Various Prosumer Group Load Forecasts

A Short-Term Optimal Scheduling Model for Wind-Solar-Hydro-Thermal Complementary Generation System Considering Dynamic Frequency Response

Stochastic Economic Dispatch of Hydro-Thermal-Wind-Photovoltaic Power System Considering Mixed Coal-Blending Combustion

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