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πππ The contents of this article are as follows: πππ
Contents
π₯1 Overview
1.1 Analysis of the Principle of Energy Storage Assisting Grid Peak Shaving
1.2 System Peak Shaving Optimization Index Model
1.3 Energy Storage System Capacity Configuration Model
π2 Operating Results
2.1 Mode Settings
2.2 New Energy Consumption Curve (Mode 1 – Mode 3)
2.3 Operating Results under Scenario 3
2.4 Energy Storage Configuration Results
2.5 Two Sensitivity Analyses
π3 References
π4 Matlab Code, Data, Article Explanation
1 Overview
Source of Literature:
Abstract: Configuring energy storage systems is an effective means to reduce the peak load burden on units and increase the acceptance capacity of wind power. This article proposes a configuration scheme for energy storage assisting grid peak shaving. The outer model is an optimization configuration model, consisting of a multi-factor optimization model based on the net profit of the energy storage system, the improvement of the standard deviation of thermal power unit output, and the newly added wind power acceptance capacity. An iterative calculation method is used to obtain multi-factor indicators for all schemes within the configuration alternatives, selecting the optimal value as the configuration result of the energy storage system that balances technical and economic aspects. The indicators of the outer model rely on parameters output from the inner model for calculation, where the inner model is an optimization scheduling model that comprehensively considers the operating costs of the energy storage system, the operating costs of thermal power units, and the penalty costs for wind curtailment, aiming to minimize the system’s peak shaving operating costs, optimize the wind power acceptance capacity, and obtain the charging and discharging power of the energy storage system and the output of thermal power units. Finally, based on measured data from a local power grid, the effectiveness of the configuration scheme is verified, and the economic analysis of the energy storage system over its entire life cycle is conducted.
Keywords: Energy storage peak shaving; Deep peak shaving of thermal power; Configuration scheme; Scheduling strategy; Economic analysis;
1.1 Analysis of the Principle of Energy Storage Assisting Grid Peak Shaving
Currently, the peak shaving situation of the power grid is that there is sufficient spinning reserve during peak load periods, but during low load periods, the downward adjustment flexibility of units is severely insufficient, leading to a large amount of wind curtailment. The basic principle of energy storage assisting thermal power unit peak shaving is shown in Figure 1.
As shown in Figure 1, the deep peak shaving of energy storage assisting thermal power units can effectively alleviate the peak shaving pressure on the power grid and reduce wind curtailment. The peak shaving effect produced by the energy storage system mainly depends on its configuration scheme; the higher the configuration, the better the peak shaving effect, but the cost also increases significantly. The configuration of the energy storage system should balance economic indicators and technical indicators.
1.2 System Peak Shaving Optimization Index Model
1.3 Energy Storage System Capacity Configuration Model
For detailed mathematical models and explanations, see Section 4.
2 Operating Results
2.1 Mode Settings
Basic Peak Shaving: 50% output, Pmin=0.5*Pmax
Deep Peak Shaving: 40% output, Pmin=0.4*Pmax, 600MW can perform deep peak shaving, 200-300 cannot (50% output). Oil injection, 30% output. Scenario settings
2.2 New Energy Consumption Curve: (Mode 1 – Mode 3)
2.3 Operating Results under Scenario 3
2.4 Energy Storage Configuration Results
2.5 Two Sensitivity Analyses
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3
% Energy storage battery (corresponding to formula 30)
4
summ2=0;
5
for l=1:1:24
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summ2=summ2+max(x2(1,l),0)*ng+min(x2(1,l),0)/np;
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end
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c =[c,summ2==0];% Capacity balance constraint
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summ4=E0;
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for l=1:1:24
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summ4=summ4+max(x2(1,l),0)*ng+np*min(x2(1,l),0);
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c =[c,Ehmax*0.1<=summ4<=Ehmax*0.9];% Capacity upper and lower limit constraints
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end
14
for l=1:1:24
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summ9=max(x2(1,l),0)*ng+np*min(x2(1,l),0);
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c =[c,-Pgmax<=summ9<=Pgmax];% Power upper and lower limit constraints
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end
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% Wind turbine
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c =[c,0<=x3<=fj];% Renewable energy consumption constraint
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% Daily load balance constraint
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c =[c,sum(x1(:,i))-sum(x2(:,i))+sum(x3(:,i))==load(i)];%
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end
24
25
%% Objective function
26
27
% Energy storage device (formula 1)
3 References
Some theoretical sources are from the internet; if there is any infringement, please contact for deletion.
[1] Li Junhui, Zhang Jiahui, Li Cuiping, et al. Configuration scheme and economic analysis of energy storage systems participating in peak shaving. Journal of Electrical Engineering Technology, 2021, 36(19): 4148-4160. DOI:10.19595/j.cnki.1000-6753.tces.200678.
4 Matlab Code, Data, Article Explanation
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