CN103236705B - For the optimization method of the double-energy storage system stored energy capacity of power distribution network peak load shifting - Google Patents

Abstract

The invention discloses a method for optimizing the energy storage capacity of a dual energy storage system used for peak shifting and valley filling of distribution networks in the technical field of power system energy storage equipment design. Including: respectively establishing the energy storage capacity optimization objective function of the two energy storage systems; setting the initial value of the optimization times and the initial value of the energy storage capacity of the two energy storage systems; respectively setting the initial value of the energy storage capacity of the two energy storage systems Substituting into the energy storage capacity optimization objective function of the respective energy storage system, the optimal value of the energy storage capacity of the respective energy storage system is obtained through optimization calculation; then the optimal value is substituted into the energy storage capacity optimization objective function of the respective energy storage system, through The optimal value of the energy storage capacity of the two energy storage systems is obtained through optimization calculation; the two adjacent optimal values are compared, and if they are the same, two energy storage systems are respectively established according to the two adjacent optimal values. The method provided by the invention realizes the optimization of the configuration of the energy storage capacity of the dual energy storage system when the power distribution network cuts peaks and fills valleys.

Description

Optimization method of energy storage capacity of dual energy storage system for distribution network peak shaving and valley filling

technical field

The invention belongs to the technical field of energy storage equipment design in electric power systems, and in particular relates to an optimization method for the energy storage capacity of a dual energy storage system used for peak-shaving and valley-filling of distribution networks.

Background technique

With the development of social economy and the improvement of people's living standards, the load in the power system presents the characteristics that the peak-to-valley load difference increases year by year, and the maximum load utilization hours decrease year by year. This will cause the scale of power equipment in the links of generation, transmission, and distribution to increase with the increase of the annual maximum load, but the annual maximum load utilization hours of the equipment will decrease, reducing the economics of power equipment investment and causing social resources. Underutilized.

With the development of modern power grid technology, energy storage technology has been gradually introduced into the power system. Energy storage can effectively realize demand-side management, eliminate peak-valley differences between day and night, smooth load, improve the utilization rate of power equipment, and reduce power supply costs. It can also promote the utilization of new energy. Energy storage technology has become an important means to achieve peak shaving and valley filling in the distribution network. Research on battery energy storage technologies represented by lithium-ion batteries and all-vanadium flow redox batteries has made great progress.

Whether the investment in the energy storage system is reasonable is directly related to its capacity configuration. Therefore, optimizing the capacity of the energy storage system for peak-shaving and valley-filling of the distribution network can not only obtain the capacity configuration that meets the requirements of load-shaving peak-shaving and valley-filling, but also can maximize economic benefits.

Contents of the invention

The purpose of the present invention is to propose a method for optimizing the energy storage capacity of a dual energy storage system for peak-shaving and valley-filling of distribution networks, which is used to solve the configuration of energy storage capacity of dual-energy storage systems during peak-shaving and valley-filling of distribution networks Not an optimal problem.

In order to achieve the above object, the technical solution proposed by the present invention is a method for optimizing the energy storage capacity of a dual energy storage system for peak-shaving and valley-filling of distribution networks, which is characterized in that the method includes:

Step 1: Record the two energy storage systems as the first energy storage system and the second energy storage system respectively, and respectively establish the energy storage capacity optimization objective function of the first energy storage system and the energy storage capacity optimization objective of the second energy storage system function;

Step 2: Set the initial value of optimization times j to j=0, and set the initial value of the energy storage capacity of the first energy storage system to Set the initial energy storage capacity of the second energy storage system to be

Step 3: Substitute the initial value of the energy storage capacity of the second energy storage system into the optimization objective function of the energy storage capacity of the first energy storage system, and obtain the optimal value of the energy storage capacity of the first energy storage system through optimization calculation

Substitute the initial value of the energy storage capacity of the first energy storage system into the optimization objective function of the energy storage capacity of the second energy storage system, and obtain the optimal value of the energy storage capacity of the second energy storage system through optimization calculation

Step 4: Order Will Substituting into the energy storage capacity optimization objective function of the first energy storage system, the optimal value of the energy storage capacity of the first energy storage system is obtained through optimization calculation

Will Substituting into the energy storage capacity optimization objective function of the second energy storage system, the optimal value of the energy storage capacity of the second energy storage system is obtained through optimization calculation

Step 5: Judging whether it is satisfied at the same time and If both and Then execute step 6; otherwise, let j=j+1, return to step 4;

Step 6: Separately with and The first energy storage system and the second energy storage system are established as the energy storage capacities of the first energy storage system and the second energy storage system.

The energy storage capacity optimization objective function of the first energy storage system is:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; delay</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; environment</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; income</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; delay</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; environment</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; income</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; ;</span>$

Among them, S _1-delay is the delayed power supply and transmission equipment investment after the first energy storage system is put into operation, S _{1_delay} = R _{p_vest} · P _{1_ESS} , R _{p_vest} is the unit power input of power supply and transmission equipment, P _{1_ESS} is the first energy storage system power and t _{l1_k} and t _{l2_k} are the start and end times of the low load period on the k-th day, respectively, and n ₁ is the life of the first energy storage system;

S _{1_enviroment} is the environmental benefit of the first energy storage system, $S_{1\_\mathrm{environment}=(\underset{p=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{1\_\mathrm{metal}\_p}{\mathrm{\&eta;}}_{1\_\mathrm{metal}\_p}-R_{1\_\mathrm{recycle}})\&Center\; Dot;{\mathrm{\&eta;}}_{1\_\mathrm{能源}}\&CenterDot;{\mathrm{E.}}_1,}$ R _{1_metal_p} is the price of metal p, m is the type of metal contained in the first energy storage system, η _{1_metal_p} is the content of metal p in the unit weight of the first energy storage system, R _{1_recycle} is the first energy storage system waste disposal facility per unit weight required expenditure, η _{1_energy} is the energy-to-weight ratio of the first energy storage system;

S _{1_income} is the direct benefit generated when the first energy storage system has low storage and high power generation, S _{1_income} = (R _{1_out} -R _{1_in} )·E ₁ , R _{1_out} is the price of grid output power when the first energy storage system has low storage and high power generation, R _{1_in} is the price of grid input electric energy when the first energy storage system has low storage and high power generation;

S _{1_P,E} is the sum of power cost and capacity cost of the first energy storage system, $S_{1\_P,\mathrm{E.}}=(C_{1\_p}\&CenterDot;P_{1\_\mathrm{ESS}}+C_{1\_\mathrm{E.}}\&Center\; Dot;{\mathrm{E.}}_1)\&CenterDot;\frac{{\mathrm{\&alpha;}}_1{(1+{\mathrm{\&alpha;}}_1)}^{{\mathrm{no}}_1}}{{(1+{\mathrm{\&alpha;}}_1)}^{{\mathrm{no}}_1}-1},$ C _{1_p} is the unit power cost of the first energy storage system, C _{1_E} is the unit capacity cost of the first energy storage system, α ₁ is the investment return rate of the first energy storage system;

S _{1_m} is the annual maintenance expenditure of the first energy storage system, S _{1_m} = C _{1_m} · E ₁ ; C _{1_m} is the annual maintenance expenditure per unit capacity of the first energy storage system;

E ₁ is the energy storage capacity of the first energy storage system to be optimized;

After the second energy storage system is put into operation, the investment in power supply and transmission equipment will be delayed. R _{p_vest} is the unit power input of power supply and transmission equipment, is the power of the second energy storage system and t _{l1_k} and t _{l2_k} are the start and end times of the low load period on the k-th day, respectively, and n ₂ is the life of the second energy storage system;

is the environmental benefit of the second energy storage system, $S_{2\_\mathrm{environment}}^{*}=(\underset{q=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{2\_\mathrm{metal}\_q}{\mathrm{\&eta;}}_{2\_\mathrm{metal}\_q}-R_{2\_\mathrm{recycle}})\&Center\; Dot;{\mathrm{\&eta;}}_{2\_\mathrm{能源}}\&Center\; Dot;{\mathrm{E.}}_2^{*},$ R _{2_metal_q} is the price of metal q, m is the type of metal contained in the second energy storage system, η _{2_metal_q} is the content of metal q in the unit weight of the second energy storage system, R _{2_recycle} is the second energy storage system’s waste disposal facility per unit weight The required expenditure, η _{2_energy} represents the energy-to-weight ratio of the second energy storage system;

It is the direct benefit generated when the second energy storage system has low storage and high power generation. R _{2_out} is the price of grid output power when the second energy storage system has low storage and high power generation, and R _{2_in} is the price of grid input power when the second energy storage system is low storage and high power generation;

is the sum of power cost and capacity cost of the second energy storage system, $S_{2\_P,\mathrm{E.}}^{*}=(C_{2\_p}\&Center\; Dot;P_{2\_\mathrm{ESS}}+C_{2\_\mathrm{E.}}\&CenterDot;{\mathrm{E.}}_2^{*})\&Center\; Dot;\frac{{\mathrm{\&alpha;}}_2{(1+{\mathrm{\&alpha;}}_2)}^{{\mathrm{no}}_2}}{{(1+{\mathrm{\&alpha;}}_2)}^{{\mathrm{no}}_2}-1},$ C _{2_p} is the unit power cost of the second energy storage system, C _{2_E} is the unit capacity cost of the second energy storage system, α ₂ is the return on investment of the second energy storage system;

is the annual maintenance expenditure of the second energy storage system, C _{2_m} is the annual maintenance expenditure per unit capacity of the second energy storage system;

is the initial or optimal value of the energy storage capacity of the second energy storage system;

The constraint condition of the energy storage capacity optimization objective function of the first energy storage system is E ₁ ≥0.

The optimal value of the energy storage capacity of the first energy storage system is obtained through optimization calculation Particle swarm optimization method is used.

The energy storage capacity optimization objective function of the second energy storage system is

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; delay</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; environment</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; income</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; delay</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; environment</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; income</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; ;</span>$

Among them, S _2-delay is the delayed input of power supply and transmission equipment after the second energy storage system is put into operation, S _{2_delay} = R _{p_vest} P _{2_ESS} , R _{p_vest} is the unit power input of power supply and transmission equipment, and P _{2_ESS} is the input of the second energy storage system power and t _{l1_k} and t _{l2_k} are the start and end times of the low load period on the k-th day, respectively, and n ₂ is the life of the second energy storage system;

S _{2_enviroment} is the environmental benefit of the second energy storage system, $S_{2\_\mathrm{environment}}=(\underset{q=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{2\_\mathrm{metal}\_q}{\mathrm{\&eta;}}_{2\_\mathrm{metal}\_q}-R_{2\_\mathrm{recycle}})\&CenterDot;{\mathrm{\&eta;}}_{2\_\mathrm{能源}}\&CenterDot;{\mathrm{E.}}_2,$ R _{2_metal_q} is the price of metal q, m is the type of metal contained in the second energy storage system, η _{2_metal_q} is the content of metal q in the unit weight of the second energy storage system, R _{2_recycle} is the second energy storage system’s waste disposal facility per unit weight The required expenditure, η _{2_energy} represents the energy-to-weight ratio of the second energy storage system;

S _{2_income} is the direct benefit generated when the second energy storage system has low storage and high power generation, S _{2_income} = (R _{2_out} -R _{2_in} )·E ₂ , R _{2_out} is the price of grid output power when the second energy storage system has low storage and high power generation, R _{2_in} is the price of grid input electric energy when the second energy storage system has low storage and high power generation;

S _{2_P,E} is the sum of power cost and capacity cost of the second energy storage system, $S_{2\_P,\mathrm{E.}}=(C_{2\_p}\&Center\; Dot;P_{2\_\mathrm{ESS}}+C_{2\_\mathrm{E.}}\&Center\; Dot;{\mathrm{E.}}_2)\&Center\; Dot;\frac{{\mathrm{\&alpha;}}_2{(1+{\mathrm{\&alpha;}}_2)}^{{\mathrm{no}}_2}}{{(1+{\mathrm{\&alpha;}}_2)}^{{\mathrm{no}}_2}-1},$ C _{2_p} is the unit power cost of the second energy storage system, C _{2_E} is the unit capacity cost of the second energy storage system, α ₂ is the return on investment of the second energy storage system;

S _{2_m} is the annual maintenance expenditure of the second energy storage system, S _{2_m} = C _{2_m} · E ₂ ; C _{2_m} is the annual maintenance expenditure per unit capacity of the second energy storage system;

_E2 is the energy storage capacity of the second energy storage system to be optimized;

After the first energy storage system is put into operation, the investment in power supply and transmission equipment will be delayed, R _{p_vest} is the unit power input of power supply and transmission equipment, is the power of the first energy storage system and t _{l1_k} and t _{l2_k} are the start and end times of the low load period on the k-th day, respectively, and n ₁ is the life of the first energy storage system;

is the environmental benefit of the first energy storage system, $S_{1\_\mathrm{environment}}^{*}=(\underset{p=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{1\_\mathrm{metal}\_p}{\mathrm{\&eta;}}_{1\_\mathrm{metal}\_p}-R_{1\_\mathrm{recycle}})\&CenterDot;{\mathrm{\&eta;}}_{1\_\mathrm{能源}}\&Center\; Dot;{\mathrm{E.}}_1^{*},$ R _{1_metal_p} is the price of metal p, m is the type of metal contained in the first energy storage system, η _{1_metal_p} is the content of metal p in the unit weight of the first energy storage system, R _{1_recycle} is the first energy storage system waste disposal facility per unit weight required expenditure, η _{1_energy} is the energy-to-weight ratio of the first energy storage system;

It is the direct benefit generated when the first energy storage system has low storage and high power generation. R _{1_out} is the price of grid output power when the first energy storage system has low storage and high power generation, and R _{1_in} is the price of grid input power when the first energy storage system is low storage and high power generation;

is the sum of power cost and capacity cost of the first energy storage system, $S_{1\_P,\mathrm{E.}}^{*}=(C_{1\_p}\&Center\; Dot;P_{1\_\mathrm{ESS}}+C_{1\_\mathrm{E.}}\&Center\; Dot;{\mathrm{E.}}_1^{*})\&Center\; Dot;\frac{{\mathrm{\&alpha;}}_1{(1+{\mathrm{\&alpha;}}_1)}^{{\mathrm{no}}_1}}{{(1+{\mathrm{\&alpha;}}_1)}^{{\mathrm{no}}_1}-1},$ C _{1_p} is the unit power cost of the first energy storage system, C _{1_E} is the unit capacity cost of the first energy storage system, α ₁ is the investment return rate of the first energy storage system;

is the annual maintenance expenditure of the first energy storage system, C _{1_m} is the annual maintenance expenditure per unit capacity of the first energy storage system;

is the initial or optimal value of the energy storage capacity of the first energy storage system;

The constraint condition of the energy storage capacity optimization objective function of the second energy storage system is E ₂ ≥0.

The optimal value of the energy storage capacity of the second energy storage system is obtained through optimization calculation Particle swarm optimization method is used.

The method provided by the invention realizes the optimization of the configuration of the energy storage capacity of the dual energy storage system when the power distribution network cuts peaks and fills valleys.

Description of drawings

Figure 1 is a control structure diagram of a battery energy storage system used for peak shaving and valley filling in distribution networks;

Fig. 2 is a flow chart of an optimization method for the energy storage capacity of a dual energy storage system for peak shaving and valley filling in distribution networks.

Detailed ways

The preferred embodiments will be described in detail below in conjunction with the accompanying drawings. It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.

Example

In this embodiment, a lithium-ion battery energy storage system is selected as the first energy storage system, and an all-vanadium redox battery energy storage system is selected as the second energy storage system.

Figure 1 is a control structure diagram of a battery energy storage system used for peak shaving and valley filling in distribution networks. As shown in Figure 1, the battery energy storage system used for peak shaving and valley filling in distribution network consists of historical database, data acquisition module, load forecasting system, data analysis and processing module, power constraint module and battery energy storage system module.

Based on the historical database, the battery energy storage system selects data with the same conditions and similar weather as the forecast day, uses the support vector machine method to predict the forecast daily load, and calculates the peak and valley values of the load on the day according to the load forecast value, and sets them as P _rg and P _peak ; import P _rg and P _peak values into the data analysis and processing module, and load the predicted load value P _force to compare with P _rg and P _peak : when the load data P _force is less than the synthetic output low value P _rg , it is planned to carry out The energy storage system is charging. At this time, according to the battery SOC state value collected in the BMS (energy management module), it is judged whether the battery meets the SOC constraint. Fill the valley after charging, otherwise perform power correction; when the load data P _force is greater than the initial value P _peak of the synthetic output peak value, the energy storage system is to be discharged, and at this time it is judged whether the battery is based on the battery SOC state value collected in the BMS (energy management module). Satisfy the SOC constraint, if it is satisfied, the energy storage system discharges, and loads the power constraint module to judge whether the power constraint is met, and if it is satisfied, the wind cut is completed, so that the combined output after energy storage adjustment reaches the initial value P _peak of the combined output peak value; when the load data When P _force is within the range of [P _rg ,P _peak ], the energy storage system does not operate.

Fig. 2 is a flow chart of an optimization method for the energy storage capacity of a dual energy storage system for peak shaving and valley filling in distribution networks. As shown in Figure 2, the method for optimizing the energy storage capacity of a dual energy storage system for peak load shaving and valley filling provided by this embodiment includes:

Step 1: The lithium-ion battery energy storage system is used as the first energy storage system, and the all-vanadium flow redox battery energy storage system is used as the second energy storage system, and the energy storage capacity optimization objective function and the second energy storage system of the first energy storage system are respectively established. The objective function of energy storage capacity optimization for the second energy storage system.

The energy storage capacity optimization objective function of the first energy storage system is:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; delay</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; environment</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; income</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; delay</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; environment</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; income</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

In the formula (1), S _1-delay is the delay in the input of power supply and transmission equipment after the first energy storage system is put into operation, S _{1_delay} = R _{p_vest} · P _{1_ESS} , R _{p_vest} is the unit power input of power supply and transmission equipment, and P _{1_ESS} is the input of the first energy storage system The power of an energy storage system and t _{l1_k} and t _{l2_k} are the start and end time of the low load period on day k, respectively, and n ₁ is the life of the first energy storage system. Since the values _of R _{p_vest} and n1 can be determined, S1 _-delay is _a function of E1.

S _{1_enviroment} is the environmental benefit of the first energy storage system, $S_{1\_\mathrm{environment}}=(\underset{p=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{1\_\mathrm{metal}\_p}{\mathrm{\&eta;}}_{1\_\mathrm{metal}\_p}-R_{1\_\mathrm{recycle}})\&CenterDot;{\mathrm{\&eta;}}_{1\_\mathrm{能源}}\&Center\; Dot;{\mathrm{E.}}_1,$ R _{1_metal_p} is the price of metal p, m is the type of metal contained in the first energy storage system, η _{1_metal_p} is the content of metal p in the unit weight of the first energy storage system, R _{1_recycle} is the first energy storage system waste disposal facility per unit weight η _{1_energy} is the energy-to-weight ratio of the first energy storage system. Since the values of R _{1_metal_p} , m, η _{1_metal_p} , R _{1_recycle} and η _{1_energy} can be determined, S _{1_enviroment} is also a function of E ₁ .

S _{1_income} is the direct benefit generated when the first energy storage system has low storage and high power generation, S _{1_income} = (R _{1_out} -R _{1_in} )·E ₁ , R _{1_out} is the price of grid output power when the first energy storage system has low storage and high power generation, R _{1_in} is the price of grid input electric energy when the first energy storage system has low storage and high power generation. Since the values of R _{1_out} and R _{1_in} can be determined, S _{1_income} is a function of E ₁ .

S _{1_P,E} is the sum of power cost and capacity cost of the first energy storage system, $S_{1\_P,\mathrm{E.}}=(C_{1\_p}\&Center\; Dot;P_{1\_\mathrm{ESS}}+C_{1\_\mathrm{E.}}\&CenterDot;{\mathrm{E.}}_1)\&Center\; Dot;\frac{{\mathrm{\&alpha;}}_1{(1+{\mathrm{\&alpha;}}_1)}^{{\mathrm{no}}_1}}{{(1+{\mathrm{\&alpha;}}_1)}^{{\mathrm{no}}_1}-1},$ C _{1_p} is the unit power cost of the first energy storage system, C _{1_E} is the unit capacity cost of the first energy storage system, and α ₁ is the investment return rate of the first energy storage system. Since the values of C _{1_p} , α ₁ , n ₁ and C _{1_E} can be determined, S _{1_P,E} is a function of E ₁ .

S _{1_m} is the annual maintenance expenditure of the first energy storage system, S _{1_m} = C _{1_m} · E ₁ ; C _{1_m} is the annual maintenance expenditure per unit capacity of the first energy storage system. Since the value of C _{1_m} can be determined, S _{1_m} is a function of E ₁ .

E ₁ is the energy storage capacity of the first energy storage system to be optimized.

After the second energy storage system is put into operation, the investment in power supply and transmission equipment will be delayed. R _{p_vest} is the unit power input of power supply and transmission equipment, is the power of the second energy storage system and t _{l1_k} and t _{l2_k} are the start and end time of the low load period on day k respectively, and n ₂ is the life of the second energy storage system.

is the environmental benefit of the second energy storage system, $S_{2\_\mathrm{environment}}^{*}=(\underset{q=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{2\_\mathrm{metal}\_q}{\mathrm{\&eta;}}_{2\_\mathrm{metal}\_q}-R_{2\_\mathrm{recycle}})\&Center\; Dot;{\mathrm{\&eta;}}_{2\_\mathrm{能源}}\&CenterDot;{\mathrm{E.}}_2^{*},$ R _{2_metal_q} is the price of metal q, m is the type of metal contained in the second energy storage system, η _{2_metal_q} is the content of metal q in the unit weight of the second energy storage system, R _{2_recycle} is the second energy storage system’s waste disposal facility per unit weight η _{2_energy} represents the energy-to-weight ratio of the second energy storage system.

It is the direct benefit generated when the second energy storage system has low storage and high power generation. R _{2_out} is the price of grid output power when the second energy storage system has low storage and high power generation, and R _{2_in} is the price of grid input power when the second energy storage system is low storage and high power generation.

is the sum of power cost and capacity cost of the second energy storage system, $S_{2\_P,\mathrm{E.}}^{*}=(C_{2\_p}\&Center\; Dot;P_{2\_\mathrm{ESS}}+C_{2\_\mathrm{E.}}\&Center\; Dot;{\mathrm{E.}}_2^{*})\&CenterDot;\frac{{\mathrm{\&alpha;}}_2{(1+{\mathrm{\&alpha;}}_2)}^{{\mathrm{no}}_2}}{{(1+{\mathrm{\&alpha;}}_2)}^{{\mathrm{no}}_2}-1},$ C _{2_p} is the unit power cost of the second energy storage system, C _{2_E} is the unit capacity cost of the second energy storage system, α ₂ is the return on investment of the second energy storage system.

is the annual maintenance expenditure of the second energy storage system, C _{2_m} is the annual maintenance expenditure per unit capacity of the second energy storage system.

is the initial or optimal value of the energy storage capacity of the second energy storage system, in When the value of is determined, and are definite values. Thus, in When the value of is determined, S ₁ is a function of E ₁ , that is, the objective function of the energy storage capacity optimization of the first energy storage system is a function of E ₁ . At this time, the constraint condition of the energy storage capacity optimization objective function of the first energy storage system can be set as E ₁ ≥0.

The energy storage capacity optimization objective function of the second energy storage system is:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; delay</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; environment</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; income</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; delay</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; environment</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; income</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

In the formula (2), S _2-delay is the delayed input of power supply and transmission equipment after the second energy storage system is put into operation, S _{2_delay} = R _{p_vest} · P _{2_ESS} , R _{p_vest} is the unit power input of power supply and transmission equipment, and P _{2_ESS} is the first The power of the second energy storage system and t _{l1_k} and t _{l2_k} are the start and end time of the low load period on day k respectively, and n ₂ is the life of the second energy storage system. Since the values _of R _{p_vest} and n1 can be determined, S2 _-delay is a function of _E2 .

S _{2_enviroment} is the environmental benefit of the second energy storage system, $S_{2\_\mathrm{environment}}=(\underset{q=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{2\_\mathrm{metal}\_q}{\mathrm{\&eta;}}_{2\_\mathrm{metal}\_q}-R_{2\_\mathrm{recycle}})\&Center\; Dot;{\mathrm{\&eta;}}_{2\_\mathrm{能源}}\&Center\; Dot;{\mathrm{E.}}_2,$ R _{2_metal_q} is the price of metal q, m is the type of metal contained in the second energy storage system, η _{2_metal_q} is the content of metal q in the unit weight of the second energy storage system, R _{2_recycle} is the second energy storage system’s waste disposal facility per unit weight η _{2_energy} represents the energy-to-weight ratio of the second energy storage system. Since the values of R _{2_metal_p} , m, η _{2_metal_p} , R _{2_recycle} and η _{2_energy} can be determined, S _{2_enviroment} is also a function of E ₂ .

S _{2_income} is the direct benefit generated when the second energy storage system has low storage and high power generation, S _{2_income} = (R _{2_out} -R _{2_in} )·E ₂ , R _{2_out} is the price of grid output power when the second energy storage system has low storage and high power generation, R _{2_in} is the price of the grid input electric energy when the second energy storage system has low storage and high power generation. Since the values of _{R2_out} and _{R2_in} can be determined, _{S2_income} is a function of _E2 .

S _{2_P,E} is the sum of power cost and capacity cost of the second energy storage system, $S_{2\_P,\mathrm{E.}}=(C_{2\_p}\&Center\; Dot;P_{2\_\mathrm{ESS}}+C_{2\_\mathrm{E.}}\&Center\; Dot;{\mathrm{E.}}_2)\&Center\; Dot;\frac{{\mathrm{\&alpha;}}_2{(1+{\mathrm{\&alpha;}}_2)}^{{\mathrm{no}}_2}}{{(1+{\mathrm{\&alpha;}}_2)}^{{\mathrm{no}}_2}-1},$ C _{2_p} is the unit power cost of the second energy storage system, C _{2_E} is the unit capacity cost of the second energy storage system, α ₂ is the return on investment of the second energy storage system. Since the values of C _{2_p} , α ₂ , n ₂ and C _{2_E} can be determined, S _{2_P,E} is a function of E ₂ .

S _{2_m} is the annual maintenance expenditure of the second energy storage system, S _{2_m} = C _{2_m} · E ₂ ; C _{2_m} is the annual maintenance expenditure per unit capacity of the second energy storage system. Since the value of C _{2_m} can be determined, S _{2_m} is a function of E ₂ .

_E2 is the energy storage capacity of the second energy storage system to be optimized.

After the first energy storage system is put into operation, the investment in power supply and transmission equipment will be delayed, R _{p_vest} is the unit power input of power supply and transmission equipment, is the power of the first energy storage system and t _{l1_k} and t _{l2_k} are the start and end time of the low load period on day k, respectively, and n ₁ is the life of the first energy storage system.

is the environmental benefit of the first energy storage system, $S_{1\_\mathrm{environment}}^{*}=(\underset{p=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{1\_\mathrm{metal}\_p}{\mathrm{\&eta;}}_{1\_\mathrm{metal}\_p}-R_{1\_\mathrm{recycle}})\&CenterDot;{\mathrm{\&eta;}}_{1\_\mathrm{能源}}\&CenterDot;{\mathrm{E.}}_1^{*},$ R _{1_metal_p} is the price of metal p, m is the type of metal contained in the first energy storage system, η _{1_metal_p} is the content of metal p in the unit weight of the first energy storage system, R _{1_recycle} is the first energy storage system waste disposal facility per unit weight η _{1_energy} is the energy-to-weight ratio of the first energy storage system.

It is the direct benefit generated when the first energy storage system has low storage and high power generation. R _{1_out} is the price of grid output power when the first energy storage system has low storage and high power generation, and R _{1_in} is the price of grid input power when the first energy storage system is low storage and high power generation.

is the sum of power cost and capacity cost of the first energy storage system, $S_{1\_P,\mathrm{E.}}^{*}=(C_{1\_p}\&Center\; Dot;P_{1\_\mathrm{ESS}}+C_{1\_\mathrm{E.}}\&Center\; Dot;{\mathrm{E.}}_1^{*})\&Center\; Dot;\frac{{\mathrm{\&alpha;}}_1{(1+{\mathrm{\&alpha;}}_1)}^{{\mathrm{no}}_1}}{{(1+{\mathrm{\&alpha;}}_1)}^{{\mathrm{no}}_1}-1},$ C _{1_p} is the unit power cost of the first energy storage system, C _{1_E} is the unit capacity cost of the first energy storage system, and α ₁ is the investment return rate of the first energy storage system.

is the annual maintenance expenditure of the first energy storage system, C _{1_m} is the annual maintenance expenditure per unit capacity of the first energy storage system.

is the initial value or optimal value of the energy storage capacity of the first energy storage system, in When the value of is determined, and are definite values. Thus, in When the value of is determined, S2 is a function of _E2 , that is, the energy storage capacity optimization objective function of the _second energy storage system is a function of _E2 . At this time, the constraint condition of the objective function for optimizing the energy storage capacity of the second energy storage system can be set as E ₂ ≥0.

Step 2: Set the initial value of optimization times j to j=0, and set the initial value of the energy storage capacity of the first energy storage system to Set the initial energy storage capacity of the second energy storage system to be

Step 3: Substitute the initial value of the energy storage capacity of the second energy storage system into the optimization objective function of the energy storage capacity of the first energy storage system, and obtain the optimal value of the energy storage capacity of the first energy storage system through optimization calculation

Since the initial energy storage capacity of the second energy storage system is therefore and Both are determined values, which are substituted into the energy storage capacity optimization objective function of the first energy storage system, that is, formula (1), and formula (1) is a function about E ₁ . When the constraint condition of formula (1) is E ₁ ≥ 0, the optimal value of variable E ₁ in formula (1) can be calculated by various optimization algorithms. In this embodiment, the particle swarm optimization method is used to obtain the optimal value of the variable E ₁ in the formula (1), which is denoted as Since the particle swarm optimization method is a commonly used method, and the particle swarm optimization calculation can be performed directly by using mathematical software such as MATLAB, the present invention does not repeat the optimization process _of the objective function S1.

Substitute the initial value of the energy storage capacity of the first energy storage system into the optimization objective function of the energy storage capacity of the second energy storage system, and obtain the optimal value of the energy storage capacity of the second energy storage system through optimization calculation

Since the initial energy storage capacity of the first energy storage system is therefore and Both are definite values, which are substituted into the energy storage capacity optimization objective function of the second energy storage system, that is, formula (2), and formula (2) is a function about E ₂ . When the constraint condition of formula (2) is E ₂ ≥ 0, the optimal value of the variable E ₂ in formula (2) can be calculated by various optimization algorithms, denoted as In this embodiment, the particle swarm optimization method is used to obtain the optimal value of the variable E ₂ in the formula (2).

Step 4: Order Will Substituting into the energy storage capacity optimization objective function of the first energy storage system, the optimal value of the energy storage capacity of the first energy storage system is obtained through optimization calculation

This step orders The value of is equal to the optimal value of the energy storage capacity of the second energy storage system obtained from the last optimization calculation Substitute it into formula (1) to perform another optimization calculation. The optimization method is the same as step 3, and the optimal value of the energy storage capacity of the new first energy storage system is obtained

make The value of is equal to the optimal value of the energy storage capacity of the first energy storage system obtained from the last optimization calculation Substitute it into formula (2) to perform another optimization calculation. The optimization method is the same as step 3, and the optimal value of the energy storage capacity of the new second energy storage system is obtained

Step 5: Judging whether it is satisfied at the same time and If both and Then execute step 6; otherwise, set j=j+1 and return to step 4.

In this step, if the energy storage capacities of the two energy storage systems obtained from two adjacent optimization results are the same, that is and Then it is considered that the equilibrium point of the energy storage capacity of the two energy storage systems has been found, and step 6 is performed at this time.

If the energy storage capacities of the two energy storage systems obtained from two adjacent optimization results are different, set j=j+1, return to step 4, perform the next optimization calculation, and continue to find the equilibrium point.

Step 6: Separately with and The first energy storage system and the second energy storage system are established as the energy storage capacities of the first energy storage system and the second energy storage system.

The above is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present invention can easily think of changes or Replacement should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (4)

1., for an optimization method for the double-energy storage system stored energy capacity of power distribution network peak load shifting, it is characterized in that described method comprises:

Step 1: two energy-storage systems are designated as the first energy-storage system and the second energy-storage system respectively, sets up the stored energy capacitance optimization object function of the first energy-storage system and the stored energy capacitance optimization object function of the second energy-storage system respectively;

Step 2: the initial value that number of times j is optimized in setting is j=0, and the stored energy capacitance initial value setting the first energy-storage system is the stored energy capacitance initial value setting the second energy-storage system is

Step 3: the stored energy capacitance optimization object function stored energy capacitance initial value of the second energy-storage system being substituted into the first energy-storage system, by optimizing the stored energy capacitance optimal value calculating the first energy-storage system

The stored energy capacitance initial value of the first energy-storage system is substituted into the stored energy capacitance optimization object function of the second energy-storage system, by optimizing the stored energy capacitance optimal value calculating the second energy-storage system

Step 4: order will substitute into the stored energy capacitance optimization object function of the first energy-storage system, by optimizing the stored energy capacitance optimal value calculating the first energy-storage system

Will substitute into the stored energy capacitance optimization object function of the second energy-storage system, by optimizing the stored energy capacitance optimal value calculating the second energy-storage system

Step 5: judge whether simultaneously to meet with if met simultaneously with then perform step 6; Otherwise, make j=j+1, return step 4;

Step 6: respectively with with stored energy capacitance as the first energy-storage system and the second energy-storage system sets up the first energy-storage system and the second energy-storage system.

2. optimization method according to claim 1, is characterized in that the stored energy capacitance optimization object function of described first energy-storage system is:

$S_1=S_{1-\mathrm{delay}}+S_{1\_\mathrm{enviroment}}+S_{1\_\mathrm{income}}-S_{1\_P,E}-S_{1\_m}+S_{2-\mathrm{delay}}^{*}+S_{2\_\mathrm{enviroment}}^{*}+S_{2\_\mathrm{income}}^{*}-S_{2\_P,E}^{*}-S_{2\_m}^{*};$

Wherein, S _1-delaydelay power supply transmission facility input amount after the first energy-storage system drops into, S _{1_delay}=R _{p_vest}p _{1_ESS}, R _{p_vest}power supply transmission facility unit power input amount, P _{1_ESS}be the first energy-storage system power and t _{l1_k}and t _{l2_k}beginning and ending time kth sky load valley period respectively, n ₁it is the life-span of the first energy-storage system;

S _{1_enviroment}the environmental benefit of the first energy-storage system, $S_{1\_\mathrm{environment}}=(\underset{p=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{1\_\mathrm{metal}\_p}{\mathrm{\&eta;}}_{1\_\mathrm{metal}\_p}-R_{1\_\mathrm{recycle}})\&CenterDot;{\mathrm{\&eta;}}_{1\_\mathrm{energy}}\&CenterDot;E_1,$ R _{1_metal_p}be the price of metal p, m is the metal species contained by the first energy-storage system, η _{1_metal_p}the content of metal p in the first energy-storage system Unit Weight, R _{1_recycle}the expenditure needed for process Unit Weight first energy-storage system waste material, η _{1_energy}it is the first energy-storage system energy anharmonic ratio;

S _{1_income}be the low storage of the first energy-storage system occurred frequently time produce direct benefit, S _{1_income}=(R _{1_out}-R _{1_in}) E ₁, R _{1_out}be the low storage of the first energy-storage system occurred frequently time electrical network export the price of electric energy, R _{1_in}be the low storage of the first energy-storage system occurred frequently time electrical network input electric energy price;

S _{1_P, E}the first energy-storage system power cost and Capacity Cost sum, $S_{1\_P,E}=(C_{1\_p}\&CenterDot;P_{1\_\mathrm{ESS}}+C_{1\_E}\&CenterDot;E_1)\&CenterDot;\frac{{\mathrm{\&alpha;}}_1{(1+{\mathrm{\&alpha;}}_1)}^{n_1}}{{(1+{\mathrm{\&alpha;}}_1)}^{n_1}-1},$ C _{1_p}the first energy-storage system unit power cost, C _{1_E}the first energy-storage system unit capacity cost, α ₁it is the first energy-storage system investment yield;

S _{1_m}the 1 energy-storage system year safeguarded expenditure, S _{1_m}=C _{1_m}e ₁; C _{1_m}the 1 energy-storage system unit capacity year safeguarded expenditure;

E ₁it is the stored energy capacitance of the first energy-storage system to be optimized;

second energy-storage system delays power supply transmission facility input amount after dropping into, r _{p_vest}power supply transmission facility unit power input amount, be the second energy-storage system power and t _{l1_k}and t _{l2_k}beginning and ending time kth sky load valley period respectively, n ₂it is the life-span of the second energy-storage system;

the environmental benefit of the second energy-storage system, $S_{2\_\mathrm{environment}}^{*}=(\underset{q=1}{\overset{m}{\mathrm{\&Sigma;}}}{R}_{2\_\mathrm{metal}\_q}{\mathrm{\&eta;}}_{2\_\mathrm{metal}\_q}-R_{2\_\mathrm{recycle}})\&CenterDot;{\mathrm{\&eta;}}_{2\_\mathrm{energy}}\&CenterDot;E_2^{*},$ R _{2_metal_q}be the price of metal q, m is the metal species contained by the second energy-storage system, η _{2_metal_q}the content of metal q in the second energy-storage system Unit Weight, R _{2_recycle}the expenditure needed for process Unit Weight second energy-storage system waste material, η _{2_energy}represent the second energy-storage system energy anharmonic ratio;

be the low storage of the second energy-storage system occurred frequently time produce direct benefit, r _{2_out}be the low storage of the second energy-storage system occurred frequently time electrical network export the price of electric energy, R _{2_in}be the low storage of the second energy-storage system occurred frequently time electrical network input electric energy price;

the second energy-storage system power cost and Capacity Cost sum, $S_{2\_P,E}^{*}=(C_{2\_P}\&CenterDot;P_{2\_\mathrm{ESS}}^{*}+C_{2\_E}\&CenterDot;E_2^{*})\&CenterDot;\frac{{\mathrm{\&alpha;}}_2{(1+{\mathrm{\&alpha;}}_2)}^{n_2}}{{(1+{\mathrm{\&alpha;}}_2)}^{n_2}-1},$ C _{2_p}the second energy-storage system unit power cost, C _{2_E}the second energy-storage system unit capacity cost, α ₂it is the second energy-storage system investment yield;

the 1 energy-storage system year safeguarded expenditure, c _{2_m}the 1 energy-storage system unit capacity year safeguarded expenditure;

stored energy capacitance initial value or the optimal value of the second energy-storage system, when optimizing number of times j=0, it is the stored energy capacitance initial value of the second energy-storage system; When optimizing number of times j>0, it is the stored energy capacitance optimal value of the second energy-storage system;

The constraints of the stored energy capacitance optimization object function of described first energy-storage system is E ₁>=0.

3. optimization method according to claim 2, is characterized in that described by optimizing the stored energy capacitance optimal value calculating the first energy-storage system adopt particle group optimizing method.

4. optimization method according to claim 3, is characterized in that described by optimizing the stored energy capacitance optimal value calculating the second energy-storage system adopt particle group optimizing method.