CN110601264B - Multi-energy optimization scheduling method considering absorption capacity of ultra-high-power heat storage electric boiler - Google Patents

Abstract

The multi-energy optimal scheduling method considering the consumption capacity of a super-high-power thermal storage electric boiler belongs to the technical field of multi-energy optimal scheduling. With reference to the existing research results, the present invention starts from the three aspects of economy, environmental protection, and maximizing the consumption of clean energy, and establishes a joint optimization objective function of wind-light-water-thermal power considering the consumption capacity of thermal storage electric boilers. By adding the controllable load of thermal storage electric boilers in the dispatching model, when clean energy such as wind power cannot be absorbed, the excess clean energy can be absorbed as a load. While ensuring the safe and stable operation of the system, it improves the wind power consumption capacity and realizes optimal clean energy dispatching. When heating in winter, after considering the heat storage and heat release capabilities of thermal storage electric boilers, electric heating can not only meet the heating needs in winter, but also reduce the waste of clean energy, which is conducive to the consumption of clean energy such as wind power. The scheduling method of the present invention is suitable for heating season in winter.

Description

Multi-energy optimal scheduling method considering the consumption capacity of ultra-high-power thermal storage electric boilers

technical field

The invention belongs to the technical field of multi-energy optimal dispatching, and in particular relates to a multi-energy optimal dispatching method taking into account the consumption capacity of a super-high-power thermal storage electric boiler.

Background technique

At present, my country's installed capacity of clean energy such as wind, water, and solar energy ranks first in the world. However, with the relative surplus of power supply, the use of clean energy is increasing, and the problem of insufficient consumption capacity has emerged. . Due to the imperfect multi-energy dispatching system of the power system, thermal power units still occupy a dominant position in power generation, which limits the consumption of clean energy and is not conducive to economic benefits and environmental improvement.

Therefore, there is an urgent need for a novel technical solution in the prior art to solve this problem.

Contents of the invention

The technical problem to be solved by the present invention is to provide a multi-energy optimal scheduling method that takes into account the consumption capacity of super-high-power thermal storage electric boilers, which is used to solve the problem of the imperfect multi-energy scheduling system of the power system in the prior art that limits the consumption of clean energy technical issues.

The multi-energy optimal scheduling method considering the consumption capacity of super-high-power thermal storage electric boilers includes the following steps, and the following steps are carried out in sequence,

Step 1: Establish an objective function for the purpose of maximizing the consumption of wind, light and water:

F＝max(P _q /P _{q max} )

In the formula, F is the objective function, P _q is the total amount of clean energy used in a day, and P _{q max} is the total power generation of clean energy in a day;

Among them, P _q =P _F +P _S +P _G

P _{q max} ＝P _Fmax +P _Smax +P _Gmax

In the formula, P _q is the total amount of clean energy used in a day, P _{q max} is the total power generation of clean energy in a day, _PF is the total amount of wind energy used in a day, _PS is the total amount of water energy used in a day, and _PG is The total amount of light energy used in a day, P _Fmax is the total amount of wind power generation in a day, P _Smax is the total amount of water power generation in a day, and P _Gmax is the total amount of light power generation in a day;

Step 2. Incorporate wind power generators, photovoltaic generators, hydroelectric generators and thermal storage electric boilers into the system, and establish a system model;

Step 3: Divide the 24 hours a day according to the set time into scheduling periods, and set model constraints

1) Set the power balance constraints of the whole network as follows:

P _Ht +P _St +P _Lt +P _Ft +P _Gt =P _Dt +P _Rebt

In the formula, P _Ht is the generating power of the thermal power unit in the period t, P _St is the generating power of the hydroelectric generating unit in the period t, P _Lt is the line loss power of the system in the period t, P _Ft is the generating power of the wind turbine in the period t, P _Gt is the power generated by the photovoltaic unit in the period t, P _Dt is the total load of the system in the period t, and P _Rebt is the electric power of the thermal storage electric boiler in the period t;

2) Set the network operation constraints as follows:

为节点b的有功功率，

为节点b的无功功率，V_b,t为节点b的电压，θ_bj,t为节点b的相位，

为电网运行电压的上限、

为电网运行电压的下限，Ψ_l,t为线路l的输电量，

为传输线传输电量上限、

为传输线传输电量下限，Y_bj∠α_bj代表节点导纳矩阵的b行j列的元素，其中Y_bj代表节点b与节点j之间的互导纳，α_bj代表节点b与节点j之间的互导纳角度，θ_bj,t＝θ_b,t-θ_j,t-α_bj，θ_bj,t为时段t内节点b与节点j的电压相角差值，θ_b,t为时段t内节点b的电压相角，θ_j,t为时段t内节点j的电压相角；In the formula, b,j∈I, I is the number of network nodes, t is the scheduling period, P _Hb,t is the active power injected into the thermal power generator set at node b, P _Fb,t is the active power injected into the wind turbine set at node b, P _Sb,t is the active power injected into the hydroelectric generator set at node b, P _Gb,t is the active power injected into the photovoltaic generator set at node b, Q _Hb,t is the reactive power injected into the thermal generator set at node b, Q _Fb,t is the reactive power injected into the wind turbine generator set at node b, Q _Sb,t is the reactive power injected into the hydroelectric generator set at node b, Q _Gb,t is the reactive power injected into the photovoltaic generator set at node b,

is the active power of node b,

is the reactive power of node b, V _b,t is the voltage of node b, θ _bj,t is the phase of node b,

is the upper limit of the grid operating voltage,

is the lower limit of grid operating voltage, Ψ _l,t is the transmission capacity of line l,

The upper limit of the transmission power for the transmission line,

Y _bj ∠α _bj represents the element in row b and column j of the node admittance matrix, where Y _bj represents the mutual admittance between node b and node j, and α _bj represents the value between node b and node j , θ _bj,t = θ _b,t -θ _j,t -α _bj , θ _bj,t is the voltage phase angle difference between node b and node j in period t, θ _b,t is the period The voltage phase angle of node b within t, θ _j,t is the voltage phase angle of node j within period t;

Step 4. Set the constraints of each unit

1) Set constraints for thermal power units

① Thermal power constraints

P _{Ht min} ≤P _Ht ≤P _{Ht max}

In the formula, P _Ht is the generating power of the thermal power unit in period t, P _{Ht min} is the minimum value of the thermal power generating power, and P _{Ht max} is the maximum value of the thermal power generating power;

② thermal power climbing constraints

-r _di Δt≤P _Ht -P _H(t-1) ≤r _ui Δt

In the formula, P _Ht , P _H(t-1) thermal power generation power of the thermal power unit in the t period and (t-1) period, r _ui is the upper limit value of the output change of unit i in the adjacent period, r _di is the lower limit value of output change of unit i in adjacent periods, Δt is the shortest interval between adjacent scheduling periods;

2) Set the constraint conditions of the hydroelectric generator set

① Hydroelectric power constraints

P _Smin ≤ P _St ≤ _{P Smax}

In the formula, P _St is the generating power of the hydroelectric generator set in the period t, P _Smax is the upper limit value of the generating power of the hydropower station, and P _Smin is the lower limit value of the generating power of the hydropower station;

② Constraints on daily traffic points

In the formula: Q _St is the water consumption in time period t, Q _{max s} is the upper limit of daily water consumption, and Q _{min s} is the lower limit of daily water consumption;

3) Set the wind turbine power constraints

0≤P _Ft ≤P _{Ft max}

In the formula, P _Ft is the on-grid power of wind turbines in the period t, and P _{Ft max} is the total amount of wind power generation in the period t;

4) Set the power constraints of photovoltaic units

0≤P _Gt ≤P _{Gt max}

In the formula, P _Gt is the on-grid power of the photovoltaic unit in the period t, and P _{Gt max} is the total amount of photovoltaic power generation in the period t;

5) Set the constraint conditions of heat storage electric boiler

① Power constraints

0≤P _Rebt ≤P _Rebmax

In the formula, P _Rebt is the power consumption of the thermal storage electric boiler in the period t, and P _{Reb max} represents the upper limit of the power of the electric boiler;

②Constraints on heat storage

Q _Rebt ≤ Q _{Reb max}

In the formula: Q _Rebt is the heat stored by the electric boiler, Q _{Reb max} is the maximum stored heat of the heat storage, P _Rebt is the power consumption of the heat storage electric boiler in the period t, Δt is the shortest interval between adjacent dispatching periods, and T is the time interval of the dispatching period total number of segments;

③ Power fluctuation constraints:

为电锅炉相邻调度时段功率变化的上限值，

为电锅炉相邻调度时段功率变化的下限值，P_Rebt为t时段内蓄热电锅炉消耗功率，P_Reb(t-1)为(t-1)时段内蓄热电锅炉消耗功率；In the formula:

is the upper limit value of the power change of the electric boiler in adjacent scheduling periods,

is the lower limit value of the power change of the electric boiler in the adjacent scheduling period, P _Rebt is the power consumption of the thermal storage electric boiler in the period t, and P _Reb(t-1) is the power consumption of the thermal storage electric boiler in the period (t-1);

Step 5. Formulation of wind-light-water-fire multi-energy dispatching plan considering thermal storage electric boiler

1) The node test system is used to arrange thermal power units, hydropower plants, photovoltaic power generation equipment and super-high-power thermal storage electric boilers to form a wind-light-water-thermal power system including thermal storage boilers, and to divide and dispatch 24 hours a day according to the set time time period, the set time is the same as the set time in step 2;

2) Set scene Ⅰ as the wind-light-water-fire combined system without thermal storage electric boiler in extremely cold weather with the lowest temperature of the day lower than -23 ℃, and scene Ⅱ as the extremely cold weather with the lowest temperature of the day lower than -23 ℃ The combined wind-light-water-fire system with heat storage electric boiler, scene III is the wind-light-water-fire combined system without heat storage electric boiler under normal weather when the lowest temperature of the day is between -23°C and 5°C. Ⅳ is the wind-light-water-fire combined system with heat storage boiler in normal weather when the lowest temperature of the day is between -23°C and 5°C.

3) According to the historical meteorological information of more than three years and the corresponding load value and clean energy power generation, the meteorological information of the forecast day is obtained through the weather forecast, and the random forest algorithm is used to predict each dispatching day in each dispatching period under each scenario. Clean energy unit output upper limit and load value;

4) Constrain the heat storage capacity of the heat storage electric boiler in one day through the constraint conditions in step four, obtain the total power consumed by the heat storage electric boiler in one day, and obtain the sum of output of each electric unit according to the power balance constraint of the whole network in step three;

5) The output of each unit must follow the following principles:

① The output of the thermal power unit is less than the sum of the load demand and the grid loss consumption, and it is connected to the grid in the order of photovoltaic generators, hydroelectric generators, and wind turbines;

If the output of the thermal power unit is greater than or equal to the sum of the load demand and the network loss consumption, proceed to step ②;

②The output of the thermal power unit is equal to the sum of the load demand and the network loss consumption, and the system keeps the thermal storage electric boiler in a shutdown state.

The output of the thermal power unit is greater than the sum of the load demand and the network loss consumption, and the thermal storage electric boiler is added to the system as a load to absorb excess clean energy;

③ If there is surplus clean energy under the maximum power operation condition of the thermal storage electric boiler, the use of clean energy should be reduced in the order of wind turbines reducing output until exiting the system, hydroelectric generating sets reducing output until exiting the system, and photovoltaic generating sets reducing output until exiting the system;

④The heat storage capacity of the thermal storage electric boiler reaches the set maximum value during the scheduling day, and the thermal storage electric boiler is shut down within the same day, until the next day, repeat steps ① to ④;

6) According to the objective function established in step 1, under the relevant constraints of step 4) in step 4, through the principle of the output sequence of each unit in step 5) in step 5, use Matlab software to call CPLEX, and the optimal solution obtained is each The output of each unit with the largest consumption of clean energy in the scenario;

7) According to the output of each unit obtained, the power flow analysis of the network is carried out,

According to the network operation constraints and the output of each unit, the voltage of each node and the power transmission between nodes are obtained.

The analysis results show that the voltage of each node and the power transmission between nodes exceed the value range of safe and stable operation of the power grid, delete the output of each unit, and return to step 6) in step 5 to redistribute the output of each unit until the voltage and The power transmission between nodes is within the value range of safe and stable operation of the power grid,

The analysis results show that the voltage of each node and the power transmission between nodes are within the numerical range of safe and stable operation of the power grid, and the results of the output of each unit are output. The output results of each unit output are the largest consumption of clean energy in each scenario of stable operation The output of each unit;

8) The output of each unit with the largest clean energy consumption in each scene of stable operation is obtained, and the maximum consumption of wind, light and water in each scene is obtained through the objective function in step 1.

The power upper limit of the ultra-high power heat storage electric boiler in the step five is 80MW.

The meteorological information in step five includes daily maximum temperature, daily minimum temperature, daily wind level and daily sunshine hours.

Through the above design scheme, the present invention can bring the following beneficial effects:

With reference to the existing research results, the present invention starts from the three aspects of economy, environmental protection, and maximizing the consumption of clean energy, and establishes a wind-light-water-thermal power joint optimization objective function considering the consumption capacity of the thermal storage electric boiler. By adding the controllable load of thermal storage electric boilers into the dispatching model, when clean energy such as wind power cannot be absorbed, the excess clean energy can be absorbed as a load. While ensuring the safe and stable operation of the system, it improves the wind power consumption capacity and realizes optimal clean energy dispatching. When heating in winter, after considering the heat storage and heat release capacity of the thermal storage electric boiler, the electric heating method can not only meet the heating demand in winter, but also reduce the waste of clean energy, which is conducive to the consumption of clean energy such as wind power.

The dispatching method of the present invention is suitable for the heating season in winter, when residents and businesses need to be heated in winter, taking into account the capacity of the ultra-high-power thermal storage electric boiler, and storing the electric energy generated by clean energy power generation in the form of thermal energy when the load is low. Under the premise of ensuring the safe and stable operation of the system by releasing heat energy to supply residents and commercial heating, it not only meets the heating demand in winter, but also absorbs clean energy at a deeper level.

Description of drawings

The present invention will be further described below in conjunction with accompanying drawing and specific embodiment:

Fig. 1 is a network structure diagram of an embodiment of the multi-energy optimal dispatching method in consideration of the consumption capacity of a super-high-power thermal storage electric boiler according to the present invention.

Fig. 2 is a diagram of the load and output under scenario I of the embodiment of the multi-energy optimal dispatching method of the present invention considering the consumption capacity of a super-high-power thermal storage electric boiler.

Fig. 3 is a diagram of the load and output in scenario II of the embodiment of the multi-energy optimal dispatching method of the present invention considering the consumption capacity of the ultra-high-power thermal storage electric boiler.

Fig. 4 is a diagram of the load and output situation under scenario III of the embodiment of the multi-energy optimal dispatching method of the present invention considering the consumption capacity of a super-high-power thermal storage electric boiler.

Fig. 5 is a diagram of the load and output in scenario IV of the embodiment of the multi-energy optimal dispatching method of the present invention, which takes into account the consumption capacity of the ultra-high-power thermal storage electric boiler.

Detailed ways

The multi-energy optimal scheduling method considering the consumption capacity of super-high-power thermal storage electric boilers includes the following steps, and the following steps are carried out in sequence,

Step 1: Establish an objective function for the purpose of maximizing the consumption of wind, light and water. The purpose is to maximize the utilization rate of clean energy.

F＝max(P _q /P _{q max} )

In the formula, F is the objective function, P _q is the total amount of clean energy used in a day, and P _{q max} is the total power generation of clean energy in a day.

Because the purpose of the present invention is to improve the utilization rate of clean energy, the objective function needs to consider the use of clean energy and the overall situation of power generation, and express the utilization rate of clean energy more simply and clearly in the form of proportion. The clean energy considered in the present invention is mainly wind energy, water energy, and light energy, among which wind energy occupies a dominant position. Since the present invention considers wind, light and water three clean energy sources, P _q and P _{q max} are defined as:

P _q ＝P _F +P _S +P _G

P _{q max} ＝P _Fmax +P _Smax +P _Gmax

In the formula, P _q is the total amount of clean energy used in a day, P _{q max} is the total power generation of clean energy in a day, _PF is the total amount of wind energy used in a day, _PS is the total amount of water energy used in a day, and _PG is The total amount of light energy used in a day, P _Fmax is the total amount of wind power generation in a day, P _Smax is the total amount of water power generation in a day, and P _Gmax is the total amount of light power generation in a day;

Step 2. Incorporate wind power generators, photovoltaic generators, hydroelectric generators and thermal storage electric boilers into the system, and establish a system model;

Step 3: Divide the 24 hours a day into scheduling periods according to the set time, and set the model constraints 1) Set the power balance constraints of the entire network

In order to ensure the normal operation of the network, the power of the network at any time needs to meet the power generation equal to the power consumption, so there are:

P _Ht +P _St +P _Lt +P _Ft +P _Gt =P _Dt +P _Rebt

In the formula, P _Ht is the generating power of the thermal power unit in the period t, P _St is the generating power of the hydroelectric generating unit in the period t, P _Lt is the line loss power of the system in the period t, P _Ft is the generating power of the wind turbine in the period t, P _Gt is the power generated by the photovoltaic unit in the period t, P _Dt is the total load of the system in the period t, and P _Rebt is the electric power of the thermal storage electric boiler in the period t;

2) Set network operation constraints

In order to meet the safe operation of the network, the power and voltage of the network need to meet a certain operating range constraint, and within this constraint range, the scheduling of each unit is carried out. The constraints are as follows:

为节点b的有功功率，

为节点b的无功功率，V_b,t为节点b的电压，θ_bj,t为节点b的相位，

为电网运行电压的上限、

为电网运行电压的下限，Ψ_l,t为线路l的输电量，线路l的输电量等于线路l的传输功率乘以输电时间，

为传输线传输电量上限、

为传输线传输电量下限，In the formula, b,j∈I, I is the number of network nodes, t is the scheduling period, P _Hb,t is the active power injected into the thermal power generator set at node b, P _Fb,t is the active power injected into the wind turbine set at node b, P _Sb,t is the active power injected into the hydroelectric generator set at node b, P _Gb,t is the active power injected into the photovoltaic generator set at node b, Q _Hb,t is the reactive power injected into the thermal generator set at node b, Q _Fb,t is the reactive power injected into the wind turbine generator set at node b, Q _Sb,t is the reactive power injected into the hydroelectric generator set at node b, Q _Gb,t is the reactive power injected into the photovoltaic generator set at node b,

is the active power of node b,

is the reactive power of node b, V _b,t is the voltage of node b, θ _bj,t is the phase of node b,

is the upper limit of the grid operating voltage,

is the lower limit of the operating voltage of the power grid, Ψ _l,t is the transmission power of line l, and the transmission power of line l is equal to the transmission power of line l multiplied by the transmission time,

The upper limit of the transmission power for the transmission line,

is the lower limit of the transmission power of the transmission line,

Y _bj ∠α _bj represents the elements of row b and column j of the node admittance matrix, where Y _bj represents the mutual admittance between node b and node j, and α _bj represents the mutual admittance angle between node b and node j , θ _bj,t = θ _b,t -θ _j,t -α _bj , θ _bj,t is the voltage phase angle difference between node b and node j in period t, θ _b,t is the voltage phase angle difference of node b in period t Voltage phase angle, θ _j,t is the voltage phase angle of node j in period t;

Step 4. Set the constraints of each unit

Under the premise of satisfying the above network constraints, in order to ensure the safe and stable operation of each unit during dispatching, each unit also needs to meet its own operating constraints.

1) Set constraints for thermal power units

① Thermal power constraints

The generating power of a thermal power unit has a maximum and minimum limit, too small will damage the unit, and there is an upper limit on the output of the unit, and constraints are needed to limit the output of the unit:

P _{Ht min} ≤P _Ht ≤P _{Ht max}

In the formula, P _Ht is the generating power of the thermal power unit in period t, P _{Ht min} is the minimum value of the thermal power generating power, and P _{Ht max} is the maximum value of the thermal power generating power;

② thermal power climbing constraints

The power of the thermal power unit needs to meet certain constraints. The power of the unit cannot be adjusted quickly in a short period of time. The constraints are as follows:

-r _di Δt≤P _Ht -P _H(t-1) ≤r _ui Δt

In the formula, P _Ht , P _H(t-1) thermal power generation power of the thermal power unit in the t period and (t-1) period, r _ui is the upper limit value of the output change of unit i in the adjacent period, r _di is the lower limit value of output change of unit i in adjacent periods, Δt is the shortest interval between adjacent scheduling periods;

2) Set the constraint conditions of the hydroelectric generator set

① Hydroelectric power constraints

P _Smin ≤ P _St ≤ _{P Smax}

In the formula, P _St is the generating power of the hydroelectric generator set in the period t, P _{S max} is the upper limit value of the generating power of the hydropower station, and P _{S min} is the lower limit value of the generating power of the hydropower station;

② Constraints on daily traffic points

Hydropower stations follow the dispatching arrangement of the superior department to determine the demand for hydropower generation. Therefore, the daily water consumption is stipulated at a certain value.

In the formula: Q _St is the water consumption in time period t, Q _{max s} is the upper limit of daily water consumption, and Q _{min s} is the lower limit of daily water consumption;

3) Set the wind turbine power constraints

0≤PFt≤PFtmax

In the formula, P _Ft is the on-grid power of wind turbines in the period t, and P _{Ft max} is the total amount of wind power generation in the period t;

4) Set the power constraints of photovoltaic units

0≤P _Gt ≤P _{Gt max}

In the formula, P _Gt is the on-grid power of the photovoltaic unit in the period t, and P _{Gt max} is the total amount of photovoltaic power generation in the period t;

5) Set the constraint conditions of heat storage electric boiler

① Power constraints

0≤P _Rebt ≤P _Rebmax

In the formula, P _Rebt is the power consumption of the thermal storage electric boiler in the period t, and P _{Reb max} represents the upper limit of the power of the electric boiler;

②Constraints on heat storage

According to the weather forecast value of the next day, the energy stored in the boiler during the idle period has a certain limit, which can not only ensure the heating demand, but also not waste resources, that is

Q _Rebt ≤ Q _{Reb max}

In the formula: Q _Rebt is the heat stored by the electric boiler, Q _{Reb max} is the maximum stored heat of the heat storage, P _Rebt is the power consumption of the heat storage electric boiler in the period t, Δt is the shortest interval between adjacent dispatching periods, and T is the time interval of the dispatching period total number of segments;

③ Power fluctuation constraints:

为电锅炉相邻调度时段功率变化的上限值，

为电锅炉相邻调度时段功率变化的下限值，P_Rebt为t时段内蓄热电锅炉消耗功率，P_Reb(t-1)为(t-1)时段内蓄热电锅炉消耗功率；In the formula:

is the upper limit value of the power change of the electric boiler in adjacent scheduling periods,

is the lower limit value of the power change of the electric boiler in the adjacent scheduling period, P _Rebt is the power consumption of the thermal storage electric boiler in the period t, and P _Reb(t-1) is the power consumption of the thermal storage electric boiler in the period (t-1);

Step 5. Formulation of wind-light-water-fire multi-energy dispatching plan considering thermal storage electric boiler

1) The node test system is used to arrange thermal power units, hydropower plants, photovoltaic power generation equipment and ultra-high-power thermal storage electric boilers with a power limit of 80MW to form a wind-light-water-thermal power system including thermal storage boilers. Set the time to divide the scheduling period, and the set time is the same as the set time in step 2;

2) Set scene Ⅰ as the wind-light-water-fire combined system without thermal storage electric boiler in extremely cold weather with the lowest temperature of the day lower than -23 ℃, and scene Ⅱ as the extremely cold weather with the lowest temperature of the day lower than -23 ℃ The combined wind-light-water-fire system with heat storage electric boiler, scene III is the wind-light-water-fire combined system without heat storage electric boiler under normal weather when the lowest temperature of the day is between -23°C and 5°C. Ⅳ is the wind-light-water-fire combined system with heat storage boiler in normal weather when the lowest temperature of the day is between -23°C and 5°C.

3) According to the historical weather information of more than three years and the corresponding load value and clean energy power generation, the weather information includes the daily maximum temperature, the daily minimum temperature, the daily wind level and the daily The number of sunshine hours, the meteorological information of the forecast day is obtained through the weather forecast, and the random forest algorithm is used to predict the output upper limit value and load value of each clean energy unit within each dispatch period of each dispatch day under each scenario;

4) Constrain the heat storage capacity of the heat storage electric boiler in one day through the constraint conditions in step four, obtain the total power consumed by the heat storage electric boiler in one day, and obtain the sum of output of each electric unit according to the power balance constraint of the whole network in step three;

5) The output of each unit must follow the following principles:

① The output of the thermal power unit is less than the sum of the load demand and the grid loss consumption, and it is connected to the grid in the order of photovoltaic generators, hydroelectric generators, and wind turbines;

If the output of the thermal power unit is greater than or equal to the sum of the load demand and the network loss consumption, proceed to step ②;

②The output of the thermal power unit is equal to the sum of the load demand and the network loss consumption, and the system keeps the thermal storage electric boiler in a shutdown state.

The output of the thermal power unit is greater than the sum of the load demand and the network loss consumption, and the thermal storage electric boiler is added to the system as a load to absorb excess clean energy;

③ If there is surplus clean energy under the maximum power operation condition of the thermal storage electric boiler, the use of clean energy should be reduced in the order of wind turbines reducing output until exiting the system, hydroelectric generating sets reducing output until exiting the system, and photovoltaic generating sets reducing output until exiting the system;

④The heat storage capacity of the thermal storage electric boiler reaches the set maximum value during the scheduling day, and the thermal storage electric boiler is shut down within the same day, until the next day, repeat steps ① to ④;

6) According to the objective function established in step 1, under the relevant constraints of step 4) in step 4, through the principle of the output order of each unit in step 5) in step 5, use Matlab software to call CPLEX, CPLEX can solve complex business problems It is expressed as a Mathematic Programming model, and the optimal solution of the model can be obtained. The optimal solution of the model is the output of each unit with the largest amount of clean energy consumption in each scenario;

7) Perform power flow analysis of the network with the output of each unit obtained,

According to the network operation constraints and unit output (that is, unit power), the voltage of each node is solved, and the power transmission between each node is solved at the same time. The power transmission of the line is equal to the transmission power of the line multiplied by the power transmission time.

If the analysis results show that the voltage of each node and the power transmission between nodes exceed the value range for the safe and stable operation of the power grid, delete the output of each unit, and return to step 6) in step 5 to redistribute the output of each unit until the voltage of each node The power transmission between nodes and nodes is within the value range of safe and stable operation of the power grid;

If the analysis results show that the voltage of each node and the power transmission between nodes are within the numerical range of safe and stable operation of the power grid, output the results of the output of each unit, and the output of each unit output is the largest consumption of clean energy in each scenario of stable operation The output of each unit;

8) The output of each unit with the largest consumption of clean energy in each scenario of stable operation is used to obtain the maximum consumption of wind, light and water in each scenario through the objective function in step 1.

Example:

Adopt IEEE24 node test system, arrange one thermal power unit with installed capacity of 455MW, 455MW, 130MW and 130MW, wind farm with installed capacity of 210MW and 270MW, hydropower plant with 100MW, photovoltaic power generation equipment with total installed capacity of 50MW and The 80MW ultra-high-power thermal storage electric boiler forms a wind-light-water-thermal power system as shown in Figure 1. Numbers 1 to 24 in the figure are node numbers. The output of each unit is analyzed through four different scenarios. It is stipulated that scenario Ⅰ is a wind-light-water-fire combined system without thermal storage electric boiler in extremely cold weather, and scenario Ⅱ is a wind-light-water-fire system with thermal storage electric boiler in extremely cold weather. Light-water-fire combined system, scene III is the wind-light-water-fire combined system without heat storage electric boiler under normal weather, scene IV is wind-light-water-fire combined system with heat storage electric boiler under normal weather .

1) Objective function:

F＝max(P _q /P _{q max} )

In the formula, F is the objective function, P _q is the total amount of clean energy used in a day, and P _{q max} is the total power generation of clean energy in a day;

The purpose is to maximize the utilization rate of clean energy.

Since the present invention considers wind, light and water three clean energy sources, P _q and P _{q max} are defined as:

P _q ＝P _F +P _S +P _G

P _{q max} ＝P _Fmax +P _Smax +P _Gmax

In the formula, P _q is the total amount of clean energy used in a day, P _{q max} is the total power generation of clean energy in a day, _PF is the total amount of wind energy used in a day, _PS is the total amount of water energy used in a day, and _PG is The total amount of light energy used in a day, P _Fmax is the total amount of wind power generation in a day, P _Smax is the total amount of water power generation in a day, and _PGmax is the total amount of solar power generation in a day.

2) Firstly, divide the 24 hours a day into 96 scheduling segments according to 15 minutes as a time period.

See steps 3 and 4 for constraints.

3) Under the premise of satisfying the constraints of step 2) in step 3, according to the power balance of the whole network and the objective function, the output of each unit in the four scenarios can be calculated respectively. See Figure 2-Figure 5 respectively. The utilization rate of wind power is given by the following table:

Table 1 Unit output and clean energy utilization rate (including network loss)

Analyzing the above table, because the goal is to maximize the consumption of clean energy, after considering the consumption capacity of the thermal storage electric boiler, the maximum consumption of wind power output is achieved. Scenarios II and IV both consider the consumption capacity of thermal storage electric boilers, so the utilization rate of clean energy is greater than that of scenarios without thermal storage electric boilers in scenarios I and III. In addition, the demand for heat load in extremely cold weather is greater, so the heat demand is also higher, the boiler needs more electricity, and the clean energy consumption effect is better. Comparing Scenario II and Scenario IV, we can know that storage in extremely cold weather Thermal power boilers are better at absorbing clean energy. And because it uses redundant clean energy, there is almost no cost, so it also brings certain economic benefits at the same time.

Claims (3)

1. The multi-energy optimization scheduling method considering the absorption capacity of the ultra-high-power heat storage electric boiler is characterized by comprising the following steps of: comprises the following steps which are sequentially carried out,

the method comprises the following steps: an objective function is established with the aim of maximizing three clean energy sources of wind, light and water:

F＝max(P _q /P _qmax )

wherein F is an objective function, P _q Total amount of clean energy used in one day, P _qmax The total generated energy of clean energy in one day;

wherein, P _q ＝P _F +P _S +P _G

P _qmax ＝P _Fmax +P _Smax +P _Gmax

In the formula, P _q For the total amount of clean energy used in a day, P _qmax Is clear in one dayClean energy total power generation, P _F For the total amount of wind energy used in a day, P _S For the total amount of water energy used in a day, P _G For the total amount of light energy used in a day, P _Fmax Total amount of wind power generation in one day, P _Smax For the total amount of water energy generated in a day, P _Gmax The total amount of light energy power generation in one day;

step two, a wind generating set, a photovoltaic generating set, a hydroelectric generating set and a heat storage electric boiler are counted into a system, and a system model is established;

step three, dividing 24 hours in the whole day into scheduling time intervals according to set time, and setting model constraint conditions

1) Setting the constraint conditions of the power balance of the whole network as follows:

P _Ht +P _St +P _Lt +P _Ft +P _Gt ＝P _Dt +P _Rebt

in the formula, P _Ht For the power generation of the thermal generator set within the time period t, P _St Is the generating power of the hydroelectric generating set within the time period t, P _Lt Is the system line loss power, P, in time period t _Ft Is the generated power P of the wind generating set in the time period t _Gt Is the generated power P of the photovoltaic unit in the time period t _Dt Is the total system load, P, in time period t _Rebt The electric power is used for the heat storage electric boiler in the time period t;

2) The network operation constraints are set as follows:

in the formula, b, j belongs to I, I is the number of network nodes, t is the scheduling time interval, P _Hb,t Injecting active power P of thermal generator set for node b _Fb,t Injecting wind turbine generator system active power P as node b _Sb,t Injection of hydroelectric generating set active power, P, for node b _Gb,t Injected photovoltaic generator set active power, Q, for node b _Hb,t Injecting reactive power, Q, of thermal generator set for node b _Fb,t Injecting reactive power, Q, of a wind turbine into node b _Sb,t Injecting hydroelectric generating set reactive power, Q, for node b _Gb,t The reactive power of the photovoltaic generator set is injected into the node b,

is the active power of the node b and,

reactive power of node b, V _b,t Is the voltage of node b, θ _bj,t Is the phase of the node b and,

is the upper limit of the power grid operating voltage,

For the lower limit of the network operating voltage, Ψ _l,t In order to be able to transmit the electrical power of the line l,

the upper limit of the transmission power of the transmission line,

For transmission of lower limit of electric quantity, Y, by transmission line _bj ∠α _bj Elements representing b rows and j columns of the nodal admittance matrix, where Y _bj Representing the mutual admittance, α, between node b and node j _bj Representing the transadmittance angle, θ, between node b and node j _bj,t ＝θ _b,t -θ _j,t -α _bj ，θ _bj,t Is the difference between the phase angles of the voltages at node b and node j in time t, θ _b,t Is the phase angle of the voltage at node b, θ, during time period t _j,t Is the voltage phase angle of the node j in the time period t;

step four, setting self constraint conditions of each unit

1) Setting constraint conditions of thermal power generating unit

(1) Thermal power constraints

P _Htmin ≤P _Ht ≤P _Htmax

In the formula, P _Ht Generating power P for thermal power generating unit in t period _Htmin Is the minimum value, P, of the generating power of the thermal power generating unit _Htmax The maximum value of the generated power of the thermal power generating unit is obtained;

(2) thermal power climbing restraint

-r _di Δt≤P _Ht -P _H(t-1) ≤r _ui Δt

In the formula, P _Ht 、P _H(t-1) Generating power r of thermal power generating unit in t time period and (t-1) time period _ui The upper limit value r of the output variation of the unit i in the adjacent time period _di The output variation lower limit value of the unit i in the adjacent time interval is delta t, and the delta t is the shortest adjacent scheduling time interval;

2) Setting constraints of hydroelectric generating set

(1) Hydroelectric power constraint

P _Smin ≤P _St ≤P _Smax

In the formula, P _St Is the generating power of the hydroelectric generating set in the time period of t, P _Smax Upper limit value, P, of generated power for hydropower station _Smin The lower limit value of the generating power of the hydropower station;

(2) daily flow integral constraint

In the formula: q _St Is the amount of water used in time period t, Q _{max s} Is the upper limit of daily water consumption, Q _{min s} The lower limit value of the daily water consumption;

3) Setting power constraint conditions of wind generating set

0≤P _Ft ≤P _Ftmax

In the formula, P _Ft The power P of the wind generating set on the network in the time period of t _Ftmax The total amount of wind power generation in the t period;

4) Setting power constraint conditions of photovoltaic unit

0≤P _Gt ≤P _Gtmax

In the formula, P _Gt Is the power of the photovoltaic unit on the network in the t period, P _Gtmax The total photovoltaic power generation amount in a period t;

5) Setting constraint conditions of heat storage electric boiler

(1) Power constraint

0≤P _Rebt ≤P _Rebmax

In the formula, P _Rebt For the power consumption of the heat-accumulating electric boiler in the period of t, P _Rebmax Representing the upper power limit of the electric boiler;

(2) restraint of heat storage

Q _Rebt ≤Q _Rebmax

In the formula: q _Rebt Heat stored for electric boilers, Q _Rebmax For maximum heat storage capacity of heat storage, P _Rebt The power consumption of the heat accumulation electric boiler in a T period is shown, delta T is the shortest adjacent scheduling period interval, and T is the total number of the scheduling periods;

(3) and (3) power fluctuation constraint:

in the formula:

is the upper limit value of the power change of the adjacent scheduling period of the electric boiler,

for a lower limit value, P, of power variation of adjacent scheduling periods of the electric boiler _Rebt For the power consumption of the heat-accumulating electric boiler in the period of t, P _Reb(t-1) The power consumption of the heat accumulation electric boiler in the (t-1) time period;

step five, designing a wind-light-water-fire multi-energy scheduling scheme of the heat storage electric boiler

1) A thermal power generating unit, a hydraulic power plant, photovoltaic power generation equipment and an ultra-high-power heat-storage electric boiler are arranged by adopting a node testing system to form a wind-light-water-thermal power system containing the heat-storage electric boiler, and 24 hours a day is divided into scheduling time intervals according to set time, wherein the set time is the same as the set time in the second step;

2) Setting a scene I as a wind-light-water-fire combined system without a heat storage electric boiler in the extremely cold weather with the lowest temperature lower than-23 ℃ in the same day, setting a scene II as a wind-light-water-fire combined system without a heat storage electric boiler in the extremely cold weather with the lowest temperature lower than-23 ℃ in the same day, setting a scene III as a wind-light-water-fire combined system without a heat storage electric boiler in the ordinary weather with the lowest temperature between-23 ℃ and 5 ℃ in the same day, setting a scene IV as a wind-light-water-fire combined system with a heat storage electric boiler in the ordinary weather with the lowest temperature between-23 ℃ and 5 ℃ in the same day,

3) Acquiring weather information of a forecast day through weather forecast according to historical weather information of more than three years, corresponding load values and clean energy power generation capacity, and forecasting the output upper limit value and the load value of each clean energy unit in each dispatching time period of a dispatching day under each scene by using a random forest algorithm;

4) Restraining the heat storage quantity of the heat storage electric boiler in one day through the restraint conditions in the fourth step to obtain the total power required to be consumed by the heat storage electric boiler in one day, and obtaining the total output of each electric machine set according to the full-grid power balance restraint in the third step;

5) The output of each unit is required to be carried out according to the following principle in sequence:

(1) the output of the thermal power generating unit is smaller than the sum of the load demand and the grid loss consumption, and the grid connection is carried out according to the sequence of the photovoltaic generating set, the hydroelectric generating set and the wind generating set;

the output of the thermal power generating unit is greater than or equal to the sum of the load demand and the grid loss consumption, and the step (2) is carried out;

(2) the output of the thermal power generating unit is equal to the sum of the load demand and the grid loss consumption, the system keeps the heat storage electric boiler in a shutdown state,

the output of the thermal power generating unit is greater than the sum of the load demand and the grid loss, and the heat storage electric boiler is used as a load adding system to operate, so that surplus clean energy is consumed;

(3) the method comprises the following steps that (1) clean energy is remained under the maximum power operation condition of the heat storage electric boiler, the wind generating set reduces output until the system exits, the hydraulic generating set reduces output until the system exits, and the photovoltaic generating set reduces output until the system exits, so that the utilization of the clean energy is reduced;

(4) the heat storage amount of the heat storage electric boiler reaches a set maximum value in a scheduling day, the heat storage electric boiler stops running in the same day, and the steps (1) to (4) are repeated until the next day;

6) Calling CPLEX by utilizing Matlab software under the relevant constraint of the step 4) in the step five according to the target function established in the step one and under the output sequence principle of each unit in the step four in the step 5), and obtaining the optimal solution as the output of each unit with the maximum clean energy consumption in each scene;

7) According to the obtained output of each unit, the power flow analysis of the network is carried out,

obtaining the voltage of each node and the transmission quantity among the nodes according to the network operation constraint condition and the output of each unit,

the analysis result shows that the voltage of each node and the transmission quantity among the nodes exceed the numerical range of safe and stable operation of the power grid, the output of each unit is deleted, the output of each unit is redistributed in the step 6) in the step five until the voltage of each node and the transmission quantity among the nodes are in the numerical range of safe and stable operation of the power grid,

the analysis result shows that the voltage of each node and the power transmission quantity among the nodes are in the numerical range of safe and stable operation of the power grid, the output result of each unit is output, and the output result of each unit is the output of each unit with the largest clean energy consumption under each scene of stable operation;

8) And (4) obtaining the maximum consumption of the three clean energy sources of wind, light and water in each scene through the objective function in the step one according to the obtained output of each unit with the maximum consumption of the clean energy sources in each scene of stable operation.

2. The multi-energy optimal scheduling method considering the absorption capacity of the ultra-high-power heat-storage electric boiler, as claimed in claim 1, is characterized in that: and in the fifth step, the upper power limit of the ultra-high power heat storage electric boiler is 80MW.

3. The multi-energy optimization scheduling method considering the absorption capacity of the ultra-high-power heat storage electric boiler, as claimed in claim 1, is characterized in that: the meteorological information in the fifth step comprises daily maximum temperature, daily minimum temperature, daily wind level and daily sunshine hours.

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