CN113111584A - Building storage battery configuration method considering charging load of electric automobile - Google Patents

Building storage battery configuration method considering charging load of electric automobile Download PDF

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CN113111584A
CN113111584A CN202110404534.0A CN202110404534A CN113111584A CN 113111584 A CN113111584 A CN 113111584A CN 202110404534 A CN202110404534 A CN 202110404534A CN 113111584 A CN113111584 A CN 113111584A
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building
load
storage battery
battery
power
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丁研
鄢睿
王翘楚
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Tianjin University
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    • G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
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    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
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Abstract

The invention discloses a building storage battery configuration method considering charging load of an electric automobile. The method comprises the following steps of 1) establishing a total building power load model comprising an electric automobile and a building storage battery according to existing building operation data; step 2) aiming at the total load model of the building, constructing various optimization scenes according to different actual requirements of the building; and 3) establishing a comprehensive evaluation calculation method, and determining an optimal battery configuration scheme according to the pareto frontier curve. The invention provides a building storage battery configuration method considering electric vehicle load, which considers the advantages of quick response, continuous power transmission and the like of a building storage battery and configures the storage battery for a building with the electric vehicle charging load so as to optimize the running condition of the existing system.

Description

Building storage battery configuration method considering charging load of electric automobile
Technical Field
The invention relates to the field of building energy conservation, in particular to a building storage battery configuration method considering the charging load of an electric automobile.
Background
In the management of flexible loads, a storage battery has been widely used as one of energy storage means, because it has advantages such as quick response and continuous power transmission. The building storage battery can effectively improve the running state or running cost of the power grid by being matched with air conditioner load management or electric vehicle management, and the effect of the strategy can be further improved if the storage battery is configured on the basis of the existing strategy.
One of the key issues in designing and installing a battery energy storage system is how to optimally size the capacity of the battery to balance the tradeoff between the technical improvement and the added overall cost of the battery. At present, electric vehicles and charging piles are still in the development stage and are not widely popularized, so that charging loads of the electric vehicles are considered together in few buildings at present, and research on the configuration scheme of a storage battery of the buildings to optimize the existing operation condition is almost blank. Therefore, it is necessary to provide a method for configuring a building storage battery considering the charging load of an electric vehicle, so as to provide a reference for the equipment configuration planning of a building with an electric vehicle charging pile.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a method for configuring a building storage battery by considering the charging load of an electric automobile. The technical scheme adopted by the invention comprises the following steps:
step 1: according to existing operation data of a building, a building total power load model comprising an electric automobile and a building storage battery is established, and the method specifically comprises the following steps:
firstly, selecting a typical summer working day of a building, and carrying out field measurement on the following data: (1) hourly power consumption P of ground source heat pump unitHVAC(ii) a (2) Charging power of each charging pile time by time; (3) Hourly usage of office equipment.
Charging load P of electric automobileEVIs calculated as follows:
Figure BDA0003021777770000011
in the formula, n is the number of charging piles; pEV,iCharging power, kW for the ith charging pile.
The time-by-time load calculation formula of the office equipment and the lighting load is as follows:
Plight＝klight·M·Rlight (2)
Pequip＝kequip·M·Requip (3)
in the formula, PlightAnd PequipThe power load of the lighting and the equipment is kW; k is a radical oflightAnd kequipLoad density, kW/m, of lighting and equipment, respectively2(ii) a M is the building area, M2；RlightAnd RequipRespectively, the time-by-time usage of the lighting and the device.
The invention provides a building with a storage battery, so that the total electricity load of the building after the storage battery is added can consider the charge and discharge load of the storage battery besides the air-conditioning load, the charging load of an electric automobile, the lighting load and the equipment load. Therefore, the model of the total electrical load of the building including the charging load of the electric vehicle and the storage battery is as follows:
Pt＝PHVAC+PEV+Plight+Pequip-Pbat (4)
in the formula, PtThe total electric load of the building is kW; pbatThe power is the charging and discharging power of the storage battery, kW, discharging is positive, and charging is negative.
Step 2: aiming at the total load model of the building, the system operation economy and the power grid friendliness are achieved
Performing multi-objective optimization, specifically:
(1) determining an objective function
The purpose of configuring the building storage battery is to utilize the energy storage characteristic of the building storage battery to achieve the purposes of peak clipping, valley filling, load transfer and more stable operation of a power grid. While the cost is also a concern because the addition of batteries increases the cost of the configuration. It is therefore essential to minimize the total cost of the sum of the operating cost and the battery configuration cost at the time-of-use electricity price
One of the optimization objectives, with grid friendliness as the second optimization objective, can be expressed as:
Figure BDA0003021777770000021
Figure BDA0003021777770000022
Figure BDA0003021777770000023
in the formula, PmaxThe maximum charge and discharge power of the storage battery is kW; emaxIs the maximum energy capacity of the battery, kWh; alpha is alphatThe time-of-use electricity price at the time t, kWh/yuan; alpha is alpha1，α2The energy storage cost parameters are respectively 0.0709 and 0.0605, yuan/(kW.h); ptThe total load at the t moment of the system is kW; paverageIs the average time-to-time load in a day, kW.
(2) Determining optimization variables
The hourly charging and discharging power of the battery is an important factor influencing the configuration parameters of the battery and can directly influence the operation effect of the building system, so the hourly charging and discharging power of the battery is determined as an optimized variable, and the aim of improving the operation effect of the original building system is fulfilled by strategies of night power storage and daytime discharging.
(3) Determining constraints
Due to the addition of the battery, constraints imposed by the operating characteristics of the battery itself need to be taken into account. The hourly charge and discharge power of the storage battery cannot exceed a limit value, and the hourly energy of the storage battery cannot be lower than 0.2 of the total energy and cannot exceed 0.8 of the total capacity due to the limitation of the capacity of the storage battery and the consideration of safety:
-Pmax≤Pbat≤Pmax (8)
0.2Emax≤Et≤0.8Emax(9) in order to ensure the continuous charge and discharge margin, the storage battery needs to keep the charge and discharge amount balanced in one period:
Figure BDA0003021777770000031
Figure BDA0003021777770000032
wherein E istkWh for hourly battery energy; e0Is the initial energy of the battery, assumed to be 0.5Emax，kWh。
And after the function is constructed according to the steps, calculating the function by adopting a multi-target genetic optimization algorithm.
And step 3: establishing a comprehensive evaluation calculation method, and determining an optimal battery configuration scheme according to the pareto front curve, wherein the method specifically comprises the following steps:
and (3) obtaining multiple groups of optimal solutions through calculation of the multi-target genetic algorithm in the step (2), and drawing pareto front curves of the solutions according to two dimensions of power grid friendliness and operation economy. In order to balance the influence of the configured batteries on the power grid friendliness and the total cost, aiming at each pareto frontier, the following formula is adopted to calculate each point on the frontier:
Figure BDA0003021777770000033
in the formula: OverallScoreiThe comprehensive score of the ith scheme on the pareto frontier of a strategy is obtained;feeitotal cost for the ith configuration scenario, Yuan; fe (fe)originalThe original total cost of the storage battery is not configured; GFiIs the power grid friendliness of the ith scheme, kW; GForiginalThe method is the original power grid friendliness without a storage battery, kW.
Since the invention aims to add a storage battery on the basis of the existing operation strategy to improve the operation effect, the two components of the formula (12) respectively improve the operation cost and the power grid friendliness. The larger the improvement degree is, the better the improvement degree is, the scheme with the maximum comprehensive evaluation score in all schemes is selected, and the battery configuration parameters in the scheme are taken as the optimal battery configuration scheme.
The invention has the advantages of
A building storage battery configuration method considering electric vehicle charging is provided, a building total power load model is established for a building with an electric vehicle charging load, the configuration effect of batteries is optimized from two aspects of economy and power grid friendliness, a comprehensive evaluation calculation method is established, an optimal battery configuration scheme is selected, and reference is provided for similar buildings to perform equipment configuration. And the operation condition of the building can be effectively improved after the battery is configured according to the method.
Drawings
FIG. 1 is a technical flow chart of the present invention;
FIG. 2 is a graph of electrical loads of a building, except for a battery;
FIG. 3 is a pareto frontier curve chart of multi-objective optimization after a certain building is additionally provided with a storage battery;
fig. 4 is a time-by-time charge/discharge load curve diagram of a storage battery of a certain building.
Detailed Description
The invention is further illustrated by the following specific examples and the accompanying drawings. The examples are for the purpose of better understanding the present invention by those skilled in the art and are not intended to limit the present invention in any way.
As shown in fig. 1, the present embodiment provides a method for optimizing the day ahead of the air conditioner and electric vehicle charging load joint scheduling, including the following steps:
step 1: according to existing operation data of a building, a building total power load model comprising an electric automobile and a building storage battery is established, and the method specifically comprises the following steps:
in the example, first, a typical summer working day of the building is selected, and the following data are measured on site:
(1) hourly power consumption P of ground source heat pump unitHVAC(ii) a (2) Charging power of each charging pile time by time; (3) hourly usage of office equipment.
Charging load P of electric automobileEVIs calculated as follows:
Figure BDA0003021777770000041
in the formula, n is the number of charging piles; pEV,iCharging power, kW for the ith charging pile.
The time-by-time load calculation formula of the office equipment and the lighting load is as follows:
Plight＝klight·M·Rlight (14)
Pequip＝kequip·M·Requip (15)
the total electricity load curve before the building is provided with the storage battery is shown in figure 2 through the results acquired and calculated in the steps.
The invention provides a building with a storage battery, so that a building total electric load model comprising an electric automobile charging load and the storage battery has the following formula:
Pt＝PHVAC+PEV+Plight+Pequip-Pbat (16)
step 2: aiming at the total building load model, multi-objective optimization is carried out from two aspects of system operation economy and power grid friendliness, and the method specifically comprises the following steps:
(1) determining an objective function
In an example, the total cost of minimizing the sum of the operating cost and the battery configuration cost at the time of use electricity price is
One of the optimization objectives herein, with grid friendliness as the second optimization objective, can be expressed as:
Figure BDA0003021777770000051
Figure BDA0003021777770000052
Figure BDA0003021777770000053
(2) determining optimization variables
The hourly charging and discharging power of the battery is an important factor influencing the configuration parameters of the battery and can directly influence the operation effect of the building system, so the hourly charging and discharging power of the battery is determined as an optimized variable, and the aim of improving the operation effect of the original building system is fulfilled by strategies of night power storage and daytime discharging.
(3) Determining constraints
In the example, constraints imposed by the operating characteristics of the battery itself are taken into account by the incorporation of the battery. The hourly charge and discharge power of the storage battery cannot exceed a limit value, and the hourly energy of the storage battery cannot be lower than 0.2 of the total energy and cannot exceed 0.8 of the total capacity due to the limitation of the capacity of the storage battery and the consideration of safety:
-Pmax≤Pbat≤Pmax (20)
0.2Emax≤Et≤0.8Emax (21)
in order to ensure the continuous charge and discharge margin, the storage battery needs to keep the charge and discharge amount balanced in one period:
Figure BDA0003021777770000054
Figure BDA0003021777770000055
after the function is constructed according to the steps, the function is calculated by adopting a multi-target genetic optimization algorithm, and the obtained pareto front curve is shown in fig. 3.
And step 3: determining an optimal battery configuration scheme according to the pareto front curve, which specifically comprises the following steps:
and (3) obtaining multiple groups of optimal solutions through calculation of the multi-target genetic algorithm in the step (2), and drawing pareto front curves of the solutions according to two dimensions of power grid friendliness and operation economy. In order to balance the influence of the configured batteries on the power grid friendliness and the total cost, aiming at each pareto frontier, the following formula is adopted to calculate each point on the frontier:
Figure BDA0003021777770000056
in the example, all the schemes increase the cost due to the configuration of the battery, the comprehensive evaluation score in all the schemes is maximum-0.01493 according to the calculation result, the battery configuration parameter in the scheme is the optimal battery configuration scheme, and the configuration parameter is Pmax＝8.67kW，EmaxThe hourly charge-discharge power was as shown in fig. 4, at 32.83 kWh.

Claims (4)

1. A method for checking the rationality of design parameters of disturbance loads in a building is characterized by comprising the following steps:
1) according to existing building operation data, a building total power load model comprising an electric automobile and a building storage battery is established: the method comprises the steps of carrying out field measurement on a building with an electric automobile charging pile, collecting space-time modulation load, electric automobile charging load, illumination and equipment load of the building, obtaining an existing total power load curve, and adding a building storage battery on the basis to obtain a building total power load model containing the electric automobile charging load and the storage battery.
2) Aiming at the total building load model, multi-objective optimization is carried out from two aspects of system operation economy and power grid friendliness: and (3) adopting a multi-objective genetic optimization algorithm, taking the power grid friendliness and the operation economy of the system as objective functions, taking the time-by-time charging and discharging load of the battery as optimization variables, determining constraint conditions according to actual conditions, and performing optimization calculation on the day-ahead prediction model.
3) Establishing a comprehensive evaluation calculation method, and determining an optimal battery configuration scheme according to the pareto front curve: and establishing an evaluation calculation method considering both the operation economy and the power grid friendliness, finding out a score optimal point on the pareto front edge, determining the score optimal point as a configuration scheme with the best comprehensive performance, and obtaining the battery configuration parameters at the moment as references for configuring the battery.
2. The computing method of claim 1, wherein: the method comprises the following steps of 1) establishing a building total power load model containing the electric automobile and a building storage battery according to existing building operation data, and specifically comprises the following steps:
firstly, selecting a typical summer working day (more than or equal to 15) of a plurality of buildings, and carrying out field measurement on the following data: (1) hourly power consumption P of ground source heat pump unitHVAC(ii) a (2) Charging power of each charging pile time by time; (3) hourly usage of office equipment. And calculating the time-by-time average values of the data respectively to be used as various electricity consumption data of the building on a typical summer working day.
Charging load P of electric automobileEVIs calculated as follows:
Figure FDA0003021777760000011
in the formula, n is the number of charging piles; pEV，iCharging power, kW for the ith charging pile.
The time-by-time load calculation formula of the office equipment and the lighting load is as follows:
Plight＝klight·M·Rlight (2)
Pequip＝kequip·M·Requip (3)
in the formula, PlightAnd PequipThe power load of the lighting and the equipment is kW; k is a radical oflightAnd kequipLoad density, kW/m, of lighting and equipment, respectively2(ii) a M is the building area, M2；RlightAnd RequipRespectively, the time-by-time usage of the lighting and the device.
The invention provides a building with a storage battery, so that the total electricity load of the building after the storage battery is added can consider the charge and discharge load of the storage battery besides the air-conditioning load, the charging load of an electric automobile, the lighting load and the equipment load. Therefore, the model of the total electrical load of the building including the charging load of the electric vehicle and the storage battery is as follows:
Pt＝PHVAC+PEV+Plight+Pequip-Pbat (4)
in the formula, PtThe total electric load of the building is kW; pbatThe power is the charging and discharging power of the storage battery, kW, discharging is positive, and charging is negative.
3. The computing method of claim 2, wherein: the step 2) is to perform multi-objective optimization from two aspects of system operation economy and power grid friendliness aiming at the total building load model, and specifically comprises the following steps:
(1) determining an objective function
The purpose of configuring the building storage battery is to utilize the energy storage characteristic of the building storage battery to achieve the purposes of peak clipping, valley filling, load transfer and more stable operation of a power grid. While the cost is also a concern because the addition of batteries increases the cost of the configuration. Therefore, the total cost of minimizing the sum of the operation cost and the battery configuration cost at the time-of-use electricity price is one of the optimization targets in the text, and the grid friendliness is the second optimization target, which can be expressed as:
Figure FDA0003021777760000021
Figure FDA0003021777760000022
Figure FDA0003021777760000023
in the formula, PmaxThe maximum charge and discharge power of the storage battery is kW; emaxIs the maximum energy capacity of the battery, kWh; alpha is alphatThe time-of-use electricity price at the time t, kWh/yuan; alpha is alpha1，α2The energy storage cost parameters are respectively 0.0709 and 0.0605, yuan/(kW.h); ptThe total load at the t moment of the system is kW; paverageIs the average time-to-time load in a day, kW.
(2) Determining optimization variables
The hourly charging and discharging power of the battery is an important factor influencing the configuration parameters of the battery and can directly influence the operation effect of the building system, so the hourly charging and discharging power of the battery is determined as an optimized variable, and the aim of improving the operation effect of the original building system is fulfilled by strategies of night power storage and daytime discharging.
(3) Determining constraints
Due to the addition of the battery, constraints imposed by the operating characteristics of the battery itself need to be taken into account. The hourly charge and discharge power of the storage battery cannot exceed a limit value, and the hourly energy of the storage battery cannot be lower than 0.2 of the total energy and cannot exceed 0.8 of the total capacity due to the limitation of the capacity of the storage battery and the consideration of safety:
-Pmax≤Pbat≤Pmax (8)
0.2Emax≤Et≤0.8Emax (9)
in order to ensure the continuous charge and discharge margin, the storage battery needs to keep the charge and discharge amount balanced in one period:
Figure FDA0003021777760000031
Figure FDA0003021777760000032
wherein E istkWh for hourly battery energy; e0Is the initial energy of the battery, assumed to be 0.5Emax，kWh。
And after the function is constructed according to the steps, calculating the function by adopting a multi-target genetic optimization algorithm.
4. The computing method of claim 1, wherein: the step 3) of establishing a comprehensive evaluation calculation method, and determining an optimal battery configuration scheme according to the pareto frontier curve specifically comprises the following steps:
and (3) obtaining multiple groups of optimal solutions through calculation of the multi-target genetic algorithm in the step (2), and drawing pareto front curves of the solutions according to two dimensions of power grid friendliness and operation economy. In order to balance the influence of the configured batteries on the power grid friendliness and the total cost, aiming at each pareto frontier, the following formula is adopted to calculate each point on the frontier:
Figure FDA0003021777760000033
in the formula: OverallScoreiThe comprehensive score of the ith scheme on the pareto frontier of a strategy is obtained; fe (fe)iTotal cost for the ith configuration scenario, Yuan; fe (fe)originalThe original total cost of the storage battery is not configured; GFiIs the power grid friendliness of the ith scheme, kW; GForiginalThe method is the original power grid friendliness without a storage battery, kW.
Since the invention aims to add a storage battery on the basis of the existing operation strategy to improve the operation effect, the two components of the formula (12) respectively improve the operation cost and the power grid friendliness. The larger the improvement degree is, the better the improvement degree is, the scheme with the maximum comprehensive evaluation score in all schemes is selected, and the battery configuration parameters in the scheme are taken as the optimal battery configuration scheme.
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