WO2022126950A1 - Method and system for controlling demand response of building central air conditioning - Google Patents

Abstract

Provided are a method and system for controlling the demand response of building central air conditioning: obtaining basic data and environmental data of a building where central air conditioning is located; receiving a demand response instruction from an electrical grid, and obtaining a demand response time; according to the obtained data, a user temperature comfort range, and a user-acceptable temperature adjustment range within a demand response time, obtaining a plurality of pre-cooling policies and a plurality of policies for shutting down some cooling units; removing the pre-cooling policies in which the pre-cooling utility period is shorter than the response time length of the electrical grid instruction; solving for a remaining policy by using the objective of minimizing the loss of comfort or maximizing the gain, to obtain a final demand response control policy.

Description

Demand response control method and system for building central air conditioning technical field

The present disclosure relates to the technical field of power demand response, and in particular, to a demand response control method and system for a central air conditioner in a building.

Background technique

The statements in this section merely provide background related to the present disclosure and do not necessarily constitute prior art.

According to the survey, building energy consumption accounts for as much as 40% of global energy consumption today, and by 2050, the proportion of building energy consumption is expected to reach 50%. The growth during this period is equivalent to the combined energy consumption of Russia and India today. With the continuous increase of power system load, demand response has gradually attracted people's attention, and buildings with large electricity demand have also become an important demand response resource. People's reliance on air conditioners is becoming more and more intense. In summer, the electricity load has broken new highs year after year, and the air conditioner load accounts for 30%-40% of the peak load. The air conditioner load can be adjusted through reasonable control methods. Compared with split air conditioners, the central air conditioning system has the characteristics of larger capacity and stronger controllability, and has higher demand response potential and mining significance.

The central air-conditioning system determines the controllability of its load due to its own system characteristics. In theory, the control methods of the central air-conditioning system are mainly divided into rigid regulation and flexible regulation. At present, rigid control is mainly to turn off the central air conditioner during the demand response period, and flexible control is mainly to change the outlet water temperature of the refrigeration unit, increase the set temperature at the end of the central air conditioner, and pre-cooling. On this basis, the regulation strategy of building central air conditioning is fully considered in the scenario of demand response.

The inventor found that during the execution of demand response, in order to achieve the purpose of load reduction, the operating state of the air conditioner was changed, which would inevitably have a certain impact on the building users, and most of the existing load adjustment methods did not take into account the benefits on the user side or Comfort, simple load reduction will inevitably lead to high customer dissatisfaction.

SUMMARY OF THE INVENTION

In order to solve the deficiencies of the prior art, the present disclosure provides a demand response control method and system for a central air conditioner in a building. The demand response strategy parameters are solved through a double-layer model, so as to achieve the goal of the lowest load of the refrigeration unit, and finally obtain the control of the strategy. The parameters and the benefits and comfort losses brought to users can be used to screen out the final demand response strategy for users from the perspective of comfort priority or revenue priority, which has a wide range of applications.

In order to achieve the above object, the present disclosure adopts the following technical solutions:

A first aspect of the present disclosure provides a demand response control method for a central air conditioner in a building.

A demand response control method for central air conditioning in a building, comprising the following steps:

Obtain the basic data and environmental data of the building where the central air conditioner is located, receive the demand response command from the power grid, and obtain the demand response time;

According to the obtained data, the user's temperature comfort zone and the temperature adjustable zone within the user's acceptable demand response time, a number of pre-cooling strategies and a number of strategies for shutting down some refrigeration units are obtained;

Remove the pre-cooling strategy whose pre-cooling utility period is less than the response time length of the power grid command, and solve the remaining strategy with the goal of minimum comfort loss or maximum benefit, and obtain the final demand response control strategy.

As some possible implementations, including two-tier control:

The first layer of control calculates the demand response regulation strategy, and obtains a number of pre-cooling strategies and strategies for shutting down some refrigeration units;

The second layer of control controls the energy efficiency improvement of the refrigeration unit, and obtains the load rate of the operating refrigeration unit, the chilled water outlet temperature, the cooling water return water temperature, and the power of the refrigeration unit in each strategy.

As some possible implementations, all temperatures between the minimum value of the temperature adjustable interval and the minimum temperature comfort interval are used as the pre-cooling temperature respectively, and the temperature between the maximum temperature adjustable interval and the maximum temperature comfort interval is used as the pre-cooling temperature. Corresponding to the indoor maximum temperature, forming a number of pre-cooling strategies.

As some possible implementations, each pre-cooling strategy is respectively substituted into a preset pre-cooling model to obtain the pre-cooling period time, the pre-cooling utility period time, the indoor temperature change and the building cooling load change.

As a further limitation, according to a preset model of shutting down some refrigeration units, the indoor temperature change under the strategy of shutting down a certain number of refrigeration units and the total cooling capacity of the remaining working refrigeration units are obtained.

As a further limitation, take the change in building cooling load and the total cooling capacity of the remaining working refrigeration units as the total cooling capacity of each operating refrigeration unit, and use the preset model to obtain the load rate, chilled water, and chilled water of each operating refrigeration unit in each strategy. Outlet water temperature, cooling water return water temperature and the power of the refrigeration unit.

As a further limitation, obtain the outdoor temperature corresponding to the response time, calculate the corresponding baseline load, and further obtain the response load according to the obtained refrigeration unit power of each strategy;

According to the obtained response load, combined with the actual income, the income of each response strategy is obtained;

According to the obtained indoor temperature changes, the comfort loss of each strategy is obtained.

A second aspect of the present disclosure provides a demand response control system for a central air conditioner in a building, including:

The data acquisition module is configured to: acquire the basic data and environmental data of the building where the central air conditioner is located, receive the demand response command from the power grid, and obtain the demand response time;

The control strategy acquisition module is configured to: obtain a plurality of pre-cooling strategies and a plurality of strategies for shutting down some refrigeration units according to the obtained data, the user's temperature comfort zone and the temperature adjustable zone within the user's acceptable demand response time;

The control strategy screening module is configured to: remove the pre-cooling strategy whose pre-cooling utility period is less than the response time length of the power grid command, solve the remaining strategy with the goal of minimum comfort loss or maximum benefit, and obtain the final demand response control strategy.

A third aspect of the present disclosure provides a computer-readable storage medium on which a program is stored, and when the program is executed by a processor, implements the steps in the demand response control method for a central air conditioner in a building described in the first aspect of the present disclosure.

A fourth aspect of the present disclosure provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, the processor implementing the program as described in the first aspect of the present disclosure when the processor executes the program The steps in a demand response control method for central air conditioning in a building.

Compared with the prior art, the beneficial effects of the present disclosure are:

1. The method, system, medium or electronic device described in this disclosure, considering the pre-cooling strategy and the strategy of shutting down part of the refrigeration unit, adopts the double-layer model to solve the parameters of the demand response strategy, and achieves the goal of the lowest load of the refrigeration unit. After obtaining the control parameters of the strategy and the benefits and comfort losses brought to users, the final demand response strategy can be screened out for users from the perspective of comfort priority or revenue priority, which has a wide range of applications.

2. With the method, system, medium or electronic device described in the present disclosure, after calculating the required cooling load according to the pre-cooling strategy and the strategy of shutting down some refrigeration units, the energy efficiency of the running refrigeration units is improved to achieve the same cooling capacity The lower refrigeration unit load is the lowest, which enables better load regulation.

Advantages of additional aspects of the disclosure will be set forth in part in the description that follows, and in part will become apparent from the description below, or will be learned by practice of the disclosure.

Description of drawings

The accompanying drawings that constitute a part of the present disclosure are used to provide further understanding of the present disclosure, and the exemplary embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation of the present disclosure.

FIG. 1 is a schematic flowchart of a demand response control method for a central air conditioner in a building according to Embodiment 1 of the present disclosure.

Detailed ways

The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and/or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and/or combinations thereof.

The embodiments of this disclosure and features of the embodiments may be combined with each other without conflict.

Example 1:

As shown in FIG. 1 , Embodiment 1 of the present disclosure provides a demand response control method for a central air conditioner of a building, which solves the demand response strategy parameters through a double-layer model and achieves the goal of minimizing the load of the refrigeration unit, and finally obtains the control parameters of the strategy and Loss of revenue and comfort to users.

The first layer mainly considers the strategy of pre-cooling and shutting down some refrigeration units. The pre-cooling period time t _pre , the pre-cooling temperature T _pre , and the pre-cooling utility period time t _off of each pre-cooling strategy are obtained by solving the model in S3.1 , indoor maximum temperature T _off , indoor temperature change T _in (t), building cooling load Q _ch (t); the number n of possible operating refrigeration units for each strategy of shutting down some refrigeration units is obtained by solving the model in S3.2 , the number of refrigerating units that can be closed, the number s of the remaining working refrigerating units, the indoor temperature change T _in (t), and the total cooling capacity Q _p (t) of the remaining refrigerating units in operation.

The second layer is to reasonably distribute the cooling load of each strategy on the basis of the first layer, and maximize the energy efficiency of the refrigeration unit through the model of 3.3, thereby realizing the maximization of the response load, and obtain the cooling unit of each strategy. Load rate η, chilled water outlet temperature T _chw , cooling water return water temperature T _cw . Further, the response load _Pre , the gain S _e and the comfort loss C ₂ of each strategy can be calculated from the formula described in S2 of the present embodiment.

Finally, after the decision-making process in S3.4, the final demand response strategy is screened out for users from the perspective of comfort priority or revenue priority.

Specifically, it includes the following:

S1: Basic Computational Model

S1.1: Building Cooling Load Model

According to the law of conservation of energy, it is as follows:

In order to maintain a constant temperature in the building, the sum of the instantaneous heat gain Q _ci of the building and the heat storage capacity Q _x of the enclosure structure should be equal to the cooling capacity Q _ch of the central air conditioner, where the instantaneous heat gain Q _ci of the building is determined by the external wall and roof transients Hourly cooling load _Qwq formed by heat transfer, hourly cooling load Qwc formed by transient heat transfer of external windows, hourly cooling load Qfs formed by solar radiation heat _passing through glass windows, and hourly cooling load _Qfs formed by heat dissipation of indoor electrical equipment The hourly cooling load Q _e , the hourly cooling load Q _l formed by the heat dissipation of indoor lighting equipment, the hourly cooling load Q _p formed by the heat dissipation of the indoor human body, and the fresh air load Q _nw are composed. The calculation formulas are:

Q _ch =Q _cl +Q _x

Q _ci =Q _wq +Q _wc +Q _fs +Q _e +Q _l +Q _p +Q _nw

Q _wq =∑{K _i F _i (T _out -T _in )}

Q _wc =∑[K _c F _c (T _out -T _in )]

Q _fs =∑(q _f F _c C _s C _n C _cl )

Q _e =1000n ₁ n ₂ n ₃ N _e

Q _l =1000n ₄ n ₅ n ₆ n ₇ N _l

Q _nw ≈1.01fT _out -1.01fT _in +38.5f

Q _x =H _i S _in dT _in

In the formula: F _i is the area of the outer wall or roof, m ² ; K _i is the heat transfer coefficient of the outer wall or roof, W/(m ² ·K); T _in is the interior design temperature, ° _C ; The area of the window, m ² ; K _c is the heat transfer coefficient of the outer window, W/(m ² ·K); T _out is the outdoor air temperature, °C; Q _f is the maximum heat radiation of the outer window, W/m ² ; C _s is the correction coefficient of the outer window glass type, dimensionless; C _n is the shading coefficient of the inner shading of the outer window, dimensionless; C _cl is the cooling load coefficient of the outer window glass, dimensionless; n ₁ is the installation coefficient of the electric heating equipment , dimensionless; n ₂ is the load factor of the electric heating equipment, dimensionless; _{n 3} is the simultaneous utilization rate of the electric heating equipment, dimensionless; Ne is the installed power of the electric heating equipment, kW; n ₄ is the simultaneous utilization rate of the lighting equipment, Dimensionless; n ₅ is the heat storage coefficient of the lighting equipment, dimensionless; n ₆ is the coefficient of the power consumption of the rectifier, dimensionless; n ₇ is the installation coefficient of the lighting equipment, dimensionless; N _l is the installation power of the lighting equipment, kW ; C _r is the sensible heat dissipation and cooling load coefficient of the human body, dimensionless; n is the total number of people in public buildings, dimensionless; q _n is the sensible heat dissipation per adult man, W;

is the cluster coefficient, dimensionless; q _q is the latent heat dissipation per adult man, W; f is the fresh air volume, g/s; H _i is the heat storage coefficient of the inner wall, W/(m ² ·K); S _in is the inner wall area, m ² .

S1.2: Room temperature variation model

During the cooling period of the building, the central air-conditioning refrigeration unit continues to provide cooling to keep the room temperature down; during the shutdown period, the central air-conditioning and refrigeration unit stops working. Therefore, there is a relationship between the indoor air heat balance of the building during the shutdown period and the cooling period:

cVρdT _in =Q _ci dt-Q _x

cVρdT _in =Q _ci dt-Q _x -q _r dt

In the formula: c is the specific heat of air at constant pressure, taken as 0.28J/kg·℃; V is the cooling space volume of public buildings, in m ³ ; ρ is the air density, taken as 1.29kg/m ³ ; q _r is the air-conditioning terminal delivery the cooling capacity, W.

The thermodynamic equation of the central air-conditioning in the building during the shutdown period and the cooling period is obtained as:

in:

By discretizing the time t, and assuming that the cooling capacity delivered at the end of the central air-conditioning system during the cooling period is q _r (t), the time-varying equation of the room temperature of the building during the shutdown period and the cooling period can be obtained.

The time-varying equation at room temperature during the cooling period:

The time-varying equation at room temperature during the shutdown period:

T _in (t+1)=C·T _in (t)+(1-ε)·D(t+1)

where:

S1.3: Refrigeration unit energy consumption model

In the central air-conditioning cold source system, the energy consumption of the refrigeration unit accounts for the largest proportion and it runs under partial load for a long time. During the actual operation of the refrigeration unit, the cooling load of the unit, the temperature of the chilled water supply and the temperature of the cooling water inlet have an impact on the operating energy efficiency of the refrigeration unit. The effect of the mathematical model is as follows:

COP=a ₁ +a ₂ η+a ₃ T _chw +a ₄ T _cw +a ₅ ηT _chw +a ₆ ηT _cw +a ₇ T _chw T _cw

Where: COP is the operating energy efficiency of the refrigeration unit, η is the unit load rate, kW; _{Qch is the actual cooling capacity of the unit, kW; Q is the rated cooling capacity of the unit, kWs; Tchw is} the chilled water supply temperature, °C; T _cw is the return water temperature of cooling water, °C; a ₁ -a ₇ are model coefficients.

The energy consumption calculation of the refrigeration unit is as follows:

In the formula, P _chiller is the energy consumption of the refrigeration unit, kW.

S2: Demand Response Strategy Evaluation

S2.1: Baseline Load Calculation

Baseline load is to predict the load of users who do not participate in demand response within the response time. The calculation of the baseline load this time adopts the mean value method. The mean value method takes the mean value of the load during the corresponding response time N days before the execution date of the demand response as the baseline load. The calculation of the baseline load is as follows:

In the formula: P _b is the baseline load, kW; P _{b, ij} is the load of the j-th control period in the corresponding response time on the ith day before the demand response execution day, kW, the response time is t _h min, and the control period is hmin,

Indicates rounded up.

S2.2: Response load calculation

Where: Pre is the response load, kW; P _avi,i is the actual load of the ith control cycle, kW; P _{cbl ,i} is the baseline load of the ith control cycle, kW. Assuming that the response time is t _h min and the regulation period is hmin,

Indicates rounded up.

S2.3: Earnings Calculation

When users perform demand response and generate load shedding, they can obtain corresponding compensation according to the contract signed with the grid. The formula for calculating revenue is as follows:

S _e =P _re ·u

In the formula: _Se is the income obtained from the execution of this demand response, yuan; _Pre is the response load this time, kW; u is the income obtained by reducing the load by 1kW, yuan/kW.

S2.4: Evaluation of User Comfort Loss

During the execution of demand response, the indoor temperature will change from the original comfortable temperature range [T _min , T _max ] to [T' _min , T' _max ] due to changes in the operating state of the air conditioner, where T ' _min is the minimum indoor temperature, _T'min≤Tmin ; _T'max is the _maximum indoor temperature, _{T'max ≥Tmax} . The user's discomfort is caused by the indoor temperature being higher than T _max or lower than T' _min during the execution demand response time. The user's comfort loss is calculated as follows:

In the formula: C ₂ represents the degree of discomfort of the user; α _i is the degree of discomfort of the indoor temperature in the i-th regulation cycle, and the regulation cycle is hmin,

Indicates round up; as follows:

_In the formula, T _in is the current indoor temperature; T _min and T _max are the lower and upper limits of the user's comfortable temperature, respectively, and T' _min and T' _max are the lower and upper limits of the indoor temperature, respectively. When it is within the comfort zone, the user's discomfort degree α is 0.

S3: central air-conditioning demand response control strategy

The flexible regulation strategy of central air conditioning can realize load reduction or transfer without affecting user comfort, so as to meet the requirements of reducing load during demand response time. The central air-conditioning flexible control strategies mainly involved in this embodiment mainly include pre-cooling, shutting down some refrigeration units, and calculating the required cooling load according to the first two strategies, and then improving the energy efficiency of the running refrigeration units to achieve the same cooling The chiller unit load is the lowest at the maximum capacity.

S3.1: Precooling

In the context of demand response, pre-cooling is also an effective way to achieve, and pre-cooling is mainly divided into pre-cooling period and pre-cooling utility period. The pre-cooling period refers to a period of time before the start time of demand response, during which the indoor temperature is lowered to a room temperature level that may be lower than the user's usual room temperature, and the refrigerator increases the cooling output, so that the indoor temperature is reduced to a certain lower level stop at temperature. The pre-cooling utility period means that after the pre-cooling period ends, under the action of building heat storage, even the conveying room without cooling capacity can maintain within a certain temperature range for a certain period of time. Turn it on again when the room temperature slowly rises to a room temperature level that may be higher than the user's usual level.

Assuming that the pre-cooling period is t _pre , the pre-cooling effective period is t _off , and the user's usual indoor temperature setting range is [T _min , T _max ]. In the pre-cooling period, in order to make more cooling, the indoor temperature will be lower than T _min , and this temperature is the pre-cooling temperature T _pre ; in order to prolong the response time as much as possible, the indoor temperature at the end of the pre-cooling utility period can be allowed to be higher than T _max , this temperature is the indoor maximum temperature T _off . Assuming that the temperature adjustable range within the user-acceptable demand response time is [T′ _min , T′ _max ], the problem is transformed into reaching the minimum temperature T′ _min during the pre-cooling period and reaching the maximum temperature T at the end of the pre-cooling utility period ′ _max , t _pre and t _off are solved according to the room temperature change model mentioned above, and the corresponding solution model is as follows:

T′ _min ≤T _in (t)≤T′ _max

_t∈tpre

T _in (t+1)=C·T _in (t)+(1-ε)·D(t+1),t∈t _off

Q _ch (t)=∑q _r (t)

The realization of pre-cooling is to prepare the cooling capacity of the pre-cooling utility period in advance in the pre-cooling period, which also leads to an increase in the electricity consumption in the pre-cooling period. For users, although the implementation of demand-side response will bring certain benefits, the increase in energy consumption during the pre-cooling period will also bring certain additional investment. Therefore, for the pre-cooling strategy, it is necessary to incorporate the load conditions and electricity charges in the pre-cooling period into the evaluation factors. This requires calculating the extra electricity cost during the pre-cooling period, that is, the extra pre-cooling electricity cost. The actual benefit obtained by the user is the difference between the compensation obtained by performing the demand-side response and the extra pre-cooling electricity cost, as shown below:

Additional pre-cooling electricity fee:

In the formula: pre is the response load, kW; P′ _av,i is the actual load of the ith control cycle during the precooling period, kW; P′ _{cbl ,i} is the baseline load of the ith control cycle during the precooling period , kW; _ec is the electricity charge during the pre-cooling period, Yuan/kWh. The pre-cooling period is t _pre min, and the corresponding regulation period is hmin,

Indicates rounded up.

Actual income:

S' _e =S _e -S _c

In the formula: S′ _e is the actual benefit of the user under the pre-cooling strategy, yuan; S _e is the compensation obtained by the user during the pre-cooling utility period, yuan.

Taking a building as an example, assuming that the daily comfortable temperature range of users in the building is [24℃, 26℃], and the temperature adjustable range within the acceptable demand response time of users is [22℃, 29℃], then the building is feasible. The pre-cooling strategy and the corresponding comfort loss are as follows:

S3.2: Shut down some refrigeration units

Most public buildings are equipped with multiple refrigeration units, and the number of refrigeration units in operation can be appropriately reduced for the purpose of load reduction within the response time. First, according to the building load model, the cooling load required in the response time is estimated, and then the number of refrigeration units that can be operated is calculated as n, then the number of refrigeration units that can be turned off ω=1,2...n-1, as shown below:

In the formula: n is the original operating quantity of the predicted refrigeration unit within the response time; _Qch is the cooling load of the central air conditioner within the response time, kW; Qn _is the rated cooling capacity of a single refrigeration unit, kW;

Indicates rounded up.

Then the cooling capacity of the remaining refrigeration units in operation is:

Q _ch (t) = Q _p (t)

In the formula: Q _p is the total cooling capacity of the remaining operating refrigeration units, kW; s is the number of remaining working refrigeration units, s=n-ω. According to the existing control logic of refrigeration units, the cooling load of multiple refrigeration units is evenly shared, that is,

It is the actual cooling capacity of each operating refrigeration unit, kW.

Since the reduction of the number of refrigeration units in operation will inevitably lead to a reduction in the cooling capacity, the reduction in the cooling capacity will make the indoor temperature T _m higher than T _max . According to the number of shutdowns of different refrigeration units, the indoor temperature can be solved by the room temperature change model when the strategy of shutting down some refrigeration units is executed, and the user comfort loss of executing the strategy can be further calculated.

Taking a building as an example, assuming that the daily comfortable temperature range of users in the building is [24°C, 26°C], and the original number of refrigeration units in the response time is predicted to be 3, then the feasible pre-cooling strategy for the building and the corresponding comfort The degree loss is as follows:

serial number	Number of shutdowns/ω	Indoor maximum temperature/T m	loss of comfort
1	1 set	27℃	0.52
2	2 units	29℃	0.82

S3.3: Energy Efficiency Improvement of Refrigeration Units

The total energy consumption of multiple refrigeration units in a central air conditioner is closely related to the load distribution scheme among the equipment under partial load. Therefore, it is necessary to consider the performance differences of each unit to find a feasible energy-saving scheme. The COP optimization method is to maximize the COP value of the refrigeration unit group by changing the outlet temperature of the chilled water and the distribution of the load rate when the outlet temperature of the chilled water is the same under the condition of a certain cooling load. Improve system performance, achieve optimal energy efficiency, and consume the least electricity when the cooling capacity is fixed. The required cooling capacity is determined according to the previous control strategy, and the optimization objective is solved in combination with the following constraints, and then the optimal load distribution scheme and chilled water outlet temperature are obtained.

optimize the target:

Optimization constraints:

Cooling capacity constraints:

Chilled water outlet temperature constraints:

T _chw,min ≤T _chw ≤T _chw,max

T _chw,1 =T _chw,2 =...=T _chw,i

Cooling water return temperature constraints:

T _cw,min ≤T _cw ≤T _cw,max

T _cw,1 =T _cw,2 =...=T _cw,i

Refrigeration unit load rate constraints:

η _i,min ≤η _i ≤1

In the formula: COP _i (t) is the energy efficiency value of the ith operating refrigeration unit after optimization; T _chw,i is the chilled water outlet temperature of the ith operating refrigeration unit, ℃; T _chw,min is the minimum allowable chiller Outlet water temperature, °C; T _chw,max is the maximum allowable outlet water temperature of the refrigerator, °C; T _cw,i is the cooling water return water temperature of the i-th operating refrigeration unit, °C; T _cw,min is the minimum allowable cooling water of the refrigerator Return water temperature, °C; T _cw,max is the maximum allowable cooling water return water temperature of the refrigerator, °C; η _i,min is the minimum load rate of the refrigerator operation; S is the number of operating refrigeration units, sets; Q _on,i (t) is the cooling capacity of the ith operating refrigeration unit, kW.

The cooling unit load at this time is as follows:

In the formula: p _chiller,i (t) is the load of the ith operating refrigeration unit, kW.

Calculate the cooling load for the strategies of pre-cooling and shutting down some refrigeration units, ignoring the loss in the process of cooling capacity, and assuming that the cooling load is equal to the cooling capacity of the refrigerator. After the cooling capacity, it is brought into the energy efficiency improvement model for calculation and solution. The load rate of the refrigeration unit, the chilled water outlet temperature, the cooling water return temperature, and the load of the refrigeration unit can be obtained, and the response load of each strategy can be further evaluated and the benefits can be obtained. Taking a building as an example, the demand response subsidy is 30 yuan/kW. The details are as follows:

S3.4: Decisions on Response Policy

According to the relevant calculation results of the above strategies, there are 6 strategies for pre-cooling and 2 strategies for shutting down some refrigeration units, a total of 8 response strategies. A choice needs to be made among these 8 strategies, and the strategy that will ultimately be implemented in demand response is selected. The decision of the response strategy needs to go through two layers of screening. The first layer is the screening of time, that is, according to the response time length of the power grid command (set as t _DR ), the strategy that meets the requirements is selected, that is, t _off ≥ t _DR in the pre-cooling is selected. strategy, and all strategies for shutting down some refrigeration units (because all strategies for shutting down some refrigeration units can run for a long time, but at the cost of an overall increase in indoor temperature). The strategy obtained after the first layer of strategy screening is passed through the second layer of screening to make the final strategy decision.

The second level of decision-making is mainly from two perspectives, namely, comfort priority and profit priority. Comfort priority is to obtain the comfort loss after the calculation of each strategy is completed, and the strategy with the smallest comfort loss is selected as the final demand response strategy; income priority is to obtain the gain after the calculation of each strategy is completed. The strategy with the greatest profit is selected as the final demand response strategy.

Assuming that the t _DR requirement of a power grid command is 40 minutes, the strategies selected after the first layer of screening include strategies 3, 5, and 6 for pre-cooling and strategies 1 and 2 for shutting down some refrigeration units. Then carry out the screening of the second layer of strategies. According to the principle of comfort priority, the final selected strategy is strategy 1 of shutting down some refrigeration units, that is, the load rate of 1# refrigeration unit is 92%, and the load rate of 2# refrigeration unit is 87%. %, the chilled water supply temperature is 8.5 °C, and the cooling water return water temperature is 28.3 °C; according to the principle of revenue priority, the final selected strategy is the 5 strategies of pre-cooling, that is, the pre-cooling starts 32 minutes before the response start time, and the pre-cooling period The load rate of the 1# refrigeration unit is 80%, the load rate of the 2# refrigeration unit is 85%, the load rate of the 3# refrigeration unit is 86%, the chilled water outlet temperature is 9°C, and the cooling water return temperature is 28.5°C. Shut down the refrigeration unit when the start time arrives.

S4: Overall Implementation Ideas

For the demand-side response command of the power grid, after the user receives the response time command from the power grid, first, according to the daily work arrangement of the building, whether there is any interference event such as equipment maintenance or important meetings that need to be carried out within the response time, according to the advance communication with the power grid. It is stipulated in the contract that the user can report to the power grid that the demand-side response cannot be executed when there is a pre-specified interference event by both parties. If there is no interference event conflict, continue to perform the following steps, estimate its own response load and report the subscribed load to the grid side. First, obtain the outdoor temperature within the response time, and bring it into the building load model and the room temperature change model. At the same time, the first-layer response strategy calculation in 3.1 and 3.2 is carried out, and the calculation process of the energy efficiency improvement of the second-layer refrigeration unit is further carried out. On the basis of calculating the indoor temperature, refrigeration unit load, and baseline load, the response load of the demand response strategy evaluation and the user's comfort loss are calculated. The response load information of the strategy to be executed is reported to the power grid, and the response can be executed according to the pre-selected response strategy when the response starts. The overall summary is as follows:

S4.1: Receive the demand response command from the power grid and obtain the response time.

S4.2: Check whether there are any interference events that conflict with the response time according to the building's schedule. If there are interference events in the power grid, report the grid interference events and fail to perform this demand response. If not, go to step 3.

S4.3: Acquire the corresponding outdoor temperature within the response time, and calculate the corresponding baseline load as shown in S2.1 of this embodiment.

S4.4: The first layer (calculation of demand response regulation strategy)

S4.4.1: Pre-cooling strategy: obtain T _min , T _max , T′ _min , T′ _max , take all the temperatures in the interval [T′ _min , T _min ] as the pre-cooling temperature T _pre , which are respectively the same as [T _max ] , T′ _max ] corresponds to the indoor maximum temperature T _off in the interval, forming various pre-cooling strategies. Bring each pre-cooling strategy into the pre-cooling model in S3.1 respectively, the pre-cooling period time t _pre and the pre-cooling utility period time t _off can be obtained, and the indoor temperature change T _in (t) and the building cooling load change can be obtained. _Qch (t).

S4.4.2: Strategy for shutting down some refrigeration units: The model brought into S3.2 calculates the number n of refrigeration units that may operate, and calculates the number of shut down refrigeration units ω=1,2…n in combination with the model in 1.2. The indoor temperature change T _in (t) of the -1 strategy, and the total cooling capacity Q _p (t) corresponding to the number of remaining working refrigeration units s=n-ω.

S4.5: Second layer (energy efficiency improvement of refrigeration units)

Consider the building cooling load Q _ch (t) and cooling capacity Q _p (t) calculated by various strategies in S4.4 as the total cooling capacity of each operating refrigeration unit

The model in S3.3 is brought into the calculation, and the load rate of the refrigeration units operating in each strategy, the chilled water outlet temperature and the cooling water return water temperature, and the power of the refrigeration units can be obtained.

S4.6: Demand Response Strategy Evaluation

S4.6.1: Response load: According to the cooling unit power of each strategy obtained in S4.5, and the baseline load obtained in S4.2 and brought into the model of S2.2, the response load can be obtained.

S4.6.2: Revenue calculation: After obtaining the response load in S4.6.1, you can bring the model in S2.3 to solve the revenue of each response strategy. Note that the pre-cooling strategy needs to be combined with the actual revenue of S3.1 calculate.

S4.6.3 Comfort loss: The indoor temperature change T _in (t) of each strategy in S4.4 is brought into the model of S2.4 to solve the comfort loss, and the comfort loss of each strategy is obtained.

S4.7: Decision on Demand Response Strategy

After evaluating each response strategy, make a decision according to S3.4, and get a certain demand response strategy that needs to be finally determined.

S4.8: Response reporting and execution

The response load of the demand response strategy determined to be executed is reported to the power grid, and a response command is formed to wait for the response time to be executed immediately.

Example 2:

Embodiment 2 of the present disclosure provides a demand response control system for a central air conditioner in a building, including:

The data acquisition module is configured to: acquire the basic data and environmental data of the building where the central air conditioner is located, receive the demand response command from the power grid, and obtain the demand response time;

The control strategy acquisition module is configured to: obtain a plurality of pre-cooling strategies and a plurality of strategies for shutting down some refrigeration units according to the obtained data, the user's temperature comfort zone and the temperature adjustable zone within the user's acceptable demand response time;

The control strategy screening module is configured to: remove the pre-cooling strategy whose pre-cooling utility period is less than the response time length of the power grid command, solve the remaining strategy with the goal of minimum comfort loss or maximum benefit, and obtain the final demand response control strategy.

The working method of the system is the same as the demand response control method for the central air conditioner of the building provided in Embodiment 1, and will not be repeated here.

Example 3:

Embodiment 3 of the present disclosure provides a computer-readable storage medium on which a program is stored, and when the program is executed by a processor, implements the steps in the demand response control method for a central air conditioner in a building described in Embodiment 1 of the present disclosure.

Example 4:

Embodiment 4 of the present disclosure provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, the implementation is as described in Embodiment 1 of the present disclosure. The steps in a demand response control method for central air conditioning in a building.

c One skilled in the art will appreciate that embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media having computer-usable program code embodied therein, including but not limited to disk storage, optical storage, and the like.

The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flows of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. During execution, the processes of the embodiments of the above-mentioned methods may be included. The storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM) or the like.

The above descriptions are only preferred embodiments of the present disclosure, and are not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included within the protection scope of the present disclosure.

Claims (10)

1. A demand-response control method for central air-conditioning in a building, which is characterized by comprising the following steps:

   Obtain the basic data and environmental data of the building where the central air conditioner is located, receive the demand response command from the power grid, and obtain the demand response time;

   According to the obtained data, the user's temperature comfort zone and the temperature adjustable zone within the user's acceptable demand response time, a number of pre-cooling strategies and a number of strategies for shutting down some refrigeration units are obtained;

   The pre-cooling strategy whose pre-cooling utility period is less than the response time length of the power grid command is removed, and the remaining strategy is solved with the goal of minimum comfort loss or maximum benefit, and the final demand response control strategy is obtained.
2. The demand-response control method for building central air-conditioning according to claim 1, characterized in that: it comprises double-layer control;

   The first layer control calculates the demand response regulation strategy, and obtains a number of pre-cooling strategies and strategies for shutting down some refrigeration units;

   The second layer of control controls the energy efficiency improvement of the refrigeration unit, and obtains the load rate of the operating refrigeration unit, the chilled water outlet temperature, the cooling water return water temperature, and the power of the refrigeration unit in each strategy.
3. The building central air-conditioning demand response control method according to claim 1 or 2, characterized in that:

   All temperatures between the minimum value of the adjustable temperature range and the minimum value of the temperature comfort zone are taken as the pre-cooling temperature respectively, which corresponds to the maximum indoor temperature between the maximum value of the temperature adjustable zone and the maximum value of the temperature comfort zone. Form a number of pre-cooling strategies.
4. The building central air-conditioning demand response control method according to claim 1 or 2, characterized in that:

   Substitute each pre-cooling strategy into the preset pre-cooling model, and obtain the pre-cooling period time, pre-cooling utility period time, indoor temperature change and building cooling load change.
5. The building central air-conditioning demand response control method as claimed in claim 4, wherein:

   According to the preset model of shutting down some refrigeration units, the indoor temperature change under the strategy of shutting down a certain number of refrigeration units and the total cooling capacity of the remaining working refrigeration units are obtained.
6. The building central air-conditioning demand response control method of claim 5, wherein:

   Taking the change of building cooling load and the total cooling capacity of the remaining working cooling units as the total cooling capacity of each operating cooling unit, the preset model is used to obtain the load rate, chilled water outlet temperature, and cooling water return in each strategy. Water temperature and power of refrigeration unit.
7. The building central air-conditioning demand response control method of claim 6, wherein:

   Obtain the outdoor temperature corresponding to the response time, calculate the corresponding baseline load, and further obtain the response load according to the obtained refrigeration unit power of each strategy;

   According to the obtained response load, combined with the actual income, the income of each response strategy is obtained;

   According to the obtained indoor temperature changes, the comfort loss of each strategy is obtained.
8. A demand-response control system for central air-conditioning in a building, characterized in that it includes:

   The data acquisition module is configured to: acquire the basic data and environmental data of the building where the central air conditioner is located, receive the demand response command from the power grid, and obtain the demand response time;

   The control strategy acquisition module is configured to: obtain a plurality of pre-cooling strategies and a plurality of strategies for shutting down some refrigeration units according to the acquired data, the user's temperature comfort zone and the temperature adjustable zone within the user's acceptable demand response time;

   The control strategy screening module is configured to: remove the pre-cooling strategy whose pre-cooling utility period is less than the response time length of the power grid command, solve the remaining strategy with the goal of minimum comfort loss or maximum benefit, and obtain the final demand response control strategy.
9. A computer-readable storage medium on which a program is stored, characterized in that, when the program is executed by a processor, the steps in the demand response control method for a central air conditioner in a building according to any one of claims 1-7 are implemented.
10. An electronic device, comprising a memory, a processor, and a program stored on the memory and running on the processor, wherein the processor implements the program described in any one of claims 1-7 when the processor executes the program The steps in a demand response control method for central air conditioning in a building.

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