GB2626815A - Method, system, computer program and computer readable storage medium for providing a load control pattern to at least one appliance load component of a - Google Patents

Abstract

A electric or power load control pattern is provided to at least one appliance electric load component of a building 2, which has several appliance electric load components. Electric load data related to the building 2, is collected or sensed S1, e.g. aggregate electric load profile of the building 2, electric tariff. An output profile is generated S2 depending on all information related to the building 2 which is characteristic for a load shifting pattern and/or for a load curtailing pattern. At least one load control pattern is generated S3 for the building 2 depending on the output profile. Th load control pattern is provided S4 to an appliance load component.

Description

Description

METHOD, SYSTEM, COMPUTER PROGRAM AND COMPUTER READABLE

STORAGE MEDIUM FOR PROVIDING A LOAD CONTROL PATTERN TO AT

LEAST ONE APPLIANCE LOAD COMPONENT OF A BUILDING COMPRISING SEVERAL APPLIANCE LOAD COMPONENTS

A method for providing a load control pattern to at least one appliance load component of a building is provided. In 10 addition, a system, a computer program and a computer readable storage medium are provided.

Generally, in order to reduce a carbon footprint of a building, there is a need for an intelligent load management, which yields optimum reduction in electricity operation cost of a building. Inter alia, with an increase of connected metering devices within buildings it is possible to leverage data to operate buildings at their efficient points.

An object to be solved is to provide a particularly simple method for minimize electricity cost of a building. Furthermore, a system and a computer program, which are able to perform such a method, are provided. In addition, a computer readable storage medium with such a computer program is provided.

The object is solved by the subject-matter of the independent claims. Advantageous embodiments, implementations and further developments are the subject-matter of the respective dependent claims.

A method for providing a load control pattern to at least one appliance load component of a building comprising several -2 -appliance load components is specified. For example, the building is a residential building, a commercial complex, an office building and/or a factory building. The building can be a hybrid of at least two of a residential building, a commercial complex, an office building and a factory building.

Exemplarily, the building comprises a plurality of appliance load components. The appliance load components can be categorised in several categories. For example, the building comprises several appliance load components of several categories. The categories can comprise at least one of a resistive load category, a capacitive load category, an inductive load category and a non-linear load. It is further conceivable that at least one of the categories comprises several sub-categories.

Each appliance load component is configured to consume electrical power, i.e. being an appliance electrical load.

The appliance electrical load is, inter alia, dependent on a need of the building and/or at least one user of the building.

Exemplarily, the building is connected to a power network, comprising at least one of a power network grid, a power storage, and renewable energy sources. At least some of the appliance load components or all appliance load components of the building are configured to be provided with electrical power by the power network. In particular, the renewable energy sources are part of the building.

According to at least one embodiment of the method, at least two information related to the building are provided. -3 -

Exemplarily, at least some of the information are characteristic for at least a part of a load or the total load of the building and/or for the power network.

According to at least one embodiment of the method, an output profile is generated depending on all information related to the building, wherein the output profile is characteristic for a load shifting pattern and/or for a load curtailing pattern.

This is, for example, a first main stage of the method. In the first main stage, an amount of load to be shifted and/or to be curtailed is determined, in particular for the whole building. The generated output profile is characteristic for a load of all of the appliance load components. The amount of load, in particular an optimal amount of load, to be shifted is characteristic for the load shifting pattern. The amount of load, in particular an optimal amount of load, to be curtailed is characteristic for the load curtailing pattern.

The load shifting pattern is characteristic to move the power consumption from one time period to another time period. The load curtailing pattern is characteristic to reduce the power consumption.

In particular, an electricity cost of the building is minimized through load shifting and/or load curtailing when generating the output profile, resulting in a building load profile. The building load profile is, for example, forecasted and used in an optimization problem resulting in the output profile. Exemplarily, the forecast in the first main stage is an aggregated load forecast of the building. In particular, the minimization and the aggregated load forecast are part of the first main stage. -4 -

According to at least one embodiment of the method, at least one load control pattern for the building is generated depending on the output profile.

This is, for example, a second main stage of the method. In the second main stage, the load control pattern is generated to realize a load shift and/or a load curtailment provided by the first main stage, with respect to at least one of the appliance load components. Exemplarily, each load control pattern is characteristic for a realization of a load shift and/or a load curtailment with respect to one of the appliance load components, in particular to all appliance load components of one category.

According to at least one embodiment of the method, the load control pattern is provided to at least one of the appliance load components. In this stage, at least one actionable input in the form of the load control pattern is provided to the building, in particular to at least one of the appliance load components. For example, the load control pattern is characteristic for a load shift action and/or to a load curtailment action provided to individual appliance load components.

The method described herein above is, exemplarily, performed in the order indicated. The method described herein above is, exemplarily, a computer implemented method. It is conceivable that at least some of the method stages can be performed simultaneously.

An idea of the method described herein is, inter alia, to use a method with a first and a second main stage for intelligent -5 -load management for optimizing electricity costs of the building. In the first main stage, for example, the buildings electricity cost is minimized. In the second main stage, the output profile is generated in order to realize load shifting and load curtailment of specific appliance load components.

Advantageously, the method is generic and can incorporate a variety of appliance load components and can be deployed on a computing platform or a cloud platform. Furthermore, the approach using the first and the second main stage advantageously ensures that a mathematical complexity of the optimization is reduced, such that no need of high-end computational power is needed.

Since the present method is deployable on the cloud platform and further is executable in particular fast, the method can be easily scaled to multiple buildings. Additionally, no need of a change of hardware is needed in the corresponding buildings for using this method.

According to at least one embodiment of the method, the information are characteristic for at least one of the following information: an aggregated building load profile, a curtailable load limit, preferred load shifting hours, power network parameters, electricity tariff.

The aggregated building load profile comprises, for example, all loads of the appliance load components of the building. The loads of the appliance load components can be acquired by at least one metering device of the building. The at least one metering device can be also part of at least some of the appliance load components. -6 -

The curtailable load limit is, for example, an amount of load which can be curtailed. By indicating preferred load shifting hours, building operation preferences can be considered. This is that the information can further comprise building operation preferences.

Power network parameters can comprise, inter alia, specific power information of the power network grid, the power storage, and the renewable energy sources. Further, the electricity tariff can be characteristic for power costs of the respective power network.

According to at least one embodiment of the method, the output profile is generated by a mixed integer linear programming optimization objective function. The mixed integer linear programming optimization objective function is, exemplarily, configured to minimize the electricity cost of the building.

The mixed integer linear programming optimization objective function is, in particular, a mathematical function used to determine an optimal solution for a problem. For example, the objective function is used to minimise energy costs of the building and/or an energy consumption of the building.

According to at least one embodiment of the method, the mixed integer linear programming optimization objective function is dependent on the information, in particular all information.

According to at least one embodiment of the method, the load shifting pattern and/or the load curtailing pattern is characteristic for an optimised amount of load to be shifted and/or curtailed dependent on a time parameter. For example, -7 -the time parameter is defined within a time period. The time period is, for example, at least several hours, at last one day, at least one month and/or at least one year.

Exemplarily, the forecasting described herein above can comprise an adaptive seasonal persistent forecasting algorithm.

According to at least one embodiment of the method, when generating the at least one load control pattern, the output profile is disaggregated with respect to different appliance load components by means of a forecast method. This is that the forecast in the second main stage is an individual load forecast of the building for different appliance load components, e.g. for different categories or sub-categories.

According to at least one embodiment of the method, when generating the at least one load control pattern, the forecast method includes an adaptive seasonal forecasting.

According to at least one embodiment of the method, the generation of the at least one load control pattern is additionally depending on at least one user preference.

According to at least one embodiment of the method, with the load control pattern, at least one of a heating, a ventilation and/or an air-conditioning setpoint profile, a lighting load switching profile, a pumping switching profile, is adjusted.

This is that the appliance load components can be categorised, e.g. in a heating category, a ventilation category, an air-conditioning category, a lighting category -8 -and/or a pumping category. In the second stage, the aggregated output profile is disaggregated with respect to different appliance load components -in particular the output profile is disaggregated to different categories. Each load control pattern is subsequently solely provided to one of the categories and/or sub-categories.

Furthermore, a system for providing a load control pattern to at least one appliance load component is specified. The system is configured to perform the method described herein. Therefore, all features and embodiments disclosed in connection with the method are also disclosed in connection with the system and vice versa.

According to at least one embodiment of the system, the system comprises a building comprising several appliance load components.

According to at least one embodiment of the system, the 20 system comprises a network, which is configured to be connected to an internal computational element or to an external computational element.

The internal computational element and/or the external computational element are configured to execute the method described herein before. The internal computational is, for example, part of the building. The external computational is, for example, spaced apart from the building.

In addition a computer program is specified comprising instruction which, when the computer program is executed by a computer, causes the computer program to execute the method described herein. -9 -

Further, a computer readable storage medium is specified on which the computer program described herein is stored.

Exemplary embodiments of the method are explained in more detail below with reference to the Figures.

Figure 1 shows a flowchart of the method for providing a load control pattern to at least one appliance load component of a 10 building according to an exemplary embodiment.

Figure 2 shows a flowchart of a part of the method according to an exemplary embodiment.

Figure 3 shows a system which is configured to perform the method according to an exemplary embodiment.

Figures 4 to 11 each shows exemplarily different loads.

Elements of the same structure or function are marked with the same reference signs across all Figures.

Method stage Si according to the exemplary embodiment of Figure 1 comprises that at least two information related to the building 2 are provided. Each information is characteristic for an aggregated building 2 load profile, a curtailable load limit, preferred load shifting hours, power network parameters or an electricity tariff.

In a method stage S2, an output profile is generated depending on all information related to the building 2. The information, i.e. the aggregated building load profile, the electricity tariff used by the building 2, preferred load -10 -shifting hours and the amount of load, e.g. in kW, which can be curtailed, are the input of a mixed integer linear programming optimization problem -using a mixed integer linear programming optimization function, which exemplarily has the following form: min(f) = (Demand charge month X Pgrid,max mo) + Energy charger x 132, ,d,t) (Loadcurtaitt x Interruption cost 10) load) For example, "Demand chargementh" is the monthly demand charge component of the electricity tariff of the building 2, "Energy charge" is the energy charge component of the electricity tariff at time instant "t" of the month, "Pgrid.t" is the power drawn from the grid at time instant "t", "Load,,,,iii_t" is the amount of load curtailed or shifted at time instant "t".

The optimization constraints are as follows: For all "t": -Pgrid max Pgrid,t For all "t": Loadeurtait,t < Maximum load curtail allowed For all "t" Pgrid t LOad curtail t = Loadr For all "tsh" in allowed load shifting hours in 'd' days: LOadreduce,tsh,d ± Load incre ase,tsh,d ± Loa dcurtail,ts it,d = Loadrsio For all "tsh" in allowed load shifting hours in 'd' days: &sit Loadreduce,tsh,d Etsh Load increase,tsh,d Exemplary, in the method stage S2, an optimal amount of load to be shifted and/or to be curtailed is determined considering operator preferences, the load profile and site electricity tariffs. The output of method stage S2 is the output profile being characteristic for a load shifting pattern and/or for a load curtailing pattern.

In a next method stage 53, at least one load control pattern is generated for the building 2 depending on the output profile. For this, the output profile is disaggregated into individual appliance load components.

The appliance load components are, exemplarily grouped in different categories. The categories are characteristic for the appliance load components used for one of the following: heating, ventilation and/or air-conditioning, lighting and pumping. This is, the output profile is disaggregated into individual categories, each of which comprising at least some of the appliance load components.

The disaggregated categories of the appliance load components are forecasted using algorithms such as Persistent forecasting. Based on the output profile, user preferences and forecasted appliance load components, at least one of a heating, a ventilation and/or an air-conditioning setpoint profile, a lighting load switching profile, a pumping switching profile, is generated comprised by the load control pattern.

Subsequently, in a method stage S4, the at least one load control pattern is provided to at least one of the appliance load components, in particular to all appliance load components of at least one category.

-12 -In method step S22, building operation preferences can be provided, such that the output profile is also generated dependent on the building operation preferences.

In method step S5, user preferences can be provided, such that the load control pattern is also generated dependent on the user preferences.

Method stage S3 according to the exemplary embodiment of Figure 2 further comprises, as already explained in connection to Figure 1, that user preferences are provided in a method stage S5. Subsequently, the appliance load components are forecasted in a method stage S6. Based on the stages S5 and 56, a heating, a ventilation and/or an air-conditioning setpoint profile, a lighting load switching profile and/or a pumping switching profile -forming the load control pattern -is generated in method stage 57.

Actions to be performed based on the generated profiles can be displayed in method stage 58.

The system 1 according to the exemplary embodiment of Figure 3 comprises a building 2 and a network 3, by which the building 2 is connected to an internal computational element 4 or to an external computational element 5. It is conceivable that the building 2 is connected to both, the internal computational element 4 and the external computational element 5.

Furthermore, the system 1 can comprise several metering 6 devices, being connected to the internal computational element 4. For example, the metering devices 6 of the -13 -building 2 are connected to the internal computational element 4, which is configured to provide data from the metering devices 6 to the external computational element 5 via the network 3, comprising a wireless connection. In this case, the external computational element 5 can be a cloud application configured for executing the method. Further, in this case, the internal computational element 4 is used for providing the information.

The system 1 is configured, inter alia, to provide a load control pattern to at least one appliance load component, as described in connection with Figures 1 and 2.

Figures 4, 5, 6 and 7 represent a use case for the method described in Figures 1 and 2. A power in the units of kW is depicted on the y-axis of the Figures 4, 5, 6 and 7. The x-axis shows a time period of one day, indicated by the time of the day.

In Figure 4, the aggregated aggregated load of the building 2 is shown being the output profile. The output profile is subsequently disaggregated, i.e. decomposed, into different categories of appliance load components. The category comprising some of the appliance load components shown in Figure 5 is characteristic for a lighting load profile. The category comprising some other of the appliance load components shown in Figure 6 is characteristic for a heating, a ventilation and/or an air-conditioning profile. The category comprising some other of the appliance load components shown in Figure 6 is characteristic for a computer load profile. Here the lightening and the heating, ventilation and/or air-conditioning are identified to be controllable loads.

-14 -The region marked in Figures 4 and 6 are representative for a peak load period which can be modified in order to achieve electricity savings.

Figures 8 and 9 represent a load control pattern, wherein Figure 8 is referring to Figure 6 and Figure 9 is referring to Figure 5.

In particular, in Figure 8, a heating, a ventilation and/or an air-conditioning setpoint profile is shown. The curve P1 is characteristic for an original setpoint and the curve P2 is characteristic for the optimised setpoint of the load control pattern. In fact, on the y-axis in Figure 8, a temperature corresponding to the setpoint is indicated in °C.

In Figure 8, the temperature setpoint is increased from 26 to 29 deg C at 10:00 am -which reduces the load of the corresponding appliance load components by 6.5 kW -and from 27 to 29 deg C at 10:15 am -which reduces the load of the corresponding appliance load components by 3.5 kW.

In particular, in Figure 9, a lighting load switching profile is shown. The curve P3 is characteristic for an original lighting load and the curve P4 is characteristic for the optimised lighting load according to the load control pattern. In fact, on the y-axis in Figure 8, a power in kW is indicated.

According to Figure 9, the lighting load is reduced by 2.5 kW at 10:00 am and by 1.5 kW at 10:15 am -which is performed due to load control pattern.

-15 -In Figure 10, the aggregated load of the building 2 is shown being the output profile for one month.

In Figure 11, the optimized load profile is shown. In the upper curve of Figure 11, the upper dashed line indicates a maximal load of the building 2 according to Figure 10 and the lower dashed line indicates a maximal load of the building 2 with the optimized load profile. In the lower curve of Figure 11, load shifts are indicated. On the y-axis of the upper and 10 lower curve, the power in kW is indicated.

For example, the building 2 has peak demand charge of 5 $/kW, peak energy charge of 0.15 $/kWh and off-peak energy charge of 0.11 $/kWh. A curtailable load of 30 kW is considered here and load interruption cost of 0.15$/kWh is assumed. The inputs are fed to method stage S2 and optimized load profile for 1 month is obtained, which is shown in Figure 11, which is achieved by the load control pattern.

-16 -Reference signs list 1 system 2 building 3 network 4 internal computational element external computational element 6 metering device 31_38,S22 steps

Claims (10)

1. Claims 1. A method for providing a load control pattern to at least 5 one appliance load component of a building (2) comprising several appliance load components, comprising: -providing at least two information related to the building (2), -generating an output profile depending on all information related to the building (2), wherein the output profile is characteristic for a load shifting pattern and/or for a load curtailing pattern, -generating at least one load control pattern for the building (2) depending on the output profile, and -providing the at least one load control pattern to at least one of the appliance load components.
2. 2. The method according to claim 1, wherein -the information are characteristic for at least one of the 20 following information: an aggregated building load profile, a curtailable load limit, preferred load shifting hours, power network parameters, electricity tariff.
3. 3. The method according to one of claims 1 or 2, wherein -the output profile is generated by a mixed integer linear programming optimization objective function, and -the mixed integer linear programming optimization objective function is dependent on the information.
4. 4. The method according to one of claims 1 to 3, wherein -the load shifting pattern and/or the load curtailing pattern is characteristic for an optimised amount of load to be shifted and/or curtailed dependent on a time parameter.
5. -18 - 5. The method according to one of claims 1 to 4, wherein when generating the at least one load control pattern -the output profile is disaggregated with respect to different appliance load components by means of a forecast method, and -the forecast method includes an adaptive seasonal forecasting.
6. 6. The method according to one of claims 1 to 5, wherein -the generation of the at least one load control pattern is additionally depending on at least one user preference.
7. 7. The method according to one of claims 1 to 6, wherein -with the load control pattern, at least one of a heating, a ventilation and/or an air-conditioning setpoint profile, a lighting load switching profile, a pumping switching profile, is adjusted.
8. 8. System (1), which is configured to perform the method according to one of the preceding claims, comprising -a building (2) comprising several appliance load components, and -a network (3), which is configured to be connected to an internal computational element (4) or to an external computational element (5).
9. 9. Computer program comprising instructions which, when the computer program is executed by a computer, cause the computer program to execute the method according to one of the claims 1 to 7.-19 -
10. 10. Computer-readable storage medium on which the computer program according to claim 9 is stored.