FR3114699A1 - Device and method for automatic load management - Google Patents

Abstract

Automatic Load Management Device and Method This disclosure relates to a load management device (114) comprising: an input interface for receiving electrical power consumption readings at a customer site; a memory storing a power usage algorithm defining power consumption rules to be applied based on the power consumption readings; and an output interface for controlling a plurality of electrical loads at the customer site based on the power usage algorithm. Figure for the abstract: Fig. 1

Description

Device and method for automatic load management

This disclosure relates generally to the field of electronic power management devices and systems, and in particular to a device, system, and method for power management at one or more sites.

A technical difficulty encountered on a recurring basis by power supply networks is to balance, at all times, the response to demand in order to avoid overloading or underloading the network, which could lead to outages. feed.

One mechanism used by energy companies to help balance demand response on the grid is to set tariffs that incentivize customers to keep their power consumption below agreed limits during certain hours of the day and periods of the day. year. For example, in France, there is a Tax on the use of the public electricity network (TURPE, "Taxe d'Utilisation du Réseau Public d'Électricité") which finances the transport and distribution of electricity on the network. Each electricity customer accepts a certain TURPE tariff, revised annually, based on their expected energy needs. The tariff includes a penalty payment each time the energy consumption at a customer site exceeds an agreed limit defined by the TURPE tariff. In this way, financial incentives are provided to encourage a stable use of electricity, and/or a predictable load on the transmission network. Other countries have similar mechanisms with similar objectives.

An electricity customer can thus reduce his energy bill, and also help meet the technical objective of balancing demand response on the grid, by limiting the number of times his energy consumption exceeds the agreed limit. However, there is a technical difficulty in satisfying this objective, in that it is often difficult for an electricity user to anticipate which consumption peaks he is likely to experience.

Certain solutions based on a pressure drop have been proposed in the prior art to help an electricity user avoid exceeding usage limits. In particular, when the total power consumption of a site exceeds the limit, one or more loads are deactivated in order to bring the consumption back to the agreed limit. However, a disadvantage of such pressure drop techniques is that they can have unpredictable negative impacts on operations at a customer site, particularly in the case of industrial users.

There is therefore a need in the art for a technical solution allowing the management, in real time or in near real time, of the power consumption at the level of an electricity customer's site which leads to an improved balancing of response to demand on a supply network, and thus to a reduction in electricity costs for the user.

An objective of the embodiments of the present description is to at least partially satisfy one or more of the needs of the art.

According to one aspect, there is provided a load management device comprising: an input interface for receiving electric power consumption readings at a customer site; a memory storing a power usage algorithm defining power consumption rules to be applied based on the power consumption readings; and an output interface for controlling a plurality of electrical loads at the customer site based on the power usage algorithm.

According to one embodiment, the energy usage algorithm defines: one or more priorities to be applied between two or more loads of the plurality of loads when a power consumption threshold is exceeded, the power consumption threshold being example between 85% and 95% of a power consumption limit; and/or one or more load activation periods during which one or more loads are to be activated; and/or one or more load deactivation periods during which one or more loads are to be deactivated.

According to one embodiment, one or more of the plurality of electrical loads is an electric heater configured to heat an area to a set temperature during a heating use period, and the input interface is further configured to receive one or more temperature readings and/or forecasts, and the energy utilization algorithm defines one or more temperature thresholds of the temperature readings and/or forecasts below which said one or more electric heaters must be activated in advance of the period of use of the heating.

According to one embodiment, one or more of the plurality of electrical loads is a cooling system configured to cool an area to a setpoint temperature during a cooling use period, and the input interface is further configured to receive one or more temperature readings and/or forecasts, and the power usage algorithm defines one or more temperature thresholds of the temperature readings and/or forecasts above which said one or more cooling systems must be activated in advance of the cooling use period.

According to another aspect, there is provided a load management system comprising: the above load management device; and a centralized processing system configured: to generate the energy usage algorithm based on historical power consumption readings of the plurality of loads over a period of at least two months and based on a or more power consumption constraints; and to transmit the power usage algorithm to the load management device.

In another aspect, there is provided a load management method comprising: receiving, via an input interface of a load management device, power consumption readings at a customer site; and generating, at an output interface of the load management device, control signals to control a plurality of loads at the customer site based on an energy usage algorithm stored in a memory of the load management device, the energy use algorithm defining power consumption rules to be applied based on power consumption readings.

According to one embodiment, the power usage algorithm defines: one or more priorities to be applied between two or more loads of the plurality of loads when a period of excessive power consumption is detected; and/or one or more load activation periods during which one or more loads are to be activated; and/or one or more load deactivation periods during which one or more loads are to be deactivated.

According to one embodiment, one or more of the plurality of loads is an electric heater configured to heat an area to a setpoint temperature during a heating use period, the method further comprising: receiving, by the input interface, one or more readings and/or temperature forecasts; the comparison, by the load management device, of said one or more readings and/or temperature forecasts with one or more temperature thresholds defined by the energy use algorithm; and activating said one or more electric heaters in advance of the heating use period if at least one of the temperature readings and/or forecasts is below said one or more thresholds.

According to one embodiment, one or more of the plurality of electrical loads is a cooling system configured to cool an area to a setpoint temperature during a period of cooling use, the method further comprising: receiving, by the input interface, one or more temperature readings and/or forecasts; the comparison, by the load management device, of said one or more readings and/or temperature forecasts with one or more temperature thresholds defined by the energy use algorithm; and activating said one or more cooling systems in advance of the cooling use period if at least one of the temperature readings and/or forecasts is above said one or more thresholds.

According to one embodiment, the method further includes: generating, by a centralized processing system, the power usage algorithm based on historical power consumption readings of the plurality of loads over a period at least two months and based on one or more power consumption constraints; and storing the power usage algorithm in the memory of the load management device.

These characteristics and advantages, as well as others, will be set out in detail in the following description of particular embodiments given on a non-limiting basis in relation to the attached figures, among which:

there is a block diagram illustrating a power system according to an exemplary embodiment of the present description;

there is a block diagram illustrating an automatic load management system according to an exemplary embodiment of the present description;

there is a block diagram of a control device for the in more detail according to an exemplary embodiment of the present description;

there is a flowchart illustrating steps in an automatic load management method according to an exemplary embodiment of the present description;

there is a flowchart illustrating a method for automatically managing power consumption at a customer site according to an exemplary embodiment of the present description;

there is a graph representing electrical energy consumption at a customer site for a period of 13 months according to an exemplary embodiment of the present description;

there is a graph representing electrical energy consumption at a customer site as a function of a percentage of points evaluated according to an exemplary embodiment;

there is a graph representing electrical energy consumption compared with subscribed power limits; And

there is a graph representing electrical energy consumption at a customer site during certain time ranges of energy tariffs, as a function of a percentage of points evaluated.

The same elements have been designated by the same references in the different figures. In particular, the structural and/or functional elements common to the various embodiments may have the same references and may have identical structural, dimensional and material properties.

For the sake of clarity, only the steps and elements useful for understanding the embodiments described have been represented and are detailed. For example, devices for monitoring and storing power consumption by different types of electrical loads are well known to those skilled in the art, and will not be described in detail.

Unless otherwise specified, when reference is made to two elements connected together, this means directly connected without intermediate elements other than conductors, and when reference is made to two elements connected (in English "coupled") between them, this means that these two elements can be connected or be linked through one or more other elements.

In the following description, when referring to absolute position qualifiers, such as "front", "rear", "up", "down", "left", "right", etc., or relative, such as the terms "above", "below", "upper", "lower", etc., or to qualifiers of orientation, such as the terms "horizontal", "vertical", etc., it reference is made unless otherwise specified to the orientation of the figures.

Unless specified otherwise, the expressions “about”, “approximately”, “substantially”, and “of the order of” mean to within 10%, preferably within 5%.

There is a block diagram illustrating a power system 100 according to an exemplary embodiment of this disclosure.

In the example of the , the power system 100 includes two customer sites 102, 104, a central power management system 106, a market server (MARKETS) 107 and a power grid operator server (GRID OPERATOR FOOD) 108.

A customer site in the power system 100 corresponds to a site that includes electrical loads and/or electricity storage, the electrical energy being transferred to the customer site from the power network and/or from the customer site to the supply network. For example, one or more power supply contracts are in place involving customer sites 102, 104 and power grid operators, establishing a business relationship between the entities. Although two customer sites 102, 104 are shown in the embodiment of the , in other embodiments there may be any number of customer sites managed by the central power management system 106.

Each of the customer sites 102, 104 includes flexible electrical energy resources, in other words electrical loads and/or electrical energy storage that can be adapted to meet present and future needs.

In the example of the , customer site 102 includes electrical energy storage and electrical loads, and customer site 104 includes electrical energy generation and electrical loads. However, it would also be possible for a site to include both electrical energy storage and electrical generators, in addition to electrical loads, and for some sites to include only electrical loads, electrical generators or electrical storage. electric energy.

For example, the customer site 102 includes a high capacity battery bank 110 which can, for example, receive or supply up to 10 MW of electrical energy, and has, for example, a storage capacity of between 10 kWh and 20 MWh or more. . The battery bank 110 is for example connected via a battery management system (BMS) 112 to an on-site monitoring and control interface (DR BOX) 114, which will be referred to below as Demand Response (DR) box, or more simply DR box. The DR box 114 is for example a programmable logic controller (PLC), and is also for example configured to implement energy management, similar to the role of an energy management system (EMS).

The customer site 102 also includes, for example, one or more electrical loads 118, represented by a plant in the example of the , connected to the DR box 114 via one or more programmable logic controllers (PLC) 120. For example, the electrical loads 118 correspond to industrial loads, such as loads corresponding to electrical machines, lighting, industrial furnaces or other forms of heating, cooling systems such as refrigeration and/or air conditioning systems and/or other forms of electrical energy consuming loads. For example, said one or more electric loads 118 have a maximum combined consumption ranging from 100 kW to 400 MW or more. However, in some embodiments, there is flexibility in the level of electrical power consumed by site 104. For example, consumption may be reduced from the maximum consumption level by at least 50 kW, and in some embodiments up to several tens of megawatts or more.

For example, the DR box 114 is connected to one or more field meters (METER(S)) 116 to monitor active and reactive powers for single and/or three phases, and/or other electrical properties. For example, on-site meters 116 include one or more electric meters monitoring an electric current supplied to and/or by the site, one or more electric meters monitoring an electric current supplied to or drawn from the battery bank 110, one or more power meters monitoring phases of the electrical signals, and one or more AC (alternating current) frequency meters monitoring the frequency of the power supply voltages present on the power network, seen by the site 102. Other properties which can be measured include electrical energy and power factor. The DR box 114 is for example configured to collect meter data from these counters 116. In addition, the DR box 114 is for example configured to provide the communication interface between the customer site 102 and the central management system 106.

For example, DR box 114 may communicate with central power management system 106, and in some cases with customer equipment, via the Internet. For example, although not shown in , the connection between the DR box 114 and the Internet is made via either a switched communications network, such as via an ADSL modem (asymmetric digital link on subscriber line) , or via a wireless connection, for example comprising a cellular communications network.

The customer site 104 includes for example a DR box 114 and one or more counters 116 which play a role similar to those of the customer site 102, and which will not be described again in detail. The customer site 104 also includes, for example, one or more electrical loads 118, which are for example similar to the loads 118 of the customer site 102, and which are connected to the DR box 114 via one or more PLCs 120. Besides, in the example of the , the customer site 104 comprises a plurality of electric power generators (POWER GENERATOR) 122, which are for example photovoltaic generators, wind turbines, generators, or other types of power generators.

Although in the example of the a single DR box 114 is provided for each site 102, 104, in alternative embodiments some sites may include more than one DR box 114.

The central management system 106 comprises for example a control and data acquisition system 128, which is for example a control and data acquisition system (SCADA), in charge of receiving data from each DR boxes 114, and the supply of control signals to customer sites 102, 104 via the DR boxes 114. In particular, the SCADA 128 is for example in charge of the transmission of control signals to the DR boxes of the customer sites 102, 104 to control electrical power supplied to or from the site, and/or electrical power applied to or drawn from battery bank 110. In addition, the SCADA 128 is for example in charge of acquiring and storing data measurements from the sites 102, 104, and also information concerning the state of the sites, such as the state of charge of the battery bank 110 in the case where the site has a battery.

The central management system 106 also includes, for example, a distributed energy resource management system (DERMS) 130, which is, for example, a computer platform configured to organize resource operations in relation to the loads or batteries of different customer sites of the system. 100. The DERMS 130 also provides for example an interface with the market server 107, and with the power network operator server 108.

For example, the market server 107 provides information relating to the price of electricity for current and/or future periods, and also information relating to activations required by the system operator 108.

The power network operator server 108 corresponds for example to a computer platform of a power network operator supplying electricity to customer sites. In Europe, the supply network operator corresponds for example to the transmission network operator (TSO) (Transmission Network Operator – TSO), and/or to the distributed system operator (DSO). For example, power grid operator server 108 provides activation commands to DERMS 130, and DERMS 130 provides control data, such as monitoring data and/or load statuses, to the server. supply network operator 108.

For example, DERMS 130 is configured to determine how power usage at customer sites can be scaled in light of electricity prices for current and/or future periods to reduce energy costs and/or generate revenue at customer sites, for example through fee reductions or balancing of network services. For example, the DERMS 130 is configured to transmit control signals to customer sites indicating periods during which charging the battery bank 110 from the power grid should be given priority, for example in view of relatively low prices of electricity. electricity, and periods during which the discharge of the battery bank 110 to the supply network should have priority, for example in view of relatively high electricity prices.

There is a block diagram illustrating an automatic load management system according to an exemplary embodiment of the present description.

The system of includes an energy usage scheduling module (ENERGY USAGE SCHEDULING), which is for example configured to generate an energy usage algorithm (ENERGY USAGE ALGORITHM) for a given customer site (CUSTOMER SITE) based on power consumption constraints (POWER CONSUMPTION CONSTRAINTS), and analysis of historical power consumption data from the customer site. The energy usage algorithm is for example transmitted to and stored in a memory of a device at the customer site capable of controlling one or more loads based on the energy usage algorithm, and thereby reducing a peak in power consumption for at least certain time intervals. This makes it possible, for example, to obtain a reduced energy cost in cases where the agreed energy tariff includes penalties for exceeding certain power usage limits. In some embodiments, the power usage algorithm may enable additional financial gain at the customer site by negotiating offsets with demand response actors (DRYAGE ACTORS), if for example the power usage algorithm includes the ability to reduce power consumption depending on the level of power demand on the power grid.

The system of is intended to be implemented in the power supply system 100 of the . For example, the usage scheduling module is implemented by the scheduling and monitoring module 132, and the power consumption constraints are provided by the markets server 107, or could be entered manually based on the tariff contracted. The energy use algorithm is for example stored by a memory of the DR unit 114 of the customer site. For example, module 132 generates, and stores at DR box 114 at each of customer sites 102, 104, a corresponding power usage algorithm to control power usage at the corresponding site.

There is a block diagram of part of the DR box (DR BOX) 114 of the customer sites 102, 104 of the according to an exemplary embodiment of the present description.

The DR box 114 comprises for example a processing device (P) comprising one or more processors, such as one or more microprocessors or microcontrollers. The DR box 114 further comprises a memory (MEMORY) 304 and input/output interfaces (I/O INTERFACES) 306 connected to the processing device 302 via a bus 308. For example, the memory 304 is non-volatile memory such as FLASH memory, and stores firmware that is executed by processing device 302 to implement the functions of DR box 114. DR box 304 may further include volatile memory , such as RAM (random access memory), for example DRAM (dynamic RAM) or SRAM (static random access memory). The memory 304 stores for example the energy use algorithm (ENERGY USE ALGORITHM) generated by the energy use programming module of the .

There is a flowchart illustrating the steps of an automatic load management method according to an exemplary embodiment of the present description. This method is for example implemented by appropriate hardware, such as by the elements of the system of the , and in particular by the DR box 114 and the central management system 106. Alternatively, one or more of the steps could be implemented manually, as will be explained in more detail below.

During a step 401, an initial energy tariff is for example selected for a given customer site. Such a selection could for example be made by the planning and monitoring module 132 of the central management system 106. According to a variant, this selection could be made manually. An example of a tariff selection based on the TURPE system applied in France will now be described. Of course, other pricing structures could be applied.

The TURPE system currently applied in France is a version known as TURPE 5. The following voltage ranges are defined, one of which is for example selected according to the power requirement of a customer site:
– LV ≤ 36 kVA: Low voltage connection (U ≤ 1 kV) to the distribution network (distribution network or "RPD");
- LV > 36 kVA: Low voltage connection (U ≤ 1 kV) to the distribution network (Pmax subscribed < 230 kW);
– MV: High voltage connection A (1 kV < U ≤ 50 kV) to the distribution network (Pmax subscribed of approximately 40 MW);
– HTB1: High voltage connection B1 (63 and 90 kV) to the transmission network (transmission network, or "RPT") (subscribed Pmax of 50 MW);
– HTB2: B2 high voltage connection (150 and 225 kV) to the transmission network (subscribed Pmax of 250 MW);
– HTB3: B3 high voltage connection (400 kV) to the transmission network (Pmax > 250 MW).

The LV ≤ 36 kVA and HTB3 voltage ranges, for example, have tariff structures that do not allow for a significant gain, and will therefore be excluded below.

In the present example, a tariff of the TURPE, known as the annual withdrawal component ("the annual withdrawal component"), is particularly considered here. For each of the voltage ranges indicated above, there is a different tariff version for each of three consumption profiles: long use (LU), medium use (MU) and short use (CU). There is also a choice between a winter peak: fixed or mobile. A fixed peak means for example that the cost of consumption during certain hours of the day will be higher than at others. For example, the times concerned are certain peak times each day from Monday to Saturday during the months of December, January and February, the peak times being, in one example, from 9 am to 11 am and from 6 pm to 8 pm. A moving peak average is based on PP1 days (peak period 1) of the French capacity market, corresponding to a maximum of 25 days between November ¹ and March 31, each identified the day before (D-1) by the TSO (for example, the "RTE" organization in France), and applies for a maximum of 150 hours. Such a mobile tariff is suitable for consumers able to reduce their consumption during these specific days.

For each tariff version, the annual withdrawal component CS is for example determined by the following equation: Or :
- i designates the time range of the energy tariff;
- bi is a power weighting coefficient defined by the time range i as a function of the voltage range and the tariff version;
- PSi is the subscribed power of time slot i;
- ci is an energy weighting coefficient for the time range i depending on the voltage range and the tariff version;
- Ei is the active energy withdrawn over one year during time period i, expressed in kWh;
- Pj is the average excess power over 10 minutes in kWh;
- j is the excess 10-minute point set for time range i; And
- for the HTA 1 tariff, an excess power coefficient is 0.11 rather than 0.04 for HTB1 and HTB2.

For example, there are five energy tariff time ranges defined as follows:
- i = 1: peak (for example winter);
- i = 2: peak hours, high season (for example winter)
- i = 3: off-peak hours, high season;
- i = 4: peak hours, low season (eg summer);
- i = 5: off-peak hours, low season.

In certain embodiments, the energy tariff imposes the condition that the subscribed power limits satisfy the following condition: .
In other words, it is not possible for a high power subscription to be chosen only for peak periods/high season.

The selection of the initial tariff involves for example the selection of one of the voltage ranges, and a selection of a subscribed power for each of the five energy tariff time ranges. For example, a voltage domain is selected based on the voltage need at the customer site, and the contracted power is for example selected as a function of the size of the customer site, and the anticipated power consumption of the loads. . The selection is for example made manually.

During a step 402, an acquisition phase is for example performed at the customer site. This acquisition is for example performed by the DR box 114 located at the customer site. An example of an acquisition phase will be described below in relation to the .

There is a graph representing electrical energy consumption, in kW, at a customer site for a period of 13 months from January 2019 to January 2020. Such a long acquisition phase of at least 12 months has the advantage of allowing data to be collected for all seasons of a year. However, other shorter acquisition phases between 1 and 3 months would also be possible. The curve of the represents for example the average power consumed during each time interval of 10 minutes of the acquisition phase.

Again in connection with the , during a step 403, an energy use algorithm is generated. This step is for example implemented by the central power management system 106, such as by the monitoring and planning module 132 (see ), based on data collected during the acquisition phase. The energy utilization algorithm is generated to reduce the cost of energy consumed. This is for example obtained by reducing the power consumption peaks by modifying the times at which the energy is consumed. This makes it possible, for example, to select lower subscribed power limits, and/or makes it possible to reduce the occurrences of excess power usage that exceeds a given subscribed power limit. As one skilled in the art will understand, reduced energy cost for the same amount of energy consumed implies that energy use is smoothed and/or shifted to periods of low demand, thereby helping to achieve the objective. technique for improving load balancing on the electricity network.

Considering as an example the energy consumption represented by the graph of the , it can be observed that the power consumption peaks occur during a relatively small number of time intervals, as will be described below in connection with Figures 7 and 8.

There is a graph representing electrical energy consumption at a customer site as a function of a percentage of points evaluated, based on the phase of acquisition of the . Each evaluated point corresponds for example to an average power consumption over a time interval of 10 minutes. In the example of the , less than 10 percent of the assessed points is beyond 1 MW, and only 1 or 2 percent is beyond 1.5 MW.

There is a graph representing electrical energy consumption compared to subscribed power limits. The curve 802 represents the subscribed power for off-peak hours, high season (i=3), which is for example equal to 1289 kW. The power subscribed for peak hours, high season (i=2), and for peak hours (i=1) is for example the same. Curve 804 represents the subscribed power for off-peak hours, low season (i=5), which is for example equal to 1550 kW. The power subscribed for peak hours, low season (i=4) is for example the same. A curve 806 represents a maximum power Pmax consumed for each month. A curve 808 represents the number of excess power usage events for each month. Of the fifteen excess energy use events, all occur in July except for one in June.

A certain cost saving could be obtained by adjusting the subscribed powers as follows:
- peak hours (i=1): reduction from 1289 kW to 950 kW;
- peak hours, high season (i=2): reduction from 1289 kW to 1000 kW;
- off-peak hours, high season (i=3): reduction from 1289 kW to 1000 kW;
- peak hours, low season (i=4): reduction from 1550 to 1500; And
- off-peak hours, low season (i=5): reduction from 1550 to 1500.

By switching from a fixed peak to a moving peak as described above, it would also be possible to reduce the subscribed power from 950 kW to 800 kW, as long as the limit is not exceeded during the corresponding PP1 days.

Another gain can be obtained by adjusting the consumption profile at the customer site, as will be described in more detail below in connection with the .

There is a graph representing electrical energy consumption at the customer site as a function of a percentage of points evaluated. The curve of the illustrates, in particular, consumption during the low season (i=4 and i=5). It can be seen that, by adjusting the consumption profile in relation to approximately 20 hours in this range, it is possible to reduce the contracted power from 1500 kW to 1400 kW.

In one embodiment, generating the power usage algorithm involves:
- the determination, on the basis of energy consumption data, of the main loads present at the level of the site. For example, this can be done by analyzing data consumption to detect the signature of certain types of installations, as known to those skilled in the art. For example, loads that are less than a certain percentage, such as 1% or less, of the site's total energy consumption can be ignored;
- the determination of the impact of each of the loads identified on the overall consumption during each time interval of 10 minutes; And
- the determination of the flexibility of each of the loads, for example by a sub-measurement of the power consumed by each load, and/or by interrogating the corresponding activity to determine its range of acceptable instructions. In some cases, at least some of this information is entered manually.

For example, each load is assigned:
- a power consumption chronogram indicating the highest and lowest consumption for each 10-minute time interval;
- high daily and low daily power consumption;
- high and low power consumption during certain time periods and for certain types of installations, such as for HVAC (heating, ventilation, and air conditioning).

With the above information, the power usage algorithm can for example be generated in order to redistribute the daily power consumption among the 10 minute time intervals, and thus reduce power consumption peaks. In addition, a priority can be assigned to certain loads. For example, the HVAC consumption moment can be generally advanced in time by a certain amount, depending on the thermal inertia of the heated or cooled area, and this type of load can be assigned a relatively low priority in the case excess power usage is detected. The synchronization of certain processes can be completely flexible. Other loads, such as lighting, for example, are not flexible at all, and may be assigned the highest priority for security reasons. Thus, the energy use algorithm is for example designed in order to take into account the amount of flexibility and the priority of each load. By way of example, a heating system may have a default setpoint of 24°C, but flexibility to reduce this setpoint to 22°C momentarily in order to reduce electrical power consumption, such a modification implying for example that the heating system will stop heating, and thus the electrical power consumption, for at least a 10 minute range.

In some embodiments, a separate power usage algorithm is defined for each power usage range, to adapt power consumption based on each corresponding subscribed power limit.

Referring again to the , during a step 404, the energy use algorithm is for example loaded on the customer site, and for example stored by a memory of the DR unit 114. The energy use algorithm is then activated in order to control the activation state of the loads present at the customer site. For example, the DR box 114 is configured to control the activation and deactivation of loads by activating or deactivating switches supplying a power supply to each of the loads, and/or by sending control signals, comprising for example one or more instructions, to the loads in order to modify their operation.

In some embodiments, it would also be possible for a customer site to enter into a load management commitment, as represented by a step 405 in , for example by agreeing to reduce the consumption of power drawn from the grid at certain times when needed, in exchange for reduced energy prices. Such a mechanism is for example also managed by the energy use algorithm.

The operation of the energy use algorithm at the customer site will be described below in more detail in relation to the .

There is a flowchart illustrating a method of automatically managing power consumption at a customer site according to an exemplary embodiment of the present description. The process steps of the are for example implemented by the DR box 114, or similar equipment, at the customer site. This has the advantage of allowing energy management to continue even if there is a breakdown in communications between the customer site and the central energy management system.

During a step 501, power consumption readings are received, for example collected by the counters 116 of the . In some embodiments, power consumption readings are received at regular time intervals, with each reading corresponding to, for example, a time range of 1 minute, 5 minutes, or up to 10 minutes, depending on responsiveness. desired from the system. The readings indicate for example an average power during the range, or a power gradient.

During a step 502, it is determined whether a power threshold has been exceeded. For example, the power threshold is set at a level that is lower than the limit above which penalties apply. In some embodiments, the power threshold is set between 85 and 95 percent of this limit.

If the threshold has not been exceeded, the method returns to step 501, during which new readings are received.

If the threshold has been exceeded, during a step 503, one or more of the loads are controlled based on the strategy defined by the power usage algorithm. For example, this may involve some load shedding, such as removing power to one or more of the lower priority loads.

There may be one or more additional control mechanisms to trigger reordering of the loads at the customer site. For example, as represented by a step 504, the control of the loads can be triggered each time a new time slot begins, this time slot corresponding for example to the time intervals of 10 minutes described above, or to time intervals of another duration. This allows scheduled activation of certain loads, such as heating or cooling devices.

Additionally or alternatively, as represented by step 505, load control may be triggered when a temperature threshold is exceeded by one or more temperature readings. For example, this temperature threshold may correspond to the temperature of a target zone to be heated or cooled, such as the interior temperature of a refrigerator or an oven. According to a variant, it could be an ambient or outdoor temperature. A temperature sensor is for example used to detect the temperature at the appropriate location. The energy use algorithm is then for example configured to adjust the synchronization of the heating or cooling phases according to the temperature readings, and in particular according to whether the temperature threshold is exceeded or not. In some embodiments, there may be more than one temperature threshold. For example, in the case of an outside temperature lower than 5°C, the energy use algorithm is configured to activate the heating between 6 a.m. and 8 a.m., whereas in the case of a outdoor temperature between 5°C and 15°C, the energy use algorithm is configured to activate the heating between 7 a.m. and 8 a.m.

For example, an electric heater at the customer site is configured to heat an area to a setpoint temperature for a period of heating use, and the input interface 306 (see ) of the DR box 114 is configured to receive one or more readings and/or temperature forecasts. The energy use algorithm defines for example one or more temperature thresholds of the readings and/or temperature forecasts below which said one or more radiators must be activated in advance of the period of use of the heating.

As a further example, a cooling system at the customer site is for example configured to cool a zone to a setpoint temperature during a cooling use period, and the input interface 306 (see ) is configured to receive one or more temperature readings and/or forecasts. The energy use algorithm defines, for example, one or more temperature thresholds of the temperature readings and/or forecasts above which said one or more cooling systems must be activated in advance of the cooling use period .

An advantage of the embodiments described here is that the management, in real time or near real time, of the power consumption at an electricity customer site is possible, and leads to an improved balancing between the response to demand on a supply network, and therefore to a reduction in electricity costs for the user.

Various embodiments and variants have been described. The person skilled in the art will understand that certain features of these various embodiments and variations could be combined, and other variations will occur to the person skilled in the art. In particular, it will be obvious to the person skilled in the art that the method described here could be applied to customer sites having any number of electrical loads, and possibly having one or more generators and/or electrical batteries. Further, the methods may be implemented by more than one power management device or DR box at different locations at a customer site, and in communication with each other, such as through SCADA or other centralized hardware.

Further, while embodiments have been described in which the analysis is based on 10 minute time intervals, in other embodiments a different time granularity could be used, such as 1 minute intervals. , 5 minutes, 30 minutes or 1 hour.

Finally, the practical implementation of the embodiments and variants described is within the abilities of those skilled in the art based on the functional indications given above.

Claims (10)

Load management device (114) comprising:
- an input interface (306) for receiving electrical power consumption readings at a customer site;
- a memory (304) storing a power usage algorithm defining power consumption rules to be applied based on the power consumption readings; And
- an output interface for controlling a plurality of electrical loads at the customer site based on the power usage algorithm. A load management device according to claim 1, wherein the power usage algorithm defines:
- one or more priorities to be applied between two or more loads of the plurality of loads when an electrical consumption threshold is exceeded, the electrical consumption threshold being for example between 85% and 95% of an electrical consumption limit; and or
- one or more load activation periods during which one or more loads must be activated; and or
- one or more load deactivation periods during which one or more loads must be deactivated. A load management device according to claim 1 or 2, wherein one or more of the plurality of electrical loads is an electric heater configured to heat an area to a set temperature during a period of use of the heater, and the input interface is further configured to receive one or more temperature readings and/or forecasts, and wherein the power usage algorithm defines one or more temperature thresholds of the temperature readings and/or forecasts above below which said one or more electric heaters must be activated in advance of the period of use of the heating. A load management device according to any of claims 1 to 3, wherein one or more of the plurality of electrical loads is a cooling system configured to cool an area to a setpoint temperature during a period of use of the cooling, and the input interface is further configured to receive one or more temperature readings and/or forecasts, and wherein the power usage algorithm defines one or more temperature thresholds of the readings and/or temperature forecasts above which said one or more cooling systems must be activated in advance of the period of use of the cooling. Load management system including:
- the load management device (114) according to any one of claims 1 to 4; And
- a centralized processing system (106) configured: to generate the energy usage algorithm based on historical power consumption readings of the plurality of loads over a period of at least two months and based on one or more power consumption constraints; and to transmit the power usage algorithm to the load management device. Load management method comprising:
- receiving, through an input interface (306) of a load management device (114), power consumption readings at a customer site; And
- generating, at an output interface (306) of the load management device, control signals to control a plurality of loads (118) at the customer site based on a utilization algorithm energy stored in a memory (304) of the load management device, the energy usage algorithm defining energy consumption rules to be applied based on power consumption readings. A method according to claim 6, wherein the power usage algorithm defines:
- one or more priorities to be applied between two or more loads of the plurality of loads when a period of excessive electricity consumption is detected; and or
- one or more load activation periods during which one or more loads must be activated; and or
- one or more load deactivation periods during which one or more loads must be deactivated. A method according to claim 6 or 7, wherein one or more of the plurality of electrical loads is an electric heater configured to heat an area to a set temperature during a period of heating use, the method further comprising:
- the reception, via the input interface, of one or more readings and/or temperature forecasts;
- the comparison, by the load management device, of said one or more readings and/or temperature forecasts with one or more temperature thresholds defined by the energy use algorithm; And
- the activation of said one or more electric heaters in advance of the period of use of the heating if at least one of the readings and/or temperature forecasts is below said one or more thresholds. A method as claimed in any of claims 6 to 8, wherein one or more of the plurality of electrical loads is an electrical cooling system configured to cool an area to a setpoint temperature during a period of cooling use, the method further comprising:
- the reception, via the input interface, of one or more readings and/or temperature forecasts;
- the comparison, by the load management device, of said one or more readings and/or temperature forecasts with one or more temperature thresholds defined by the energy use algorithm; And
- the activation of said one or more cooling systems in advance of the period of use of the cooling if at least one of the readings and/or temperature forecasts is above said one or more thresholds. A method according to any of claims 6 to 9, further comprising:
- generating, by a centralized processing system (106), the energy usage algorithm based on historical power consumption readings of the plurality of loads over a period of at least two months and over the basis of one or more power consumption constraints; And
- the storage of the energy use algorithm in the memory (304) of the load management device.