EP3469675A1

EP3469675A1 - Method and device for controlling at least one electric apparatus

Info

Publication number: EP3469675A1
Application number: EP17732602.2A
Authority: EP
Inventors: Egbert Wouter Joghum Robers; Kaz Marc VERMEER; Jorrit LUCAS
Original assignee: Peeeks BV
Current assignee: Peeeks BV
Priority date: 2016-06-10
Filing date: 2017-06-09
Publication date: 2019-04-17
Also published as: WO2017213509A1; NL2016935A; NL2016935B1

Abstract

The present invention relates to a method and device for controlling at least one electric apparatus, comprising a calculator for calculating an expected power demand of the at least one apparatus for a certain time slot, communication means, for communicating the expected power demand to a power grid operator or transmission system operator and a controller, configured for supplying the predicted amount of power to the apparatus.

Description

Method and device for controlling at least one electric apparatus

The present invention relates to a method and device for controlling at least one electric apparatus. In particular, the invention relates to controlling the at least one electric apparatus dependent on the state of the electrical grid, that is, the amount of electric energy available on the grid compared to the energy demand at the same time.

An electrical grid in itself cannot store energy. At any moment, the amount of electricity generated and put into the grid has to be equal to the amount of electricity drawn by energy consumers. If there is a shortage (the grid as a whole needs more electricity than what is generated) this can lead to a dropping of voltage in the grid, also called a brownout. Brown-outs can damage equipment connected to the grid. Also, the whole grid or parts thereof can experience black-outs: when this occurs the energy transport comes to a full stop and the grid has to be started up completely. If there is a surplus of electricity (i.e. more electricity is generated than what is consumed) this can lead to over voltage, which can also damage equipment connected to or part of the grid. Also these over voltages can result in tripping of safeguards, creating a black out. Surpluses or shortages also have other effects on the grid besides the voltage drops or spikes. The spinning mass present in generators connected to the grid experiences a larger resistance, as the load on the grid is larger than was intended. This leads the generators to slow down, which in turns leads to a lower frequency in the grid, as the rotational speed of these generators is tied directly to the grid frequency. This poses an additional reason to keep the grid balanced: some equipment uses this grid frequency as a time keeping mechanism.

Keeping stability of the grid is not easy, and the complexity of this task is increasing. Not only is the amount of generators and consumers running in the millions, but many of the consumers are not under any form of control by the parties responsible for keeping the grid stable: any individual can at will switch on or off their light, water heater, computer or other appliance. On top of this, the amount of electricity consuming assets is ever increasing, and due to the prices of photovoltaic panels dropping, the amount of electricity generated out of control of utilities or grid operators is also increasing. Due to the increase in photovoltaic and wind generators driven by government incentives to promote clean energy generation the relative amount of uncontrollable generation compared to controlled generation is increasing: wind and solar is strongly depending on weather circumstances.

Most countries have an authority charged with the task to keep the national grid balanced, the national grid operator or Transmission System Operator (TSO). Using several types of reserves, the TSO can adapt the electric generation capacity to follow the instantaneous energy demand from its grid. The TSO forecasts the total electricity demand and supply one day ahead, in 15 minute intervals. These 15 -minute time- intervals are referred to as Program Time Units, or PTUs. In order to create the forecast, the TSO requires every party with a direct connection to the grid to send an E- programme, in which they describe their energy demand and supply for the next day. These programs have to be balanced: for every PTU, the expected amount of generated electricity has to match the expected electricity demand. A party required to send in such a program is called a Balance Responsible Party (BRP), which refers to the requirement of perfect balance in their E-programmes. After collecting all programs from the BRPs, the TSO is able to forecast the electricity demand and supply for the next day.

During the following day, the TSO monitors the actual electricity supply and demand. The power availability on the grid at any moment is the amount of electricity that is generated (supply) minus the amount of energy that is used (demand). If more electricity is generated than demanded, there is an over-capacity. If less electricity is generated than demanded, there is an under-capacity. When any imbalance appears, the TSO takes measures in order to re-balance the grid as soon as possible.

Other authorities can have similar tasks. Examples of other authorities are: DSOs (Distribution System Operators), electricity generators, electric utilities, power exchanges, regulators or demand-response aggregators. The authorities usually have automated systems that perform these tasks automatically. So when we refer to the authority, we particularly mean their APIs, computer systems and/or control systems. This can derived from context.

However the processes to balance the electricity grid can be painstaking and include manual labor, in particular as soon as the number of actors increases. It is a goal to take away the disadvantages of the prior art, in particular when the number of actors becomes large, for instance above 500 actors.

The invention thereto proposes an automated device for controlling at least one electric apparatus, comprising a calculator for calculating an expected power demand of the at least one apparatus for a certain time slot, communication means, for communicating the expected power demand to a power grid operator or transmission system operator, a controller, configured for supplying the predicted amount of power to the apparatus. The device according to the invention thus actually controls the energy use of an apparatus, and contributes to the grid balance, by matching the actual use to the predicted use.

But at a point there may be a situation where there is a surplus / over-capacity or a deficit / under-capacity of electricity in the electricity grid. This situation can be determined from indicators, which can be combined: The voltage of the electricity grid, the grid frequency, the phase shift of the electricity grid, price signals in the energy market, particularly a published imbalance price. Some of these signals (for example the imbalance price) have a time lag. To solve this the invention uses prediction to predict that signal. For this prediction models are used, in combination with the other indicators. These prediction models are trained with historical data. These models can be regression models.

In a preferred embodiment, the communication means are configured for receiving information on power availability on the grid; and wherein the controller is further configured for supplying more than the predicted power to the at least one electric apparatus when there is public information on the situation of an over-capacity; and supplying less than the predicted power to the at least one electric apparatus when there is public information on the situation of an under-capacity.

This embodiment has the advantage that the device can compensate for an imbalance caused by other apparatuses on or off a site. The communication means may for instance be configured for deriving the information on power availability in the electricity grid via the instantaneous energy price. This price is an indicator for the energy (im)balance of the grid. The invention proposes an apparatus for optimizing electricity use for one or more electricity users. It controls controllable electricity apparatuses, such as cooling machines, electrical heating machines or pump systems. It uses energy measurement to predict the electricity use of the electricity users. An advantage of this method is that energy cost can be lowered without actually lowering electricity usage. On a local level this is the case because parties that supply energy can benefit from the balance in the electricity grid and reimburse the energy user. On a macro level this is also true, because by balancing the electricity grid, there is more room for cheap, sustainable forms of electricity generation such as solar or wind energy, which will lower cost for electricity in the future.

An electricity user according to the present invention can be a site with an electricity connection and one or more controllable electricity assets. Also it can be a controllable electricity asset itself; this is an electric apparatus that has a (partially) controlled power consumption. Also an energy user can be an organization owning one or more of the above.

The invention is focused on the use in combination with assets of at least 50kW. The cost of application on assets with less power is not in a proper ratio with the effect it can have on the balancing markets.

The way that the energy users are monitored can for instance be measuring the electricity use, but instead thereof or in addition thereto measuring the amount of people that work at a location, measuring financial transactions, measuring maintenance of one or more electrical apparatuses.

In an embodiment of the present invention, in the device according to the invention, the calculator is configured for calculating the expected power demand of the at least one apparatus based on indirect indicators, different than measured power demand. The predictions of the energy use of an electrical asset may be an important factor in this invention. These predictions are made with forecasting models. These models can range from simple linear regression, but more powerful methods can be used, such as Exponential Triple smoothing: trend and seasonality corrected exponential smoothing (Winter's model), regression of Gaussian processes, neural networks, fuzzy logic and other machine learning or statistical techniques.

Preferably these predictions use other sources than just the energy monitoring to get better predictions such as: personnel roster, financial transactions, good received, goods shipped, Enterprise Resource Planning statistics, maintenance schedule or

measurements from other energy users and/or the examples given above: measuring the amount of people that work at a location, measuring financial transactions, measuring maintenance of one or more electrical apparatuses. These alternative sources are for instance used as follows.

In the case of a cooled trading area the refrigeration machines are, for safety and comfort, switched off when people are working in the cooled area. This affect the spread of the electricity consumption of this location as they will likely cool more in hours that no personnel is present. The personnel roster can here be used to enhance the prediction of electricity consumption.

In another case, an ice skating rink's electricity consumption fluctuation can primarily be attributed to the activity of the cooling machines. The type of activities that take place in the ice skating rink greatly affects the needed temperature. In case of competition races, the ice needs to have a higher quality than on normal training days. This is done by further decreasing the temperature of the ice, which requires the cooling machines to be more active on those days. This connection with the race schedule can be used to enhance predictions of electricity consumption.

The system employs statistical analysis to find the correlation between the indirect indicators and the electrical ones. For this simple correlation methods can be used as well as more advanced techniques, such as Gaussian Processes, neural networks and other Machine Learning techniques. For example there is a relation between visitors and the electrical use of a cooling machine for an ice skating rink. Finding the amount of visitors can come directly from counting systems, cash registers, drinks sold in the cafeteria, but also prognoses based on previous years, day of the week and weather conditions. The same ice skating rink may be influenced by the amount of employees, opening of doors (which need a door sensor) and finance running through books. One or more of these factors can be taken into account.

For a simple example the use of electricity is, or can be assumed, linearly (with an offset) dependent on the amount of visitors. Finding the offset and slope of the relation can be calculated with a simple least mean squares filter method.

The method can also be used to predict other important parameters, because it has very good knowledge about the energy use. Changes in the energy use can be symptoms of changing use, wear on machines or changes in the business that the energy user is in. Therefore the method according to the invention may be used the method to predict for example: Required resources, such as personnel, forklifts, money or maintenance to electric apparatuses.

Also the method may be used to detect that the situation at the energy user has changed. For example there are more electrical apparatuses installed, or a machine has changed properties, changing the behaviour.

An embodiment of the invention consists of a refrigeration machine on a site with a cold store warehouse. The refrigeration machine is at least partially controlled by a box that communicates to the cooling machine, giving set points for power or temperature, also the box gets information from the cooling machine, for example: various temperatures, power, currents, voltages, warnings, errors, or messages. The box also connects to a server that hosts the predictor. The server also is connected to power measurements of the site where the refrigeration machine is located. For example the entire-site power or the power of major electricity users, including the refrigeration machine are measured in near-real time. The server hosts a controller that decides what the refrigeration machine should do. These decisions are communicated back to the box that gives set points to the refrigeration machine. Besides the device mentioned above, the invention further relates to a method for controlling at least one electric apparatus, comprising the steps of calculating an expected power demand of the at least one apparatus for a certain time slot,

communicating the expected power demand to a power grid operator or transmission system operator and supplying the predicted amount of power to the apparatus.

In particular, the method may further comprise the steps of receiving information on power availability in the electricity grid, supplying more than the predicted power to the at least one electric apparatus when there is an over-capacity communicated by the grid operator or transmission system operator, and supplying less than the predicted power to the at least one electric apparatus when there is an under-capacity communicated by the grid operator or transmission system operator.

In an embodiment, the method comprises the step of deriving the information on power availability in the electricity grid via the instantaneous energy price, or the step of deriving the information on power availability from calculating the expected power demand of the at least one apparatus based on indirect indicators, different than measured power demand. In some occasions the electricity user has to prove that a certain amount of energy or power or a change in power is used or generated. This proof has to be given to an authority, such as a TSO or a BRP. This prove usually is electricity meter data.

However this proof may be tampered with. Current solutions are: restricting amount of time you have to offer the proof, in order to restrict tampering and/or a trusted 3^rd party that measures and keeps records. According to the present invention, it is proposed that the latter is replaced by a so called blockchain or similar distributed book keeping system. This way tampering of the records is prevented.

A blockchain is a distributed database that maintains a continuously-growing list of data records hardened against tampering and revision. It consists of data structure blocks which hold exclusively data in initial blockchain implementations, and both data and programs in some of the more recent implementations with each block holding batches of individual (trans)actions and the results of any blockchain executables. Each block contains a timestamp and information linking it to a previous block. To a blockchain, energy transaction need to take place. The blockchain registers these transactions.

For example, in financial transactions of Bitcoins the following takes place. To send bitcoins, one needs two things: a bitcoin address and a private key. A bitcoin address is generated randomly, and is simply a sequence of letters and numbers. The private key is another sequence of letters and numbers, but unlike the bitcoin address, this is kept secret. A bitcoin address may be considered as a safe deposit box with a glass front. Everyone knows what is in it, but only the private key can unlock it to take things out or put things in.

When a first person wants to send bitcoins to a second person, he uses a private key to sign a message with the input (the source transaction(s) of the coins), amount, and output (recepient's address).

He then sends them from her bitcoin wallet out to the wider bitcoin network. From there, other bitcoin agents in the network verify the transaction, putting it into a transaction block and eventually solving it.

In the present case, transactions of Energy are made (kWh) in a certain time slot. The measurements of the energy use at a certain site can be inserted into the block chain as well, to get verified energy uses. For this, the energy meter can contain and/or generate private keys.

The information can be requested from the block chain by simply requesting the verified transactions from the actors in the network. The blockchain can also be used to differentiate between two actors on a single measurement point, such as two energy suppliers on a single connection, two demand- response aggregators in a (sub-)grid or even suppliers, aggregators and individual users in a more complex structure. In those cases all the actions of each actor, agreements between the actors and regulation can be added into the blockchain. In an embodiment the aforementioned authority can be partially or fully a blockchain. In that case the authority would be a DAO (A decentralized autonomous organization). A decentralized autonomous organization (DAO) is a organization that is run through rules encoded as computer programs called smart contracts. A DAO's financial transaction record and program rules are maintained on a blockchain.

In an embodiment the blockchain is used in combination with smart contracts. Smart contracts are computer protocols that facilitate, verify, or enforce the negotiation or performance of a contract, or that make a contractual clause unnecessary. Smart contracts usually also have a user interface and often emulate the logic of contractual clauses. Clauses may thus be made partially or fully self-executing, self-enforcing, or both.

The above mentioned examples are for illustrative purposes only and do in no sense limit the scope of protection of the present invention, as defined in the following claims.

Claims

1. Device for controlling at least one electric apparatus, comprising:

A calculator for calculating an expected power demand of the at least one apparatus for a certain time slot;

Communication means, for communicating the expected power demand to an authority, such as a power grid operator or transmission system operator;

A controller, configured for supplying the predicted amount of power to the apparatus,

characterised in that:

the calculator is configured for calculating the expected power demand of the at least one apparatus based on indirect indicators, different than measured power demand.

2. Device according to claim 1, wherein the indirect indicators are chosen from the group of:

A personnel roster,

financial transactions,

good received,

- goods shipped,

a maintenance schedule, or

data from a different electric apparatus.

3. Device according to claim 1 or 2, wherein the calculator is configured for

calculating the expected power demand of the at least one apparatus based on data from Enterprise Resource Planning software.

4. Device according to any of the preceding claims, comprising a blockchain for record keeping.

5. Device according to claim 1, wherein:

the communication means are further configured for receiving information on power availability on the electricity grid; and wherein:

the controller is further configured for: o supplying more than the predicted power to the at least one electric apparatus when there is an over-capacity in the grid; and

o supplying less than the predicted power to the at least one electric

apparatus when there is an under-capacity in the grid.

6. Device according to claim 2, wherein the communication means are configured for receiving the information on power availability from an authority.

7. Device according to claim 2, wherein the communication means are configured for deriving the information on power availability on the electricity grid via an instantaneous energy price.

8. Method for controlling at least one electric apparatus, comprising the steps of: calculating an expected power demand of the at least one apparatus for a certain time slot;

communicating the expected power demand to an authority;

supplying the predicted amount of power to the apparatus,

characterised by:

deriving the information on power demand from calculating the expected power demand of the at least one apparatus based on indirect indicators, different than measured power demand.

9. Method according to claim 8, wherein the indirect indicators are any of

personnel roster, financial transactions, good received, goods shipped, a maintenance schedule, or the expected power demand of the at least one apparatus based on data from a different electric apparatus.

10. Method according to claim 8 or 9, further comprising the step of deriving the information on power demand from calculating the expected power demand of the at least one apparatus based on data from Enterprise Resource Planning software.

11. Method according to claim 8, 9 or 10, wherein records are collected and/or kept in a blockchain.

12. Method according to claim 12, further comprising the steps of:

supplying more than the predicted power to the at least one electric apparatus when there is an over-capacity; and

supplying less than the predicted power to the at least one electric apparatus when there is an under-capacity.

13. Method according to claim 12, further comprising the step of receiving the information on power availability in the electricity grid from an authority.

14. Method according to claim 12, further comprising the step of deriving the information on power availability in the electricity grid via an instantaneous energy price.