Method for stabilizing the electrical energy supply grid

Abstract

The present invention relates to a method for stabilizing an electric energy grid having at least one control area, the method comprising the steps of: determining, for at least one control area, a forecast of control area differences for a future time interval (e.g., starting from one hour in the past) and a forecast of the balancing power required for said time interval using methods from the field of artificial intelligence, preferably a Markov chain function; and procuring and supplying the forecasted balancing power to the electric energy grid for the future time interval. The method according to the present invention allows for good quantitative planning of balancing power requirements, which can be traded quantitatively, for example, as secondary balancing power through an intraday electricity market. The share of variable renewable energy in the balancing power can also be increased.

Description

[Technical field]

[0001] The entire content of the priority application German Patent Application No. 102019212773.8 is incorporated herein by reference. [Background technology]

[0002] The present invention relates to a method for the stabilization of an electrical energy supply grid having at least one control area, the method being conceived in relation to the at least one control area.

[0003] An overview of the structure and functioning of the electrical energy supply grid is given in [1].

[0004] From a system-technical point of view, the electrical energy system includes the totality of all technical facilities necessary for the realization of the generation, transmission and distribution of electrical energy within the system boundary for specific control-technical reasons. For frequency and active power control, the area defined by the system boundary is called the control area.

[0005] The input power per time unit fed into the grid, i.e. the conversion of energy, for example rotational or thermal energy, into electrical energy (corresponding to energy production), is defined with a negative sign. The output power drawn from the grid per time unit, i.e. the conversion of electrical energy of the grid into other forms of energy, for example thermal or kinetic energy (for example rotational energy), (corresponding to energy consumption), is defined conversely with a positive sign.

[0006] In a deregulated electricity market, the power trading business, or more precisely the energy trading business, realized for the time being without knowledge of grid coordination, requires the establishment of so-called balancing groups and balancing areas. In each balancing group and each balancing area, the predicted discharge power and the contractually secured supply power are coordinated or balanced according to a plan so that they are equal. The integration of all balancing groups into the system balance allows the grid coordination to maintain and account for the balance between the generated and consumed electrical energy according to a plan.

[0007] A balancing group therefore contrasts feed-in and discharged power, which must remain largely balanced at all times for physical reasons or from a frequency regulation point of view. The grid operator compensates for the remaining differences with feed-in reserves or balancing power, as will be more precisely referred to below.

[0008] Both the supply and discharge power transitions are planned on the basis of specific "schedules". When implementing all the schedules of a balancing group, and therefore of the entire control area, control area variances always arise as a result of unexpected deviations from the predicted load progression or unplanned losses of generating capacity.

[0009] Thus, the control area variance (also called the control area balance or system balance) is the sum of all the supply outputs and discharge outputs in the control area. For each balancing group, the sum of all the supply outputs and discharge outputs in the balancing group is called the variance balancing group aggregation or balancing group variance.

[0010] The grid operator must eliminate these control area differences by using positive or negative reserves, so-called balancing reserves, within the scope of its frequency maintenance duties. The grid operator generally obtains the right to purchase balancing reserves in advance, after a prior open tender for power plants operating at part load, so-called spinning reserves, located inside and outside its control area. In the meantime, a reserve is provided by these plants. When utilized, a corresponding amount of balancing power, positive and negative, is further provided. For the provision of balancing reserves, capacity costs are charged at a capacity price, and for the supply of balancing power, power costs are charged at a metered price. The capacity costs are added to the grid usage costs, and the power costs are charged to the balancing group responsible for the supply of balancing power on a causal basis.

[0011] Furthermore, in the case of large renewable energy installations, so-called supply management can be used if meteorological conditions would result in a higher output from the renewable energy installation, in particular from a wind power installation, than can be distributed or transmitted within the grid. Supply management consists in reducing the output of the renewable energy installation in the relevant grid section by the amount necessary to locally prevent a grid bottleneck.

[0012] Supply reserves are mainly sourced through flexible production, i.e. the controllable supply output of controllable renewable energies such as biogas plants, hydropower or hydrogen and fossil fuels or nuclear energy, and through variable production, i.e. the variable supply output of uncontrollable renewable energies that are dependent on the weather, such as wind or solar energy.

[0013] Conventional systems for calculating the required reserve capacity are designed to only react or to make very short-term, forward-looking adjustments. Allowing schedule deviations that are beneficial for the system to remain at the balancing group level is referred to in this context as passive balancing. Here, the starting point is information about the control area balance that exists in real time. Here, there is no time in advance for trading balancing power in advance.

[0014] So far, the time for intraday trading has only been shortened to reduce imbalances and balancing power demands due to less forecasting errors on production and consumption, using forecasting algorithms similar to those disclosed in the present invention to minimize regulating power, especially for renewable energy consumption and production.

[0015] The patent document WO 2005 / 023333 shows a method for operating an entire energy grid in the case of distributed energy production. The grid is made up of three supply levels where energy is produced and distributed. The method provides a mechanism for stabilizing the grid through the use of balancing power and describes the cooperation of distributed producers.

[0016] In the prior art, the imbalance between production and demand is resolved primarily by supply reserves from flexible power plants. In this case, priority is given to energy from conventional power plants based on fossil fuels, which leads to increased CO2 production. The procurement issues linked to the supply of balancing power as power plant reserves and linked to the procurement of supply reserves are assigned to each balancing group manager in the form of adjustment power in response to the balancing group difference. In this procedure, the demand for balancing power cannot be planned and the size of the supply of balancing power is not dynamically determined depending on the situation. The metered price arises only when the balancing power is demanded and is determined after the conclusion of the commercial transaction for the balancing power. [Prior art documents] [Patent documents]

[0017] [Patent Document 1] International Publication No. 2014 / 166524 [Non-patent literature]

[0018] [Non-Patent Document 1] Schwab, AJ, “Elektroenergiesysteme-Erzeugung, Uebertragung und Verteilung elektrischer Energie“, 5. Auflage, Springer Verlag, Berlin, 2017 Summary of the Invention [Problem to be solved by the invention]

[0019] The object of the invention is to improve the planability of the balancing power required to eliminate control area differences in an electric energy supply network and the stability of the electric energy supply network. [Means for solving the problem]

[0020] The problem is solved by a method according to claim 1, a computer program according to claim 8 and a computer program product according to claim 9. Advantageous configurations of the invention are contained in the dependent claims.

[0021] The invention is based on the idea of ​​improving the plannability of pre-supply reserves, i.e. the predicted control area difference, through the prediction of the beneficial energy storage and flexibility control for the system, using both flexible and variable production, which results in increased plannability, increased stability of the electrical energy grid and an increased share of variable renewable energies.

[0022] The method according to the invention for stabilization of an electrical energy supply grid having at least one control area comprises, for the at least one control area, the following steps: - A future point in time t from the present N and the length of the interval Δt; - temporal interval [t N ,t N +Δt], the time course of the difference in control area ΔP RZ Determining (t) through a method in the field of artificial intelligence, preferably a function using a Markov chain; - temporal interval [t N ,t N +Δt] required balancing power ΔE RL is expressed as the time interval [t N ,t N +Δt], the time course of the difference in control area ΔP RZ (t), - temporal interval [t N ,t N +Δt]

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[0023] The method according to the invention allows for good quantitative planning of the balancing power requirements, which can then be quantitatively traded as secondary balancing power, for example also through the intraday power market. The share of variable renewable energies in the balancing power can also be increased.

[0024] The prediction for the control zone difference is preferably determined by the calculation of a Markov chain, in particular by the calculation of a higher order Markov chain. For this purpose, the algorithm CondEx is preferably used. The algorithm is derived from a basic physical model with assumptions based on direct probability. The algorithm CondEx can be trained by itself and is able to recognize and predict elaborated patterns.

[0025] In a preferred embodiment of the present invention, the time interval [t N ,t N +Δt] required balancing power ΔE RL is the time interval [t N ,t N +Δt], the time course of the difference in control area ΔP RZ (t). In addition, the time interval [t N ,t N +Δt] for the balancing power required RLvoraus is the time interval [t N ,t N +Δt]

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[0026] Thus, the control zone variance and its prediction are determined in a mathematically straightforward manner.

[0027] In various configurations of the method according to the invention, which are modifications of the last-mentioned embodiment and are described below, a condition for system profitability is determined, whereby system profitability is understood to be the degree of consistency of advance reserves (in the context of the forecast of the grid state), i.e. the agreement between forecasted reserves and actual required reserves.

[0028] As a predicted, uncertainly determined magnitude, the pre-balancing power is in some of these embodiments determined to a value different from zero only under certain conditions, depending on selected criteria of benefit to the system. Such conditions may consist in the predicted control area variance having the same sign as the balance between predicted positive and negative supply reserves and / or having a different sign from the predicted grid frequency variance, and / or in the absence of supply management or in the predicted pre-balancing reserve being negative.

[0029] In a preferred embodiment of the present invention, the time interval [t N ,t N +Δt] required balancing power ΔE RL is a time interval [t N ,t N +Δt], the time course of the control area difference ΔP RZ (t). Furthermore, if a second condition for the system's usefulness is met, or if multiple second conditions for the system's usefulness are cumulatively met, the time interval [t N ,t N +Δt] for the balancing power required RLvoraus is the time interval [t N ,t N +Δt]

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[0030] In a further preferred embodiment of the invention, the first condition or one of the first conditions for the usefulness of the system is a control zone difference ΔP RZ The sign of (t) is the balance P between positive and negative reserve capacity at time t. RL The second condition or one of the second conditions for the usefulness of the system is the same as the sign of the time interval [t N ,t N +Δt] predicted control locus difference

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[0031] In a further preferred embodiment of the invention, the first condition or one of the first conditions for the usefulness of the system is a control zone difference ΔP RZ The sign of (t) is the predicted grid frequency difference Δω at time t. progn The second condition or one of the second conditions for the usefulness of the system is a time interval [t N ,t N +Δt] predicted control locus difference

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[0032] In a further preferred configuration of the invention, the first condition or one of the first conditions for the usefulness of the system is that the supply management signal Einsman(t) at a particular time t has a value "not supply management" or that the advance supply reserve ΔP at the time t has a value "not supply management". RZ The second condition or one of the second conditions regarding the usefulness of the system is that at time t N Predicted supply management signals in the relevant region at Einsman progn (t N ) has a value of "not supply management" or the time interval [t N ,t N +Δt] predicted control locus difference

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[0033] The first condition for usefulness for the above system is the required balancing power ΔE RL When calculating or predicting the required balancing power ΔE RLvoraus They may be applied individually or cumulatively.

[0034] The various conditions of system usefulness according to various embodiments of the present invention raise the potentially possible share of secondary balancing power that is plannable within the framework of the smart balancing mechanism and therefore quantitatively tradable through the intraday electricity market to a relative share of up to a potential 77% in the control area balance to be adjusted depending on the criteria used for system usefulness, thereby lowering the share of "must run capacity" based on traditional fossil energy sources based on increased plannability.

[0035] The plannability of the management instruments for procuring reserves also increases the possibility of integrating the weather-sensitive forecasts of variable renewable energies into a unified process of forecasting, trading and procurement of balancing electricity from renewable energies. In this case, it will be important to reduce the CO2 emissions relative to balancing electricity from conventional plants. The share of balancing electricity from renewable energies in the control area balance can thereby potentially rise to 77%, depending on the criteria regarding the usefulness for the system and the availability of renewable energies.

[0036] In this way, by using storage and flexibility to the system's advantage, through the forecasting of grid-determining variables grid bottlenecks, grid frequency, supply reserves and control area variances, a jointly planned pre-balancing power from flexible and variable production is traded within the framework of a smart balancing process in the sense of a pre-determined power and associated actual metered price, enabling an optimized combined use of flexibility and renewable energies.

[0037] In a further preferred configuration of the invention, the current and required balancing power ΔE RLvoraus The time instant t at which the time interval for which is predicted begins N The time interval between is at least one hour.

[0038] Therefore, conversely, the implementation of the mechanism for determining balancing power, aimed at the plannability of the imbalance between energy production and energy consumption in the electric energy supply network, is brought forward by at least one hour before the time of requesting balancing power. Not only the price for the procurement of capacity (capacity price), but also the power to be procured is quantitatively determined and traded, including at a unit price, so that procurement can be carried out quantitatively after determining in advance a unit price that can be minimized due to plannability.

[0039] The present invention develops balancing power procured by renewable energies while simultaneously minimizing balancing power on a wide scale, for example in the double-digit percentage range. The application-specific use of the preferably used forecasting algorithm CondEx places a crucial application scenario of artificial intelligence methods in the context of renewable energies, integrated plannability, tradability and stabilization of the energy system.

[0040] The potential for reducing CO2 emissions that this offers must be considered as broad.

[0041] The method according to the invention can further be automated through the means of intelligent communication using type-based messages between actors (demonstrators) connected to each other via communication lines within the energy supply system.

[0042] In summary, the present invention and its preferred embodiments are based on a combination of forecasts regarding the various variables that determine the balance of energy production and energy consumption and the benefits to the system of the flexibility to be used. A large part of the balancing power can be traded in terms of pre-determining reserves at least one "hour ahead" within the framework of a smart balancing mechanism and planned for the market size in terms of price as for the amount of energy. In this case, a larger share of renewable energy can be used as such, with adjustments through the intraday market being pre-empted.

[0043] In the following, examples of the present invention will be described in detail with reference to the accompanying drawings, which are to be understood as illustrative and not limiting of the present invention. [Brief description of the drawings]

[0044] [Figure 1a] FIG. 13 shows a one-hour forecast of the control area variance in the control area of ​​the supply network operator TransnetBW. [Figure 1b] FIG. 1b shows the predicted control area variance for the control area according to FIG. 1a after connecting the prediction of the usefulness of the control area variance for the system. [Figure 2a] FIG. 1 shows a one-hour forecast (of signs) of the balance of reserve capacity in the control area of ​​the supply network operator TransnetBW. [Figure 2b] FIG. 2b shows a one-day-ahead forecast of grid frequency variance for the control area according to FIG. 2a. [Figure 3a] FIG. 1 shows the hour-ahead forecast of pre-provision reserves in the control area of ​​the supply network operator TransnetBW after connecting the forecast of the beneficial effect of pre-provision reserves on the system through the same sign as the forecasted control area variance. [Figure 3b] FIG. 3b shows the day ahead reserve for the control area according to FIG. 3a after connecting a prediction of the beneficial effect of the reserve on the system through the opposite sign to the predicted grid frequency difference ("day ahead"). [Figure 4] Demonstrator interaction diagram for field testing of “hour ahead” smart balancing supported by prediction using CondEx. [Diagram 5] FIG. 1 illustrates a circuit for adjusting pre-supply reserve forecasts and demands. [Figure 6] FIG. 1 illustrates a circuit for predicting and adjusting demand for pre-supply reserves beneficial to the system. [Figure 7] FIG. 13 illustrates an agent-based domain model of the business logic layer realized in CondEx for use case modeling with roles and intelligent communication on type-based messages following a publish-subscribe model. [Figure 8] FIG. 11 is an interaction diagram of the demonstrator in a field test of forecast-supported hour-ahead planning and pre-balancing power trading using CondEx by a grid operator. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0045] Examples of the present invention are described in detail below.

[0046] A computer-implemented control range difference over N time steps of length Δt.

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[0047] At this time,

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[0048]

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[0049] The method according to the invention uses known mathematical techniques, also called artificial intelligence techniques, to predict events relating to future scenarios.

[0050] The field of application is smart balancing based on the prediction of control area differences, whereby the stabilization of the system, for example in sub-networks of energy suppliers, can be regulated by being able to act in a beneficial way for the system in the form of foresight tracking adjustments.

[0051] Informed forecasts regarding control area variances, instead of information that may possibly be provided by the supply network operator

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[0052] Differences within a balancing group are left alone if they are beneficial to the system for national economic minimization of regulated and balanced power, and are otherwise resolved by linking to the intraday market, as is common in the past. In general, flexibility in this regard can be used to the benefit of the system.

[0053] With such a configured smart balancing process, a time window of at least one hour is available in the method according to the invention for system-beneficial stabilization of an electrical energy grid.

[0054] Therefore, for schedule deviations that are beneficial to the system, frequency differential countermeasures and reserve requirements are planned "hours ahead."

[0055] In the application of one-hour-ahead prediction of pre-balancing power, the steps of the above equations can be implemented, for example, in an embodiment with N=4 and Δt=15 minutes. In this case, experiments have shown that the accuracy of the one-hour-ahead prediction of the control range difference is remarkably high, with a correlation coefficient of 0.42 to the measured control range difference. In this case, the power range

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[0056] The steps in the above equation are performed according to the adjustment circuit of FIG.

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[0057] The resulting control variables are

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[0058] In FIG. 1a, a qualitatively good agreement between measurement and prediction is observed for the rising and falling edges in the center, shifted in time by one time step and therefore synchronized for the prediction period of four time steps.

[0059] For the period from mid-August to mid-September 2018, the balance of control area variances

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[0060] For the realization of the embodiment, a known algorithm, here CondEx, based on an Nth order Markov chain, has been correspondingly extended to conditional expectation, where N is the number of time steps to be predicted. The real-time and robustness of the method is adaptive to computational power and databases / information.

[0061] In the case of application of hour-ahead planning and trading of pre-balancing power by the grid operator, in order to avoid bottlenecks in reserves with respect to supply reserves, the grid operator uses the hour-ahead information obtained on the pre-balancing power to review and, if necessary, adjust its balancing power allocation through the intraday market. The procurement of balancing power traded in the intraday market can result from a smart balancing step, as described above, but may also be done through already established mechanisms for procuring supply reserves (see Figure 8).

[0062] A further area of ​​application is the qualification of the usefulness of advance reserves to the system through forecasting the sign of the balance between positive and negative reserves.

[0063] In this case, the predicted control area difference

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[0064]

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[0065] In this case, the balance between positive and negative reserve capacity

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[0066] In the case of applying the one-hour-ahead forecast of the sign of the balance between positive and negative reserve capacity with N=4, the balance between positive and negative reserve capacity is

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[0067] A further field of application is the determination of the usefulness of pre-supply reserves to a system through the prediction of the sign of grid frequency discrepancies.

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[0068]

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[0069] Therefore, qualitative criteria for advance determination of reserve capacity that allows statements to be made about whether frequencies will meet forecasts are determined "day ahead" of commencement.

[0070] In the application example of 1-day-ahead grid frequency forecasting, according to Fig. 2b (correlation is 0.7), the 1-day-ahead grid frequency forecasting with P=1

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[0071] A further area of ​​application is the definition of the benefits to the system of advance supply reserves through supply management forecasting.

[0072] In this case, the pre-balancing power is calculated only when the supply management signal in the relevant region is predicted to be "not supply management" or when the pre-balancing reserve is negative.

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[0073]

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[0074] The supply management signal is determined as the conditional expectation of an Mth order Markov chain using intraday forecasts over M time steps of length 1 hour. This is particularly interesting for highly heterogeneous systems, e.g. wind oversupply in areas with many wind farms connected to other systems.

[0075] In the application example of 5-hour-ahead forecasting of supply management, an M=5 (5 hours ahead) intraday bottleneck forecast is made possible solely on the basis of the real-time published supply management signals of the "supply network traffic lights" of the supply network operator SchleswigHolsteinNetzAG, with an average correlation coefficient of 0.35 between the actual and predicted signals (frequent supply management in municipalities) and is used as a preliminary step to determine the advance supply reserves in order to exclude the simultaneous occurrence of bottlenecks. In this case, the discretization in the state space between both states, "1" for "supply management" and "0" for "not supply management", is:

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[0076] A further application area is the one-hour-ahead forecast beneficial to the system of pre-balancing power, where the above mentioned application cases are filtered through a combination according to the regulation circuit of FIG. 6 with respect to their beneficialness to the system.

[0077] In this case, in addition to the adjustment circuit of FIG. 5, the sign of the balance between positive and negative reserve power, the sign of the grid frequency difference, and a cascade-type inquiry of supply management are made through forecasting.

[0078] The control area is

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[0079] The steps from the first equation, either alone (i.e. without applying the system-beneficiality condition) or in combination with one or more steps to verify the system-beneficiality of pre-dispatch reserves (i.e. with the system-beneficiality condition), may typically be used for trading of pre-balanced electricity to be procured by the grid operator or for the appropriate determination of the balancing group manager in the smart balancing process:

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[0080] The predicted control area variance, taking into account the prediction of the benefit to the system, is shown by way of example in Fig. 1b. In Fig. 3a, the pre-supply reserve is shown in comparison with the control area variance. The predicted balance of positive and negative reserve must have the same sign as the predicted control area variance in Fig. 1a. Additionally, the benefit to the system is confirmed through the opposite sign of the predicted grid frequency variance, as is clear from Fig. 3b.

[0081] If two control areas have opposite signs for their control area balances, the pre-fed reserve is determined to a value different from zero and activated only for those control areas where the additional steering to the sign of the grid frequency difference (as opposed to the grid frequency difference) would be beneficial for the system. For the other of both control areas, the imbalance in the corresponding balancing group is not eliminated in that time step. Therefore, only the simultaneous steering to the grid frequency and the control area difference ensures the benefit to the system for each control area.

[0082] As a simple measure of system benefit, the prediction without the benefit based on the first equation is adjusted with the previous measurements of the control area difference for the time being. This gives a corrected reduction potential in the control area balance of 58% positive balancing power and 38% negative balancing power with pre-balancing power. The incorrectly adjusted non-system benefit percentages associated with the prediction without the benefit of the system of the pre-balancing power in the control area balance are -8% for positive balancing power and -17% for negative balancing power.

[0083] If the prediction without the benefits to the system is combined with the prediction with the benefits to the system for the signs of the predicted balances for positive and negative secondary balancing power based on the second equation, a pre-balancing power reduction potential in the control area balance of 56% for positive balancing power and 28% for negative balancing power is obtained. The misaligned non-beneficial percentages of the pre-balancing power in the control area balance with this combination of predictions are -4% for positive balancing power and -20% for negative balancing power.

[0084] When the system-beneficial forecast is combined with the system-beneficial forecast of the system-beneficial sign of the predicted grid frequency difference relative to the sign of the predicted control area balance, a pre-balancing power reduction potential in the control area balance of 71% for positive balancing power and 55% for negative balancing power is obtained. The misaligned non-system-beneficial fraction of the control area balance pre-balancing power associated with this combination of forecasts is 13% for positive balancing power and 17% for negative balancing power.

[0085] Of particular importance in this benchmark is the experimental quantification of the method's error in the form of a "fraction of pre-balancing power that is not beneficial for a misaligned system," which is a number with respect to magnitude, about 20% of the pre-balancing power.

[0086] The method operates on pre-balancing power according to a forecast based on the above-mentioned method with and without the benefits to the system, with a remaining efficiency of 80%. The efficiency of the possibility of reducing the control area balance (pre-determined) by pre-balancing power according to the above-mentioned method including one of the first conditions on benefits to the system is 32% when divided by the sign of the balance of positive and negative reserve power and 6% when divided by the grid frequency difference. Excluding the conditions on benefits to the system, the efficiency is 59%.

[0087] The success of the technology was quantified using simulation scenarios, where hour-ahead determination of pre-supply reserves and beneficial control of the system were technically implemented in field tests (on-site). For the field tests of interacting demonstrators, the use case modeling system CondEx, realized by agents communicating between different computers ("remotely"), was used.

[0088] The interaction diagram of agents in hour-ahead smart balancing supported by prediction is shown in Fig. 4.

[0089] The planning and procurement of pre-balancing power by the grid operator is shown in Figure 8.

[0090] The domain model of the underlying software architecture of CondEx according to Fig. 7 shows the division of the business logic and use case modelling demonstrator with agents playing a role in controlling the energy supply system and communicating with each other through typology-based messages.

[0091] Type-based messaging is an interface that facilitates identification and execution of "Intents" within which the intelligent communication paradigm is realized, which combines aspects of artificial intelligence in the form of (predictive) algorithms from the domain of data science with software technical concepts of distributed, selectively synchronous or parallel (asynchronous) processes and corresponding middleware. Type-based messaging allows the integration of object-oriented programming principles such as encapsulation (in the sense of reusability and extensibility) with modern actors, microservices and cloud-based technologies through a publish-subscribe model.

[0092] An agent is able to "see and understand" as an autonomous and intelligently acting subject. It is networked with its surroundings, for example through sensors for weather data and for load measurements, and derives predictions from the measurements in the sense of understanding the system in the future.

[0093] A further application case is the performance of forecasts using artificial neural networks.

[0094] By combining recurrent neural networks with conventional perceptrons or tree-based long short-term memory (TreeLSTM), there are techniques that allow multi-layer neural networks to take multi-dimensional forecast data, e.g. weather forecasts, as input for predicting time-series-based variables that determine the system.

[0095] Furthermore, the prediction can be performed using any predictive method in the field of data science or machine learning.

[0096] In a further configuration of the invention, the results of the determination of the pre-supply reserve and the predicted benefit to the system according to the above-mentioned method are used as input variables for the forecast of the regulated power price, which estimates public market data on trading of balancing power and regulated power prices. This can be done by a method using artificial neural networks. As a special case, it is possible to limit the input variables to the regulated power prices traded up to the time of creating the forecast. In this case, it is possible to use the first-mentioned forecasting method for the control area difference (without the condition on the benefit to the system). The predicted regulated power price can be evaluated as a criterion for deciding whether or not the imbalance in the balancing group is eliminated within the framework of the smart balancing process, instead of the pre-supply reserve based on the first-mentioned forecasting method or instead of the benefit to the system based on the further forecasting method described above.

[0097] The currently valid mixed price method (MPV) is suspected to be the cause of the serious system instability that occurred in the German grid over three days in June 2019, as reported, for example, in the Frankfurter Allgemeine Zeitung on July 2, 2019. Extreme grid conditions have been accepted to a large extent so far because the balancing power costs, here the metered price (i.e. the cost of requesting balancing power) and thus the cost of regulating power by MPV, could be cheaper than intraday procurement and intraday management to actively resolve the imbalance (sticking to the timetable). What intraday management allows and promotes benefits for the system can be resisted by the hour-ahead smart balancing according to the present invention.

[0098] MPV penalizes renewable energies, with their high metered prices and low capacity prices (i.e. procurement prices), and demand management, against conventional power plants, with their low metered prices and high capacity prices. This can be avoided by taking into account the possibility of demand when determining the weighting factors for the metered prices, instead of the uniform weighting factors for the metered prices in MPV. From this derives the demand for the introduction of a balancing electricity market, as is evident from the European Commission's guidelines on electricity balancing.

[0099] Based on the above-mentioned forecasting method (including or excluding the condition on the benefit to the system), the pre-balancing power is determined as the integral of the conditional (demand) possibility and the possibility on the benefit to the system and the imbalance (as a cause of the demand). Thus, the pre-balancing power implements the above-mentioned approach of separating the unified weighting coefficient for the metered price in MPV through the use of the possibility on the electricity or the regulated electricity price by the algorithm. Moreover, the pre-balancing power is the possibility of trading not only the price but also the quantity of electricity, which is especially significant in the context of the balancing electricity market.

[0100] In structuring the mechanism based on the demandability of different types of energy and flexibility, the different types of energy and flexibility are differentiated according to traditional and renewable energy source classes, as well as according to technologies for demand management and sector linkage.

Claims

1. A method for stabilization of an electric energy supply grid having at least one control area, comprising, for at least one said control area, the following steps: - A future time t from the present Ｎ and the length of the interval Δt; - N is the number of time steps to be predicted, and the time interval [t Ｎ , t Ｎ +Δt] [0010] determining a prediction [0025] is the step determined as the conditional expectation of the Markov chain, said time interval [t Ｎ , t Ｎ +Δt] [0030] to the time interval [t Ｎ , t Ｎ +Δt]. ＲＬｖｏｒａｕｓ determining - predicted balancing power ΔE ＲＬｖｏｒａｕｓ and - the electrical energy supply network is connected to the time interval [t Ｎ , t Ｎ +Δt] predicted balancing power ΔE ＲＬｖｏｒａｕｓ providing a The method comprises:

2. The time interval [t Ｎ , t Ｎ +Δt]. ＲＬｖｏｒａｕｓ is the time interval [t Ｎ , t Ｎ +Δt] [0045] and the length of the interval Δt.

3. When one condition related to the benefit to the system is satisfied, or when multiple conditions related to the benefit to the system are cumulatively satisfied, the time interval [t Ｎ , t Ｎ +Δt]. ＲＬｖｏｒａｕｓ is the time interval [t Ｎ , t Ｎ +Δt] [0050] and the interval length Δt, and is zero otherwise. The condition or one of the conditions regarding the usefulness to the system is a predicted control range difference in the time interval [t N , t N +Δt]. [006] has the same sign as the sign of the predicted balance P RLprogn t N of positive and negative reserve power in said time interval [t N , t N +Δt], The condition or one of the conditions regarding the usefulness to the system is a predicted control range difference in the time interval [t N , t N +Δt]. [0070] the sign of the predicted grid frequency difference Δω progn t N in said time interval [t N , t N +Δt] is different; and / or The condition or one of the conditions for the usefulness of the system is that the predicted supply management signal Einman progn (t N ) in the corresponding region at the time t N has a value of “not supply management” or that the predicted control area difference in the time interval [t N , t N +Δt] is [0080] The method of claim 1 , wherein is negative.

4. Current time and the predicted required balancing power ΔE ＲＬｖｏｒａｕｓ The time instant t at which the time interval begins Ｎ The method according to any one of claims 1 to 3, wherein the time interval between is at least 1 hour.

5. A computer program for carrying out the method according to any one of claims 1 to 4 when said method is carried out on a computer.

6. A computer program product having program code stored on a machine readable medium and comprising the computer program of claim 5.

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