WO2010057516A1

WO2010057516A1 - Method for determining electrical load flows in an electrical energy supply grid

Info

Publication number: WO2010057516A1
Application number: PCT/EP2008/009980
Authority: WO
Inventors: Thomas Werner
Original assignee: Siemens Aktiengesellschaft
Priority date: 2008-11-20
Filing date: 2008-11-20
Publication date: 2010-05-27

Abstract

The invention relates to a method for determining electrical load flows in an electrical energy supply grid, wherein load flows matching the actual load flows as precisely as possible can be determined with relatively little effort, in that by comparing the actual load flow at at least one measurement location (M1, M2) to a load flow calculated for the at least one measurement location (M1, M2) using assumed load flows, a dynamic adaptation of load profiles (20a - 20d) is performed, in that at least one modified load profile derived from each previously used load profile is formed, and a load flow for the at least one measurement location (M1, M2) is calculated using the modified load profiles so derived. Those modified load profiles are used in place of the previously used load profiles (20a - 20d) for future determinations of the load flow, for which the least deviation of the load flow from the actual load flow at the at least one measurement location (M1, M2) is determined.

Description

description

Method for determining electrical load flows in an electrical energy supply network

In the control and monitoring of electrical power grids the most accurate knowledge of the current and future occurring in the network at different sections load flows is necessary. Namely, knowing these load flows, production, transmission and distribution capacities required for providing and transporting the quantities of electrical energy required by different electrical consumers can be set and planned. In addition, the load flows can be controlled in the electrical power supply network such that a gleichmaßige as possible utilization of the power supply network is present, so that no overloads occur at any point of the electrical power grid.

However, in particular in electrical energy distribution networks, ie those sections of the energy supply networks which are set up for distributing the electrical energy to the respective end users, measuring devices which can provide measured values which determine precise out ^{¬ statements} over the respective ones are only at comparatively few selected measuring points Condition of the load flow can be used in the electrical energy supply network. The operator of the electrical power supply networks rely on to assess current and zukunftige load river in some sections of the electrical Energiever ^¬ supply network on the basis of so-called "load profiles" Therefore, these load profiles for different electrical loads and for certain times probably occurring specify tend load river. For example, there Load profiles that indicate the consumption behavior of electrical energy of private households, office buildings, sports facilities, public facilities and various industrial installations in the manner of the electrical load, the load profile indicates the power output likely to be required at a particular time to meet the energy needs of the particular electrical load. These load profiles may, for example, depend on the particular time of day (eg day, night, certain hours with high or low energy demand), a specific weekday (eg weekdays, weekends, public holidays, special days with high or low energy requirements) or the season be (eg summer, winter).

The load profiles used to determine the load flows are usually determined statistically from the energy consumption behavior of the respective electrical end users determined in the past, as well as from empirical values and determined statically in a control and control system of the electrical power supply network. The load flows determined on the basis of the load profiles therefore never agree wholly with the actual load flows in the electrical energy supply network. In addition, not only is the energy consumption behavior of the electrical energy consumers to be taken into account, it can also feeds smaller decentralized power generation units occur in the electrical energy grid (for example, inputs of excess energy from electric photovoltaic systems), which cause a change in the load flows in the electrical energy supply network.

Therefore, if one compares the load flows calculated by the load profiles with load flows determined at specific selected measuring points of the electrical energy supply network, deviations will usually occur.

The operators of electric power grids have therefore started to scale the individual load profiles, taking into account the network configuration and heuristic considerations, on the basis of the actual load flows determined at the selected measuring points. However, this requires a comparatively high level of effort to investigate scaling factors. In addition, if you change a network configuration, you must recalculate the scaling factors.

The invention is therefore based on the object of specifying a method for determining electrical load flows in an electrical energy supply network, in which load flows can be determined with comparatively little effort, which correspond as exactly as possible to the actual load flows in the electrical energy supply network, without the number of to increase meters installed in the energy supply network.

To solve this problem, a method for determining electrical load fluxes in an electrical energy supply network is proposed in which load currents assumed in the energy supply network are calculated using individual sections of the energy supply network, the load profiles indicating time-dependent load flows in their respective part of the energy supply network.

At at least one measuring point, an actual load flow at the at least one measuring point is recorded in the energy supply network and a dynamic adaptation of the load profiles is determined by comparing the actual load flow at the at least one measuring point with a load flow calculated on the basis of the assumed load flow for the at least one measuring point carried out by each of at least one of each load profile previously used derived modified load profile is formed and calculated on the basis of the modified load profiles for the at least one measuring point, a load flow is calculated. Those modified load profiles are used instead of the previously used load profiles for future determinations of the load flows in the energy supply network, for which the smallest deviation of the load flow from the actual load flow at the at least one measuring point is determined. For example, a mathematical optimization method can be used to determine the modified load profiles.

On the one hand, the particular advantage of the method according to the invention is that no statically defined load profiles are used, and thus dynamic adaptation of the load profiles to changing consumer and / or feed behavior of the individual electrical consumers can take place. In addition, this can be done to adapt to changing network configurations. On the other hand, in order to carry out this method, it is not necessary to carry out a previous determination of concrete load profiles and scaling factors associated with great expense, since the load profiles themselves are changed dynamically.

Advantageously, a mathematical evolution strategy can be used to form the modified load profiles. The advantage of such an evolutionary strategy is, among other things, that it is possible to dispense with a closed formulation of an optimization problem. On the contrary, it is sufficient to evaluate the quality of the modified load profiles and to select the best load profiles for the next computation processes by means of given algorithms for load flow calculation in electrical energy supply networks and the existing measured values.

A further advantageous development of the method according to the invention consists in that, in order to select the modified load profiles to be used for future determinations of the load flows in the energy supply network, it is also checked whether the modified load profiles lead to violations of limit values in the energy supply network, and only those modified load profiles which lead to the least violation of limit values. In this way it can be prevented that load profiles are accepted for the calculation of the load flows, which mathematically a solution of the optimization problem, but to a violation of physically prescribed limits of the electrical energy supply network - such as maximum allowable currents or voltage bands to be observed - drove. Such modified load profiles have been evaluated with a low quality value, so to say, and are not used for future determinations of the load flows in the electrical energy supply network.

A further advantageous embodiment of the method according to the invention provides that the method is repeated until the deviations between the load flow at the at least one measuring point determined using the modified load profiles and the actual load flow at the measuring point determined on the basis of the measured values falls below a predetermined first threshold. In this way, a continuous dynamic adaptation of the load profiles used to calculate the load flow to the actual load flow determined by measurement can take place until the deviations are acceptably low.

Alternatively, it can also be provided that the method is repeated until the change in the deviations between the load flow at the at least one measuring point determined using the modified load profiles and the actual load flow at the measuring point determined on the basis of the measured values falls below a predetermined second threshold value , In this case, the optimization process is aborted when only small improvements between individual generations of modified load profiles occur.

In the following the invention will be explained in more detail by means of exemplary embodiments. Show this

Figure 1 is a schematic representation of a portion of an electrical energy supply network and Figure 2 is a schematic representation of a process flow diagram for explaining a method for determining electrical load flow in an electrical energy supply network.

FIG. 1 shows a section 10 of a power supply network not further described below. The section 10 of the electrical power supply network shown only by way of example comprises a first busbar 11, which is, for example, a busbar of a

110 kV energy transmission network can act. The section 10 of the electrical energy supply network also has a second busbar 12, which may be, for example, a busbar of a 10 kV distribution network, for example for the distribution of electrical energy within a municipal area. The second bus bar 12 is connected to the first bus bar 11 via a transformer station 13 in which a conversion of the electrical energy from the high voltage level (110 kV) to the lower voltage level (10 kV) is made.

From the second busbar 12 go off branches 14, 15 and 16, are supplied via the electrical end consumers 17a, 17b, 17c and 17d with electrical energy. The branch 15 is also divided into two branch branches 15a and 15b, via which the end consumers 17b and 17c are connected via the branch 15 to the second busbar 12.

In addition to the energy supply through the branches 14 to 16, it is also possible that the electrical end consumers 17a to 17d via these branches 14 to 16 excess electrical energy from self-generation (for example, electrical energy that is generated with a cogeneration plant or a photovoltaic system) in feed in the electrical energy supply network. Concretely, for example, the electrical end user 17a may be a housing estate, the end consumers 17b and 17c may be commercial customers, and the end electrical consumer 17d may be an office building. Of course, other and / or additional electrical energy consumers may be provided, some examples of other electrical energy consumers are sports facilities, public facilities, shopping centers and farms.

For controlling and monitoring the electrical load flows in the electrical energy supply network, a network control center 18 is provided. The network control center 18 receives measured values 19 a and 19 b provided at selected measuring points M 1 and M 2, which give an indication of the load flows at the respective measuring point M 1 or M 2. For this purpose, the measuring devices 19a or 19b can, for example, determine measured quantities such as active and / or reactive powers, currents, voltages or voltage angles at their measuring point M1 or M2 and transmit corresponding measured values to the network control point 18.

Since an explicit measurement is only possible with measuring points M1 and M2 at comparatively few selected locations in the electrical energy supply network, the network control center 18 can not determine a complete overview of all load flows taking place in the electrical energy supply network on the basis of the existing measured values alone. Since a complete metrological coverage of the electrical energy supply network would only have to be accomplished with comparatively high installation costs and high costs, the energy supply companies usually fall back on so-called load profiles, in which a different usage or feed behavior for different types of electrical end consumers electrical energy for certain times of the day, weekdays and seasons.

In general it can be said that in a power supply network different customer groups, ie different types of End consumers, are present, which show a relatively similar consumption behavior. Examples of such customer groups are household customers, commercial customers and agricultural customers. In FIG. 1, these customer groups are indicated as end consumers 17a to 17d. Each of these end consumers 17a to 17d can be described by a typified load profile.

In the example according to FIG. 1, therefore, there is a load profile 20a for the end consumer 17a, which indicates the particular time-dependent use or feed behavior of a housing estate of a specific size. Likewise, load profiles 20b, 20c and 20d exist for the end users 17b, 17c and 17d, which indicate a typical usage behavior for commercial operations and office buildings. Utilizing the load profiles 20a to 2Od, the network control center 18, knowing the topology of section 10 of the electrical power grid and using well-known load flow calculation algorithms in electrical energy supply networks, can calculate the load flows in section 10 of the electrical grid that result were when the use or feed behavior of the end user 17a to 17d exactly correspond to the assumed load profiles. In this assumed special case, therefore, the same load flows had to be determined on the basis of the load profiles 20a to 2Od for the selected measuring points M1 and M2 within the measuring accuracy, as they are also indicated by the measurements of the actual load flows by the measuring devices 19a and 19b.

Usually, however, the usage or feed-in behavior of the individual end users can not be specified exactly by statically predefined load profiles, so that deviations will result between the load flows calculated on the basis of the load profiles at the measuring points M1 and M2 and the actual load flows determined by measurement. In the following, therefore, a method is to be described with which the load profiles can be adapted dynamically to the respective actual states in the section 10 of the electrical energy supply network.

For this purpose, first of all, on the basis of the predetermined load profiles 20a to 2Od for the measuring points M1 and M2, certain assumed load flows are compared with the actual measured load flows occurring there by measurement. Should differences arise, then the load profiles 20a to

2Od changes made so that this results in modified load profiles. This process can be performed as often as desired, resulting in a certain amount of modified load profiles for each of the load profiles 20a to 2Od. On the basis of all modified load profiles generated in this way, the assumed load flows for the measuring points M1 and M2 can again be calculated in this way. Finally, from the set of modified load profiles, those load profiles are selected on the basis of which load flows result at the measuring points M1 and M2, which have the smallest deviations from the actual load flows determined by measurements.

To select the best modified load profiles, for example, the following objective function to be optimized can be evaluated:

In equation (1)

M: number of measuring points considered; m: running index of the measuring points M; f: measured value at the respective measuring point; s: vector of the optimization variable of the load profile; F: function that maps the vector of the optimization variable to the corresponding measured value f; and w: optional weighting factor.

Equation (1) represents a so-called "penalty function", which overvalues any deviations by squaring and thus assigns solutions with large deviations an above-average numerical value (= low quality value) and solutions with small deviations a comparatively low numerical value (high quality value).

Concretely, according to equation (1), each load profile is considered to be one

Vector s considered, the bottlenecks of the individual load profiles and scaling values, with which the respective nodes can be scaled accordingly includes. In this case, the support points specify, so to speak, the basic load profile for a specific end user type. The scaling values are needed because different numbers of these end-user types with different levels of energy consumption can be connected to the individual removal points in the energy supply network.

On the basis of these vectors s representing the load profiles, it is possible to determine values of accepted load flows using a load flow which results from conventional network calculation algorithms and the network topology, which values are associated with the measured values f at the corresponding measuring points (according to FIG M2) in the section 10 of the electrical energy supply network can be compared. As already mentioned, measured values which can be used for characterizing load flows can be used as measured values f, for example effective and / or reactive powers, currents, voltages or voltage angles.

Those modified load profiles which give the smallest deviations from the actual measured values with regard to the load flow over the entirety of the measuring points in the relevant section of the electrical energy supply network, are then to be used as future-oriented Load profiles 20a to 2Od are assigned to the end consumers 17a to 17d and, if necessary, serve as further basis for the formation of further modified load profiles in further optimization runs.

In order to prevent such modified load profiles from being used for future calculations which, although purely mathematical, describe an optimized solution but do not correspond to the physical conditions of the electrical energy supply network, the objective function can be determined according to

Equation (1) can be extended by one violation term, resulting in an extended objective function according to equation (2):

M 1 I i Σ (f _m -F, M) ² + Σ (s _r -G _r (s)) ² > min (2) m = \ W. W

In this case, the additional components used mean:

R: number of injured constraints; r: running index of injured constraints; g: limit of a constraint; and

G: Function that maps the vector of the optimization variable s to the corresponding constraint.

As secondary conditions, for example, maximum currents in the branches 14, 15 and 16 or on the busbars 11 and 12 and voltage bands to be maintained on the busbars (for example 110 kV on the first busbar 11 and 10 kV on the second busbar 12) can be used. Using the advanced objective function according to

Equation (2) allows such load profiles, which result in comparatively large violations of the specified limits of certain secondary conditions, to be excluded from the outset from the use of future load profiles, since they are given a comparatively poor rating by the added infringement term. Those modified load profiles which best meet the extended objective function according to equation (2) are used as load profiles for the future determination of the load flows in the electrical energy supply network.

The described method can be repeated so often, that by constant modification of the previously used load profiles such load profiles result, which result in small deviations from the actual load profiles determined by measurement or only small improvements compared to the loader profiles. Due to the possibility of a continuous dynamic adaptation, the load profiles can also be adapted to changing topology conditions of the energy supply network or time-varying decentralized energy feeds from the end consumers into their respective branches.

The use of mathematical evolution strategies lends itself to generating the modified load profiles. In general, optimization problems are solved with mathematical methods from the field of optimal planning, e.g. with the dynamic programming, the Lagrang 'see relaxation or the mixed-integer linear optimization. However, these optimization procedures require a closed and adapted formulation of the optimization problem, which is often either very expensive or even impossible. Furthermore, these methods require special features of the optimization problem, which are often not given, e.g. Convexity or Markov's property. Due to the changing nature of the topology of the power grid over time, the existing optimization problem had to be constantly redefined, which is a considerable effort.

The idea of evolutionary strategies in this context is therefore to easily modify a set of given load profiles under the modified load profile Select the best ones and take as output load profiles for new modifications. This process continues until it finds the optimum of the technical problem. The solution process is therefore very strongly oriented towards the model of natural evolution.

For computer-based use, the solutions of the optimization problem are represented by real-valued vectors s. The evolutionary process begins with an initial generation of load profiles that consists of a number of vectors called parents. The first step, recombination, combines the genetic information of two or more parents. This can e.g. by an averaging of the parental vectors involved or by a piecewise recombination of the parent genes. The recombination is followed by the mutation, in which the individual genes of the recombinants are slightly modified. After generating the number of so-called children required for a population, each solution vector is evaluated using a quality function, e.g. equations (1) or (2). The best children of the current generation in the sense of the quality function are designated as parents of the next generation. The evolutionary process continues until a termination criterion is met. This can e.g. reaching a maximum number of generations or falling below a predetermined minimum improvement of the last generation.

With reference to Figure 2, the method for adapting the load profiles will be explained again. FIG. 2 shows a mathematical process flow diagram according to which the following steps are carried out:

According to a first initialization step 21 "INIT", first load lot startup solvers are generated, which provide evolutionary strategy origins, which can be populated with random numbers if no further information is available. or already with existing load profiles that appear suitable for approximate description of the load flows in the power grid. These may, for example, be load profiles obtained from measurements of past load flows or those already calculated by the method at an earlier point in time. Thereafter, the starting loops of the load flow values for the scaling are determined. These starting solutions are filled either with random numbers, with the connected services of the end users or with archived data.

After the startup solutions have been generated, the actual optimization process takes place. First, in a modification step 22, "MOD" modified load profiles are generated, for example, by mutation and recombination.

In accordance with a following calculation step 23 "CALC", the results of the load flow determinations are determined on the basis of the modified load profiles and the deviations from the measured values and, if necessary, the secondary conditions, for example, according to equations (1) or (2) ertu ttelt These deviations are squared, weighted This results directly in the objective function value of the considered solution, ie the combination of the modified load profiles, so that in a following evaluation step 24 "EVAL" the quality of the respective solution can be determined in the sense of the evolution strategy.

All evaluated solutions are collected according to a further step 25 ("DEPOT"). According to step 26, it is checked whether there are a sufficient number of solutions (a sufficiently large "population") so that a meaningful selection can be made.

The selection is made according to a selection step 27 "SEL." The modified load profiles with the lowest target function values-that is, the highest quality-are selected and, according to the evolution strategy, serve as parents of the next generation. In step 28, the method is terminated as soon as the value of the objective function falls below a predetermined limit or the changes from generation to generation are only very small. Otherwise, those described above

Steps repeated from the modification step 22.

The found values for the best vectors s, ie the best interpolation points of the load profiles and their scaling factors, thus indicate the best estimate of the load behavior at the respective times and are selected according to a final step 29 as future load profiles to be used. However, if significant deviations from the measured load flows or changes in the network topology occur, the method can be carried out again so that continuous adaptation is possible.

Thus, with the described function, a method can be provided which allows adjustment of the stan-ended load profiles used in an electrical power supply network and in this case back accesses comparatively easy to implement mathematical optimization processes to ^¬.

The advantages of the method described are, among others:

- A precise knowledge of the load or generation profiles for the different load types is not required. They are automatically determined by the procedure.

The method is auto-adaptive; it adapts independently to changes in consumer behavior or producer behavior. Interventions by the operator are not necessary. - The method is independent of heuristics and can therefore be easily used for different network types and network configurations.

- The results of the load flow calculation do not deviate or only slightly from the existing measured values. This makes them plausible and acceptable to the operator.

- Through the use of evolutionary strategies can be dispensed with a closed formulation of the optimization problem. This makes it possible to use standard methods from network control or network planning without changes to the algorithms for the required load flow calculation. This significantly reduces implementation times.

- All measured variables, which are determined with the help of the net calculation, can be used in this procedure

(e.g., active and reactive power, current, voltage or voltage angle).

Claims

claims

1. A method for determining electrical load flows in an electrical energy supply network, in which

- load flows assumed in the energy supply network using individual sections (10) of the energy supply network associated with load profiles (20a-2Od), the load profiles (20a-2Od) indicating time-dependent load flows in their respective part of the energy supply network;

- an actual load flow at the at least one measuring point (Ml, M2) indicative measured values are recorded at at least one measuring point (Ml, M2) in the energy supply network; and

- By comparing the actual load flow at the at least one measuring point (Ml, M2) with a calculated on the basis of the assumed load flow for the at least one measuring point (Ml, M2) load flow dynamic adjustment of the load profiles (20a - 2Od) is made by

- In each case at least one of each load profile (20a - 2Od) previously used derived modified load profile is formed and based on the thus formed modified load profiles for the at least one measuring point (Ml, M2) a load flow is calculated; and

- Those modified load profiles instead of the previously used load profiles (20a - 2Od) are used for future investigations of the load flow in the power grid, for which the smallest deviation of the load flow from the actual load flow at the at least one measuring point (Ml, M2) is determined.

2. The method of claim 1, wherein a mathematical evolution strategy is used to form the modified load profiles.

3. The method according to claim 1 or 2, characterized in that

to check whether the modified load profiles lead to violations of limit values in the energy supply network and to select only those modified load profiles which are among the least violations of limit values, in order to select the modified load profiles to be used for future determinations of the load flows in the energy supply network to lead.

4. Method according to one of the preceding claims, characterized in that

the method is repeated until the deviations between the load flow determined using the modified load profiles at the at least one measuring point (M1, M2) and the actual value determined on the basis of the measured values

Load flow at the measuring point (Ml, M2) falls below a predetermined first threshold.

5. Method according to one of claims 1 to 3, characterized in that

the method is repeated until the change in the deviations between the load flow determined using the modified load profiles at the at least one measuring point (M1, M2) and the actual load flow at the measuring point (M1, M2) determined on the basis of the measured values falls below a predetermined second threshold.