to ascertain scheduled second powers on the basis of the reduced or increased maximum providable powers; and

to control the load flows according to the ascertained second powers.

In some embodiments, additionally an external controlling power scheduled for an electrical grid that is superordinate to the electrical grid is taken into account according to the internal controlling power. In other words, the electrical grid can by and large provide controlling power (positive or negative) for a grid that is superordinate to said electrical grid. This can also be done with focus on the grid nodes, so that one or more, if necessary different, grid nodes contribute to the external controlling power.

Furthermore, the methods described herein comply with future requirements for electrical grids (known in Germany by the term Redispatch 2.0). The provision of controlling power (flexibility) from the electrical grid for overlaid grid levels or superordinate grids is ensured, while flexibility and energy use in the internal electrical grid is also optimized, in this case by the control apparatus.

In some embodiments, the external controlling power and/or a grid topology is transmitted to the control apparatus by a control unit of the superordinate grid. In other words, the external controlling power and/or the grid topology, which may include the electrical grid and/or the grid that is superordinate thereto, is transmitted to the control apparatus by the grid operator of the superordinate grid. In some embodiments, the grid topology of the electrical grid can be transmitted to the control platform by the grid operator of the electrical grid. This means that the grid boundary conditions and the grid nodes of the control platform are advantageously known.

In some embodiments, the first powers are ascertained by means of a first optimization method on the basis of a first target function by taking account of the grid boundary conditions, the first powers being the variables of the first target function. In other words, a first mathematical optimization is performed to ascertain the first powers. This involves extremizing, that is to say minimizing or maximizing, the first target function, which quantifies a property to be optimized with respect to the load flows. The first powers are the variables of the first target function, and so they are ascertained, or their values are computed, by the extremization of the first target function. The first target function is extremized by taking account of constraints. In the present case, the constraints of the optimization problem include the grid constraints, which means that these are taken into account for the first optimization. In other words, the solution to the first optimization problem, which corresponds to the first powers, recognizes the constraints. The first target function may be the total energy turnover, primary energy input, total carbon dioxide emissions and/or total costs with respect to load flows.

In some embodiments, a sequence of the energy systems, according to which sequence the providable powers at one of the grid nodes are reduced or increased, is stipulated on the basis of the first optimization. In other words, for a grid node, the reserve power ascertained for that grid node can typically be provided by multiple energy systems. To stipulate which energy system is used first or which energy systems are used for the controlling power in the first place, it is possible to determine the contributions that the energy system makes to the result (value of the target function) of the optimization problem. If the target function is minimized, the energy system having the lowest contribution is used first for the controlling power, that is to say said controlling power is subtracted from the maximum providable amount of energy transmitted by said energy system. The energy system having the next highest contribution is then used, creating a sequence of the energy systems that corresponds to the aforementioned sequence until the required controlling power is fully covered. For example, the energy systems are arranged according to their specific carbon dioxide emissions. Furthermore, an arrangement (sequence) of the energy systems according to the specific fees associated with provision of the controlling power (flexibility costs) is possible.

In some embodiments, the second powers are ascertained by means of a second optimization method on the basis of a second target function by taking account of the grid boundary conditions, the second powers being the variables of the second target function. In other words, the second powers, as already preferably the first powers, are ascertained or computed by means of an optimization. The optimizations in this instance can each be regarded as simulations or predictions or forecasts with regard to the load flows, since they each compute the load flows and the associated first or second powers for a future time range within which the load flows then actually take place on the basis of the second powers. In other words, the optimization methods are also simulation methods. The difference between the first powers (first optimization) and second powers (second optimization) is that the second powers take account of the grid-node-resolved controlling power. The above statements about the first optimization can also be used for the second optimization.

In some embodiments, the first and second target functions are the same. In other words, the first and second optimization methods are based on the same target functions. The constraints are fundamentally different, however, since the constraints of the second optimization comprise the maximum providable amounts of energy reduced or increased by the respective controlling power. The constraint of the second optimization thus comprises the maximum providable amounts of energy corrected for the controlling power. The constraint of the first optimization comprises the maximum providable amounts of energy transmitted from the energy systems.

In some embodiments, the grid boundary conditions comprise maximum line capacities for a load flow from one grid node to another grid node. These maximum power capacities (maximum power) or the information about the respective maximum power and/or connection capacities (maximum connected load) can be transmitted to the control platform by the energy systems and taken into account for the optimizations. The first and second powers as solutions of the respective optimization thus recognize the technical boundary conditions characterized by the maximum line or connection capacities.

In some embodiments, the internal controlling power required at a grid node is ascertained from the maximum power capacity by means of a risk factor. The risk factor can also be referred to as the utilization factor of the respective power. This allows identification or ascertainment of when a line is deemed to be loaded. For example, the risk factor is 80 percent of the maximum power capacity. Depending on the utilization level, more or less controlling power is required at the respective grid nodes.

For example, more is supposed to be supplied at a grid node i than consumed. Let us suppose that the grid node i therefore supplies to the grid node j (high consumption) via the line i→j. If this line were thus close to its maximum power capacity (limit capacity), this can be counteracted according to the present invention by additionally feeding in a power (controlling power) at the grid node j, for example, and/or reducing the load. It is thus ascertained for which node there is a need for internal controlling power (flexibility requirement). This can then be computed using said risk factor μ, for example by way of P_k=μ·P_i,j,t,max, where P_i,j,t,maxdenotes the maximum power capacity of the line i→j. The risk factor can be stipulated by a grid operator of the electrical grid and transmitted to the control apparatus, for example. The controlling power ascertained by the control apparatus can continue to be transmitted to the grid operator.

In some embodiments, the data transmitted to the control platform comprise information about a maximum connected load of the respective energy systems. This means that the respective maximum connected load (connection capacity) of the energy systems can be taken into account by the control apparatus for the optimizations. The information about the maximum connected loads can be transmitted to the control apparatus together with the information about the respective maximum providable amount of energy.

In some embodiments, the providable powers reduced or increased according to the determined controlling power are associated with a deferrable consumption, a deferrable generation and/or with a provision by an energy store of the respective energy system. This can prevent nondeferrable powers from being used for the controlling power. If the respective energy systems transmit a flag of their respective scheduled maximum providable amount of energy as deferrable or nondeferrable, the control apparatus can preferably take account of the deferrable powers within the optimizations for providing the controlling power. In other words, the energy systems can transmit information about deferrable, for example within a respective time range, scheduled powers/amounts of energy to the control apparatus. In some embodiments, the deferrable powers are taken into account for providing the reserve power.

In some embodiments, the control apparatus is used to control the load flows within a local energy market. This allows controlling power to be taken into account within a local energy market. The control apparatus and/or one of its embodiments may be particularly suitable for the operation of local energy markets, since it facilitates grid-internal regulation of the electrical grid by means of the ascertained controlling power provided by the energy systems, essentially independently of a superordinate grid. Within the context of a local energy market, the energy systems can additionally provide information about a specific fee (fee per kilowatt hour) for the scheduled maximum providable amount of energy. Thus, within the context of a local energy market, the transmitted data can also be referred to or regarded as an offer or bid.

If the control apparatus is used for a local energy market, the target functions are preferably the total costs associated with the load flows, said costs being created from the first or second power (variables) and the respective associated fee.

In some embodiments, the control apparatus forms a local energy market platform. The control apparatus may preferably be cloud-based.

In some embodiments, the method is carried out for a coming day, in particular for the next day. Particularly with regard to a local energy market, this allows day-ahead trading taking into account reserve power.

In some embodiments, the method is carried out repeatedly in time periods of one day, one hour, 15 minutes and/or 5 minutes. Particularly with regard to a local energy market, this allows intra-day trading taking into account reserve power.

FIG. 1 schematically shows an example system incorporating teachings of the present disclosure. The complete system shown comprises at least two energy systems 2, for example two buildings, a control apparatus 1 central to the energy systems 2 and a control unit 3 of an electrical grid.

The energy systems 2 can exchange energy or power via the electrical grid. These load flows are controlled between the energy systems 2 by the control apparatus 1. For this purpose, data or information can be interchanged between the energy systems 2 and the control apparatus 1, between the control apparatus 1 and the control unit 3 of the electrical grid, and between the energy systems 2 and the control unit 3 of the electrical grid. These data interchanges are symbolized in FIG. 1 by the respective arrows.

The energy systems 2 each comprise an edge device, which facilitates the data interchange and thus the communication with the control apparatus 1. Furthermore, the edge devices can be designed to communicate with the control unit of the electrical grid 4 and thus with the grid operator.

The edge devices are designed to receive and additionally process data for controlling power plants 23 of the respective energy system from the control apparatus 1. The edge devices 21 transfer these received and optionally processed data to the control unit 22 of the respective power plants 23. As a result, the power plants 23 are controlled according to the data transmitted to the edge devices 21 by the control apparatus 1. Since the power plants 23 eventually provide a power for the electrical grid via the grid connection point of the associated energy system 2, the load flows between the energy systems 2 are thus controlled by the central control apparatus 1. For example, the edge devices 23 are in the form of an energy management apparatus. The edge devices 23 further form a communication interface to the control apparatus 1.

The control apparatus 1 is in the form of a local energy market platform. Within the context of a local energy market, offers or bids for the powers/amounts of energy that the respective energy system intends to contribute to one or more of the load flows are transmitted to the local energy market platform 1 by the edge devices 23. To control the load flows, the control apparatus 1 or the local energy market platform 1 thus figuratively collects the bids of all participating energy systems 2. With this in mind, the energy systems 2 can also be referred to as participants.

Furthermore, grid boundary conditions and further requirements of the electrical grid, for example its grid topology and reserve power requirements external to the electrical grid (external flexibility requirements or requirements of superordinate grids or higher grid levels), are transmitted to the control apparatus 1 by the control unit 3.

The energy systems 2 can comprise energy subsystems, which are then treated as energy systems in the spirit of the present invention or one of its embodiments.

FIG. 2 shows a flowchart of an example method incorporating teachings of the present invention. In the embodiment that follows, the method or control apparatus 1 is used to control load flows between multiple energy systems 2 within the context of a local energy market. In this instance, the control apparatus 1 may be configured as a local energy market platform.

The energy systems 2 form the participants in the spirit of a local energy market, that is to say they intend to participate in one of the load flows. The load flows are again exchanged via an electrical grid to which the energy systems 2 are connected.

Furthermore, a control unit 3 of a grid operator of the electrical grid is involved in the method, with the result that the control unit can interchange data or information with the control apparatus 1 and the energy systems 2. The data interchanges or information interchanges are identified by the arrows 101, . . . , 105.

The method shown comprises at least S1, . . . , S5. In the present case, steps S1, . . . , S5 are carried out by the control apparatus 1. In other words, the control apparatus 1 is designed to carry out steps S1, . . . , S5.

In a step prior to steps S1, . . . , S5, the energy systems 2 transmit information about their maximum providable amount of energy

E

max
,
t

B

[kWh] or power, information about an associated minimum or maximum fee

c

min
/
max

,
t

B

[fee/kWh] and, in addition, an associated maximum connected load to the control apparatus 1. This can be done for a scheduled time or time range t. A maximum fee is transmitted for a consumption and a minimum fee is transmitted for a generation. Moveable types of generation and consumption can also be identified or transmitted as moveable. In summary, these data/this information transmitted to the control apparatus 1 can be regarded as a bid or offer for the participation of the respective energy system 2 in one of the load flows.

In particular with regard to deferrable powers, a distinction can be drawn between three offers (flexibility offers). A first flexibility offer is identified by a deferrable consumption for a time range. In this case, a maximum amount of energy to be obtained, an optionally time-dependent connected load and a maximum fee for the consumption are transmitted to the control apparatus 1 for said time range in the form of data/information.

A second flexibility offer is identified by a deferrable generation for a time range. In this case, a maximum amount of energy to be generated, an optionally time-dependent connected load and a minimum fee for the generation are transmitted to the control apparatus 1 for said time range in the form of data/information.

A third flexibility offer is identified by the use of an energy store of one of the energy systems 2 for a time range. In this case, a maximum storage capacity, a maximum charging power and minimum discharge power of the energy store (optionally time-dependent), a charging and discharge efficiency (optionally time-dependent) and a minimum fee for the use of the energy store are transmitted to the control apparatus 1 for said time range in the form of data/information.

In summary, a maximum providable power/amount of energy is transmitted to the control apparatus 1 for a scheduled time range at least by each participating energy system.

S1 comprises the control apparatus 1 ascertaining the first powers scheduled for the load flows on the basis of data/offers transmitted from the energy systems 2 to the control apparatus 1 that include the information about a maximum power providable at the respective grid node by the respective energy system 2. The transmission of said data is identified by the arrow 101.

The scheduled first powers are ascertained by means 28 a thermal optimization. The optimization or the optimization problem is preferably based on a target function in the form:

∑

t
,
n
,
k

P

t
,
n
,
k

B

·

c

min
,
t
,
k

B

-

P

t
,
n
,
k

A

·

c

max
,
t
,
n
,
k

A

+

P

dch
,
t
,
n
,
k

BAT

·

c

dch
,
min
,
t
,
n
,
k

BAT

+

P

i
,
j
,
t

G

·

c

fees
,
i
,
j
,
t

G

,

where

P

t
,
n
,
k

B

is the first power (variable) to be ascertained for a scheduled transmitted consumption (English: bid) and

c

min
,
t
,
k

B

is an associated transmitted minimum fee,

P

t
,
n
,
k

A

is the first power (variable) to be ascertained for a scheduled transmitted consumption (English: ask) and

c

max
,
t
,
n
,
k

A

is the associated maximum fee,

P

dch
,
t
,
n
,
k

BAT

(English: discharge/charge; abbreviated to dch/ch) is the first power (variable) for a scheduled and transmitted use of an energy store and

c

dch
,
min
,
t
,
n
,
k

BAT

is an associated minimum fee for the use of the energy store, in particular a battery store. The flowing power i→j scheduled via a line is denoted by

P

i
,
j
,
t

G

,

there likewise being able to be provision for a fee

c

fees
,
i
,
j
,
t

G

(grid fee) for this.

In other words,

P

t
,
n
,
k

x
=
A

,
B
,
BAT

are the decision variables (variables) determined by means of the first optimization. The variables correspond to the scheduled first powers of the subscriber k, at the grid node n at the time t or within the time range identified by t. In addition, in the present case a power associated with a generation is given a positive value and a power associated with a consumption is given a negative value within the target function, the target function or the value thereof being minimized in the present case. This determines the variables

P

t
,
n
,
k

x
=
A

,
B
,
BAT

,

or the values thereof, that correspond to the first powers.

Furthermore, the optimization problem has the following constraints:

∑
k

P

t
,
n
,
k

B

-

∑
k

P

t
,
n
,
k

A

+

∑
i

P

i
,
k
,
t

G

+

∑
k

P

ch
,
t
,
n
,
k

BAT

-

∑
k

P

dch
,
t
,
n
,
k

BAT

=
0

,

for all grid nodes n and times t within a time range T.

In addition, the constraints

P

t
,
n
,
k

B

≤

P

max
,
t
,
n
,
k

B

and

P

t
,
n
,
k

A

≤

P

max
,
t
,
n
,
k

A

are used. In this case,

P

max
,
t
,
n
,
k

A
,
B

correspond to the respective maximum providable powers transmitted to the control apparatus 1 from the energy systems 2, or, within a time interval Δt, to the respective maximum providable energies transmitted. This means that these transmitted data are taken into account for the optimization.

For energy stores (flexibility of the first type), the further constraint

E
t

BAT

=

E

t
-