Method for determining distribution node marginal price considering transmission and distribution coordination and uncertainty

Abstract

The present disclosure belongs to the technical field of power systems, and provides a distribution node marginal price determination method considering transmission-distribution coordination and uncertainty, comprising the following steps: obtaining data information of a distribution network; obtaining a distribution node marginal price according to the obtained information and a preset distribution network economic dispatching model; wherein the distribution network economic dispatching model considers transmission-distribution coordination and uncertainty, takes the minimum distribution network dispatching operation cost as an objective function, performs economic dispatching of the distribution network, and deduces the distribution node marginal price.

Description

TECHNICAL FIELD

[0001] The present disclosure belongs to the technical field of power system, and particularly relates to a method for determining marginal price of power distribution node considering coordination of transmission and distribution and uncertainty. BACKGROUND

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute the prior art.

[0003] Large-scale access of distributed power supply to power distribution system relieves environmental pressure, but also brings great challenges to power system operation. The clearing and pricing mechanism of the distribution market is an effective method to manage a large number of distributed power supplies. However, two main challenges are faced in establishing the distribution market. First, the clearing mechanism of the distribution market needs to reflect the uncertainty of the distributed power supply and provide an effective price signal for the uncertainty management and safe operation of the distribution network. Second, the clearing and pricing of the distribution market need to consider the impact of the transmission network on the distribution network and the coordination with the transmission market. The marginal price of power distribution node (DLMP) method can realize the clearing and pricing of the distribution market and optimize the operation of the distributed power supply.

[0004] According to the inventors, the existing DLMP determination method has the following defects and deficiencies:

[0005] (1) Uncertainty cannot be reflected in the clearing and pricing of the distribution market;

[0006] (2) Coordination with the transmission market is not considered. SUMMARY

[0007] In order to solve the above problems, the present disclosure provides a method for determining marginal price of power distribution node considering coordination of transmission and distribution and uncertainty, an economic dispatch model of distribution network considering uncertainty and coordination of transmission network-distribution network is established, economic dispatch results in the distribution network are obtained, and DLMP is derived for clearing and pricing in the distribution market.

[0008] According to some embodiments, the first aspect of the present disclosure provides a method for determining marginal price of power distribution node considering coordination of transmission and distribution and uncertainty, which adopts the following technical scheme:

[0009] A method for determining marginal price of power distribution node considering coordination of transmission and distribution and uncertainty, comprising the following steps:

[0010] Obtaining data information of the distribution network;

[0011] Obtaining the marginal price of power distribution node according to the obtained information and a preset economic dispatch model of the distribution network;

[0012] The power distribution network economic dispatching model considers the coordination between the power transmission network and the power distribution network and the uncertainty, takes the minimum of the power distribution network dispatching operation cost as an objective function, performs economic dispatching of the power distribution network, and derives a marginal electricity price of the power distribution node.

[0013] As a further technical limitation, the data information of the power distribution network at least includes active power output of a generator, active power demand of the power distribution network, active power output cost of a generator set, active network loss of the power distribution network, and reactive network loss of the generator.

[0014] As a further technical limitation, the objective function includes costs of active load, reactive load and standby load purchased from the power grid, and generation cost of the distributed power supply and standby cost of the steam turbine.

[0015] As a further technical limitation, the constraint condition of the objective function includes constraint conditions in a basic dispatching process, constraint conditions in a rescheduling process, power balance constraint conditions, upper and lower limit constraint conditions of unit output, unit ramp rate constraint conditions and line capacity constraint conditions.

[0016] As a further technical limitation, a Lagrange function of the constructed power distribution network economic dispatching model is calculated to obtain a node marginal electricity price at the bus and an uncertainty node marginal electricity price.

[0017] Further, the obtained node marginal electricity price at the bus and the uncertainty node marginal electricity price are sent to the power distribution network, combined with the constructed power distribution network economic dispatching model to obtain active power demand, reactive power demand and standby capacity demand of the power distribution network, and uploaded to the power transmission network.

[0018] As a further technical limitation, the coordination between the power transmission network and the power distribution network is realized through information transmission and iterative calculation, and a convergence condition of the iterative calculation is that the maximum difference between the power transmission market marginal electricity price and the uncertainty node marginal electricity price obtained by two adjacent iterations is less than a preset threshold.

[0019] According to some embodiments, a second scheme of the present disclosure provides a power distribution node marginal electricity price determination system considering power transmission and distribution coordination and uncertainty, which adopts the following technical scheme:

[0020] A power distribution node marginal electricity price determination method system considering power transmission and distribution coordination and uncertainty, comprising:

[0021] An acquisition module configured to acquire data information of a power distribution network;

[0022] A calculation module configured to obtain a power distribution node marginal electricity price according to the acquired information and a preset power distribution network economic dispatching model;

[0023] The economic dispatch model of the power distribution network considers the coordination between the power transmission network and the power distribution network and uncertainty, takes the minimum power distribution network dispatching and operation cost as an objective function, performs economic dispatch of the power distribution network, and deduces a power distribution node marginal price.

[0024] According to some embodiments, a third aspect of the present disclosure provides a computer-readable storage medium, adopting the technical scheme as follows:

[0025] A computer-readable storage medium, having a program stored thereon, which, when executed by a processor, implements the steps in the method for determining a power distribution node marginal price considering coordination between a power transmission network and a power distribution network and uncertainty, as described in the first aspect of the present disclosure.

[0026] According to some embodiments, a fourth aspect of the present disclosure provides an electronic device, adopting the technical scheme as follows:

[0027] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor, and the processor implements the steps in the method for determining a power distribution node marginal price considering coordination between a power transmission network and a power distribution network and uncertainty, as described in the first aspect of the present disclosure.

[0028] Compared with the prior art, the present disclosure has the beneficial effects that:

[0029] The present disclosure fully considers the uncertainty of the power grid and the coordination between the power transmission network and the power distribution network, constructs an economic dispatch model of the power distribution network, performs economic dispatch based on the constructed model, and determines a power distribution node marginal price, which is widely applicable to clearing and pricing in the power distribution market. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings, which form a part of the present disclosure, are used to provide further understanding of the present disclosure, and the illustrative embodiments of the present disclosure and their description serve the purpose of explaining the present disclosure. The present disclosure should not be limited by the accompanying drawings.

[0031] Figure 1 is a flowchart of the method for determining a power distribution node marginal price considering coordination between a power transmission network and a power distribution network and uncertainty in the first embodiment of the present disclosure;

[0032] Figure 2 is a PJM 5 bus system wiring diagram in the first embodiment of the present disclosure;

[0033] Figure 3 is a load prediction value in the power transmission network in the first embodiment of the present disclosure;

[0034] Figure 4 is an IEEE 33 node system wiring diagram in the first embodiment of the present disclosure;

[0035] Figure 5This refers to the nodal marginal electricity price in the transmission network of Embodiment 1 of this disclosure.

[0036] Figure 6 This refers to the marginal electricity price at uncertain nodes in the transmission network in Embodiment 1 of this disclosure.

[0037] Figure 7 The active power node variable price in the distribution network of Embodiment 1 of this disclosure

[0038] Figure 8 The reactive power node variable price in the distribution network of Embodiment 1 of this disclosure

[0039] Figure 9 This refers to the uncertain node variable price in the distribution network in Embodiment 1 of this disclosure.

[0040] Figure 10 This is a structural block diagram of the distribution node marginal electricity price determination system that takes into account transmission and distribution coordination and uncertainty in Embodiment 2 of this disclosure. Detailed Implementation

[0041] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0042] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0043] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0044] Where there is no conflict, the embodiments and features described herein can be combined with each other.

[0045] Example 1

[0046] Embodiment 1 of this disclosure introduces a method for determining the marginal electricity price of a distribution node that takes into account transmission and distribution coordination and uncertainty.

[0047] like Figure 1 The proposed method for determining the marginal electricity price at distribution nodes, taking into account transmission and distribution coordination and uncertainties, includes the following steps:

[0048] obtaining data information of the power distribution network;

[0049] obtaining data information of the power distribution network;

[0050] According to the obtained information and the preset power distribution network economic dispatching model, the marginal electricity price of the power distribution node is obtained.

[0051] As one or more embodiments, first, the clearing and pricing of the power transmission network market are performed, and specifically:

[0052] An economic dispatching model of the power transmission network is established, and the objective function thereof is:

[0053]

[0054] The constraint condition is:

[0055]

[0056]

[0057]

[0058]

[0059]

[0060]

[0061]

[0062]

[0063]

[0064] In the formula, is a bus set, is a generator, load, and power distribution network set, is a generator, load, and power distribution network set at bus i, and T is the number of dispatching time periods; l represents a line; and is the active power output and standby capacity of the generator i at time t; is the active power output prediction value of the load i at time t; is the active power demand of the power distribution network i at time t; is the standby demand of the power distribution network i at time t; and is the active power output cost and reserve capacity cost of unit i; GSF l,i is the power transfer factor from bus i to line l; F l is the maximum transmission power of line l, in MW; and are the minimum and maximum output of unit i, in MW, respectively; and are the maximum upward and downward ramp rates of unit i, in MW / h, respectively; is the active power output forecast error of load i at time t, is the upper limit of the active power output forecast error of load i at time t; the variables in the brackets are the dual variables corresponding to the constraint conditions.

[0065] Objective function (1) minimizes the total operation cost in the dispatch period. Equation (2) represents the constraint conditions in the basic dispatch process, equation (3) represents the constraint conditions in the rescheduling process, and equation (4) represents the uncertainty set of the load. Equations (2a) and (3a) are power balance constraints, equations (2b) and (3b) are upper and lower limits of unit output constraints, equations (2c) and (3c) are unit ramp rate constraints, and equations (2d) and (3d) are line capacity constraints.

[0066] The Lagrangian function corresponding to the power grid economic dispatch model (1)-(4):

[0067]

[0068] The nodal marginal price at bus i is defined as the incremental power supply cost caused by the addition of one unit of load at the node. It can be derived from the Lagrangian function as follows:

[0069]

[0070] The uncertainty nodal marginal price at bus i is defined as the incremental power supply cost caused by the addition of one unit of uncertainty at the node. It can be derived from the Lagrangian function as follows:

[0071]

[0072] As one or more embodiments, the distribution network market clearing and pricing considering uncertainty are considered, specifically:

[0073] For the distribution network at bus m of the power grid, a distribution network economic dispatch model is established, and its objective function is:

[0074]

[0075] The constraints are:

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083]

[0084]

[0085]

[0086] where, and are the set of nodes and lines in the distribution network; and are the set of distributed generation and micro-turbines; Pm(t), Qm(t), and Sm(t) are the active power demand, reactive power demand and reserve demand of the distribution network at bus m at time t; Pm(t), Qm(t), and Sm(t) are the active power price, reactive power price and reserve price at bus m at time t; and are the active and reactive power offer of distributed generation i; and are the active and reactive power output of distributed generation i at time t, Qmax(i, t) is the absolute value of the reactive power output of distributed generation i at time t; Smi(t) is the reserve offer of micro-turbine i; Smi(t) is the reserve capacity provided by micro-turbine i at time t; and are the active and reactive power forecast of load i at time t; Pmax(i, t) is the active power forecast bias uncertainty variable of load i at time t; and are the active and reactive power transfer factor of node i at time t in the base dispatch; Pmax(i, t) is the active power transfer factor of node i at time t in the re-dispatch; and Pij(t) and Qij(t) are the active and reactive power losses of the distribution network in the base scheduling process; Pij(t) and Qij(t) are the active and reactive power losses of the distribution network in the base scheduling process; and Pmin,i(t) and Pmax,i(t) are the lower and upper limits of the active power output of the distributed generator i, respectively; and Qmin,i(t) and Qmax,i(t) are the lower and upper limits of the reactive power output of the distributed generator i, respectively; min and max Vmin,i(t) and Vmax,i(t) are the lower and upper limits of the voltage at node i, respectively; i1,t Vroot(t) is the voltage at the root node at time t; vp,ij,t and vq,ij,t Sfi,j is the sensitivity factor of the active power at node i to the voltage at node j; lp,li,t and lp,li,t Sfi,l is the sensitivity factor of the active power at node i to the transmission power of line l; and Pvirt,i(t) and Qvirt,i(t) are the virtual injected active and reactive power losses at node i in the base scheduling process; and Pvirt,i(t) and Qvirt,i(t) are the virtual injected active and reactive power losses at node i in the base scheduling process; c,0 , α c,1 , α c,2 are the coefficients of the quadratic linearization, c is an integer between 1 and 12; Cmax,l is the capacity of line l; the variables in the brackets are the dual variables corresponding to the constraint conditions.

[0087] The objective function (8) minimizes the distribution network scheduling cost, including the cost of purchasing active, reactive and reserve power from the grid, the cost of distributed generator power generation and the cost of micro gas turbine providing reserve. Equation (9) represents the constraint conditions in the base scheduling process, and equation (10) represents the constraint conditions in the rescheduling process. Equations (9a), (9b), (10a) are power balance constraint conditions, equations (9c), (9d), (10b) are upper and lower limit constraint conditions of distributed generator output, equations (9e) and (10c) are node voltage constraint conditions, and equations (9f) and (10d) are line capacity constraint conditions.

[0088] The active and reactive power outputs of the distributed generators in the distribution network, the reserve capacity of the micro gas turbine, and the energy purchased from the grid by the reserve capacity can be obtained through the above economic scheduling model (8)-(10). The following Lagrange function can be derived through the economic scheduling model:

[0089]

[0090]

[0091] Similar to the definition of marginal price in the transmission market, in the distribution network, the active node marginal price at node i is defined as the incremental supply cost of adding one unit of active load at this node. It can be derived from the Lagrangian function as follows:

[0092]

[0093] The reactive node marginal price at node i is defined as the incremental supply cost of adding one unit of reactive load at this node. It can be derived from the Lagrangian function as follows:

[0094]

[0095] The uncertainty node marginal price at node i is defined as the incremental supply cost of adding one unit of active uncertainty load at this node. It can be derived from the Lagrangian function as follows:

[0096]

[0097] As one or more embodiments, the transmission-distribution network coordinated iterative calculation method, specifically:

[0098] The coordination between the transmission network and the distribution network is realized through information transmission and iterative calculation. In each iteration, the transmission network first calculates the node marginal price and the uncertainty node marginal price based on the economic dispatch model (1)-(4), and then sends the calculated price to the distribution network. After receiving the price from the transmission network, the distribution network obtains the active power demand reactive power demand and reserve capacity demand based on the economic dispatch model (8)-(10), and uploads them to the transmission network. The convergence condition of the iterative calculation is that the maximum difference between the transmission market marginal prices and obtained by adjacent two iterations is less than a set threshold ε. The convergence condition can be expressed as follows:

[0099]

[0100] where k is the iteration number.

[0101] The method proposed in the patent is verified using the PJM 5-bus example-IEEE 33-node example. The PJM 5-bus is a transmission network, and its connection diagram is shown in Figure 2 , which shows the capacity and generation bidding price of the generator; the line parameters are shown in Table 1, and the generator parameters are shown in Table 2. The load output prediction curves of buses B, C, and D are shown inFigure 3 The load forecast error at B, C, D is 10%, 5%, 0% of the corresponding load, respectively. At bus D, there are 50 identical IEEE 33-bus systems. The IEEE 33-bus system is a distribution network, and its wiring diagram is shown in Figure 4 The system includes two 0.8 MW microturbines at buses 17 and 32, respectively. The base total load of the IEEE 33-bus system is 3.715 MW and 2.3 MVar, and is at the forecast error.

[0102] Table 1 Line Parameter Table

[0103]

[0104]

[0105] Table 2 Generator Parameter Table

[0106]

[0107] The active offer price of the microturbine is $15 / MWh, the reactive offer price is $3 / MVArh, and the reserve offer price is half of the active offer price. In the transmission market, the reactive price is 10% of the active price.

[0108] Node Marginal Price in Transmission Network As shown in Figure 5 the uncertainty node marginal price As shown in Figure 6 From these two figures, it can be seen that the price at the same bus at different times is different. At the same time, the price at different buses is also different, and the price at bus D is the highest.

[0109] Active Node Variable Price in Distribution Network As shown in Figure 7 Reactive Node Variable Price As shown in Figure 8 Uncertainty Node Variable Price As shown in Figure 9 From Figure 7 , Figure 8 and Figure 9 the following conclusions can be drawn: (1) the marginal price in the distribution network is affected by the marginal price in the transmission network, and the price shape is similar to the price shape in the transmission network. (2) At the same time, the node marginal price of different nodes is different. At the same node, the node marginal price at different times is different.

[0110] Example Two

[0111] The embodiment two of the present disclosure introduces a power distribution node marginal electricity price determination system considering transmission-distribution coordination and uncertainty.

[0112] As shown in a power distribution node marginal electricity price determination system considering transmission-distribution coordination and uncertainty, comprising: Figure 10

[0113] An acquisition module is configured to acquire data information of a power distribution network.

[0114] A calculation module is configured to obtain a power distribution node marginal electricity price according to the acquired information and a preset power distribution network economic dispatching model.

[0115] The power distribution network economic dispatching model considers transmission-distribution coordination and uncertainty, takes the minimum power distribution network dispatching operation cost as an objective function, performs economic dispatching of the power distribution network, and deduces the power distribution node marginal electricity price.

[0116] The detailed steps are the same as those of the power distribution node marginal electricity price determination method considering transmission-distribution coordination and uncertainty provided in the embodiment one, and will not be repeated here.

[0117] Embodiment three

[0118] The embodiment three of the present disclosure provides a computer readable storage medium.

[0119] A computer readable storage medium has a program stored thereon, and the program is executed by a processor to implement the steps in the power distribution node marginal electricity price determination method considering transmission-distribution coordination and uncertainty provided in the embodiment one of the present disclosure.

[0120] The detailed steps are the same as those of the power distribution node marginal electricity price determination method considering transmission-distribution coordination and uncertainty provided in the embodiment one, and will not be repeated here.

[0121] Embodiment four

[0122] The embodiment four of the present disclosure provides an electronic device.

[0123] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor, and the processor executes the program to implement the steps in the power distribution node marginal electricity price determination method considering transmission-distribution coordination and uncertainty provided in the embodiment one of the present disclosure.

[0124] The detailed steps are the same as those of the power distribution node marginal electricity price determination method considering transmission-distribution coordination and uncertainty provided in the embodiment one, and will not be repeated here.

[0125] ​The specific embodiments of the present disclosure are described above with reference to the accompanying drawings, but are not intended to limit the protection scope of the present disclosure, and those skilled in the art should understand that various modifications or changes made on the basis of the technical solutions of the present disclosure without creative labor are still within the protection scope of the present disclosure.

Claims

1. A method for determining the marginal electricity price at a distribution node, taking into account transmission and distribution coordination and uncertainty, characterized in that, Includes the following steps: Obtain data information from the power distribution network; Based on the acquired information and the pre-set distribution network economic dispatch model, the marginal electricity price of the distribution node is obtained; Among them, the distribution network economic dispatch model takes into account the coordination and uncertainty of the transmission network and the distribution network, takes the minimum operation cost of distribution network dispatch as the objective function, performs economic dispatch of distribution network, and derives the marginal electricity price of distribution node; Coordination between the transmission and distribution networks is achieved through information transmission and iterative calculations. In each iteration, the transmission network first calculates the marginal electricity price at each node based on the economic dispatch model. Marginal electricity prices at uncertain nodes The calculated electricity price is then distributed to the distribution network. Upon receiving the price from the transmission network, the distribution network uses the economic dispatch model to determine its active power demand, non-active power demand, and reserve capacity demand, and then uploads this information to the transmission network. The convergence condition for the iterative calculation is the marginal electricity price in the transmission market obtained from two consecutive iterations. and The maximum difference is less than the set threshold ε, and the convergence condition is expressed as follows: In the formula, k is the number of iterations.

2. The method for determining the marginal electricity price of a distribution node considering transmission and distribution coordination and uncertainty as described in claim 1, characterized in that, The data information of the distribution network includes at least the active power output of the generators, the active power demand of the distribution network, the active power output cost of the generator sets, the active power loss of the distribution network, and the reactive power loss of the generators.

3. The method for determining the marginal electricity price of a distribution node considering transmission and distribution coordination and uncertainty as described in claim 1, characterized in that, The objective function includes the cost of active load, reactive load, and reserve load purchased from the grid, as well as the generation cost of distributed power sources and the reserve cost of steam turbines.

4. The method for determining the marginal electricity price of a distribution node considering transmission and distribution coordination and uncertainty as described in claim 1, characterized in that, The constraints of the objective function include constraints in the basic scheduling process, constraints in the rescheduling process, power balance constraints, upper and lower limits of unit output constraints, unit ramp rate constraints, and line capacity constraints.

5. The method for determining the marginal electricity price of a distribution node considering transmission and distribution coordination and uncertainty as described in claim 1, characterized in that, The Lagrangian function of the constructed distribution network economic dispatch model is calculated to obtain the nodal marginal electricity price and the uncertain nodal marginal electricity price at the bus.

6. The method for determining the marginal electricity price of a distribution node considering transmission and distribution coordination and uncertainty as described in claim 5, characterized in that, The obtained marginal electricity price at the bus and the marginal electricity price at uncertain nodes are sent to the distribution network. Combined with the constructed distribution network economic dispatch model, the functional demand, non-functional demand and reserve capacity demand of the distribution network are obtained and uploaded to the transmission network.

7. The method for determining the marginal electricity price of a distribution node considering transmission and distribution coordination and uncertainty as described in claim 1, characterized in that, The coordination between the transmission network and the distribution network is achieved through information transmission and iterative calculation. The convergence condition of the iterative calculation is that the maximum difference between the marginal electricity price of the transmission market and the marginal electricity price of the uncertain node obtained in two adjacent iterations is less than a preset threshold.

8. A system for determining the marginal electricity price of a distribution node considering transmission and distribution coordination and uncertainty, implementing the steps of the method for determining the marginal electricity price of a distribution node considering transmission and distribution coordination and uncertainty as described in any one of claims 1-7, characterized in that, include: The acquisition module is configured to acquire data information from the power distribution network. The calculation module is configured to obtain the marginal electricity price of the distribution node based on the acquired information and the preset distribution network economic dispatch model; Among them, the distribution network economic dispatch model takes into account the coordination and uncertainty of the transmission network and distribution network, takes the minimum operation cost of distribution network dispatch as the objective function, performs economic dispatch of distribution network, and derives the marginal electricity price of distribution node.

9. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps in the method for determining the marginal electricity price of distribution nodes taking into account transmission and distribution coordination and uncertainty as described in any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the method for determining the marginal electricity price of distribution nodes taking into account transmission and distribution coordination and uncertainty as described in any one of claims 1-7.

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