Distributed power supply consumption capability fine evaluation method

Abstract

The invention provides a refined evaluation method for the consumption capability of a distributed power supply. On the basis of a comprehensive evaluation model of the consumption capability of the distributed power supply under multi-dimensional constraints, under the development background of a new energy large-scale access power grid, flexible load and independent energy storage operation mode, a time sequence production simulation analysis method is used for evaluating the consumption capability of the distributed power supply. In consideration of the influence of demand side response on load characteristics, the influence of power grid dynamic reactive power support capability on the minimum output of a conventional unit and the influence of novel energy storage power transaction on energy storage adjustable capacity, a distributed power supply consumption capability improvement algorithm is provided, and the degree of refinement of distributed power supply consumption capability evaluation can be further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed power source absorptive capacity calculation, and in particular to a method for fine-grained evaluation of distributed power source absorptive capacity. Background Art

[0002] There are two main types of methods commonly used to evaluate the absorption capacity of distributed generation in distribution networks. One is the dynamic simulation method, which can verify the operation constraints of the distribution network in real time. The principle is simple, but it requires repeated verification and the simulation workload is large. The other is the mathematical optimization method, which evaluates the absorption capacity of distributed generation by considering multiple operation constraints and using mathematical optimization algorithms. The calculation results of this method are relatively accurate, but existing research ignores the impact of grid operation strategies on the absorption capacity of distributed generation under the development of new power systems.

[0003] In recent years, distributed power sources have developed rapidly. As one of the key links in the construction of new power systems, the evaluation of distributed power consumption capacity is an important guarantee for achieving local source-load balance. However, the current methods for evaluating the consumption capacity of distributed power sources are not sophisticated enough. Therefore, how to comprehensively coordinate the operation strategy of the new power system, improve the degree of refinement of the evaluation of the consumption capacity of distributed power sources, and thus more accurately evaluate the scale of distributed power development in the region is a problem worth studying. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above and / or existing problems in the evaluation of the absorption capacity of existing distributed power sources, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is to optimize the distributed power source absorption capacity evaluation method according to the new power system operation strategy.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] Step 1: Obtain basic data of the power grid in the area to be evaluated.

[0009] Step 2: Analyze the impact of basic grid data on the absorption capacity of distributed generation, and construct a constraint function for the absorption capacity of distributed generation.

[0010] Step 3: Consider the impact of the operating strategy under the new power system on the distributed generation capacity, and optimize the distributed generation capacity constraint function.

[0011] Step 4: Construct the objective function of distributed power generation capacity and conduct a refined assessment of the regional distributed power generation capacity.

[0012] The step one comprises:

[0013] The grid operation data in step 1 includes but is not limited to the minimum output value of thermal power units, the maximum output value of thermal power units, the minimum output value of hydropower units, the regional load timing curve, the maximum value of external power transmission, the maximum value of energy storage output, the distributed power supply output timing curve, the centralized new energy output value, and the minimum utilization rate of new energy.

[0014] The second step comprises:

[0015] The constraint functions include but are not limited to power balance constraint function, thermal power unit output constraint function, thermal power unit climbing constraint function, hydropower unit output constraint function, external power constraint function, energy storage output constraint function, new energy output constraint function, and new energy utilization rate constraint function.

[0016] (1) Establishing power balance constraint function, including:

[0017] The consumption of new energy sources must meet the dynamic balance between power generation and power consumption, that is, power balance:

[0018]

[0019] Where: P load (t) is expressed as the regional load value; It is represented by the output value of the i-th thermal power unit; It is expressed as the output value of the jth hydropower unit; P trans (t) represents the power value transmitted outside the region, P f (t) represents the regional new energy output value, P ess (t) represents the regional energy storage output.

[0020] (2) Establish the output constraint function of thermal power units, including:

[0021] According to the predicted maximum load and taking into account a certain amount of spare capacity, determine the startup mode of the thermal power unit, and comprehensively analyze the thermal power units of different capacities to determine the minimum technical output allowed for each thermal power unit:

[0022] P tg_down ≤P tg (t)≤P tg_up

[0023] Where: P tg (t) represents the technical output of the thermal power unit; P tg_down It is expressed as the minimum technical output of thermal power units; P tg_upIndicates the rated output of thermal power units.

[0024] (3) Establish the ramp constraint function of the thermal power unit, including:

[0025] The output of thermal power units is constrained by the ramp rate and cannot quickly track the changes in the output of renewable energy, resulting in wind and solar power abandonment. The ramp constraint of thermal power units is determined by the following formula:

[0026] P tg (t)-P tg (t-1)≤P tg_vup

[0027] P tg (t-1)-P tg (t)≤P tg_vdown

[0028] Where: P tg (t) represents the technical output of the thermal power unit at time t; P tg (t-1) represents the technical output of the thermal power unit at time t-1; P tg_vup It is expressed as the upward climbing rate of thermal power units; P tg_vdown Expressed as the downward ramp rate of the thermal power unit.

[0029] (4) Establish the output constraint function of the hydropower unit, including:

[0030] Hydropower output is significantly affected by seasons. There are two operating modes: summer and winter. Hydropower output is arranged according to a certain proportion of installed capacity in each mode:

[0031] P hg_down ≤P hg (t)≤P hg_up

[0032] Where: P hg (t) represents the technical output of the hydropower unit; P hg_down It is expressed as the minimum technical output of the hydropower unit; P hg_up Expressed as the rated output of the hydropower unit.

[0033] (5) Establishing the transmission power constraint function, including:

[0034] When a region has sufficient renewable energy output, it can consider exporting the surplus electricity. The renewable energy export power is subject to the power constraint of the export transmission line as shown in the following formula:

[0035] |P trans (t)|≤P line

[0036] Where: P trans (t) represents the new energy electricity delivered to the region; P lineIndicates the maximum value of the outgoing line power.

[0037] (6) Establishing energy storage constraint functions, including:

[0038] The energy storage output should be less than the rated power of the energy storage, and the stored power should be less than the rated capacity of the energy storage:

[0039] -P ess ≤P ess (t)≤P ess

[0040]

[0041] Where: P ess (t) represents the output value of regional energy storage at time t, P ess Indicates the energy storage rated power, E ess_n Indicates the rated capacity of energy storage.

[0042] (7) Establishing new energy output constraint functions, including:

[0043] 0≤P f (t)≤P f_max (t)

[0044] Where: P f (t) represents the output value of the new energy at time t, P f_max (t) represents the rated output of the renewable energy at time t.

[0045] (8) Establish a new energy utilization rate constraint function, including:

[0046] Allow a certain proportion of renewable energy to be abandoned during low load periods in exchange for a greater amount of renewable energy consumption:

[0047]

[0048]

[0049] Where: P f (t) represents the output value of the new energy at time t, E N is the theoretical power generation of new energy, and n is the minimum required utilization rate of new energy in the local area.

[0050] The step three comprises:

[0051] The operating strategies under the new power system include but are not limited to demand-side response, minimum start-up capacity of thermal power units, and new energy storage operation strategies.

[0052] The power balance constraint function is affected by the demand-side response, the thermal power unit output constraint function is affected by the minimum start-up capacity of the thermal power unit, and the energy storage output constraint function is affected by the new energy storage operation strategy.

[0053] (1) Demand-side response is based on the impact of active load on the absorption capacity of distributed generation. It proposes a refined calculation of regional load considering demand-side response.

[0054] P' load (t) = P load (t)+αP SL (t)+βP TL (t)

[0055] Where: P load (t) is expressed as the regional load value, P' load (t) represents the regional load value after considering the demand side response, P SL (t) is the transferred load power, P TL (t) represents the load translation power, α and β represent the response factors, which are 1 or -1. 1 represents accepting the load from other time periods, and -1 represents moving the load to other time periods.

[0056] (2) The minimum operating capacity of thermal power units takes into account the impact of the dynamic reactive power support of the power grid on the minimum output of thermal power units, and proposes a refined calculation of the minimum output of thermal power units considering voltage stability support.

[0057] P' tg (t) = min{P tg，min (t), P tg，a (t)}

[0058] Where: P' tg (t) represents the minimum output of thermal power units to ensure the reactive power support of the power grid, P tg，min (t) represents the minimum output of the thermal power unit, P tg，a (t) represents the minimum startup capacity to ensure dynamic reactive power support of the power grid.

[0059] (3) The new energy storage operation strategy considers the impact of new energy storage power market transactions on energy storage output, and proposes a refined calculation of energy storage output that takes into account the adjustable capacity of energy storage.

[0060] C=max(P ess，1 *I1+P ess，2 *I2+P ess，3 *I3)

[0061] Where: C represents the maximum benefit of energy storage, P ess，1 , P ess，2 , P ess，3 They respectively represent the energy storage capacity participating in peak-valley price difference arbitrage, peak-shaving compensation, and standby compensation. I1, I2, and I3 respectively represent the unit energy storage income participating in peak-valley price difference arbitrage, peak-shaving compensation, and standby compensation.

[0062] Considering the constraints of energy storage participating in power market transactions, it is necessary to remove the capacity of energy storage participating in peak-valley price difference arbitrage and standby compensation operation mode, that is, the peak load compensation energy storage capacity P ess，2 Participate in power balancing.

[0063] The fourth step comprises:

[0064] The objective function in step 4 determines the access scale of distributed power generation units according to different grid scales, loads, and power structure characteristics, with the goal of maximizing the annual consumption of new energy:

[0065]

[0066] P′ a (t) = min{P a (t), P' f (t)}

[0067] Where: P load (t) is expressed as the regional load value; P trans (t) represents the power value transmitted outside the region, P trans (t)>0 means the area accepts external power, P trans (t)<0 indicates power transmission outside the region; It is represented by the output value of the i-th thermal power unit; It is expressed as the output value of the jth hydropower unit; P ess (t) represents the regional energy storage output, P ess (t)<0 indicates energy storage charging, P ess (t)>0 indicates energy storage discharge; P a (t) represents the new energy consumption space; P′ f (t) is the regional distributed power output value; P′ a (t) represents the actual space for absorbing new energy; EK represents the maximum amount of electricity that the power system can absorb from new energy.

[0068] The method for evaluating the absorption capacity of distributed power sources adopts the time-series production simulation method, and the evaluation period is one year.

[0069] The beneficial effects of the present invention are as follows: on the basis of a comprehensive evaluation model of the absorption capacity of distributed power sources under multi-dimensional constraints, in the context of the development of large-scale access of new energy to the power grid, flexible loads, and independent energy storage operation modes, the impact of demand-side response on load characteristics, the impact of the dynamic reactive power support capacity of the power grid on the minimum output of conventional units, the impact of power market transactions on external power transmission, and the impact of new energy storage power transactions on the adjustable capacity of energy storage are considered, and an improved algorithm for the absorption capacity of distributed power sources is proposed, which can further improve the refinement of the evaluation of the absorption capacity of distributed power sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0071] Figure 1 The figure is a flow chart of a method for fine-grained evaluation of the absorption capacity of distributed power sources. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0074] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0075] Example 1

[0076] Reference Figure 1 , which is the first embodiment of the present invention, and provides a method for fine-grained evaluation of the absorption capacity of distributed power sources, including:

[0077] S100: Obtain basic data of the regional power grid to be evaluated.

[0078] It should be noted that the power grid operation data includes but is not limited to the minimum output of thermal power units, the maximum output of thermal power units, the minimum output of hydropower units, the regional load timing curve, the maximum output of external power, the maximum output of energy storage, the output timing curve of distributed power sources, the output of centralized new energy, and the minimum utilization rate of new energy.

[0079] S200: Analyze the impact of basic grid data on the absorption capacity of distributed power sources, and construct a constraint function for the absorption capacity of distributed power sources.

[0080] It should be noted that the constraint functions include but are not limited to power balance constraint function, thermal power unit output constraint function, thermal power unit climbing constraint function, hydropower unit output constraint function, external power constraint function, energy storage output constraint function, new energy output constraint function, and new energy utilization rate constraint function.

[0081] S300: Considering the impact of the operating strategy under the new power system on the distributed generation capacity, optimize the distributed generation capacity constraint function.

[0082] It should be noted that the operating strategies under the new power system include but are not limited to demand-side response, minimum starting capacity of thermal power units, and new energy storage operation strategies.

[0083] It should be noted that the power balance constraint function is affected by the demand-side response, the thermal power unit output constraint function is affected by the minimum start-up capacity of the thermal power unit, and the energy storage output constraint function is affected by the new energy storage operation strategy.

[0084] S400: Construct an objective function for the distributed power generation capacity and conduct a refined assessment of the regional distributed power generation capacity.

[0085] It should be noted that the objective function determines the access scale of distributed power generation units according to the characteristics of different grid scales, loads, and power supply structures, with the goal of maximizing the annual absorption of new energy.

[0086] It should be noted that the evaluation method for the absorption capacity of distributed power sources adopts the time-series production simulation method, and the evaluation cycle is one year.

[0087] Example 2

[0088] Reference Figure 1 , which is the second embodiment of the present invention, and this embodiment provides a method for fine-grained evaluation of the absorption capacity of distributed power sources. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through comparison.

[0089] Table 1 Comparison between traditional prior art and the present invention

[0090]

[0091]

[0092] As can be seen from Table 1, the present invention makes revolutionary improvements on the basis of traditional existing technologies, taking into account the impact of demand-side response on load characteristics, the impact of dynamic reactive power support capacity of the power grid on the minimum output of conventional units, and the impact of new energy storage power trading on the adjustable capacity of energy storage, and proposes an improved algorithm for distributed power generation capacity, which can further improve the refinement of distributed power generation capacity evaluation.

[0093] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for fine-grained evaluation of the absorption capacity of distributed power sources, characterized by: include, Step 1: Obtain basic data of the power grid in the area to be evaluated. Step 2: Analyze the impact of basic grid data on the absorption capacity of distributed generation, and construct a constraint function for the absorption capacity of distributed generation. Step 3: Consider the impact of the operating strategy under the new power system on the distributed generation capacity, and optimize the distributed generation capacity constraint function. Step 4: Construct the objective function of distributed power generation capacity and conduct a refined assessment of the regional distributed power generation capacity.

2. According to claim 1, a method for fine-grained evaluation of the absorption capacity of distributed power sources is characterized by: The grid operation data in step 1 includes but is not limited to the minimum output value of thermal power units, the maximum output value of thermal power units, the minimum output value of hydropower units, the regional load timing curve, the maximum value of external power transmission, the maximum value of energy storage output, the distributed power supply output timing curve, the centralized new energy output value, and the minimum utilization rate of new energy.

3. According to claim 1, a method for fine-grained evaluation of the absorption capacity of distributed power sources is characterized by: The constraint functions in step 2 include but are not limited to power balance constraint function, thermal power unit output constraint function, thermal power unit climbing constraint function, hydropower unit output constraint function, external power constraint function, energy storage output constraint function, new energy output constraint function, and new energy utilization rate constraint function.

4. The constraint function according to claim 3, characterized in that: (1) Establishing power balance constraint function, including: The consumption of new energy sources must meet the dynamic balance between power generation and power consumption, that is, power balance: Where: P load (t) is expressed as the regional load value; It is represented by the output value of the i-th thermal power unit; It is expressed as the output value of the jth hydropower unit; P trans (t) represents the power value transmitted outside the region, P f (t) represents the regional new energy output value, P ess (t) represents the regional energy storage output. (2) Establish the output constraint function of thermal power units, including: According to the predicted maximum load and taking into account a certain amount of spare capacity, determine the startup mode of the thermal power unit, and comprehensively analyze the thermal power units of different capacities to determine the minimum technical output allowed for each thermal power unit: P tg_down ≤P tg (t)≤P tg_up Where: P tg (t) represents the technical output of the thermal power unit; P tg_down It is expressed as the minimum technical output of thermal power units; P tg_up Indicates the rated output of thermal power units. (3) Establish the ramp constraint function of the thermal power unit, including: The output of thermal power units is constrained by the ramp rate and cannot quickly track the changes in the output of renewable energy, resulting in wind and solar power abandonment. The ramp constraint of thermal power units is determined by the following formula: P tg (t)-P tg (t-1)≤P tg_vup P tg (t-1)-P tg (t)≤P tg_vdown Where: P tg (t) represents the technical output of the thermal power unit at time t; P tg (t-1) represents the technical output of the thermal power unit at time t-1; P tg_vup It is expressed as the upward climbing rate of thermal power units; P tg_vdown Expressed as the downward ramp rate of the thermal power unit. (4) Establish the output constraint function of the hydropower unit, including: Hydropower output is significantly affected by seasons. There are two operating modes: summer and winter. Hydropower output is arranged according to a certain proportion of installed capacity in each mode: P hg_down ≤P hg (t)≤P hg_up Where: P hg (t) represents the technical output of the hydropower unit; P hg_down It is expressed as the minimum technical output of the hydropower unit; P hg_up Expressed as the rated output of the hydropower unit. (5) Establishing the transmission power constraint function, including: When a region has sufficient renewable energy output, it can consider exporting the surplus electricity. The renewable energy export power is subject to the power constraint of the export transmission line as shown in the following formula: |P trans (t)|≤P line Where: P trans (t) represents the new energy electricity delivered to the region; P line Indicates the maximum value of the outgoing line power. (6) Establishing energy storage constraint functions, including: The energy storage output should be less than the rated power of the energy storage, and the stored power should be less than the rated capacity of the energy storage: -P ess ≤P ess (t)≤P ess Where: P ess (t) represents the output value of regional energy storage at time t, P ess Indicates the energy storage rated power, E ess_n Indicates the rated capacity of energy storage. (7) Establishing new energy output constraint functions, including: 0≤P f (t)≤P f_max (t) Where: P f (t) represents the output value of the new energy at time t, P f_max (t) represents the rated output of the renewable energy at time t. (8) Establish a new energy utilization rate constraint function, including: Allow a certain proportion of renewable energy to be abandoned during low load periods in exchange for a greater amount of renewable energy consumption: Where: P f (t) represents the output value of the new energy at time t, E N is the theoretical power generation of new energy, and n is the minimum required utilization rate of new energy in the local area.

5. The method for fine-grained evaluation of the absorption capacity of distributed power sources according to claim 1 is characterized in that: The operation strategies under the new power system in step three include but are not limited to demand-side response, minimum start-up capacity of thermal power units, and new energy storage operation strategies.

6. The method for fine-grained evaluation of the absorption capacity of distributed power sources according to claim 1 is characterized in that: In the step 2, the power balance constraint function is affected by the demand side response, the thermal power unit output constraint function is affected by the minimum startup capacity of the thermal power unit, and the energy storage output constraint function is affected by the new energy storage operation strategy.

7. The distributed power generation capacity optimization function according to claim 5 is characterized by: The demand-side response is based on the impact of active load on the absorption capacity of distributed power sources, and proposes a refined measurement of regional load considering demand-side response. P’ load (t)=P load (t)+αP SL (t)+βP TL (t) Where: P load (t) is expressed as the regional load value, P' load (t) represents the regional load value after considering the demand side response, P SL (t) is the transferred load power, P TL (t) represents the load translation power, α and β represent the response factors, which are 1 or –1. 1 represents accepting the load from other time periods, and –1 represents moving the load to other time periods.

8. The distributed power generation absorption capacity optimization function according to claim 5 is characterized by: The minimum starting capacity of the thermal power unit is based on the influence of the dynamic reactive power support of the power grid on the minimum output of the thermal power unit, and a refined calculation of the minimum output of the thermal power unit considering the voltage stability support is proposed. P’ tg (t)=min{P tg，min (t),P tg，a (t)} Where: P′ tg (t) represents the minimum output of thermal power units to ensure the reactive power support of the power grid, P tg，min (t) represents the minimum output of the thermal power unit, P tg，a (t) represents the minimum startup capacity to ensure dynamic reactive power support of the power grid.

9. The distributed power generation absorption capacity optimization function according to claim 5 is characterized by: The new energy storage operation strategy takes into account the impact of new energy storage power market transactions on energy storage output, and proposes a refined calculation of energy storage output that takes into account the adjustable capacity of energy storage. C=max(P ess，1 *I1+P ess，2 *I2+P ess，3 *I3) Where: C represents the maximum benefit of energy storage, P ess,1 , P ess,2 , P ess,3 They respectively represent the energy storage capacity participating in peak-valley price difference arbitrage, peak-shaving compensation, and standby compensation. I1, I2, and I3 respectively represent the unit energy storage income participating in peak-valley price difference arbitrage, peak-shaving compensation, and standby compensation. Considering the constraints of energy storage participating in power market transactions, it is necessary to remove the capacity of energy storage participating in peak-valley price difference arbitrage and standby compensation operation mode, that is, the peak load compensation energy storage capacity P ess,2 Participate in power balancing.

10. The method for fine-grained evaluation of the absorption capacity of distributed power sources according to claim 1 is characterized in that: The objective function in step 4 determines the access scale of distributed power generation units according to the characteristics of different grid scales, loads, and power supply structures, with the goal of maximizing the annual consumption of new energy: P′ a (t)=min{P a (t),P′ f (t)} Where: P load (t) is expressed as the regional load value; P trans (t) represents the power value transmitted outside the region, P trans (t)>0 means the area accepts external power, P trans (t)<0 indicates power transmission outside the region; It is represented by the output value of the i-th thermal power unit; It is expressed as the output value of the jth hydropower unit; P ess (t) represents the regional energy storage output, P ess (t)<0 indicates energy storage charging, P ess (t)>0 indicates energy storage discharge; P a (t) represents the new energy consumption space; P' f (t) is the regional distributed power output value; P' a (t) represents the actual new energy consumption space; E K It means that the power system can absorb the power of renewable energy to the maximum extent possible.

11. The method for fine-grained evaluation of the absorption capacity of distributed power sources according to claim 1 is characterized in that: The method for evaluating the absorption capacity of distributed power sources in step 4 adopts a time-series production simulation method, and the evaluation period is one year.

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