CN117039901A - Station area uncertainty on-site management scheduling method based on low-voltage flexible direct current interconnection - Google Patents
Station area uncertainty on-site management scheduling method based on low-voltage flexible direct current interconnection Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J5/00—Circuit arrangements for transfer of electric power between ac networks and dc networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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Abstract
The application discloses a station area uncertainty in-situ management scheduling method based on low-voltage flexible direct current interconnection, which comprises the following steps: establishing an in-situ management strategy considering the uncertainty of the flexible direct current interconnection area; establishing a day-ahead optimization model aiming at minimizing the operation and maintenance cost of the platform area; establishing a real-time optimization model aiming at the minimum deviation of the power purchased by the station area in two stages; based on a day-ahead-real-time two-stage optimization model, a commercial solver is adopted to solve the model. The application can realize the on-site management of the uncertainty of the new energy generated power, reduce the influence of the intermittence and the fluctuation of the new energy generated power on an upper power grid, and realize the tracking of a planned power purchasing curve by the adjustment of flexible resources of the new energy generated power through a two-stage optimization model, thereby improving the consumption level of the new energy generated power and having important significance on the running scheduling of renewable energy and a power distribution network.
Description
Technical Field
The application belongs to the field of operation and optimization of power distribution networks, and particularly relates to a station area uncertainty on-site management scheduling method based on low-voltage flexible direct current interconnection.
Background
With the development and application of the distributed power technology, the permeability of new energy power generation in a power distribution network is gradually increased, and the new energy power generation system becomes a core carrier for future power development. However, due to the intermittence and fluctuation of the new energy caused by the prediction error, the consumption, development and utilization of the new energy power generation are greatly limited, and new challenges are brought to the safe and stable operation of the power distribution network. In addition, the requirements of the users of the transformer areas on the power supply reliability are increasingly improved, the original single power supply is difficult to meet the increasing requirements of the power consumption capacity and the high reliability, and meanwhile, the transformer areas cannot share the residual capacity of each other due to the open-loop operation due to the difference of the endowment of resources, so that new energy sources of the adjacent transformer areas are wasted. Therefore, a new solution is needed to solve the above problems.
Disclosure of Invention
The application aims to: in order to overcome the defects in the prior art, a station area uncertainty on-site management scheduling method based on low-voltage flexible direct current interconnection is provided, a station area flexible direct current interconnection mode based on VSC is established, a day-ahead-real-time two-stage optimization model is provided, a day-ahead stage acquires a power purchasing curve of an upper power grid with economic optimization as a target, and a real-time stage aims at minimizing deviation of the upper power purchasing curve, so that tracking of a day-ahead interaction plan power curve is realized.
The technical scheme is as follows: in order to achieve the above purpose, the application provides a station area uncertainty in-situ management scheduling method based on low-voltage flexible direct current interconnection, which comprises the following steps:
s1: an in-situ management strategy considering the uncertainty of the flexible direct current interconnection area is established, and a corresponding expression is established;
s2: according to the expression established in the step S1, a day-ahead optimization model aiming at minimizing the operation and maintenance cost of the platform area is established;
s3: according to the day-ahead optimization result, a real-time optimization model with the aim of minimizing the deviation of the power purchased by the station area in two stages is established.
S4: based on a day-ahead-real-time two-stage optimization model, a commercial solver is adopted to solve the model.
Further, the expression of the low-voltage area flexible-straight interconnection model in the step S1 is as follows:
in the formula (1), the components are as follows,active power for flowing into and out of VSC ac portsRate of->Active power for flowing into and out of the VSC dc port; k (K) VSC Is the transmission loss factor of the VSC. According to the power flow characteristics, at time t +.>One of them is always 0, corresponding +.>One is always 0; in the formula (2), the amino acid sequence of the formula (2),respectively the minimum value and the maximum value of the active power of the VSC alternating current port flowing in and out of the station area i at the moment t; in the formula (3), ->For the low-side power of transformer i at time t,/>Power at time t for the ac load of bay i, +.>The power at time t is stored for station i. In the formula (4), ->The direct current load of the station area i at the moment t;the power flowing to the station area j from the station area i through the connecting line at the moment t; pi (i) is the set of all the zones connected to zone i. P (P) i,PV And (t) is the actual photovoltaic output of the station area i at the moment t.
Further, the daily optimization model targeting to minimize the operation and maintenance cost of the area in the step S2 is as follows:
minC DA ＝C grid +C ES +C VSC +C load (6)
in the formulas (6) to (10), C DA For the total cost of the day-ahead operation plan, C grid 、C ES 、C VSC 、C load The power purchase cost, the energy storage operation maintenance cost, the VSC operation maintenance cost and the demand response compensation cost of the upper power grid are respectively; c grid 、c ES 、c VSC 、c load The method comprises the steps of purchasing electricity cost, energy storage operation maintenance cost, VSC operation maintenance cost and demand response compensation cost of an upper power grid under corresponding unit power. The subscript time t in this section of the formula has been omitted.
Further, the real-time optimization model which is established in the step S3 and aims at minimizing the deviation of the power purchased by the station in two stages is as follows:
in the formulae (11) to (13),the power purchasing quantity of the station area to the upper level in the day-ahead stage is calculated; />For the upper level electricity purchasing quantity of the real-time stage area, < + >>The deviation of the upper-level electricity purchasing in the two-stage platform area is adopted.
Further, in the step S4, based on the day-ahead-real-time two-stage optimization model, a commercial solver is adopted to solve the model, and the solving process is as follows:
a1: carrying out day-ahead stage optimization by utilizing day-ahead source load prediction data, obtaining an optimal solution of day-ahead optimization, and transmitting a planned electricity purchasing power curve of an upper power grid to day-ahead optimization;
a2: based on the planned power purchase power curve obtained by day-ahead optimization, the minimum deviation of the two-stage power purchase power is taken as a target, and the operation tuning strategy of the real-time stage is solved.
The beneficial effects are that: compared with the prior art, the AC/DC converter and the power loss brought by the AC/DC converter are greatly reduced, and the running efficiency of the transformer area is improved; compared with independent operation, the power interaction strategy of the flexible interconnection of the transformer areas is more flexible and changeable, and the direct current areas are divided in the transformer areas, so that the power interaction strategy can be more suitable for the trend and operation requirements of photovoltaic power generation and the direct current load access to the low-voltage distribution transformer areas; meanwhile, a two-stage optimization model is adopted, so that the on-site management of uncertain resources in a platform region can be realized, and the influence on an upper power grid caused by the fluctuation and intermittence of new energy is relieved.
Drawings
FIG. 1 is a flow chart of the method of the present application;
fig. 2 is a block diagram of a power grid employed in an example of the application.
Detailed Description
The present application is further illustrated in the accompanying drawings and detailed description which are to be understood as being merely illustrative of the application and not limiting of its scope, and various modifications of the application, which are equivalent to those skilled in the art upon reading the application, will fall within the scope of the application as defined in the appended claims.
As shown in fig. 1, the application provides a station area uncertainty in-situ management scheduling method based on low-voltage flexible direct current interconnection, which comprises the following steps:
s1: an in-situ management strategy is established that takes into account the zone uncertainty of the flexible direct current interconnect. The expression is as follows:
in the formula (1), the components are as follows,active power for flowing in and out of the VSC ac port,/->Active power for flowing into and out of the VSC dc port; k (K) VSC Is the transmission loss factor of the VSC. According to the power flow characteristics, at time t +.>One of them is always 0, corresponding +.>One is always 0; in the formula (2), the amino acid sequence of the formula (2),respectively the minimum value and the maximum value of the active power of the VSC alternating current port flowing in and out of the station area i at the moment t; in the formula (3), ->For the low-side power of transformer i at time t,/>Power at time t for the ac load of bay i, +.>The power at time t is stored for station i. In the formula (4), ->The direct current load of the station area i at the moment t;the power flowing to the station area j from the station area i through the connecting line at the moment t; pi (i) is the set of all the zones connected to zone i. P (P) i,PV And (t) is the actual photovoltaic output of the station area i at the moment t.
S2: according to the expression established in the step S1, a daily optimization model aiming at minimizing the operation and maintenance cost of the platform area is established.
The day-ahead optimization model targeting minimizing the area operation and maintenance costs is as follows:
minC DA ＝C grid +C ES +C VSC +C load (6)
in the formulas (6) to (10), C DA For the total cost of the day-ahead operation plan, C grid 、C ES 、C VSC 、C load The power purchase cost, the energy storage operation maintenance cost, the VSC operation maintenance cost and the demand response compensation cost of the upper power grid are respectively; c grid 、c ES 、c VSC 、c load The method comprises the steps of purchasing electricity cost, energy storage operation maintenance cost, VSC operation maintenance cost and demand response compensation cost of an upper power grid under corresponding unit power. The subscript time t in this section of the formula has been omitted.
S3: according to the day-ahead optimization result, a real-time optimization model with the aim of minimizing the deviation of the power purchased by the station area in two stages is established.
The real-time optimization model aiming at the minimum deviation of the power purchased by the station area in two stages is as follows:
in the formulae (11) to (13),the power purchasing quantity of the station area to the upper level in the day-ahead stage is calculated; />For the upper level electricity purchasing quantity of the real-time stage area, < + >>The deviation of the upper-level electricity purchasing in the two-stage platform area is adopted.
S4: based on a day-ahead-real-time two-stage optimization model, a commercial solver is adopted to solve the model. The solving process is as follows:
a1: carrying out day-ahead stage optimization by utilizing day-ahead source load prediction data, obtaining an optimal solution of day-ahead optimization, and transmitting a planned electricity purchasing power curve of an upper power grid to day-ahead optimization;
a2: based on the planned power purchase power curve obtained by day-ahead optimization, the minimum deviation of the two-stage power purchase power is taken as a target, and the operation tuning strategy of the real-time stage is solved.
Based on the above, in order to verify the effectiveness of the solution of the present application, in this embodiment, the above solution is applied as an example, specifically as follows:
and selecting a modified real platform area calculation example, and accessing a renewable distributed power supply, energy storage, direct current load and the like on the basis of an original test system, as shown in fig. 2. The ac load, dc load and new energy power generation of the two areas are shown in table 1, ignoring the network power flow constraint.
Table 1 two zone power parameters
Through two-stage optimization, real-time interaction power accurately tracks the daily front interaction power, and the total deviation of 24h interaction power of two areas is 194.61kW. Wherein, the power deviation of the station area 1 is 46.566kW and 43.616kW respectively only at 20h and 22h, and the rest time is 0; the power deviations of the station area 2 are only 9h, 11h and 21h, namely 53.971kW, 34.581kW and 9.875kW respectively. The total running cost in the day-ahead stage is 6440.13 yuan, and the total running cost in the real-time stage is 6503.06 yuan.
According to the embodiment, in the scene that the renewable distributed power source is connected into the power distribution network, the method provided by the application can realize the on-site management of the source load uncertainty in the platform region, reduce the influence of the uncertainty on the upper power grid, realize the power mutual balance between the platform regions, improve the operation efficiency of the platform region, and provide a platform region framework which is suitable for photovoltaic power generation and direct current load connection into the low-voltage power distribution platform region. In conclusion, the method has important known significance for operation scheduling of the power distribution network accessed by the renewable distributed power source.
Finally, it should be noted that the above-mentioned embodiments are merely illustrative of the technical solution of the application and not limiting thereof. It will be understood by those skilled in the art that modifications and equivalents may be made to the particular embodiments of the application, which are within the scope of the claims appended hereto.
Claims (5)
1. The method for in-situ management and scheduling of the uncertainty of the station area based on the low-voltage flexible direct current interconnection is characterized by comprising the following steps:
s1: establishing an in-situ management strategy considering the uncertainty of the flexible direct current interconnection area, and establishing a corresponding expression;
s2: according to the expression established in the step S1, a day-ahead optimization model aiming at minimizing the operation and maintenance cost of the platform area is established;
s3: according to the day-ahead optimization result, a real-time optimization model which aims at minimizing the deviation of the power purchased by the station area in two stages is established;
s4: based on a day-ahead-real-time two-stage optimization model, a commercial solver is adopted to solve the model.
2. The method for in-situ management and scheduling of the region uncertainty based on the low-voltage flexible direct current interconnection according to claim 1, wherein the expression of the low-voltage region flexible direct current interconnection model in the step S1 is as follows:
in the formula (1), the components are as follows,active power for flowing in and out of the VSC ac port,/->For inflow and outflow ofActive power of the VSC dc port; k (K) VSC A transmission loss coefficient for the VSC; according to the power flow characteristics, at time t +.>One of them is always 0, corresponding +.>One is always 0; in the formula (2), the amino acid sequence of the compound,respectively the minimum value and the maximum value of the active power of the VSC alternating current port flowing in and out of the station area i at the moment t; in the formula (3), ->For the low-side power of transformer i at time t,/>Power at time t for the ac load of bay i, +.>The power of energy storage of the station area i at the time t; in the formula (4), ->The direct current load of the station area i at the moment t;the power flowing to the station area j from the station area i through the connecting line at the moment t; pi (i) is the set of all the zones connected to zone i; p (P) i,PV And (t) is the actual photovoltaic output of the station area i at the moment t.
3. The method for in-situ management and scheduling of the uncertainty of the area based on the low-voltage flexible direct current interconnection according to claim 1, wherein the daily optimization model which is established in the step S2 and aims at minimizing the running maintenance cost in the area is as follows:
minC DA ＝C grid +C ES +C VSC +C load (6)
in the formulas (6) to (10), C DA For the total cost of the day-ahead operation plan, C grid 、C ES 、C VSC 、C load The power purchase cost, the energy storage operation maintenance cost, the VSC operation maintenance cost and the demand response compensation cost of the upper power grid are respectively; c grid 、c ES 、c VSC 、c load The method comprises the steps of purchasing electricity cost, energy storage operation maintenance cost, VSC operation maintenance cost and demand response compensation cost of an upper power grid under corresponding unit power.
4. The method for in-situ management and scheduling of the uncertainty of the station area based on the low-voltage flexible direct current interconnection according to claim 1, wherein the real-time optimization model which is established in the step S3 and aims at minimizing the deviation of the station area purchase power in two stages is as follows:
in the formulae (11) to (13),the power purchasing quantity of the station area to the upper level in the day-ahead stage is calculated; />For the upper level electricity purchasing quantity of the real-time stage area, < + >>The deviation of the upper-level electricity purchasing in the two-stage platform area is adopted.
5. The method for in-situ management and scheduling of the uncertainty of the transformer area based on the low-voltage flexible direct current interconnection according to claim 1, wherein in the step S4, a model is solved by a commercial solver based on a day-ahead-real-time two-stage optimization model, and the solving process is as follows:
a1: carrying out day-ahead stage optimization by utilizing day-ahead source load prediction data, obtaining an optimal solution of day-ahead optimization, and transmitting a planned electricity purchasing power curve of an upper power grid to day-ahead optimization;
a2: based on the planned power purchase power curve obtained by day-ahead optimization, the minimum deviation of the two-stage power purchase power is taken as a target, and the operation tuning strategy of the real-time stage is solved.
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| CN116014815A (en) * | 2022-12-30 | 2023-04-25 | 中国电力科学研究院有限公司 | Day-ahead optimal scheduling method and device for low-voltage AC/DC power distribution area |
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