CN115347574A - Regional power grid trans-regional energy scheduling method and system - Google Patents
Regional power grid trans-regional energy scheduling method and system 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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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q50/10—Services
- G06Q50/26—Government or public services
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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
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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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- 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
- H02J2300/28—The renewable source being wind energy
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention discloses a regional power grid trans-regional energy scheduling method, which comprises the following steps: s1: calling real-time operation data of a power grid; s2: processing the real-time operation data of the power grid by taking the region as a unit to obtain energy data which can be scheduled in each region and a power plant which can be scheduled in each region; s3: screening areas and power plants capable of carrying out energy scheduling according to the power scheduling model to obtain areas and power plants in the areas capable of carrying out energy scheduling finally; s4: and generating a real-time power generation dynamic scheduling strategy according to the region which can be subjected to energy scheduling and the power grid real-time operation data of the power plants in the region, and performing cross-region energy scheduling according to the scheduling strategy. The invention can adapt to the situation that the regional power generation and utilization situation changes instantly, and is convenient for a dispatcher to carry out overall control, thereby improving the efficiency of power dispatching, enhancing the rationality of power dispatching and ensuring the safe operation of a power grid.
Description
Technical Field
The invention relates to the field of power grid power dispatching, in particular to a regional power grid trans-regional energy dispatching method and system.
Background
The power dispatching is an effective management means which is adopted for ensuring safe and stable operation of a power grid, reliable external power supply and orderly operation of various power production works. In the prior art, power dispatching usually adopts a one-to-one load adjustment method, that is, load adjustment is performed on data information fed back by information acquisition equipment in a power plant, or information provided by monitoring personnel, and a regulation applied by the power plant. However, with the increase of the number and types of power plants, the distribution situation of the power plants in one area is complex, the power generation and utilization situation changes very rapidly, the existing one-to-one load adjustment method can only perform power scheduling on the power plants one to one, and does not consider the mutual influence relation among the power plants, namely, the power generation output adjustment of any power plant influences the power generation plans of other power plants, the situation of moving the whole body by one is particularly obvious during peak shaving, so that various problems such as large pressure during peak shaving, inadequate real-time power generation adjustment and incapability of comprehensively considering various situations during power generation adjustment are easily caused; meanwhile, with the increase of energy demand in recent years, environmental problems are increasingly highlighted, and the implementation of energy conservation and emission reduction and the development of low-carbon economy are effective measures corresponding to the current climate warming and haze crisis and are the necessary way for sustainable development.
Disclosure of Invention
The invention provides a method and a system for cross-regional energy scheduling of a regional power grid, aiming at solving the problems of pollution caused by inadequate regulation and control during power regulation, incapability of comprehensively considering during power generation regulation and high carbon emission in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
a cross-regional energy scheduling method for a regional power grid comprises the following steps: s1: calling real-time operation data of a power grid; s2: processing the real-time operation data of the power grid by taking the region as a unit to obtain energy data which can be scheduled in each region and a power plant which can be scheduled in each region; s3: screening areas and power plants capable of performing energy scheduling according to the power scheduling model to obtain the areas and the power plants in the areas capable of performing energy scheduling finally; s4: and generating a real-time power generation dynamic scheduling strategy according to the region which can be finally subjected to energy scheduling and the power grid real-time operation data of the power plants in the region, and performing cross-region energy scheduling according to the scheduling strategy. The method for scheduling the energy provided by the invention comprises the following steps: calling real-time operation data of a power grid; processing the real-time operation data of the power grid by taking the region as a unit to obtain region real-time scheduling data; generating a real-time power generation dynamic scheduling strategy facing to power plants in the region according to the region real-time scheduling data; and issuing a real-time power generation dynamic scheduling strategy. As the power plants are subjected to one-to-one load adjustment in the prior art, as the number and types of the power plants increase, a lot of emergency situations exist, scheduling is complex and cannot be adapted, and a systematic scheduling strategy for a plurality of power plants is not formed, and mutual action of the power plants in a region during power generation is not considered. The real-time operation data of the power grid is processed by taking the region as a unit to obtain the real-time scheduling data of the region, the overall power generation and utilization condition of the region can be reflected, and the real-time power generation dynamic scheduling strategy generated according to the real-time scheduling data can comprehensively schedule all power plants in each region and reasonably distribute the output of each power plant. For example, for a cascade basin power plant, the power generation amounts of power plants at the upstream and the downstream of the basin are mutually influenced, and a real-time power generation dynamic scheduling strategy is generated for the area where the basin is located, so that the power plants on the basin can be uniformly distributed, the distribution efficiency is improved, and the condition that one household appliance plant is adjusted to influence another power plant when one-to-one load is adjusted is avoided. At the time of heavy power dispatching tasks such as peak shaving, the method for making the strategy by uniformly acquiring the data can better play the role, can be more suitable for the situation that the regional power generation and utilization situation is changeable instantly, and is convenient for a dispatcher to carry out global control, so that the power dispatching efficiency is improved, the rationality of power dispatching is enhanced, and the safe operation of a power grid is ensured. Meanwhile, after the energy data capable of being scheduled and the power plants capable of being scheduled in each area are determined, the areas capable of being scheduled and the power plants are screened according to the power scheduling model, so that low-carbon power scheduling of each area of the power grid is realized, and carbon pollution is effectively reduced.
As a preferred scheme of the present invention, the real-time operation data of the power grid specifically includes real-time operation unit data of the power plants in each area, a unit day-ahead power utilization plan, and real-time power generation amount of the power plants; the S2 specifically comprises the following steps: s21: summarizing the daily electricity utilization plans of the units to obtain a total electricity utilization plan of each area; s22: obtaining the upper and lower output limits of each planning unit according to the real-time operation unit data; s23: summarizing the real-time power generation amount of the power plant by taking a planning unit as a unit to obtain the real-time power generation amount of the planning unit; s24: and obtaining energy data which can be scheduled in each region and a power plant which can be scheduled in each region according to the total power utilization plan, the upper and lower output limits and the real-time power generation amount of each region.
As a preferred embodiment of the present invention, the power plant includes a thermal power plant, a wind power plant, a photovoltaic power plant, and a hydroelectric power plant.
As a preferred aspect of the present invention, the power scheduling model includes a cost minimum optimization objective and a total carbon emission minimum optimization objective.
As a preferable aspect of the present invention, the objective functions of the power scheduling model include an average power generation cost objective function and an average carbon emission amount objective function.
As a preferable aspect of the present invention, the average power generation cost objective function is as follows:
wherein, C G，i As a function of the cost of power generation of the unit i of the thermal power plant, C W，j As a function of the cost of generation of the wind power plant j, C P，s As a function of the generation cost of the photovoltaic power station s of the photovoltaic power plant, N c Number of units of thermal power plant, N w Number of wind power plants, N P For the number of photovoltaic power stations of a photovoltaic power plant,
the expected active output of the thermal power plant unit i,
for the desired active power output of the wind power plant j,
is the desired active power output of the photovoltaic power plant s of the photovoltaic power plant.
As a preferred embodiment of the present invention, the target function of the average carbon emission is as follows:
wherein, the first and the second end of the pipe are connected with each other,
the expected carbon emission of the unit i of the thermal power plant,
for the desired carbon emissions of the wind power plant j,
is the desired carbon footprint of the photovoltaic power plant s of the photovoltaic power plant.
As a preferred scheme of the invention, the constraint conditions of the power scheduling model comprise power balance constraint, thermal power plant unit output constraint, node voltage constraint and branch power constraint.
A regional power grid cross-regional energy scheduling system comprises a scheduling center and a plurality of regional scheduling units, wherein the scheduling center and the regional scheduling units are both connected with a communication system.
As a preferred scheme of the invention, the dispatching center comprises an acquisition module, a sorting module and an analysis module, wherein the acquisition module is used for calling real-time operation data of the power grid; the sorting and analyzing module is used for processing the real-time operation data of the power grid by taking the region as a unit to obtain energy data which can be scheduled in each region and a power plant which can be scheduled in each region.
Therefore, the invention has the following beneficial effects: the method for energy scheduling provided by the invention processes the real-time operation data of the power grid by taking the region as a unit to obtain the real-time scheduling data of the region, can reflect the whole power generation and utilization condition of the region, and can comprehensively schedule all power plants in each region according to the generated real-time power generation dynamic scheduling strategy, thereby reasonably distributing the output of each power plant, improving the distribution efficiency and avoiding the condition that one power plant is influenced by regulating one power plant when one-to-one load is regulated. At the time of peak regulation and other heavy power dispatching tasks, the method for uniformly acquiring data to formulate a strategy can play a role, can adapt to the situation that the regional power generation and utilization conditions change instantaneously, and is convenient for a dispatcher to carry out global control, so that the power dispatching efficiency is improved, the rationality of power dispatching is enhanced, and the safe operation of a power grid is ensured. Meanwhile, after the energy data capable of being scheduled and the power plants capable of being scheduled in each area are determined, the areas capable of being scheduled and the power plants are screened according to the power scheduling model, so that low-carbon power scheduling of each area of the power grid is realized, and carbon pollution is effectively reduced.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a schematic diagram of the system architecture of the present invention.
Detailed Description
The invention is further described with reference to the following detailed description and accompanying drawings.
As shown in fig. 1, a method for scheduling regional power grid cross-regional energy includes the following steps: s1: calling real-time operation data of a power grid; s2: processing the real-time operation data of the power grid by taking the region as a unit to obtain energy data which can be scheduled in each region and a power plant which can be scheduled in each region; s3: screening areas and power plants capable of carrying out energy scheduling according to the power scheduling model to obtain areas and power plants in the areas capable of carrying out energy scheduling finally; s4: and generating a real-time power generation dynamic scheduling strategy according to the region which can be finally subjected to energy scheduling and the power grid real-time operation data of the power plants in the region, and performing cross-region energy scheduling according to the scheduling strategy. The method for scheduling the energy provided by the invention comprises the following steps: calling real-time operation data of a power grid; processing the real-time operation data of the power grid by taking the region as a unit to obtain region real-time scheduling data; generating a real-time power generation dynamic scheduling strategy facing to the power plants in the region according to the region real-time scheduling data; and issuing a real-time power generation dynamic scheduling strategy. As the power plants are subjected to one-to-one load adjustment in the prior art, as the number and types of the power plants increase, a lot of emergency situations exist, scheduling is complex and cannot be adapted, and a systematic scheduling strategy for a plurality of power plants is not formed, and mutual action of the power plants in a region during power generation is not considered. The real-time operation data of the power grid is processed by taking the region as a unit to obtain the real-time scheduling data of the region, the overall power generation and utilization conditions of the region can be reflected, and the real-time power generation dynamic scheduling strategy generated according to the real-time scheduling data can comprehensively schedule all power plants in each region and reasonably distribute the output of each power plant. For example, for a cascade basin power plant, the power generation amounts of power plants at the upstream and the downstream of the basin are mutually influenced, and a real-time power generation dynamic scheduling strategy is generated for the area where the basin is located, so that the power plants on the basin can be uniformly distributed, the distribution efficiency is improved, and the condition that one household appliance plant is adjusted to influence another power plant when one-to-one load is adjusted is avoided. At the time of heavy power dispatching tasks such as peak shaving, the method for making the strategy by uniformly acquiring the data can better play the role, can be more suitable for the situation that the regional power generation and utilization situation is changeable instantly, and is convenient for a dispatcher to carry out global control, so that the power dispatching efficiency is improved, the rationality of power dispatching is enhanced, and the safe operation of a power grid is ensured. Meanwhile, after the energy data capable of being scheduled and the power plants capable of being scheduled in each area are determined, the areas capable of being scheduled and the power plants are screened according to the power scheduling model, so that low-carbon power scheduling of each area of the power grid is realized, and carbon pollution is effectively reduced.
The real-time operation data of the power grid specifically comprises real-time operation unit data of power plants in each area, a unit day-ahead power utilization plan and real-time power generation amount of the power plants; s2 specifically comprises the following steps: s21: summarizing the daily electricity utilization plans of the units to obtain a total electricity utilization plan of each area; s22: obtaining the upper and lower output limits of each planning unit according to the real-time operation unit data; s23: summarizing the real-time power generation amount of the power plant by taking a planning unit as a unit to obtain the real-time power generation amount of the planning unit; s24: and obtaining energy data which can be scheduled in each region and a power plant which can be scheduled in each region according to the total power utilization plan, the upper and lower output limits and the real-time power generation amount of each region.
Power plants include thermal power plants, wind power plants, photovoltaic power plants, and hydroelectric power plants.
The power scheduling model includes a cost minimization optimization objective and a total carbon emissions minimization optimization objective.
The objective functions of the power scheduling model include an average power generation cost objective function and an average carbon emission amount objective function.
The average power generation cost objective function is as follows:
wherein, C G，i As a function of the cost of power generation of the unit i of the thermal power plant, C w，j As a function of the cost of generation of wind power plant j, C P，s As a function of the generation cost of the photovoltaic power station s of the photovoltaic power plant, N c Number of units of thermal power plant, N w Number of wind power plants, N P For the number of photovoltaic power stations of a photovoltaic power plant,
the expected active output of the thermal power plant unit i,
for the desired active power output of the wind power plant j,
the desired active power output of the photovoltaic power station s of the photovoltaic power plant.
The target function for the average carbon emissions is as follows:
wherein the content of the first and second substances,
for the expected carbon emission of the unit i of the thermal power plant,
for the desired carbon emissions of the wind power plant j,
is the desired carbon footprint of the photovoltaic power plant s of the photovoltaic power plant.
The constraint conditions of the power dispatching model comprise power balance constraint, thermal power plant unit output constraint, node voltage constraint and branch power constraint.
As shown in fig. 2, a regional power grid cross-regional energy scheduling system includes a scheduling center and a plurality of regional scheduling units, both of which are connected to a communication system. The dispatching center comprises an acquisition module, a sorting module and an analysis module, wherein the acquisition module is used for calling real-time operation data of the power grid; the sorting and analyzing module is used for processing the real-time operation data of the power grid by taking the region as a unit to obtain energy data which can be scheduled in each region and a power plant which can be scheduled in each region.
In this embodiment, a method for scheduling energy across regions of a regional power grid includes:
s1: and calling real-time operation data of the power grid.
In a dispatching system, collection of information such as a day-ahead power generation and utilization plan, ultra-short-term load prediction, link plan change, section tidal current quota, and a real-time running state of the system is currently achieved, so in practical application, according to a power plant type, an actual situation and the like, the following are called in the dispatching system: the method comprises the following steps of generating basic information of a power plant, real-time operation unit data, a day-ahead power generation and utilization plan, ultra-short-term load prediction data, a tie line plan, section tidal current limit, order application data, a day-in rolling plan, real-time power generation amount of the power plant, real-time water regime data (including water level, real-time ecological flow, real-time incoming water flow and the like), unit overhaul data, cross-regional day spot commodity transaction data, special power plant requirement data, certified warranty on duty qualification certification data and the like, and only needing to call power grid real-time operation data.
The mode of calling the real-time operation data of the power grid can be two types as follows: the first mode is realized by using a system interface, and interface files are transmitted to a target server by using an SFTP transmission protocol, so that a corresponding file format warehousing program is adopted for each data interface file to perform warehousing in the target server by using a data analysis program; the second way is to synchronize data into the database according to the rule of "data synchronization service", and with the database server in the three zones, the data sources include data synchronized from the three zones to the three zones, and also from the one zone to the two zones.
S2: and processing the real-time operation data of the power grid by taking the region as a unit to obtain energy data which can be scheduled in each region and a power plant which can be scheduled in each region. S2 specifically comprises the following steps:
s21: and summarizing the daily electricity utilization plans of the units to obtain a total electricity utilization plan of each area.
The statistical areas can be divided according to the existing mode, the short-distance power scheduling can be carried out, such as administrative areas, residential areas, commercial areas and the like, the power scheduling can also be carried out remotely, such as the scheduling carried out among different counties and cities, each county and city is defined as each area, historical power utilization records of each unit (such as residential buildings, parks and the like) are collected in the areas, a power utilization prediction model is trained for prediction, the prediction results are adjusted by combining power utilization plans obtained by investigation of each area, a unit day-ahead power utilization plan is obtained, and then the unit day-ahead power utilization plans in the areas are collected to obtain a regional total power utilization plan.
S22: and obtaining the upper and lower output limits of each planning unit according to the real-time operation unit data.
For convenient management, power plants in the region are grouped by taking a planning unit as a unit, the upper and lower output limits (namely the maximum value and the minimum value of generated energy) of each power plant unit are obtained according to the collected real-time operation unit data (including the unit in operation and the unit which is not in operation but available) of the power plants, and the upper and lower output limits of each power plant unit are gathered to obtain the upper and lower output limits of each planning unit.
The energy consumption condition of the power plants of each planning unit can be counted, and therefore the most energy-saving power generation strategy is selected when real-time power generation dynamic scheduling is conducted.
S23: and summarizing the real-time power generation amount of the power plant by taking a planning unit as a unit to obtain the real-time power generation amount of the planning unit.
The real-time operation data of the power grid are subjected to statistical analysis and summarization, the real-time power generation amount of each planning unit in each area is summarized to obtain the real-time power generation amount of the area, the real-time power generation amount of the area is compared with the total power utilization plan of the area to obtain the value of the whole power generation amount of the area, the adjustment range which can be made by each planning unit is displayed by the upper and lower limits of the output of each planning unit, various planning data are sequenced according to the time sequence, and the reasonability and the optimal configuration of the real-time scheduling data of the area are ensured.
S24: and obtaining energy data which can be scheduled in each region and a power plant which can be scheduled in each region according to the total power utilization plan, the upper and lower output limits and the real-time power generation amount of each region.
After the areas where power scheduling can be performed and the power plants in the areas where power scheduling can be performed are obtained, the power values of the areas where power scheduling can be performed can be calculated according to the traditional power scheduling mode, so that power scheduling is performed.
According to the method, areas and power plants capable of performing energy scheduling are screened according to the power scheduling model, so that low-carbon power scheduling of each area of the power grid is realized, and carbon pollution is effectively reduced while power scheduling is performed. The method specifically comprises the following steps: s3: and screening areas and power plants capable of carrying out energy scheduling according to the power scheduling model to obtain the areas and the power plants in the areas capable of carrying out energy scheduling finally.
The objective function of the power scheduling model is as follows:
average power generation cost objective function:
wherein, C G，i As a function of the cost of power generation of the unit i of the thermal power plant, C w，j As a function of the cost of generation of wind power plant j, C P，s As a function of the generation cost of the photovoltaic power station s of the photovoltaic power plant, N c Number of units of thermal power plant, N w Number of wind power plants, N P For the number of photovoltaic power stations of a photovoltaic power plant,
the expected active output of the thermal power plant unit i,
for the desired active power output of the wind power plant j,
is the desired active power output of the photovoltaic power plant s of the photovoltaic power plant.
Average carbon emission objective function:
wherein the content of the first and second substances,
for the expected carbon emission of the unit i of the thermal power plant,
for the desired carbon emissions of the wind power plant j,
is a desired carbon emission for photovoltaic power plants s of photovoltaic power plants.
Average regional carbon emission variance function:
wherein, N r To divide the number of regions, E i To the desired carbon emission of zone i, E j The expected carbon emissions for zone j, the difference reflecting the carbon emissions imbalance level between the regional zones, f 3 The larger the size, the more serious the pollution in some areas.
The constraint conditions of the power dispatching model comprise power balance constraint, thermal power plant unit output constraint, node voltage constraint and branch power constraint.
And power balance constraint:
in the formula, P G，i Is the active power output, P, of all thermal power plant units on node i w，i Active power output, P, for all wind power plants at node i P，i Is the active power output, P, of all photovoltaic power station photovoltaic power stations on the node i I，i Active output, Q, for all loads on node i G，i Is the reactive power of the thermal power plant unit, Q w，i For reactive power of wind power plants, Q I，i The reactive power of the photovoltaic power station of the photovoltaic power plant is 0,V for the reactive power of the load i Is the voltage amplitude of node i, θ ij Is the phase angle difference between nodes i, j, N b Is the number of nodes, G ij Is the conductance between nodes i, j, B ij Is the susceptance between nodes i, j.
Output restraint of the thermal power plant unit:
wherein the content of the first and second substances,
is the minimum value of the active power of the node i,
is the maximum value of the active power of the node i,
is the minimum value of reactive power at node i,
is the maximum reactive power value of the node i.
Node voltage constraint:
Pr(V i min ≤V i ≤V i max )≥c V i＝1，2，……N b
wherein Pr (-) is the probability of occurrence of an event, V i min Is the lower limit of the voltage amplitude of node i, V i max Is the upper voltage amplitude limit of node i, c V Is the confidence level under the node voltage constraint.
Branch power constraint:
wherein N is l Number of branches, P line，i For the active power of the branch i,
upper limit of active power for branch i, c l The confidence level of the branch active power output constraint condition is met.
S4: and generating a real-time power generation dynamic scheduling strategy according to the region which can be finally subjected to energy scheduling and the power grid real-time operation data of the power plants in the region, and performing cross-region energy scheduling according to the scheduling strategy.
The regional power scheduling model is essentially a multi-target probability optimal power flow problem and can be divided into two parts: probability trend containing new energy and multi-objective optimization. The probabilistic power flow is used for processing inequalities (node voltage constraint and branch power constraint) containing opportunity constraint in constraint conditions, an out-of-limit part is added into an original objective function as a penalty term, then a multi-objective optimization algorithm is used for solving, an area capable of performing energy scheduling when carbon emission is minimum and power plants in the area are obtained, finally a real-time power generation dynamic scheduling strategy is generated according to the output condition of each power plant, and cross-area energy scheduling is performed according to the scheduling strategy. It should be noted that, in actual engineering, each area of the whole power grid should be reasonably divided by a scheduling department in advance according to geographical locations, so as to ensure that the environment, economy and load levels among the areas are basically consistent as much as possible, and avoid that the final optimization result loses significance due to improper division and overlarge difference of carbon emission of different areas.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that are not thought of through the inventive work should be covered within the scope of the present invention.
Claims (10)
1. A cross-regional energy scheduling method for a regional power grid is characterized by comprising the following steps:
s1: calling real-time operation data of a power grid;
s2: processing the real-time operation data of the power grid by taking the region as a unit to obtain energy data which can be scheduled in each region and a power plant which can be scheduled in each region;
s3: screening areas and power plants capable of carrying out energy scheduling according to the power scheduling model to obtain areas and power plants in the areas capable of carrying out energy scheduling finally;
s4: and generating a real-time power generation dynamic scheduling strategy according to the region which can be finally subjected to energy scheduling and the power grid real-time operation data of the power plants in the region, and performing cross-region energy scheduling according to the scheduling strategy.
2. The method for dispatching the regional power grid across the regional energy according to claim 1, wherein the real-time operation data of the power grid specifically comprises real-time operation unit data of power plants in each region, a unit day-ahead power utilization plan and real-time power generation amount of the power plants;
the S2 specifically comprises the following steps:
s21: summarizing the daily electricity utilization plans of each unit to obtain a total electricity utilization plan of each area; s22: obtaining the upper and lower output limits of each planning unit according to the real-time operation unit data;
s23: summarizing the real-time power generation amount of the power plant by taking a planning unit as a unit to obtain the real-time power generation amount of the planning unit;
s24: and obtaining energy data which can be scheduled in each region and a power plant which can be scheduled in each region according to the total power utilization plan, the upper and lower output limits and the real-time power generation amount of each region.
3. The method as claimed in claim 1, wherein the power plant comprises a thermal power plant, a wind power plant, a photovoltaic power plant and a hydro power plant.
4. The method according to claim 1, wherein the power dispatching model comprises a cost minimization optimization objective and a total carbon emission minimization optimization objective.
5. The trans-regional energy scheduling method for the regional power grid according to claim 1 or 4,
the method is characterized in that the objective functions of the power dispatching model comprise an average power generation cost objective function and an average carbon emission objective function.
6. The method according to claim 5, wherein the average power generation cost objective function is as follows:
wherein, C G，i As a function of the cost of power generation of the unit i of the thermal power plant, C W，j A cost function of generation of j, C P，s As a function of the generation cost of the photovoltaic power station s of the photovoltaic power plant, N c Number of units of thermal power plant, N w Number of wind power plants, N P For the number of photovoltaic power stations of a photovoltaic power plant,
the expected active output of the thermal power plant unit i,
for the desired active power output of the wind power plant j,
the desired active power output of the photovoltaic power station s of the photovoltaic power plant.
7. The method according to claim 5, wherein the target function of the average carbon emission is as follows:
wherein, the first and the second end of the pipe are connected with each other,
the expected carbon emission of the unit i of the thermal power plant,
for the desired carbon emissions of the wind power plant j,
is a desired carbon emission for photovoltaic power plants s of photovoltaic power plants.
8. The method according to claim 5, wherein the constraints of the power scheduling model include power balance constraints, thermal power plant unit output constraints, node voltage constraints and branch power constraints.
9. A regional power grid trans-regional energy scheduling system is applicable to the regional power grid trans-regional energy scheduling method as claimed in claim 1, and is characterized by comprising a scheduling center and a plurality of regional scheduling units, wherein the scheduling center and the regional scheduling units are both connected with a communication system.
10. The regional power grid trans-regional energy scheduling system of claim 9, wherein the scheduling center comprises an acquisition module, a sorting module and an analysis module, wherein the acquisition module is used for retrieving real-time operation data of a power grid; the sorting and analyzing module is used for processing the real-time operation data of the power grid by taking the region as a unit to obtain energy data which can be scheduled in each region and a power plant which can be scheduled in each region.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116502876A (en) * | 2023-06-28 | 2023-07-28 | 国网浙江省电力有限公司宁波供电公司 | Power system resource sharing method and device, computer equipment and storage medium |
| CN116757410A (en) * | 2023-06-13 | 2023-09-15 | 杨润琴 | Power supplementing and taking strategy identification system using artificial intelligent model |
| CN117077978A (en) * | 2023-10-11 | 2023-11-17 | 浙江浙能能源服务有限公司 | Trans-regional new energy storage method and system |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757410A (en) * | 2023-06-13 | 2023-09-15 | 杨润琴 | Power supplementing and taking strategy identification system using artificial intelligent model |
| CN116757410B (en) * | 2023-06-13 | 2024-04-26 | 黑龙江信志先创科技有限公司 | Power supplementing and taking strategy identification system using artificial intelligent model |
| CN116502876A (en) * | 2023-06-28 | 2023-07-28 | 国网浙江省电力有限公司宁波供电公司 | Power system resource sharing method and device, computer equipment and storage medium |
| CN117077978A (en) * | 2023-10-11 | 2023-11-17 | 浙江浙能能源服务有限公司 | Trans-regional new energy storage method and system |
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