CN114444850A - Park energy storage planning method, device, equipment and medium based on digital twin - Google Patents

Park energy storage planning method, device, equipment and medium based on digital twin Download PDF

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Publication number
CN114444850A
CN114444850A CN202111538456.XA CN202111538456A CN114444850A CN 114444850 A CN114444850 A CN 114444850A CN 202111538456 A CN202111538456 A CN 202111538456A CN 114444850 A CN114444850 A CN 114444850A
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park
energy
energy storage
load
mathematical model
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杨超
程青
林舒
熊天龙
周特
包维瀚
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Sichuan Energy Internet Research Institute EIRI Tsinghua University
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Sichuan Energy Internet Research Institute EIRI Tsinghua University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • 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
    • G06Q10/00—Administration; Management
    • 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
    • G06Q10/06313—Resource planning in a project environment
    • G—PHYSICS
    • 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
    • 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
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • 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 embodiment of the invention provides an energy storage planning method and device of a park energy system based on a multi-dimensional digital twin technology, electronic equipment and a computer readable storage medium, wherein the energy storage planning method comprises the following steps: predicting the electrical load of the park; constructing a mathematical model of the equipment based on a multi-dimensional digital twinning technology; and optimizing the energy storage mode of the park energy system according to the power load and the equipment mathematical model. According to the invention, the factors considered by the energy storage planning are more comprehensive, and the planning is more reasonable.

Description

Park energy storage planning method, device, equipment and medium based on digital twin
Technical Field
The invention relates to the technical field of energy conservation, in particular to a method and a device for planning energy storage of a park energy system based on a multidimensional digital twin technology, electronic equipment and a computer readable storage medium.
Background
The park energy system is a comprehensive system consisting of power supply, regional heat supply, cold supply and various energy conversion devices. The industrial park energy system consists of energy stations and a cold/heat/electricity/gas energy supply pipe network, wherein the energy stations are the core of a regional comprehensive energy system. According to the distribution of the energy stations at the user side or in the garden by the user, the garden can be divided into distributed energy stations and centralized energy stations. For a centralized energy source station, the load requirements of cooling, heating, power supply and the like in a park are generally met simultaneously, and the centralized energy source station is a hub of a park energy source supply system. The centralized energy station in the regional integrated energy system is called an integrated energy station. From the perspective of energy supply, energy stations primarily supply energy and store energy. The energy system is composed of various different types of energy sources, energy production equipment, energy conversion equipment and energy storage equipment, and the energy source forms comprise cold, heat, electricity, gas and the like. The terminal energy load requirements include power requirements, heating requirements, hot water requirements, and refrigeration requirements. At the input end of the system, the energy can be wind energy, natural gas, diesel oil, solar energy, geothermal energy and the like, and through different energy conversion devices, the energy of the energy is finally converted into electric energy, heat energy and cold energy of end users through utilization and conversion at all levels. At home and abroad, research has provided a physical model level of a comprehensive energy system, including various energy forms of electricity, cold, heat, gas and the like in all links from production, conversion, storage to consumption. The development and the start of foreign energy systems are early, the factors for planning and researching the energy systems are more, the model construction is relatively complex, the random planning method of the comprehensive energy system is provided, the uncertainty of different energy prices is described in a random normal mode, the investment planning of the energy systems is taken as a first-stage optimization problem, the operation of the energy systems is taken as a second-stage optimization problem, and a two-stage model for optimizing the energy systems is constructed. The development of the domestic comprehensive energy system starts late abroad, but a rich result is obtained, and the factors for planning and researching the comprehensive energy system are simple. At present, an energy storage planning method for a park energy system with more comprehensive consideration factors is lacked.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for planning energy storage of a campus energy system based on a multidimensional digital twin technology, an electronic device, and a computer-readable storage medium, which are considered more comprehensively and planned more reasonably.
In one aspect, the present invention provides a method for planning energy storage of a park energy system based on a multidimensional digital twinning technique, including: predicting the electrical load of the park; constructing a mathematical model of the equipment based on a multi-dimensional digital twinning technology; and optimizing the energy storage mode of the park energy system according to the power load and the equipment mathematical model.
According to a particular embodiment of the invention, predicting the electrical load of a campus comprises: the total cooling load of the park building is predicted according to the following formula:
Figure BDA0003413619640000021
wherein L represents the total cooling load of the building in the park, H represents the sample building area, WγRepresents the unit area cooling load comprehensive index, m represents the total number of the building types, and n represents the nth building type.
According to a particular embodiment of the invention, predicting the electrical load of a campus comprises: predicting the industrial electrical load of the industrial users of the park according to the following formula:
Fr＝t×E×r
where Fr represents the industrial electricity load of the industrial users of the park, E represents the steam load, r represents the steam consumed per unit product, and t represents the product yield.
According to a particular embodiment of the invention, predicting the electrical load of a campus comprises: forecasting the electrical load of the campus according to the following formula:
K＝P×(1+d)j
in the formula, K represents the power load of the park, P represents the historical load, d represents the annual load growth rate, and j represents the number of years.
According to a particular embodiment of the invention, the construction of the mathematical model of the equipment based on the multidimensional digital twinning technique comprises: constructing a physical mathematical model of the power grid flow of the park energy system according to the following formula:
Figure BDA0003413619640000031
in the formula, delta P is the node injected active power, delta Q is the node injected reactive power, PGActive power, P, for the generating equipment on which the node is mountedLActive power, Q, of the load carried by the nodeGFor tapping reactive power, Q, from the nodeLAnd inputting reactive power into a node, wherein U is the voltage amplitude of the node, i and j are the node numbers at two ends of the line, G is the conductance of the line, B is the susceptance of the line, theta is the phase angle difference of the voltage of the nodes at two sides of the line, m is the number of PQ nodes, and n is the total number of nodes of the system.
According to a particular embodiment of the invention, the construction of the mathematical model of the equipment based on the multidimensional digital twinning technique comprises: constructing a physical mathematical model of the natural gas pipeline network transportation capacity of the park energy system according to the following formula:
Figure BDA0003413619640000032
wherein Z represents the natural gas pipeline flow rate, K0Representing the mass flow of natural gas, K1Representing the absolute pressure level at the beginning of the natural gas pipeline, M0Representing the compressibility of natural gas at the beginning of the pipeline, M1Represents the potential energy factor function of the natural gas, phi represents the absolute pressure level of the natural gas at the tail end of the pipeline, and B represents the resistance coefficient along the pipeline.
According to a particular embodiment of the invention, optimizing the energy storage mode of the park energy system according to the electricity load and the equipment mathematical model comprises: calculating the relationship between the stored energy and the charging and discharging power of the electrothermal energy storage equipment according to the following formula:
I＝(1-pε)×Dt-Δε
in the formula, I represents stored energy, p represents a physical energy storage consumable coefficient, D represents a scheduling time interval, t represents discharging efficiency, and epsilon represents charging efficiency;
and optimizing the energy storage mode of the park energy system according to the relation.
According to a particular embodiment of the invention, optimizing the energy storage mode of the park energy system according to the electricity load and the equipment mathematical model comprises: calculating the power distribution characteristics in a certain area of the park according to the following formula:
Figure BDA0003413619640000041
in the formula, U represents electric quantity, h represents a power supply period, q represents initial power consumption of a functional area, and i represents a re-decomposition period;
and optimizing the energy storage mode of the park energy system according to the electric quantity distribution characteristic.
In another aspect, the present invention provides an energy storage planning apparatus for a park energy system based on a multidimensional digital twinning technique, including: the forecasting module is used for forecasting the electric load of the park; the construction module is used for constructing a mathematical model of the equipment based on a multi-dimensional digital twin technology; and the optimization module is used for optimizing the energy storage mode of the park energy system according to the power load and the equipment mathematical model.
In another aspect, the present invention provides an electronic device comprising: a processor; a memory; an application program stored in the memory and configured to be executed by the processor, the application program including instructions for performing the energy storage planning method described above.
In another aspect, the present invention provides a computer-readable storage medium storing a computer program for executing the energy storage planning method.
The existing energy storage planning method has the problem that the equipment mathematical model is incomplete, so that the installed capacity of renewable energy sources is small. According to the energy storage planning method and device of the park energy system based on the multidimensional digital twinning technology, the electronic equipment and the computer readable storage medium, the energy storage planning method of the park energy system based on the multidimensional digital twinning technology is designed. The invention provides the combination of a multidimensional digital twin technology and a park energy system, and combined with the energy consumption of industrial users, the power load of a park is predicted; constructing an equipment mathematical model by adopting a multi-dimensional digital twinning technology to obtain an energy conversion rule; and the energy storage mode of the energy system is optimized, and zero heat emission is realized. Case analysis results: the average installed capacity of the optimized renewable energy is 2349.6kW, which is improved by 626.6kW compared with that before optimization, and the energy storage planning method fused with the multidimensional digital twin technology has a wider application prospect.
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Fig. 1 shows a flow diagram of a method for planning the energy storage of a park energy system based on a multidimensional digital twinning technique according to an embodiment of the invention;
fig. 2 is a schematic structural diagram of an energy storage planning apparatus of a park energy system based on a multidimensional digital twinning technique according to an embodiment of the present invention;
fig. 3 shows a schematic structural diagram of an electronic device according to an embodiment of the invention.
Detailed Description
The present invention is described in detail below with reference to specific embodiments in order to make the concept and idea of the present invention more clearly understood by those skilled in the art. It is to be understood that the embodiments presented herein are only a few of all embodiments that the present invention may have. Those skilled in the art who review this disclosure will readily appreciate that many modifications, variations, or alterations to the described embodiments, either in whole or in part, are possible and within the scope of the invention as claimed.
As used herein, the terms "first," "second," and the like are not intended to imply any order, quantity, or importance, but rather are used to distinguish one element from another. As used herein, the terms "a," "an," and the like are not intended to mean that there is only one of the described items, but rather that the description is directed to only one of the described items, which may have one or more. As used herein, the terms "comprises," "comprising," and other similar words are intended to refer to logical interrelationships, and are not to be construed as referring to spatial structural relationships. For example, "a includes B" is intended to mean that logically B belongs to a, and not that spatially B is located inside a. Furthermore, the terms "comprising," "including," and other similar words are to be construed as open-ended, rather than closed-ended. For example, "a includes B" is intended to mean that B belongs to a, but B does not necessarily constitute all of a, and a may also include C, D, E and other elements.
The terms "embodiment," "present embodiment," "an embodiment," "one embodiment," and "one embodiment" herein do not mean that the pertinent description applies to only one particular embodiment, but rather that the description may apply to yet another embodiment or embodiments. Those of skill in the art will understand that any of the descriptions given herein for one embodiment can be combined with, substituted for, or combined with the descriptions of one or more other embodiments to produce new embodiments, which are readily apparent to those of skill in the art and are intended to be within the scope of the present invention.
An energy storage planning method of a park energy system based on a multi-dimensional digital twinning technique according to an embodiment of the present invention is described below with reference to fig. 1.
According to the present embodiment, the energy storage planning method 100 includes:
s110, predicting the electric load of the park;
s120, constructing a mathematical model of the equipment based on a multi-dimensional digital twin technology;
and S130, optimizing the energy storage mode of the park energy system according to the electricity load and the equipment mathematical model.
According to the embodiment, the result of the electric/thermal energy storage planning is more economical, and the safety and the reliability of the system operation can be ensured. And establishing an electric/thermal energy storage planning model, and considering energy supply and demand balance, cold/heat/electric coupling and energy complementation to meet the load requirement. Meanwhile, the electric energy storage capacity is reduced, the waste of renewable energy sources is reduced, and both environmental benefit and economic benefit are brought.
In one embodiment, the operation principle of the multidimensional digital twinning system is as follows: when the production system runs, the service system controls the physical production line and carries out actual production activities according to the production plan.
In one embodiment, the digital twin technology may refer to a technology that makes full use of data such as a physical model, sensor update, operation history, and the like, integrates a multidisciplinary, multi-physical quantity, multi-scale, multi-probability simulation process, and performs a mapping in a virtual space to reflect a life cycle operation process of a corresponding physical device. Based on this, it is reasonable to apply the digital twin technology to the detection of the energy consumption of the whole life cycle of the building, and a new detection method is designed for the digital twin technology, so that the detection precision of the energy consumption of the whole life cycle of the building is improved fundamentally.
The concept of "twinning" can be traced back to the Apollo project of the United states space agency. In this project, NASA plans to manufacture two identical physical planes. Airplanes left on land are called twins to reflect the operational state of the mission airplane in real time. Twins are commonly used for flight training or simulation experiments to help astronauts make the right decisions when performing actual tasks. Twins are substantially identical to entities in geometry, content and properties, and the operating conditions of the entities are simulated by simulation. In summary, "digital twinning" is a process and method of describing real physical objects and building virtual models in a virtual world using digital technology. The virtual model maps and describes the physical object from the aspects of geometry, physical attributes, corresponding behaviors, rules and the like, constructs data service in a virtual world, monitors, evaluates, diagnoses, predicts and optimizes physical entities, and finally forms a virtual-real fused data twin architecture which comprises entity data, model data, service data, domain knowledge and other twin data pools of the whole product life cycle.
In one embodiment, the concept of "multidimensional" includes:
(1) model multidimensional, involving physical models, data driven models (predictive models), rule models;
(2) the data is multidimensional, and multi-source heterogeneous data of different equipment and different energy networks in a park are related.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more of the features of one or more of the embodiments described above.
According to the embodiment, the method for predicting the electric load of the park comprises the following steps:
the total cooling load of the park building is predicted according to the following formula:
Figure BDA0003413619640000071
wherein L represents the total cooling load of the building in the park, H represents the sample building area, WγRepresents the integrated index of the cooling load per unit area, m represents the total number of the building types, and n represents the nth building type.
By predicting the total cooling load of the building of the campus according to this embodiment, it is advantageous to correctly predict the overall electricity load of the campus, since the cooling load constitutes a considerable part of the total load.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
According to the embodiment, the method for predicting the electric load of the park comprises the following steps:
predicting the industrial electrical load of the industrial users of the park according to the following formula:
Fr＝t×E×r
where Fr represents the industrial electricity load of the industrial users of the park, E represents the steam load, r represents the steam consumed per unit product, and t represents the product yield.
According to this embodiment, the industrial users of the campus are in the majority, so predicting the industrial load is helpful in predicting the overall load of the campus.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
According to the embodiment, the method for predicting the electric load of the park comprises the following steps:
forecasting the electrical load of the campus according to the following formula:
K＝P×(1+d)j
in the formula, K represents the electrical load of the park, P represents the historical load, d represents the annual load growth rate, and j represents the number of years.
According to the embodiment, the power utilization load of the park is predicted according to the historical load of the park, so that the power utilization load can be estimated and predicted as accurately as possible when data are lacked.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
According to the embodiment, when planning the equipment capacity of the comprehensive energy source station of the industrial park, firstly, the power utilization characteristics of the user are analyzed to obtain the energy load curve of the user. And then predicting the energy load of the user in a certain future period according to the economic development level and the battery energy storage capacity of the user, so that a load prediction result of the user can be obtained. When the load prediction method based on the index method is adopted, for a typical industrial enterprise, the load prediction method is composed of two parts of building envelope environment heat exchange and equipment processing production heat dissipation, and generally takes building cold/heat load as a main part. The total cooling load calculation formula of the building is as follows:
Figure BDA0003413619640000081
in the formula (1), H represents a sample building area, WγRepresents the unit area cooling load comprehensive index, m represents the total number of the building types, and n represents the nth building type. Height of hot steam and electric load and product type of industrial userIn this regard, analysis and prediction are required based on the production plan of the enterprise, and it is generally assumed that steam load/power load is approximately proportional to output production. Therefore, the yield value consumption method is adopted for analysis and prediction. The industrial electrical load expression is as follows:
Fr＝t×E×r (2)
in the formula (2), E represents the steam load, r represents the steam consumed per unit product, and t represents the product yield. Generally, in engineering practice, if insufficient analysis data is available, a proportion increase method is adopted to simply predict the load according to the existing historical data and engineering experience. The load prediction formula is as follows:
K＝P×(1+d)j (3)
in the formula (3), P represents the historical load, d represents the annual load growth rate, and j represents the number of years. And (3) further analyzing the load change trend after acquiring the load curve of the park user according to collection or analysis by combining the formulas (1) to (3), so as to obtain a load prediction result. On the basis, the forecasting of the electric load of the park is completed.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
According to the embodiment, based on the multidimensional digital twinning technology, the equipment mathematical model is constructed, and the method comprises the following steps:
constructing a physical mathematical model of the power grid flow of the park energy system according to the following formula:
Figure BDA0003413619640000091
in the formula, delta P is the node injected active power, delta Q is the node injected reactive power, PGActive power, P, for the generating equipment on which the node is mountedLActive power, Q, of loads carried by the nodeGFor tapping reactive power, Q, from the nodeLFor node inflow reactive power, U is node voltage amplitude, i, j are two linesThe end nodes are numbered, G is the line conductance, B is the line susceptance, theta is the voltage phase angle difference of the nodes on two sides of the line, m is the number of PQ nodes, and n is the total number of the nodes of the system.
According to the embodiment, the power grid is an important component of the energy system, a mathematical model of the power grid tide is constructed, and the method plays a great role in constructing the equipment mathematical model of the park.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
According to the embodiment, based on the multidimensional digital twinning technology, the equipment mathematical model is constructed, and the method comprises the following steps:
constructing a physical mathematical model of the natural gas pipeline network transportation capacity of the park energy system according to the following formula:
Figure BDA0003413619640000101
in the formula, Z represents, K0Representing the mass flow of natural gas, K1Representing the absolute pressure level at the beginning of the natural gas pipeline, M0Representing the compressibility of natural gas at the beginning of the pipeline, M1Represents the potential energy factor function of the natural gas, phi represents the absolute pressure level of the natural gas at the tail end of the pipeline, and B represents the resistance coefficient along the pipeline.
According to this embodiment, the natural gas energy also constitutes an important part of the park energy system, and is relatively stable in usage, and is suitable for building mathematical models.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
The operation principle of the multi-dimensional digital twin system is as follows: when the production system runs, the service system controls the physical production line,and carrying out actual production activities according to the production plan. In the future, the analysis and calculation results can be fed back to the park energy system, and the alarm, control optimization and energy storage planning of the production process are realized. Power supply equipment in the park energy system mainly comprises distributed renewable energy power generation, an energy storage battery, an electric automobile charging pile and a power distribution network. The equipment can realize the production, transmission and storage of clean electric energy and is an important component of an industrial park comprehensive energy system. The power grid flow of the park energy system adopts the alternating current flow of the power distribution network to extract the energy conversion rule[9]The expression of the physical mathematical model is as follows:
Figure BDA0003413619640000111
in the formula, delta P is the node injected active power, delta Q is the node injected reactive power, PGActive power, P, for the generating equipment on which the node is mountedLActive power, Q, of the load carried by the nodeGFor tapping reactive power, Q, from the nodeLAnd inputting reactive power into a node, wherein U is the voltage amplitude of the node, i and j are the node numbers at two ends of the line, G is the conductance of the line, B is the susceptance of the line, theta is the phase angle difference of the voltage of the nodes at two sides of the line, m is the number of PQ nodes, and n is the total number of nodes of the system. The natural gas supply includes natural gas sources, pipelines, compressors, etc. and, in general, the relevant parameters, such as pipeline pressure, flow rate, etc., do not change with time. The parameters in the dynamic power flow model may change over time. The expression of the physical mathematical model of the natural gas pipe network conveying capacity is as follows:
Figure BDA0003413619640000112
in the formula (5), K0Representing the mass flow of natural gas, K1Representing the absolute pressure level at the beginning of the natural gas pipeline, M0Representing the compressibility of natural gas at the beginning of the pipeline, M1Represents the potential energy factor function of the natural gas, phi represents the absolute pressure level of the natural gas at the tail end of the pipeline, and B represents the pressure level along the pipelineThe coefficient of resistance. Meanwhile, the electricity is converted into gas by electrolyzing water to obtain hydrogen, and the hydrogen and carbon dioxide are further synthesized into methane and other gases, so that electric energy is converted into relatively convenient gas for storage. With the rapid development of renewable energy sources and supply and demand, current in a power grid flows to a storage battery after being rectified, the storage battery discharges and flows back to the power grid through an inverter, and therefore bidirectional flow of electric energy between the battery and the power grid is achieved. The structure of the battery energy storage system comprises an energy storage unit, a battery energy management system, a filter and the like, wherein a battery is the core of the energy storage unit and consists of a plurality of battery units and is used for storing and releasing electric energy, and the battery management system monitors and controls the output voltage, the current, the temperature and the state of charge of the energy storage system in real time, so that the safe, efficient and economic operation of the energy storage system is ensured. On the basis, the establishing step of the equipment mathematical model is completed.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
According to this embodiment, according to the power consumption load with equip mathematical model, optimize the energy storage mode of garden energy system, include:
calculating the relation between the stored energy and the charging and discharging power of the electrothermal energy storage device according to the following formula:
I＝(1-pε)×Dt-Δε
in the formula, I represents stored energy, p represents a physical energy storage consumable coefficient, D represents a scheduling time interval, t represents discharging efficiency, and epsilon represents charging efficiency;
and optimizing the energy storage mode of the park energy system according to the relation.
According to the embodiment, the electric heat energy storage is a main form of energy storage, and the performance of the energy storage device can be accurately judged by calculating the relation between the stored energy and the charging and discharging power of the electric heat energy storage device, so that the setting and the operation of the energy storage device are correctly planned.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
According to this embodiment, according to the power consumption load with equip mathematical model, optimize the energy storage mode of garden energy system, include:
calculating the power distribution characteristics in a certain area of the park according to the following formula:
Figure BDA0003413619640000121
in the formula, U represents electric quantity, h represents a power supply period, q represents initial power consumption of a functional area, and i represents a re-decomposition period;
and optimizing the energy storage mode of the park energy system according to the electric quantity distribution characteristic.
According to this embodiment, optimize the energy storage mode in garden according to electric quantity distribution characteristic, be favorable to the position distribution of rational planning energy storage device or equipment more, improve energy storage device utilization efficiency, reduce the loss of the energy in long distance transportation way.
The energy storage planning method of the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention is described below. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
According to the embodiment, the energy storage mode of the energy system must meet the requirement of the dislocation distribution of the same energy in time, and the supply and demand mismatch of energy supply can be adjusted in time, so that the energy system can be used as a secondary adjustment means of a comprehensive energy system of a functional area to make up the energy supply and demand mismatch caused by multi-energy complementation. In the operation process of an energy system, the electric energy storage mainly plays roles in stabilizing the uncertainty of the output of renewable energy and improving the economical efficiency of system operation, can store electric energy when the load of a power grid is low, and release the electric energy when the load of the power grid is high, and can be used for peak clipping and valley filling to reduce the fluctuation of the power grid. At present, electric energy storage equipment mainly comprises lithium ion batteries, lead-acid batteries, sodium-sulfur batteries and flow batteries, and megawatt demonstration application is realized in the fields of renewable energy grid connection, distributed power generation, micro-grids and the like. An electric boiler in the heat accumulating type electric boiler is a coupling unit for energy form conversion, generally uses new energy sources such as photovoltaic energy, wind power energy and the like as power sources, and outputs hot water or high-temperature steam through electromagnetic induction or resistance heating. The installation of the heat storage tank can break through the traditional 'fixing the electricity with the heat' operation mode, so that the electricity load of the electric boiler can be controlled, the electricity load is increased in a low-load period, and redundant electricity is converted into heat to be stored. During peak load periods, the electrical load demand is reduced and the stored heat energy is used for heating. Therefore, wind power can be more effectively utilized in the valley period, the peak clipping and valley filling effects can be achieved, even the combined heat and power generation unit can be turned off under extreme conditions, the electric boiler is completely used for heating, and zero heating emission is realized. Among the various cold storage methods, ice storage stores a cooling amount by changing water into ice, and the ice storage amount is much smaller than a water storage amount. Assuming that a lead-acid storage battery, a heat storage tank and a cold storage tank are used as physical devices for storing electric heat energy, the relational expression of the stored energy and the charge and discharge power is as follows:
I＝(1-pε)×Dt-Δε (6)
in the formula (6), p represents the physical energy storage consumable coefficient, D represents the scheduling time interval, t represents the discharging efficiency, and epsilon represents the charging efficiency. The problem of comprehensive energy demand of users is solved through the space-time coupling of cold, heat and electricity and the complementation of energy demand, and cold, heat and electricity can be generated, transmitted, converted and supplied in a system. Meanwhile, the cross complementarity of various energy sources and the flexible and reliable characteristics of the thermoelectric generator set can efficiently absorb new energy sources with strong volatility, such as photovoltaic energy, wind power energy and the like. However, the energy storage plan of the regional integrated energy system including the multifunctional area is no longer the capacity configuration of a single independent energy system, and the capacity requirements of energy supply, transmission, conversion and energy storage devices in various energy forms are comprehensively considered. Considering that the functional region is equivalent to the whole of the decomposable state, an expression of the electric quantity distribution characteristic in a certain region is obtained as follows:
Figure BDA0003413619640000141
in the formula (7), h represents a power supply period, q represents initial power consumption of the functional region, and i represents a re-decomposition period. And when the multifunctional interval is cooperatively planned, planning is carried out according to different user requirements. Based on the analysis, the difference and the time-space complementarity of the source network charge storage of the cold and heat electricity in different types of functional areas are considered, the time distribution characteristic of the electric automobile, the flexibility of temperature load and the thermal inertia of a heating system are utilized to optimize the charge and discharge of the electric automobile, the room temperature and the temperature of the refrigeration storage, and an equipment planning model which comprehensively considers the source network charge storage difference of the multifunctional areas and has the entity energy storage of the regional comprehensive energy system with the collaborative virtual energy storage is constructed. On the basis, the optimization step of the energy storage mode of the energy system is completed.
The following describes a specific implementation process of the energy storage planning method for the park energy system based on the multidimensional digital twinning technology according to an embodiment of the present invention. This embodiment is a specific example of the embodiment of fig. 1, and may include one or more features of one or more of the embodiments described above.
In the embodiment, an industrial park in south China is taken as a research object. The industrial park has 13 industrial users, which is equivalent to 13 load nodes of the whole park. The four load nodes include four load types: electricity, heat, cold, and gas. The three load nodes include three load types: electricity, heat, and cold. The three load nodes include electrical and thermal load types. The heat load refers to hot water for industrial production with the water supply temperature of 140-170 ℃ and the water return temperature of 30-45 ℃, the heat supply of the building space, and the cold load refers to the cold supply amount of the building space. The basic parameters of the park equipment are shown in the table 1:
TABLE 1 basic parameters and prices of the equipment
Figure BDA0003413619640000142
Case analysis was performed according to table 1. In addition to the above conditions, the industrial park also includes 24 road network nodes. Energy substitution stations are selected according to local resource conditions, geographical environments and policy factors, and comprise a cold and hot combined power supply station, a photovoltaic station, an electric heating boiler, a gas boiler, an absorption refrigerator, a natural gas station and an energy storage substitution station. For the cold and heat load of a building, the area is located in a subtropical climate area, no heating demand exists all the year round, but the refrigeration demand does not exist, the cold load demand exists all the year round except before and after spring festival, the cold load demand in summer is a cold supply peak period in 6, 7, 8 and 9 months, and the cold load demand in the period accounts for more than 55% of the total amount of the year round.
By combining the multidimensional digital twinning technology, the energy storage planning method for the park energy system designed by the embodiment is utilized to optimize the park energy storage scheme, and the installed capacity of renewable energy sources before and after optimization is obtained, as shown in table 2:
TABLE 2 installed capacity of renewable energy (kW)
Figure BDA0003413619640000151
As can be seen from the table 2, under different scene conditions, the average installed capacity of the renewable energy source after optimization is 2349.6kW, and the average installed capacity before optimization is 1723kW, which indicates that the designed energy storage planning method has higher performance.
An energy storage planning apparatus for a park energy system based on a multi-dimensional digital twinning technique according to an embodiment of the present invention is described below with reference to fig. 2.
According to the present embodiment, the energy storage planning apparatus 200 includes:
a prediction module 210 for predicting the electrical load of the campus;
the construction module 220 is used for constructing a mathematical model of the equipment based on a multi-dimensional digital twinning technology;
and the optimizing module 230 is used for optimizing the energy storage mode of the park energy system according to the power load and the equipment mathematical model.
An electronic device according to an embodiment of the invention is described below with reference to fig. 3.
As shown in fig. 3, electronic device 300 includes one or more processors 310 and memory 320.
The processor 310 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 300 to perform desired functions.
Memory 320 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium and executed by the processor 310 to implement the energy storage planning methods of the various embodiments of the present application described above and/or other desired functions.
In one example, the electronic device 300 may further include: an input device 330 and an output device 340, which are interconnected by a bus system and/or other form of connection mechanism (not shown).
For example, the input device 330 may be a microphone or an array of microphones for capturing a speech input signal; may be a communications network connector for receiving the collected input signals from a cloud or other device; but may also include, for example, a keyboard, mouse, etc.
The output device 340 may output various information including the determined distance information, direction information, and the like to the outside. The output devices 340 may include, for example, a display, speakers, printer, and the like, as well as a communication network and its connected remote output devices.
Of course, for simplicity, only some of the components of the electronic device 300 relevant to the present application are shown in fig. 3, and components such as buses, input/output interfaces, and the like are omitted. In addition, electronic device 300 may include any other suitable components depending on the particular application.
In addition to the above-described methods and apparatuses, embodiments of the present application may also be a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform the steps in the display control methods according to the various embodiments of the present application described hereinabove.
The computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The concepts, principles and concepts of the invention have been described above in detail in connection with specific embodiments (including examples and illustrations). It will be appreciated by persons skilled in the art that embodiments of the invention are not limited to the specific forms disclosed above, and that many modifications, alterations and equivalents of the steps, methods, apparatus and components described in the above embodiments may be made by those skilled in the art after reading this specification, and that such modifications, alterations and equivalents are to be considered as falling within the scope of the invention. The scope of the invention is only limited by the claims.

Claims (11)

1. An energy storage planning method of a park energy system based on a multidimensional digital twinning technology comprises the following steps:
predicting the electrical load of the park;
constructing a mathematical model of the equipment based on a multi-dimensional digital twinning technology;
and optimizing the energy storage mode of the park energy system according to the power load and the equipment mathematical model.
2. An energy storage planning method according to claim 1 in which the predicting of the electrical load of a campus comprises:
the total cooling load of the park building is predicted according to the following formula:
Figure FDA0003413619630000011
wherein L represents the total cooling load of the building in the park, H represents the sample building area, WγRepresents the unit area cooling load comprehensive index, m represents the total number of the building types, and n represents the nth building type.
3. An energy storage planning method according to claim 1 in which the predicting of the electrical load of a campus comprises:
predicting the industrial electrical load of the industrial users of the park according to the following formula:
Fr＝t×E×r
where Fr represents the industrial electricity load of the industrial users of the park, E represents the steam load, r represents the steam consumed per unit product, and t represents the product yield.
4. An energy storage planning method according to claim 1 in which the predicting of the electrical load of a campus comprises:
forecasting the electrical load of the campus according to the following formula:
K＝P×(1+d)j
in the formula, K represents the power load of the park, P represents the historical load, d represents the annual load growth rate, and j represents the number of years.
5. An energy storage planning method according to any one of claims 1 to 4 in which the construction of an equipment mathematical model based on a multi-dimensional digital twinning technique comprises:
constructing a physical mathematical model of the power grid flow of the park energy system according to the following formula:
Figure FDA0003413619630000021
in the formula, delta P is the node injected active power, delta Q is the node injected reactive power, PGActive power, P, for the generating equipment on which the node is mountedLActive power, Q, of the load carried by the nodeGFor tapping reactive power, Q, from the nodeLAnd inputting reactive power into a node, wherein U is the voltage amplitude of the node, i and j are the node numbers at two ends of the line, G is the conductance of the line, B is the susceptance of the line, theta is the phase angle difference of the voltage of the nodes at two sides of the line, m is the number of PQ nodes, and n is the total number of nodes of the system.
6. An energy storage planning method according to any one of claims 1 to 4 in which the construction of an equipment mathematical model based on a multi-dimensional digital twinning technique comprises:
constructing a physical mathematical model of the natural gas pipeline network transport capacity of the park energy system according to the following formula:
Figure FDA0003413619630000022
wherein Z represents the natural gas pipeline flow rate, K0Representing the mass flow of natural gas, K1Representing the absolute pressure level at the beginning of the natural gas pipeline, M0Representing the compressibility of natural gas at the beginning of the pipeline, M1Represents the potential energy factor function of the natural gas, phi represents the absolute pressure level of the natural gas at the tail end of the pipeline, and B represents the resistance coefficient along the pipeline.
7. An energy storage planning method according to any one of claims 1 to 4 in which the optimizing the energy storage mode of the park energy system in dependence on the electrical load and the equipment mathematical model comprises:
calculating the relation between the stored energy and the charging and discharging power of the electrothermal energy storage device according to the following formula:
I＝(1-pε)×Dt-Δε
in the formula, I represents stored energy, p represents a physical energy storage consumable coefficient, D represents a scheduling time interval, t represents discharging efficiency, and epsilon represents charging efficiency;
and optimizing the energy storage mode of the park energy system according to the relation.
8. An energy storage planning method according to any one of claims 1 to 4 in which the optimizing the energy storage mode of the park energy system in dependence on the electrical load and the equipment mathematical model comprises:
calculating the electricity distribution characteristics in a certain area of the park according to the following formula:
Figure FDA0003413619630000031
in the formula, U represents electric quantity, h represents a power supply period, q represents initial power consumption of a functional area, and i represents a re-decomposition period;
and optimizing the energy storage mode of the park energy system according to the electric quantity distribution characteristic.
9. An energy storage planning device of a park energy system based on a multidimensional digital twinning technology comprises:
the forecasting module is used for forecasting the electric load of the park;
the construction module is used for constructing a mathematical model of the equipment based on a multi-dimensional digital twin technology;
and the optimization module is used for optimizing the energy storage mode of the park energy system according to the power load and the equipment mathematical model.
10. An electronic device, comprising:
a processor;
a memory;
an application program stored in the memory and configured to be executed by the processor, the application program comprising instructions for performing the energy storage planning method according to any of claims 1 to 8.
11. A computer-readable storage medium having stored thereon a computer program for executing the energy storage planning method according to any of claims 1 to 8.
CN202111538456.XA 2021-12-15 2021-12-15 Park energy storage planning method, device, equipment and medium based on digital twin Pending CN114444850A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115494801A (en) * 2022-09-09 2022-12-20 广东鑫光智能系统有限公司 Plate production line building method and terminal
CN117613903A (en) * 2024-01-23 2024-02-27 国网冀北电力有限公司 User side energy storage dispatching optimization control method and device based on digital twin architecture

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115494801A (en) * 2022-09-09 2022-12-20 广东鑫光智能系统有限公司 Plate production line building method and terminal
CN117613903A (en) * 2024-01-23 2024-02-27 国网冀北电力有限公司 User side energy storage dispatching optimization control method and device based on digital twin architecture
CN117613903B (en) * 2024-01-23 2024-04-05 国网冀北电力有限公司 User side energy storage dispatching optimization control method and device based on digital twin architecture

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