CN113902167A - Comprehensive intelligent energy system configuration optimization method and device considering station house investment - Google Patents
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Abstract
The invention belongs to the field of energy system configuration optimization, and provides a comprehensive intelligent energy system configuration optimization method and device considering station and house investment. The method comprises the steps of obtaining project basic data, equipment data and civil engineering data; based on the energy station equipment type selection model, under the operation constraint of each energy model and the electricity, heat and cold power balance constraint in the comprehensive intelligent energy system, obtaining the equipment type selection, the capacity planning scheme, the output of each type of equipment, the energy station investment condition, the pollutant emission and the comprehensive energy efficiency ratio of the comprehensive intelligent energy system; the energy station equipment type selection model has the objective functions of considering station house investment, and having the lowest total cost of the system full life cycle, the lowest annual pollutant discharge amount and the highest comprehensive energy efficiency ratio.
Description
Technical Field
The invention belongs to the field of energy system configuration optimization, and particularly relates to a comprehensive intelligent energy system configuration optimization method and device considering station house investment.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The comprehensive intelligent energy system planning and designing method is influenced by complex factors such as mutual coupling of multiple energy sources, random fluctuation of energy sources and loads, participation of multiple main bodies and the like, the comprehensive intelligent energy system planning and designing process depends on a large amount of manpower at present, repeated planning, single design scheme, incomplete evaluation and the like are easy to occur, not only is the planning and designing efficiency low, but also a large amount of manpower resources are wasted, and the requirements on cost calculation accuracy and project timeliness are difficult to meet, so that the practical, reliable, accurate and effective planning and designing method is needed.
The existing comprehensive intelligent energy system configuration optimization method usually only focuses on selection of system equipment capacity, neglects investment estimation of an energy station house, and the part of investment usually accounts for a large proportion of total project investment and has obvious influence on an optimization result.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a comprehensive intelligent energy system configuration optimization method and device considering station house investment, which can realize the purpose of relatively accurately optimizing and selecting the comprehensive intelligent energy system configuration by considering the station house investment.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a comprehensive intelligent energy system configuration optimization method considering station house investment, which comprises the following steps:
acquiring project basic data, equipment data and civil engineering data;
based on the energy station equipment type selection model, under the operation constraint of each energy model and the electricity, heat and cold power balance constraint in the comprehensive intelligent energy system, obtaining the equipment type selection, the capacity planning scheme, the output of each type of equipment, the energy station investment condition, the pollutant emission and the comprehensive energy efficiency ratio of the comprehensive intelligent energy system;
the energy station equipment type selection model has the objective functions of considering station house investment, and having the lowest total cost of the system full life cycle, the lowest annual pollutant discharge amount and the highest comprehensive energy efficiency ratio.
The second aspect of the present invention provides an apparatus for optimizing a comprehensive intelligent energy system configuration, which considers station house investment, comprising:
the data acquisition module is used for acquiring project basic data, equipment data and civil engineering data;
the optimization configuration module is used for selecting a model based on the energy station equipment type, and obtaining the equipment type selection, the capacity planning scheme, the output of each type of equipment, the energy station investment condition, the pollutant discharge amount and the comprehensive energy efficiency ratio of the comprehensive intelligent energy system under the operation constraint of each energy model and the electricity, heat and cold power balance constraint in the comprehensive intelligent energy system;
the energy station equipment type selection model has the objective functions of considering station house investment, and having the lowest total cost of the system full life cycle, the lowest annual pollutant discharge amount and the highest comprehensive energy efficiency ratio.
A third aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, implements the steps of the method for optimizing an integrated intelligent energy system configuration considering station building investment as described above.
A fourth aspect of the present invention provides a computer device, including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method for optimizing an integrated intelligent energy system configuration, considering station house investment.
Compared with the prior art, the invention has the beneficial effects that:
in the invention, the calculation of the investment of the station house of the energy station is taken into consideration, the optimal area of the energy station is obtained by utilizing the genetic algorithm, a basis is provided for the design of the energy station, the accurate total investment of the comprehensive intelligent energy system can be more accurately obtained, the economic index is more comprehensive, and the practical guiding significance is realized.
The comprehensive intelligent energy system configuration optimization method realizes the collaborative optimization of various energy forms, solves the problems of single design scheme, unreasonable system configuration structure, incomplete evaluation and the like in the planning process of the comprehensive intelligent energy system, obviously reduces the workload of planning designers, improves the planning and designing efficiency, and has important significance for the planning and designing of computer-aided comprehensive intelligent energy systems.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a schematic flow chart illustrating a method for optimizing configuration of an integrated intelligent energy system according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a calculation process of station house investment of an energy station according to an embodiment of the invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Example one
As shown in fig. 1, the present embodiment provides a method for optimizing a configuration of an integrated intelligent energy system considering station-house investment, which specifically includes the following steps:
step 1: project basic data, equipment data and civil engineering data are obtained.
The project basic data comprise project area, building type, typical daily electricity, cold, hot and hot water time-by-time load, available resource quantity and resource price of the project.
The available resource amount of the project comprises the amount of illumination amplitude, wind power, electricity, gas, geothermal energy, water source and the like at the location of the project.
The resource prices include local electricity prices, gas prices, water prices, and other resource prices.
The equipment data comprises investment cost, maintenance cost and efficiency of each type of equipment in unit capacity and electric cold and hot output limit of each unit of equipment.
The civil engineering data is used for calculating the investment of the energy station house and comprises unit volume construction costs of an energy station inner wall, an energy station outer wall, reinforced concrete columns, beams, water proofing, heat preservation, foundations and the like.
Step 2: based on the energy station equipment type selection model, under the operation constraint of each energy model and the electricity, heat and cold power balance constraint in the comprehensive intelligent energy system, obtaining the equipment type selection, the capacity planning scheme, the output of each type of equipment, the energy station investment condition, the pollutant emission and the comprehensive energy efficiency ratio of the comprehensive intelligent energy system;
the energy station equipment type selection model has the objective functions of considering station house investment, and having the lowest total cost of the system full life cycle, the lowest annual pollutant discharge amount and the highest comprehensive energy efficiency ratio.
The total system investment cost of the energy station investment is the sum of the total investment, the annual maintenance cost, the annual fuel cost and the annual electricity purchasing cost of a project, and the total investment of the project consists of the station building investment, the equipment investment in the station building and other costs except the station building and equipment investment.
Specifically, the total investment cost of the system for the economic target-energy station investment is f:
total cost minimum in M years of full life cycle, Cinv、Com，y、Cfuel，y、Cgrid，yThe total investment, annual maintenance cost, annual fuel cost, annual electricity purchase cost of the project are respectively.
Total cost minimum in M years of full life cycle, Cinv、Com，y、Cfuel，y、Cgrid，yRespectively, total investment, annual maintenance cost, annual fuel cost, annual electricity purchase cost of the project, wherein:
Cinv＝Cinv，sta+Cinv，equ+Cinv，oth
in the formula, Cinv，staThe station building investment is calculated and obtained by a station building investment module; cinv，equFor the equipment investment in the station building, it is determined from the equipment capacity and unit capacity investment of each equipment, i.e.
k is the equipment type; cinv，othFor other than station building and equipment investmentOther costs, determined by station and equipment investments multiplied by a scaling factor L, i.e. Cinv，oth＝(Cinv，sta+Cinv，equ)×L。
In the formula, NtTaking 8760 hours as the total time period number of one year;
for operating and maintenance costs of the unit load of the apparatus i, Ei，tFor the load of the device i at the t-th time period, for distributed power supplies such as gas combustion engines, wind power generation and photovoltaic cells, Ei，tIs the electrical power (kW) they actually run during the t-th period; for heating/cooling devices such as gas boilers, heat pumps, chiller units and lithium bromide absorption chiller units, Ei，tIs the hot/cold power they provide during the t-th period; for energy storage devices such as regenerative tanks and cold storage tanks, Ei，tIs the power they store/discharge during the t-th period.
In the formula (I), the compound is shown in the specification,
is the heat quantity of the fuel for the t-th period,
is the fuel price for the t-th period. For the gas-using equipment in the system, the output energy can be converted into the corresponding gas quantity according to the relation between the output energy and the gas quantity.
In the formula (I), the compound is shown in the specification,
for the electricity purchase to the grid during the t-th period of the system,
and (4) the electricity price for purchasing electricity in the t-th period.
Environmental protection target-annual pollutant emissions are Po:
in the formula (I), the compound is shown in the specification,
is the heat of the natural gas consumed in the t period of the system, betagasIs the pollutant emission of burning natural gas;
is the amount of electricity purchased from the grid during the t-th period of the system, betagridIs the pollutant discharge amount of coal-fired power generation.
The comprehensive energy efficiency ratio target-comprehensive energy efficiency ratio is PER:
in the formula, EiIs the amount of power generation by the i-th power generation device,
is the heating amount of the jth heating apparatus,
is the refrigerating capacity, Q, of the kth refrigerating planttotThe total energy of the consumed primary energy is the total energy.
In a specific implementation, the operating constraints of each energy model include equipment installation capacity constraints, equipment output constraints, and power interaction constraints with a large power grid.
Constraint conditions are as follows:
1) equipment installation capacity constraints
In the formula (I), the compound is shown in the specification,
the maximum installation capacity of each device is limited by objective conditions, such as the limit of mobile capital, floor space and the like.
2) Device force constraints
For non-energy storage devices, their time period t load output Qi，tShould be less than the installed capacity of the device
For wind power generation and photovoltaic cells, a capacity coefficient F is introduced in consideration of randomness and fluctuation of output of the wind power generation and photovoltaic cells, and the capacity coefficient F represents the ratio of annual average output power of the wind power generation and photovoltaic cells to rated power:
the output power of the wind power generation and the photovoltaic cell is as follows:
3) interaction power constraint with large power grid
In the formula (I), the compound is shown in the specification,
the upper limit value of the interaction power of the system and the large power grid is shown.
4) Electric energy balance constraint
In the formula, PGIs a collection of power generating units; pLIs a collection of electric devices in the system; ereq (Ereq)tThe power load requirement of the user side in the t-th time period;
5) thermal energy balance constraint
In the formula, HOIs a collection of thermal devices; hLIs a collection of heat consuming devices in the system; hreqd，tThe heat load demands of the user side in the t period comprise heating load demands and hot water load demands;
6) cold energy balance constraint
In the formula, COIs a collection of refrigeration equipment; cLIs a collection of cold-using devices in the system; creqtThe cold load requirement of the user side in the t-th time period;
as shown in fig. 2, in the investment calculation process, in addition to various equipment investments, energy station house investments are simultaneously considered, and the energy station house area is associated with the equipment floor area by the following specific method:
and obtaining the model and quantity information of different equipment in the energy station through equipment type selection and equipment capacity planning.
And acquiring the length, width, height and other size data of each device.
And checking the sizes of the front and the back of the equipment and the adjacent equipment to be reserved according to relevant standards and specifications, and correcting the length, the width and the height data.
And optimizing the layout of the equipment by using a genetic algorithm to obtain an optimal layout scheme.
The optimization of the layout of the equipment by using genetic algorithm belongs to the prior art, and will not be described in detail here.
And the matching areas of an energy station passageway, an electrical room, an instrument control room and the like are increased in the calculation result.
And obtaining the total investment cost of the energy station house according to the civil engineering data.
Solving the planning model to obtain equipment type selection, a capacity planning scheme, output of various types of equipment, energy station investment conditions, pollutant discharge amount and comprehensive energy efficiency ratio of the comprehensive intelligent energy system; wherein, the investment situation of the energy station comprises the total system investment cost and the annual operation cost of the investment of the energy station.
According to the comprehensive intelligent energy system configuration optimization method considering station house investment, a device type combination capable of meeting load requirements is selected according to user load requirements, energy prices and local resource endowments, a better combination mode is obtained through calculation and comparison, the capacity configuration of the computing device and the required energy station house investment are optimized, total cost, pollutant emission and system energy efficiency indexes are compared, and the goals of optimal economy, lowest pollutant emission and maximum energy efficiency are achieved.
Example two
The embodiment provides a comprehensive intelligent energy system configuration optimization device considering station house investment, which specifically comprises the following modules:
the data acquisition module is used for acquiring project basic data, equipment data and civil engineering data;
the optimization configuration module is used for selecting a model based on the energy station equipment type, and obtaining the equipment type selection, the capacity planning scheme, the output of each type of equipment, the energy station investment condition, the pollutant discharge amount and the comprehensive energy efficiency ratio of the comprehensive intelligent energy system under the operation constraint of each energy model and the electricity, heat and cold power balance constraint in the comprehensive intelligent energy system;
the energy station equipment type selection model has the objective functions of considering station house investment, and having the lowest total cost of the system full life cycle, the lowest annual pollutant discharge amount and the highest comprehensive energy efficiency ratio.
It should be noted that, each module in the present embodiment corresponds to each step in the first embodiment one to one, and the specific implementation process is the same, which is not described herein again.
EXAMPLE III
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the method for optimizing an integrated intelligent energy system configuration involving station house investment as described above.
The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
Example four
The embodiment provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the method for optimizing the configuration of the comprehensive intelligent energy system considering station house investment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A comprehensive intelligent energy system configuration optimization method considering station house investment is characterized by comprising the following steps:
acquiring project basic data, equipment data and civil engineering data;
based on the energy station equipment type selection model, under the operation constraint of each energy model and the electricity, heat and cold power balance constraint in the comprehensive intelligent energy system, obtaining the equipment type selection, the capacity planning scheme, the output of each type of equipment, the energy station investment condition, the pollutant emission and the comprehensive energy efficiency ratio of the comprehensive intelligent energy system;
the energy station equipment type selection model has the objective functions of considering station house investment, and having the lowest total cost of the system full life cycle, the lowest annual pollutant discharge amount and the highest comprehensive energy efficiency ratio.
2. The method as claimed in claim 1, wherein the total investment cost of the energy station is the sum of the total investment of the project, the annual maintenance cost, the annual fuel cost and the annual electricity purchase cost, and the total investment of the project is composed of the construction investment of the station, the equipment investment in the station and other costs except the station and equipment investment.
3. The method of claim 1, wherein the operating constraints of each energy model include equipment installation capacity constraints, equipment output constraints, and interaction power constraints with a large power grid.
4. The method as claimed in claim 1, wherein the project basic data includes project area, building type, typical daily electricity, time-by-time load of cold, hot and hot water, available resource amount of the project and resource price.
5. The method as claimed in claim 1, wherein the equipment data includes investment cost, maintenance cost and efficiency per unit capacity of each type of equipment, and electric cooling and heating output limit per unit equipment.
6. The method as claimed in claim 1, wherein the civil engineering data is used for energy station and house investment calculation, including cost per unit volume.
7. The method as claimed in claim 1, wherein the energy station investment situation includes a total system investment cost and an annual operating cost of the energy station investment.
8. An integrated intelligent energy system configuration optimization device considering station house investment is characterized by comprising the following components:
the data acquisition module is used for acquiring project basic data, equipment data and civil engineering data;
the optimization configuration module is used for selecting a model based on the energy station equipment type, and obtaining the equipment type selection, the capacity planning scheme, the output of each type of equipment, the energy station investment condition, the pollutant discharge amount and the comprehensive energy efficiency ratio of the comprehensive intelligent energy system under the operation constraint of each energy model and the electricity, heat and cold power balance constraint in the comprehensive intelligent energy system;
the energy station equipment type selection model has the objective functions of considering station house investment, and having the lowest total cost of the system full life cycle, the lowest annual pollutant discharge amount and the highest comprehensive energy efficiency ratio.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for optimizing an integrated intelligent energy system configuration taking account of station house investments according to any one of claims 1 to 7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method for optimizing an integrated intelligent energy system configuration taking account of station building investments according to any one of claims 1 to 7.
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| CN111899120A (en) * | 2020-06-19 | 2020-11-06 | 国网浙江省电力有限公司经济技术研究院 | Method for establishing comprehensive energy planning and operation combined optimization model |
| CN112991087A (en) * | 2020-06-19 | 2021-06-18 | 国网能源研究院有限公司 | Energy simulation and optimal scheduling method, system and equipment for comprehensive energy system |
| CN113033900A (en) * | 2021-03-30 | 2021-06-25 | 中国电力科学研究院有限公司 | Park level comprehensive energy system capacity optimal configuration method and system |
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| CN116611199A (en) * | 2023-02-24 | 2023-08-18 | 中国市政工程华北设计研究总院有限公司 | Genetic algorithm-based capacity optimization configuration method for multi-energy complementary heating system |
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