CN113904382B - Multi-energy power system time sequence operation simulation method and device, electronic equipment and storage medium - Google Patents

Multi-energy power system time sequence operation simulation method and device, electronic equipment and storage medium Download PDF

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CN113904382B
CN113904382B CN202111246448.8A CN202111246448A CN113904382B CN 113904382 B CN113904382 B CN 113904382B CN 202111246448 A CN202111246448 A CN 202111246448A CN 113904382 B CN113904382 B CN 113904382B
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power
heat
thermal
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time
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CN113904382A (en
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方保民
胡伟
马晓伟
李延和
孙云超
任景
张馨月
李兵
张鑫
薛晨
向异
王光辉
徐有蕊
李剑
陈春萌
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Tsinghua University
State Grid Qinghai Electric Power Co Ltd
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State Grid Qinghai Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H02J3/472—For selectively connecting the AC sources in a particular order, e.g. sequential, alternating or subsets of sources
    • 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
    • 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]
    • 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
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • 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
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The application belongs to the field of power system time sequence operation simulation, and relates to a multi-energy power system time sequence operation simulation method, a device, electronic equipment and a storage medium. Firstly, establishing an operation model of a wind power source, a photovoltaic source and other multi-energy power sources; optimizing the middle-long month end storage capacity of a reservoir with the regulating capacity more than a day by taking a month as a time scale; carrying out step hydroelectric power decomposition with the day as a time scale; and finally, performing rolling operation optimization on the power system by taking hours as a time scale, wherein the established model can be converted into a mixed integer linear programming problem to solve the mixed integer linear programming problem, and a annual time sequence operation simulation result is obtained. The method balances the long-range time sequence related modeling capability and the short-time fluctuation modeling capability, improves the calculation efficiency, and simultaneously accurately describes the operation risk of the system in the annual time division rate. The method has guiding significance for planning and running of the renewable energy power generation base, and provides assistance for clean exploration of the power grid configured by multi-energy complementary energy storage.

Description

Multi-energy power system time sequence operation simulation method and device, electronic equipment and storage medium
Technical Field
The application belongs to the field of power system time sequence operation simulation, and relates to a multi-energy power system time sequence operation simulation method, a device, electronic equipment and a storage medium.
Background
With the continuous improvement of the permeability of renewable energy sources, the power supply structure of an electric power system is greatly changed, the power grid cleaning is greatly promoted in China, and a development path combining multi-energy complementation and energy storage configuration is explored. Taking Qinghai province as an example, the clean energy generating capacity of the power plant reaches 847 hundred million kilowatt-hours in 2020, and two multi-energy combined power generation bases of ten million kilowatt level are built. However, the uncertainty and fluctuation of wind power and photovoltaic output greatly increase the diversity and complexity of the running modes of the power grid, and the running of the multi-energy power supply presents complex space-time coupling characteristics.
The traditional random production simulation method based on the continuous load curve can perform rapid operation simulation of wind, light, water, fire and other power sources, but is difficult to consider complicated time sequence operation constraints such as climbing of thermal power, photo-thermal power, energy storage and the like. Deterministic production simulations based on time series load curves are generally only reproducible for typical day or week scheduling plans, are no longer applicable in high proportion renewable energy systems with high annual operating risk, and cannot utilize the long term storage capacity of various generalized stored energy in the system. Therefore, the time sequence operation simulation method for the multi-energy power system containing the high-proportion renewable energy sources needs to be provided by comprehensively considering the fluctuation of the renewable energy sources and the running characteristics of water power, light heat and energy storage. Because wind power and solar power generation completely depend on natural resources, the power generation output is 'eating by the day', and human intervention is difficult to perform. The time distribution of the wind-solar resources has uncertainty and fluctuation in a short term, and the water resources have seasonal characteristics of a certain regularity in a long term. Therefore, when a system containing high proportion or even full clean energy is researched, a method for arranging a typical operation mode of a unit in advance in a traditional power grid cannot be adopted to meet the load requirements of the power grid in each time scale, the wind, light and water resource characteristics and the multi-energy power supply operation characteristics are required to be analyzed, and an operation simulation method capable of coordinating different time scales is provided.
Disclosure of Invention
The present disclosure aims to solve the above technical problems at least to a certain extent, and based on the findings and knowledge of the inventors regarding the fact that wind power, photovoltaic power, hydropower and photo-thermal all belong to natural resource constraint power sources, and naturally have different space-time distribution characteristics. The hydroelectric power generation capacity depends on the natural runoff and the storage capacity scheduling plan, and the natural runoff has the characteristic of smooth and seasonal variation in the month. The photo-thermal energy-generating capacity depends on the direct solar irradiation amount, and exhibits periodicity with the period of days and daytime variability. The time sequence operation simulation method of the multi-energy power system needs to combine the endowment characteristics of resources of different energy forms in different time scales, promote coordination and complementation of various power supplies in operation, and reflect the operation condition of the system more comprehensively and finely.
In view of this, the present disclosure proposes a time sequence operation simulation method, device, electronic equipment and storage medium for a multi-energy power system, and provides a multi-time scale coordinated operation simulation method for multi-energy complementary power generation systems with multiple power types including thermal power, wind power, photovoltaic, cascade hydroelectric power, photo-thermal power, energy storage, and the like, which respectively models the middle-long term and short term phases, and adopts different constraint assumptions and objective functions in the two phases according to the difference of the characteristics of the multi-energy power source in each time scale, so as to realize the optimal decision of the power planning of the multi-energy complementary power generation system.
According to a first aspect of the present disclosure, a method for simulating time-series operation of a multi-energy power system is provided, including:
establishing a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal power and energy storage;
optimizing the month end reservoir capacity of the reservoir with the regulating capacity more than a day by taking the maximum annual total available power generation amount of the step hydropower as an optimization target, and decomposing the step hydropower electric quantity by taking the day as a time scale;
and taking the minimum running cost of the multi-energy power system as an optimization target to obtain a time sequence running simulation result of the multi-energy power system in the unit of hours.
Optionally, the building of the multi-energy power supply operation characteristic model of wind power, photovoltaic, thermal power, step hydropower, photo-thermal and energy storage includes:
(1) The wind power and photovoltaic output model is established as follows:
PW t +PW t Cur ＝PW t ',PW t ≥0,PW t Cur ≥0
PV t +PV t Cur ＝PV t ',PV t ≥0,PV t Cur ≥0
wherein ,PWt and PVt To-be-optimized output of wind power and photovoltaic at t time, PW t' and PVt ' the predicted upper force limit at the time t of wind power and photovoltaic respectively, PW t Cur and PVt Cur The wind discarding power and the light discarding power at the moment t are respectively;
(2) The thermal power generating unit model is built as follows:
taking a thermal power unit as a cluster, introducing three continuous variables of on-line capacity, startup capacity and shutdown capacity, and establishing a thermal power unit combination model taking the start-stop and climbing constraint of the unit into consideration, wherein the operation constraint is as follows:
wherein ,λmin Is the minimum output coefficient of the thermal power,is the online capacity of the thermal power generating unit at the moment t, < + >> and />The starting capacity and the shutdown capacity of the thermal power generating unit at the moment t are respectively alpha G and βG The minimum start-up time and the minimum stop time of the thermal power generating unit are respectively;
(3) Establishing a photo-thermal energy flow model, comprising:
(3-1) solar thermal Power collected by light field
wherein ,for the heat collecting power of the light field, +.>Is determined by the light field area, the direct solar irradiation quantity and the heat collecting efficiency, S SF Is the light field heat collection area, DNI t Is the direct solar irradiation quantity at the moment t, eta SF Is the heat collection efficiency of the light field;
(3-2) establishing a thermal power balance equation between the optical field and the heat-conducting medium:
wherein ,is the thermal power absorbed by the heat conducting medium from the heat collecting optical field,/->The heat rejection power of the light field comprises the heat loss in the heat collection process and the artificial heat rejection power of the scheduling control;
(3-3) establishing a thermal power balance equation between the heat-conducting medium, the heat storage device, and the power generation module as follows:
wherein ,is a heat storage deviceHeating power absorbed from the heat-conducting medium, +.>Is the heat release power of the heat storage device released to the heat transfer medium, < >>Is the thermal power delivered by the heat conducting medium to the power generation module;
(3-4) establishing a time period coupling relation of heat storage device for storing heat as follows:
wherein ,is the energy stored by the heat storage device at the time t, gamma TES Is the heat dissipation coefficient, eta of the heat storage device TES,c and ηTES,d The heat charging and heat releasing efficiencies are respectively;
(3-5) setting the charging and discharging power constraint of photo-thermal as follows:
wherein , and />Respectively, the upper limit of the charging powerAnd lower limit (L)> and />Upper and lower heat release power limits, respectively, +.> and />Respectively representing the charge and discharge states of the heat storage device at the time t, < >>1 indicates that the heat storage device is charged at time t, < >>1, the heat storage device releases heat at the time t;
(3-6) setting the constraint of the heat storage range of the photo-thermal as follows:
wherein , and />The upper limit and the lower limit of the heat storage capacity of the heat storage device are respectively;
(3-7) setting start-end heat storage capacity constraint in the optimization period of the photo-thermal power station as follows:
wherein , and />The heat storage quantity of the heat storage device at the moment 0 and the moment T respectively;
(3-8) establishing a thermoelectric conversion relation function of the power generation module in photo-thermal as follows:
wherein ,Pt CSP Is the power generation power of the photo-thermal unit, is determined by the thermal power and thermoelectric conversion efficiency of the heat conducting medium to the power generation module, wherein eta CSP Is the thermoelectric conversion efficiency;
(3-9) establishing the output constraint of the photo-thermal unit as follows:
wherein , and />The upper limit and the lower limit of the output of the photo-thermal unit are respectively +.>Representing the operating state of the photo-thermal unit at time t, < >>A1 indicates that the unit is in a starting state, +.>A value of 0 indicates that the unit is in a shutdown state;
(3-10) establishing the operation constraint of the photo-thermal unit as follows:
wherein , and />Respectively represents the start-stop operation of the unit at the time t, < >>1 indicates that the unit is started at the time t, +.>1 means that the machine set is stopped at the moment t, alpha CSP and βCSP The minimum start-up time and the minimum stop time of the photo-thermal unit are respectively;
(3-11) setting climbing constraint of the photo-thermal unit as follows:
wherein ,rCSP Is the climbing rate of the photo-thermal unit;
(4) The electric energy storage system model is built as follows:
(4-1) establishing a time period coupling relation of the state of charge of the electric energy storage system, namely a constraint equation of an electric energy storage system model as follows:
wherein ,is the electric quantity stored by the electric energy storage system at the moment t, gamma ESS Is the electric quantity dissipation coefficient, eta of the electric energy storage system ESS,c and ηESS,d Charge and discharge efficiencies, respectively;
(4-2) setting charge-discharge power constraints of the electrical energy storage system as follows:
wherein , and />Charging power upper and lower limits, respectively, < -> and />Upper and lower discharge power limit, respectively, < >> and />Respectively representing the charge and discharge states of the energy storage system at the time t, < > >For 1 is the stored energy charged at time t +.>1 represents that the stored energy is discharged at the time t;
(4-3) setting the limit of the electric storage amount range as follows:
wherein , and />Respectively an upper limit and a lower limit of the stored energy and the stored electric quantity;
(4-4) establishing state of charge constraints at the beginning and end of an energy storage system optimization cycle as follows:
wherein , and />The electric quantity stored by the energy storage system at the moment 0 and the moment T respectively;
(4-5) setting design parameter constraints of the energy storage system as follows:
wherein ,kESS Is the maximum discharge time of the energy storage system;
(5) The method comprises the steps of establishing a cascade hydropower model, wherein the operation constraint of the cascade hydropower comprises hydraulic constraint, electric power constraint and a hydropower energy conversion relation, and the upstream and downstream of the reservoir are connected with each other through upstream and downstream discharging flow and downstream warehousing flow.
Optionally, the optimizing the final storage capacity of the reservoir with the regulating capacity more than a day with the maximum annual total available power generation of the step hydropower is performed, and the step hydropower electric quantity decomposition is performed by taking the day as a time scale, including:
the objective function of the long-term reservoir capacity scheduling model in the reservoir is that the annual power generation total amount of each cascade hydropower station is the largest:
constraint conditions of the long-term reservoir capacity scheduling model in the reservoir comprise:
(1) The hydropower station energy form hydropower conversion relation is established as follows:
wherein ,for the total monthly power generation of hydropower station i, +.>Is the average water head of the unit h in the hydropower station i,is the total power generation water quantity, ρ is the density of water, g is the gravitational acceleration, η PH Is the water-electricity conversion efficiency; the water-electricity conversion efficiency eta is calculated in practice PH Taking the value as a fixed value;
(2) Establishing a relation between the maximum power generation amount and the minimum power generation amount of the hydropower station unit:
wherein ,is the minimum guaranteed power generation of the unit h, +.>The theoretical full power generation amount calculated by the installed capacity of the unit h;
(3) The water balance equation is established as follows:
wherein ,generating water quantity for i months of hydropower station, < >>Discarding water for i months of the hydropower station;
(4) The reservoir water storage capacity constraint is established as follows:
wherein ,Vi m Minimum water storage capacity of reservoir to be ensured for ith hydropower station, V i M Is the firsti maximum water storage capacity allowed by hydropower stations;
(5) The reservoir water discharge amount constraint is established as follows:
wherein ,Vi discharge,M The maximum allowable drainage flow of the ith hydropower station;
(6) The water storage capacity constraint at the beginning and the end of the scheduling period is established as follows:
wherein ,Ωyear A hydropower station label set with more than month adjusting capability;
optionally, the obtaining the time sequence operation simulation result of the multi-energy power system by taking the minimum operation cost of the multi-energy power system as the optimization target includes:
(1) The step hydropower short-term operation simplified model is established as follows:
on the basis of completing water quantity and electric quantity distribution by medium-long term operation simulation, the step hydropower in short term operation simulation adopts a simplified unit model, and only the electric power constraint part is considered, so that the calculation complexity is reduced.
wherein ,is the daily maximum power generation constraint of hydropower station i,/->The daily hydroelectric power generation capacity of each step is obtained through medium-term operation simulation calculation;
(2) The short-term operation model of other types of power supplies is established as follows:
the power system satisfies the source load power balance at any time as follows:
wherein ,is the local load at time t, +.>The power is the power sent by the power system at the moment t;
the positive and negative standby capacities of the power system are jointly provided by water power, light and heat and energy storage, and constraint conditions are as follows:
wherein , and />The capacity up-regulation and capacity down-regulation requirements of the power system at the moment t are respectively;
the optimization objective of the power supply short-term operation model is to minimize the annual operation cost of the power system, wherein the optimization objective comprises the generation cost of each type of power supply and wind power, photovoltaic, hydroelectric and photo-thermal power discarding punishment, and the objective function of the power supply short-term operation model is as follows:
wherein ：CG Is the unit power generation cost of the thermal power in the power supply planning scheme containing the thermal power, C Water and CCSP Is the unit power generation cost of water electricity and photo-heat, C Cur Is the electricity discarding punishment cost of wind power, photovoltaic, hydroelectric and photo-thermal.
According to a second aspect of the present disclosure, a multi-energy power system time sequence operation simulation apparatus is provided, including:
the model building module is used for building a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal and energy storage;
the step hydroelectric power decomposition module is used for optimizing the month end reservoir capacity of the reservoir with the adjustment capacity more than a day by taking the total annual available power generation amount of step hydroelectric power as the maximum optimization target, and carrying out step hydroelectric power decomposition by taking the day as a time scale;
and the simulation module is used for obtaining a time sequence operation simulation result of the multi-energy power system by taking the minimum operation cost of the multi-energy power system as an optimization target.
According to a third aspect of the present disclosure, an electronic device is presented, comprising:
a memory for storing computer-executable instructions;
a processor configured to perform:
establishing a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal power and energy storage;
optimizing the month end reservoir capacity of the reservoir with the regulating capacity more than a day by taking the maximum annual total available power generation amount of the step hydropower as an optimization target, and decomposing the step hydropower electric quantity by taking the day as a time scale;
And taking the minimum running cost of the multi-energy power system as an optimization target to obtain a time sequence running simulation result of the multi-energy power system in the unit of hours.
According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program for causing the computer to execute:
establishing a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal power and energy storage;
optimizing the month end reservoir capacity of the reservoir with the regulating capacity more than a day by taking the maximum annual total available power generation amount of the step hydropower as an optimization target, and decomposing the step hydropower electric quantity by taking the day as a time scale;
and taking the minimum running cost of the multi-energy power system as an optimization target to obtain a time sequence running simulation result of the multi-energy power system in the unit of hours.
The embodiment of the disclosure shows a time sequence operation simulation method of a multi-energy power system, a refined operation model is established for a multi-energy complementary power generation system, the storage capacity of a reservoir with the regulating capacity more than a day is optimized by taking a month as a time scale, and the optimal distribution result of the total power generation capacity of step hydropower on time sequence and among steps is determined by taking the day as the time scale. The source-load characteristic difference and the multi-energy complementary coordination are considered, and a time sequence operation simulation model with multi-time scale coordination is established. The method balances the long-range time sequence related modeling capability and the short-time fluctuation modeling capability, improves the calculation efficiency, and simultaneously accurately describes the operation risk of the system in the annual time division rate. The method has a certain guiding significance for planning and running of the renewable energy power generation base, and provides assistance for the power grid cleaning probe taking the configuration of multi-energy complementation and energy storage as the idea.
Additional aspects and advantages of the disclosure 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 application.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the present application and that other drawings may be obtained from these drawings by those of ordinary skill in the art without inventive effort.
Fig. 1 is a flow chart illustrating a multi-energy power system time series operation simulation method according to one embodiment of the present disclosure.
Fig. 2 is a schematic diagram of a multi-energy power system time series operation simulation device according to one embodiment of the present disclosure.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Fig. 1 is a schematic flow chart of a multi-energy power system time sequence operation simulation method according to one embodiment of the disclosure, and as shown in fig. 1, the method may include the steps of:
in step 1, a multi-energy power supply operation characteristic model describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal and energy storage is established.
In one embodiment, the building of the multi-energy power supply operation characteristic model of wind power, photovoltaic, thermal power, step hydropower, photo-thermal and energy storage comprises:
(1) The wind power and photovoltaic output model is established as follows:
PW t +PW t Cur ＝PW t ',PW t ≥0,PW t Cur ≥0 (1)
PV t +PV t Cur ＝PV t ',PV t ≥0,PV t Cur ≥0 (2)
wherein ,PWt and PVt To-be-optimized output of wind power and photovoltaic at t time, PW t' and PVt ' the predicted upper force limit at the time t of wind power and photovoltaic respectively, PW t Cur and PVt Cur The wind discarding power and the light discarding power at the moment t are respectively;
(2) The thermal power generating unit model is built as follows:
taking a thermal power unit as a cluster, introducing three continuous variables of on-line capacity, startup capacity and shutdown capacity, and establishing a thermal power unit combination model taking the start-stop and climbing constraint of the unit into consideration, wherein the operation constraint is as follows:
wherein ,λmin Is the minimum output coefficient of the thermal power,is the online capacity of the thermal power generating unit at the moment t, < + >> and />The starting capacity and the shutdown capacity of the thermal power generating unit at the moment t are respectively alpha G and βG The minimum start-up time and the minimum stop time of the thermal power unit are respectively determined according to the actual running condition of the thermal power unit;
(3) Establishing a photo-thermal energy flow model, comprising:
dividing the photo-thermal power station into three components of a heat collection light field, a heat storage device and a power generation module, wherein a constraint equation describes the characteristics of each component and the transfer process of energy among the components.
(3-1) solar thermal Power collected by light field
wherein ,for the heat collecting power of the light field, the solar heat collecting power of the light field is calculated in the formula (9), wherein the heat collecting power of the light field is +.>Is determined by the light field area, the direct solar irradiation (DNI) and the heat collection efficiency, S SF Is the area of the light field collection area,DNI t is the direct solar irradiation quantity at the moment t, eta SF Is the heat collection efficiency of the light field;
(3-2) establishing a thermal power balance equation between the optical field and the heat-conducting medium:
wherein ,is the thermal power absorbed by the heat conducting medium from the heat collecting optical field,/->The heat rejection power of the light field comprises the heat loss in the heat collection process and the artificial heat rejection power of the scheduling control;
(3-3) establishing a thermal power balance equation between the heat-conducting medium, the heat storage device, and the power generation module as follows:
wherein ,is the charging power absorbed by the heat storage device from the heat conducting medium, < > >Is the heat release power of the heat storage device released to the heat transfer medium, < >>Is the thermal power delivered by the heat conducting medium to the power generation module;
(3-4) establishing a time period coupling relation of heat storage device for storing heat as follows:
wherein ,is the energy stored by the heat storage device at the time t, gamma TES Is the heat dissipation coefficient, eta of the heat storage device TES,c and ηTES,d The heat charging and heat releasing efficiencies are respectively;
(3-5) setting the charging and discharging power constraint of photo-thermal as follows:
wherein , and />The upper limit and the lower limit of the charging power are respectively +.> and />Upper and lower heat release power limits, respectively, +.> and />Respectively representing the charge and discharge states of the heat storage device at the time t, < >>1 indicates that the heat storage device is charged at time t, < >>1, the heat storage device releases heat at the time t;
(3-6) setting the constraint of the heat storage range of the photo-thermal as follows:
wherein , and />The upper limit and the lower limit of the heat storage capacity of the heat storage device are respectively;
(3-7) setting start-end heat storage capacity constraint in the optimization period of the photo-thermal power station as follows:
wherein , and />The heat storage quantity of the heat storage device at the moment 0 and the moment T respectively;
(3-8) establishing a thermoelectric conversion relation function of the power generation module in photo-thermal as follows:
wherein ,Pt CSP Is the power generation power of the photo-thermal unit, is determined by the thermal power and thermoelectric conversion efficiency of the heat conducting medium to the power generation module, wherein eta CSP The thermoelectric conversion efficiency is generally a fixed value;
(3-9) establishing the output constraint of the photo-thermal unit as follows:
wherein , and />The upper limit and the lower limit of the output of the photo-thermal unit are respectively related to the configuration capacity of the photo-thermal power generation module, and the upper limit and the lower limit of the output of the photo-thermal unit are +.>Representing the operating state of the photo-thermal unit at time t, < >>A1 indicates that the unit is in a starting state, +.>A value of 0 indicates that the unit is in a shutdown state;
(3-10) establishing the operation constraint of the photo-thermal unit as follows:
wherein , and />Respectively represents the start-stop operation of the unit at the time t, < >>1 indicates that the unit is started at the time t, +.>1 means that the machine set is stopped at the moment t, alpha CSP and βCSP The minimum start-up time and the minimum stop time of the photo-thermal unit are respectively;
(3-11) setting climbing constraint of the photo-thermal unit as follows:
wherein ,rCSP Is the climbing rate of the photo-thermal unit;
(4) The electric energy storage system model is built as follows:
(4-1) establishing a time period coupling relation of the state of charge of the electric energy storage system, namely a constraint equation of an electric energy storage system model as follows:
wherein ,is the electric quantity stored by the electric energy storage system at the moment t, gamma ESS Is the electric quantity dissipation coefficient, eta of the electric energy storage system ESS,c and ηESS,d Charge and discharge efficiencies, respectively;
(4-2) setting charge-discharge power constraints of the electrical energy storage system as follows:
wherein , and />Charging power upper and lower limits, respectively, < -> and />Upper and lower discharge power limit, respectively, < >> and />Respectively representing the charge and discharge states of the energy storage system at the time t, < >>For 1 is the stored energy charged at time t +.>1 represents that the stored energy is discharged at the time t; />
(4-3) setting the limit of the electric storage amount range as follows:
wherein , and />Respectively an upper limit and a lower limit of the stored energy and the stored electric quantity;
(4-4) establishing state of charge constraints at the beginning and end of an energy storage system optimization cycle as follows:
wherein , and />The electric quantity stored by the energy storage system at the moment 0 and the moment T respectively;
(4-5) setting design parameter constraints of the energy storage system as follows:
wherein ,kESS Is the maximum discharge time of the energy storage system;
(5) The method comprises the steps of establishing a cascade hydropower model, wherein the operation constraint of the cascade hydropower comprises hydraulic constraint, electric power constraint and a hydropower energy conversion relation, and the upstream and downstream of the reservoir are connected with each other through upstream and downstream discharging flow and downstream warehousing flow. Since there is a strong correlation between the step hydropower over different time scales, detailed description will be given below and will not be repeated here.
In the step 2, the final storage capacity of the reservoir with the regulating capacity more than a day is optimized by taking the maximum annual total available power generation amount of the step hydropower as an optimization target, and the step hydropower electric quantity decomposition is carried out by taking the day as a time scale.
In the embodiment of the disclosure, the month end reservoir capacity of each cascade reservoir is used as a variable to be optimized, the maximum annual total available power generation amount of the upstream cascade hydropower is used as an optimization target, a medium-long-term reservoir capacity scheduling plan of a regulating reservoir for many years is provided, the month end reservoir capacity plan of the reservoir provided by long-term operation simulation is used as a boundary, electric quantity decomposition is carried out by taking a day as a time scale, and the daily power generation amount of each cascade hydropower is optimized.
In one embodiment, the optimizing the end-of-month reservoir capacity of the reservoir with the regulating capability more than a day with the maximum annual total available power generation of the step hydropower as an optimizing target, and performing step hydropower electric quantity decomposition with the day as a time scale comprises the following steps:
establishing a long-term reservoir capacity scheduling model in a multi-year regulating reservoir: and taking the month end reservoir capacity of each cascade reservoir as a variable to be optimized, and giving a medium-long term reservoir capacity scheduling plan of the regulating reservoir for many years by taking the total annual available power generation amount of the upstream cascade hydropower as an optimization target.
The objective function of the long-term reservoir capacity scheduling model in the reservoir is that the annual power generation total amount of each cascade hydropower station is the largest:
constraint conditions of the long-term reservoir capacity scheduling model in the reservoir comprise:
(1) The hydropower station energy form hydropower conversion relation is established as follows:
wherein ,for the total monthly power generation of hydropower station i, +.>Is the average water head of the unit h in the hydropower station i,is the total power generation water quantity, ρ is the density of water, g is the gravitational acceleration, η PH Is the water-electricity conversion efficiency; the water-electricity conversion efficiency eta is calculated in practice PH Taking a constant value, in one embodiment of the present disclosure takes a value of 0.80 to 0.94.
(2) Establishing a relation between the maximum power generation amount and the minimum power generation amount of the hydropower station unit:
/>
wherein ,is the minimum guaranteed power generation of the unit h, +.>The theoretical full power generation amount calculated by the installed capacity of the unit h;
(3) The water balance equation is established as follows:
because no upstream and downstream water flow time lag exists on a month-level time scale, the water quantity increase of the lower-level reservoir consists of natural water inflow and lower water discharge of the upper-level reservoir, and the water quantity consumption consists of total power generation water quantity and total water discarding quantity;
wherein ,generating water quantity for i months of hydropower station, < >>Discarding water for i months of the hydropower station;
(4) The reservoir water storage capacity constraint is established as follows:
wherein ,Vi m Minimum water storage capacity of reservoir to be ensured for ith hydropower station, V i M The maximum water storage capacity allowed for the ith hydropower station;
(5) The reservoir water discharge amount constraint is established as follows:
wherein ,Vi discharge,M The maximum allowable drainage flow of the ith hydropower station;
(6) The water storage capacity constraint at the beginning and the end of the scheduling period is established as follows:
wherein ,Ωyear A hydropower station label set with more than month adjusting capability;
for a hydropower station which assumes equal water storage at the beginning of the year and at the end of the year, but which does not have more than month regulation capacity, the average water storage per month is considered to be equal, and the balance within the month is ensured by the day regulation capacity of the reservoir.
And finally, optimizing daily power generation capacity of each step of hydropower by taking a reservoir month end reservoir capacity plan given by long-term operation simulation as a boundary. The optimization target is the operation cost of the system in the month, the constraint conditions are the operation characteristics of various power supplies and the balance constraint of the system electric quantity, and other power supply constraint conditions refer to the operation model established in the step 1.
And 3, taking the minimum running cost of the multi-energy power system as an optimization target to obtain a time sequence running simulation result of the multi-energy power system in the unit of hours.
In one embodiment, the optimizing the operation cost of the multi-energy power system to obtain the time sequence operation simulation result of the multi-energy power system in units of hours includes:
(1) The step hydropower short-term operation simplified model is established as follows:
on the basis of completing water quantity and electric quantity distribution by medium-long term operation simulation, the step hydropower in short term operation simulation adopts a simplified unit model, and only the electric power constraint part is considered, so that the calculation complexity is reduced.
/>
Wherein equation (37) is a daily maximum power generation constraint of the hydropower station i,the daily hydroelectric power generation capacity of each step is obtained through medium-term operation simulation calculation;
(2) The short-term operation model of other types of power supplies is established as follows:
and (3) in the short-term operation simulation, the operation constraint of wind power, photovoltaic, photo-thermal and energy storage refers to the multi-energy power supply operation characteristic model in the step (1). In addition to the power characteristics constraints, the model constraints also take into account power system operating constraints, including power balance constraints and reserve capacity constraints.
The power system satisfies the source load power balance at any time as follows:
wherein ,is the local load at time t, +.>The power is the power sent by the power system at the moment t;
the positive and negative standby capacities of the power system are jointly provided by water electricity, light heat and energy storage, and constraint conditions are shown in a formula (42):
wherein , and />The capacity up-regulation and capacity down-regulation requirements of the power system at the moment t are respectively;
the optimization objective of the power supply short-term operation model is to minimize the annual operation cost of the power system, wherein the optimization objective comprises the generation cost of each type of power supply and the electricity discarding penalty of renewable energy sources such as wind power, photovoltaic, hydroelectric and photo-thermal, and the objective function of the power supply short-term operation model is as follows:
wherein ：CG Is the unit power generation cost of the thermal power in the power supply planning scheme containing the thermal power, C Water and CCSP Is the unit power generation cost of water electricity and photo-heat, C Cur Is the electricity discarding punishment cost of wind power, photovoltaic, hydroelectric and photo-thermal.
Corresponding to the above-mentioned multi-energy power system time sequence operation simulation method, the present disclosure also proposes an embodiment of a multi-energy power system time sequence operation simulation device.
Fig. 2 illustrates a multi-energy power system time sequence operation simulation device according to an embodiment of the present disclosure, including:
the model building module is used for building a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal and energy storage;
the step hydroelectric power decomposition module is used for optimizing the month end reservoir capacity of the reservoir with the adjustment capacity more than a day by taking the total annual available power generation amount of step hydroelectric power as the maximum optimization target, and carrying out step hydroelectric power decomposition by taking the day as a time scale;
and the simulation module is used for obtaining a time sequence operation simulation result of the multi-energy power system by taking the minimum operation cost of the multi-energy power system as an optimization target.
The embodiment of the disclosure also provides an electronic device, including:
A memory for storing computer-executable instructions;
a processor configured to perform:
establishing a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal power and energy storage;
optimizing the month end reservoir capacity of the reservoir with the regulating capacity more than a day by taking the maximum annual total available power generation amount of the step hydropower as an optimization target, and decomposing the step hydropower electric quantity by taking the day as a time scale;
and taking the minimum running cost of the multi-energy power system as an optimization target to obtain a time sequence running simulation result of the multi-energy power system in the unit of hours.
Embodiments of the present disclosure also propose a computer-readable storage medium having stored thereon a computer program for causing the computer to execute:
establishing a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal power and energy storage;
optimizing the month end reservoir capacity of the reservoir with the regulating capacity more than a day by taking the maximum annual total available power generation amount of the step hydropower as an optimization target, and decomposing the step hydropower electric quantity by taking the day as a time scale;
and taking the minimum running cost of the multi-energy power system as an optimization target to obtain a time sequence running simulation result of the multi-energy power system in the unit of hours.
It should be noted that, in the embodiments of the present disclosure, the processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (FieldProgrammable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor, or the processor may be any conventional processor or the like, and the memory may be used to store the computer program and/or the module, and the processor may implement various functions of the multi-energy power system time series operation simulation method by executing or executing the computer program and/or the module stored in the memory, and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, graphics data, etc.) created by the operating system during running of the application program, and the like. In addition, the memory may include a high-speed random access memory, and may further include a nonvolatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), a memory device of at least one magnetic disk, or a Flash memory device.
Based on such understanding, the present disclosure may implement all or part of the flow of the method of the above embodiments, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the above-described apparatus embodiments are merely illustrative, and the units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the device embodiment drawings provided by the disclosure, the connection relation between the modules represents that the modules have communication connection therebetween, and may be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
While the foregoing is directed to the preferred embodiments of the present disclosure, it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present disclosure, and such modifications and adaptations are intended to be comprehended within the scope of the present disclosure.

Claims (4)

1. The time sequence operation simulation method for the multi-energy power system is characterized by comprising the following steps of:
establishing a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal power and energy storage;
optimizing the month end reservoir capacity of the reservoir with the regulating capacity more than a day by taking the maximum annual total available power generation amount of the step hydropower as an optimization target, and decomposing the step hydropower electric quantity by taking the day as a time scale;
taking the minimum running cost of the multi-energy power system as an optimization target to obtain a time sequence running simulation result of the multi-energy power system in units of hours;
the multi-energy power supply operation characteristic model for wind power, photovoltaic, thermal power, step hydropower, photo-thermal and energy storage is established, and the multi-energy power supply operation characteristic model comprises the following components:
(1) The wind power and photovoltaic output model is established as follows:
PW t +PW t Cur ＝PW t ',PW t ≥0,PW t Cur ≥0
PV t +PV t Cur ＝PV t ',PV t ≥0,PV t Cur ≥0
wherein ,PWt and PVt To-be-optimized output of wind power and photovoltaic at t time, PW t' and PVt ' the predicted upper force limit at the time t of wind power and photovoltaic respectively, PW t Cur and PVt Cur The wind discarding power and the light discarding power at the moment t are respectively;
(2) The thermal power generating unit model is built as follows:
taking a thermal power unit as a cluster, introducing three continuous variables of on-line capacity, startup capacity and shutdown capacity, and establishing a thermal power unit combination model taking the start-stop and climbing constraint of the unit into consideration, wherein the operation constraint is as follows:
wherein ,λmin Is the minimum output coefficient of the thermal power,is the online capacity of the thermal power generating unit at the moment t, < + >>Andthe starting capacity and the shutdown capacity of the thermal power generating unit at the moment t are respectively alpha G and βG The minimum start-up time and the minimum stop time of the thermal power generating unit are respectively;
(3) Establishing a photo-thermal energy flow model, comprising:
(3-1) solar thermal Power collected by light field
wherein ,for the heat collecting power of the light field, +.>Is determined by the light field area, the direct solar irradiation quantity and the heat collecting efficiency, S SF Is the light field heat collection area, DNI t Is the direct solar irradiation quantity at the moment t, eta SF Is the heat collection efficiency of the light field;
(3-2) establishing a thermal power balance equation between the optical field and the heat-conducting medium:
wherein ,is the thermal power absorbed by the heat conducting medium from the heat collecting optical field,/->The heat rejection power of the light field comprises the heat loss in the heat collection process and the artificial heat rejection power of the scheduling control;
(3-3) establishing a thermal power balance equation between the heat-conducting medium, the heat storage device, and the power generation module as follows:
wherein ,is the charging power absorbed by the heat storage device from the heat conducting medium, < >>Is the heat release power of the heat storage device released to the heat transfer medium, < >>Is the thermal power delivered by the heat conducting medium to the power generation module;
(3-4) establishing a time period coupling relation of heat storage device for storing heat as follows:
wherein ,is the energy stored by the heat storage device at the time t, gamma TES Is the heat dissipation coefficient, eta of the heat storage device TES,c and ηTES,d The heat charging and heat releasing efficiencies are respectively;
(3-5) setting the charging and discharging power constraint of photo-thermal as follows:
wherein , and />The upper limit and the lower limit of the charging power are respectively +.> and />An upper limit and a lower limit of the heat release power respectively, and />Respectively representing the charge and discharge states of the heat storage device at the time t, < >>1 indicates that the heat storage device is charged at time t, < >>1, the heat storage device releases heat at the time t;
(3-6) setting the constraint of the heat storage range of the photo-thermal as follows:
wherein , and />The upper limit and the lower limit of the heat storage capacity of the heat storage device are respectively;
(3-7) setting start-end heat storage capacity constraint in the optimization period of the photo-thermal power station as follows:
wherein , and />The heat storage quantity of the heat storage device at the moment 0 and the moment T respectively;
(3-8) establishing a thermoelectric conversion relation function of the power generation module in photo-thermal as follows:
wherein ,Pt CSP Is the power generation power of the photo-thermal unit, and the thermal power and thermoelectric power transmitted to the power generation module by the heat conducting mediumConversion efficiency determination, wherein η CSP Is the thermoelectric conversion efficiency;
(3-9) establishing the output constraint of the photo-thermal unit as follows:
wherein , and />The upper limit and the lower limit of the output of the photo-thermal unit are respectively +.>Representing the operating state of the photo-thermal unit at time t, < >>A1 indicates that the unit is in a starting state, +.>A value of 0 indicates that the unit is in a shutdown state;
(3-10) establishing the operation constraint of the photo-thermal unit as follows:
wherein , and />Respectively represents the start-stop operation of the unit at the time t, < >>1 indicates that the unit is started up at the time t,1 means that the machine set is stopped at the moment t, alpha CSP and βCSP The minimum start-up time and the minimum stop time of the photo-thermal unit are respectively;
(3-11) setting climbing constraint of the photo-thermal unit as follows:
wherein ,rCSP Is the climbing rate of the photo-thermal unit;
(4) The electric energy storage system model is built as follows:
(4-1) establishing a time period coupling relation of the state of charge of the electric energy storage system, namely a constraint equation of an electric energy storage system model as follows:
wherein ,is the electric quantity stored by the electric energy storage system at the moment t, gamma ESS Power dissipation that is an electrical energy storage system Coefficient, eta ESS,c and ηESS,d Charge and discharge efficiencies, respectively;
(4-2) setting charge-discharge power constraints of the electrical energy storage system as follows:
wherein , and />Charging power upper and lower limits, respectively, < -> and />Upper and lower discharge power limit, respectively, < >> and />Respectively representing the charge and discharge states of the energy storage system at the time t, < >>For 1 is the stored energy charged at time t +.>1 represents that the stored energy is discharged at the time t;
(4-3) setting the limit of the electric storage amount range as follows:
wherein , and />Respectively an upper limit and a lower limit of the stored energy and the stored electric quantity;
(4-4) establishing state of charge constraints at the beginning and end of an energy storage system optimization cycle as follows:
wherein , and />The electric quantity stored by the energy storage system at the moment 0 and the moment T respectively;
(4-5) setting design parameter constraints of the energy storage system as follows:
wherein ,kESS Is the maximum discharge time of the energy storage system;
(5) Establishing a cascade hydroelectric model, wherein the operation constraint of the cascade hydroelectric comprises hydraulic constraint, electric power constraint and a hydropower energy conversion relation, and the upstream and downstream of the reservoir are connected with each other through upstream and downstream discharging flow and downstream warehousing flow;
optimizing the month end reservoir capacity of the reservoir with the regulating capacity more than a day by taking the maximum annual total available power generation amount of the step hydropower as an optimization target, and carrying out step hydropower electric quantity decomposition by taking the day as a time scale, wherein the method comprises the following steps of:
The objective function of the long-term reservoir capacity scheduling model in the reservoir is that the annual power generation total amount of each cascade hydropower station is the largest:
constraint conditions of the long-term reservoir capacity scheduling model in the reservoir comprise:
(1) The hydropower station energy form hydropower conversion relation is established as follows:
wherein ,for the total monthly power generation of hydropower station i, +.>Is the month average water head of the unit h in the hydropower station i, < > in->Is the total power generation water quantity, ρ is the density of water, g is the gravitational acceleration, η PH Is the water-electricity conversion efficiency; the water-electricity conversion efficiency eta is calculated in practice PH Taking the value as a fixed value;
(2) Establishing a relation between the maximum power generation amount and the minimum power generation amount of the hydropower station unit:
wherein ,is the minimum guaranteed power generation of the unit h, +.>The theoretical full power generation amount calculated by the installed capacity of the unit h;
(3) The water balance equation is established as follows:
wherein ,generating water quantity for i months of hydropower station, < >>Discarding water for i months of the hydropower station;
(4) The reservoir water storage capacity constraint is established as follows:
wherein ,Vi m Minimum water storage capacity of reservoir to be ensured for ith hydropower station, V i M The maximum water storage capacity allowed for the ith hydropower station;
(5) The reservoir water discharge amount constraint is established as follows:
wherein ,Vi discharge,M The maximum allowable drainage flow of the ith hydropower station;
(6) The water storage capacity constraint at the beginning and the end of the scheduling period is established as follows:
wherein ,Ωyear Hydropower station with more than month adjusting capacityThe set of reference numbers,
taking the minimum running cost of the multi-energy power system as an optimization target, obtaining a time sequence running simulation result of the multi-energy power system in units of hours, comprising the following steps:
(1) The step hydropower short-term operation simplified model is established as follows:
on the basis of completing water quantity and electric quantity distribution by medium-long term operation simulation, step hydropower in short term operation simulation adopts a simplified unit model, and only the electric power constraint part is considered so as to reduce calculation complexity;
wherein ,is the daily maximum power generation constraint of hydropower station i,/->The daily hydroelectric power generation capacity of each step is obtained through medium-term operation simulation calculation;
(2) The short-term operation model of other types of power supplies is established as follows:
the power system satisfies the source load power balance at any time as follows:
wherein ,is the local load at time t, +.>The power is the power sent by the power system at the moment t;
the positive and negative standby capacities of the power system are jointly provided by water power, light and heat and energy storage, and constraint conditions are as follows:
wherein , and />The capacity up-regulation and capacity down-regulation requirements of the power system at the moment t are respectively;
the optimization objective of the power supply short-term operation model is to minimize the annual operation cost of the power system, wherein the optimization objective comprises the generation cost of each type of power supply and wind power, photovoltaic, hydroelectric and photo-thermal power discarding punishment, and the objective function of the power supply short-term operation model is as follows:
wherein ：CG Is the thermal power in a power supply planning scheme containing thermal powerUnit power generation cost of C Water and CCSP Is the unit power generation cost of water electricity and photo-heat, C Cur Is the electricity discarding punishment cost of wind power, photovoltaic, hydroelectric and photo-thermal.
2. A multi-energy power system time sequence operation simulation device, comprising:
the model building module is used for building a multi-energy power supply operation characteristic model for describing wind power, photovoltaic, thermal power, step hydropower, photo-thermal and energy storage;
the step hydroelectric power decomposition module is used for optimizing the month end reservoir capacity of the reservoir with the adjustment capacity more than a day by taking the total annual available power generation amount of step hydroelectric power as the maximum optimization target, and carrying out step hydroelectric power decomposition by taking the day as a time scale;
the simulation module is used for obtaining a time sequence operation simulation result of the multi-energy power system by taking the minimum operation cost of the multi-energy power system as an optimization target;
the model building module is further used for:
(1) The wind power and photovoltaic output model is established as follows:
PW t +PW t Cur ＝PW t ',PW t ≥0,PW t Cur ≥0
PV t +PV t Cur ＝PV t ',PV t ≥0,PV t Cur ≥0
wherein ,PWt and PVt To-be-optimized output of wind power and photovoltaic at t time, PW t' and PVt ' the predicted upper force limit at the time t of wind power and photovoltaic respectively, PW t Cur and PVt Cur The wind discarding power and the light discarding power at the moment t are respectively;
(2) The thermal power generating unit model is built as follows:
taking a thermal power unit as a cluster, introducing three continuous variables of on-line capacity, startup capacity and shutdown capacity, and establishing a thermal power unit combination model taking the start-stop and climbing constraint of the unit into consideration, wherein the operation constraint is as follows:
wherein ,λmin Is the minimum output coefficient of the thermal power,is the online capacity of the thermal power generating unit at the moment t, < + >>Andthe starting capacity and the shutdown capacity of the thermal power generating unit at the moment t are respectively alpha G and βG The minimum start-up time and the minimum stop time of the thermal power generating unit are respectively;
(3) Establishing a photo-thermal energy flow model, comprising:
(3-1) solar thermal Power collected by light field
wherein ,for the heat collecting power of the light field, +.>Is determined by the light field area, the direct solar irradiation quantity and the heat collecting efficiency, S SF Is the light field heat collection area, DNI t Is the direct solar irradiation quantity at the moment t, eta SF Is the heat collection efficiency of the light field;
(3-2) establishing a thermal power balance equation between the optical field and the heat-conducting medium:
wherein ,is the thermal power absorbed by the heat conducting medium from the heat collecting optical field,/->The heat rejection power of the light field comprises the heat loss in the heat collection process and the artificial heat rejection power of the scheduling control;
(3-3) establishing a thermal power balance equation between the heat-conducting medium, the heat storage device, and the power generation module as follows:
wherein ,is the charging power absorbed by the heat storage device from the heat conducting medium, < >>Is the heat release power of the heat storage device released to the heat transfer medium, < >>Is the thermal power delivered by the heat conducting medium to the power generation module;
(3-4) establishing a time period coupling relation of heat storage device for storing heat as follows:
wherein ,is the energy stored by the heat storage device at the time t, gamma TES Is the heat dissipation coefficient, eta of the heat storage device TES,c and ηTES,d The heat charging and heat releasing efficiencies are respectively;
(3-5) setting the charging and discharging power constraint of photo-thermal as follows:
wherein , and />The upper limit and the lower limit of the charging power are respectively +.> and />An upper limit and a lower limit of the heat release power respectively, and />Respectively representing the charge and discharge states of the heat storage device at the time t, < >>1 indicates that the heat storage device is charged at time t, < >>1, the heat storage device releases heat at the time t;
(3-6) setting the constraint of the heat storage range of the photo-thermal as follows:
wherein , and />The upper limit and the lower limit of the heat storage capacity of the heat storage device are respectively;
(3-7) setting start-end heat storage capacity constraint in the optimization period of the photo-thermal power station as follows:
wherein , and />The heat storage quantity of the heat storage device at the moment 0 and the moment T respectively;
(3-8) establishing a thermoelectric conversion relation function of the power generation module in photo-thermal as follows:
wherein ,Pt CSP Is the power generation power of the photo-thermal unit, is determined by the thermal power and thermoelectric conversion efficiency of the heat conducting medium to the power generation module, wherein eta CSP Is the thermoelectric conversion efficiency;
(3-9) establishing the output constraint of the photo-thermal unit as follows:
wherein , and />The upper limit and the lower limit of the output of the photo-thermal unit are respectively +.>Representing the operating state of the photo-thermal unit at time t, < >>A1 indicates that the unit is in a starting state, +.>A value of 0 indicates that the unit is in a shutdown state;
(3-10) establishing the operation constraint of the photo-thermal unit as follows:
wherein , and />Respectively represents the start-stop operation of the unit at the time t, < >>1 indicates that the unit is started up at the time t,1 means that the machine set is stopped at the moment t, alpha CSP and βCSP The minimum start-up time and the minimum stop time of the photo-thermal unit are respectively;
(3-11) setting climbing constraint of the photo-thermal unit as follows:
wherein ,rCSP Is the climbing rate of the photo-thermal unit;
(4) The electric energy storage system model is built as follows:
(4-1) establishing a time period coupling relation of the state of charge of the electric energy storage system, namely a constraint equation of an electric energy storage system model as follows:
wherein ,is the electric quantity stored by the electric energy storage system at the moment t, gamma ESS Is the electric quantity dissipation coefficient, eta of the electric energy storage system ESS,c and ηESS,d Charge and discharge efficiencies, respectively;
(4-2) setting charge-discharge power constraints of the electrical energy storage system as follows:
wherein , and />Charging power upper and lower limits, respectively, < -> and />Upper and lower discharge power limit, respectively, < >> and />Respectively representing the charge and discharge states of the energy storage system at the time t, < >>For 1 is the stored energy charged at time t +.>1 represents that the stored energy is discharged at the time t;
(4-3) setting the limit of the electric storage amount range as follows:
wherein , and />Respectively an upper limit and a lower limit of the stored energy and the stored electric quantity;
(4-4) establishing state of charge constraints at the beginning and end of an energy storage system optimization cycle as follows:
wherein , and />The electric quantity stored by the energy storage system at the moment 0 and the moment T respectively;
(4-5) setting design parameter constraints of the energy storage system as follows:
wherein ,kESS Is the maximum discharge time of the energy storage system;
(5) Establishing a cascade hydroelectric model, wherein the operation constraint of the cascade hydroelectric comprises hydraulic constraint, electric power constraint and a hydropower energy conversion relation, and the upstream and downstream of the reservoir are connected with each other through upstream and downstream discharging flow and downstream warehousing flow;
the step hydroelectric power decomposition module is also used for:
the objective function of the long-term reservoir capacity scheduling model in the reservoir is that the annual power generation total amount of each cascade hydropower station is the largest:
Constraint conditions of the long-term reservoir capacity scheduling model in the reservoir comprise:
(1) The hydropower station energy form hydropower conversion relation is established as follows:
wherein ,for the total monthly power generation of hydropower station i, +.>Is the average water head of the unit h in the hydropower station i,is the total power generation water quantity ρThe density of water, g is the gravitational acceleration, eta PH Is the water-electricity conversion efficiency; the water-electricity conversion efficiency eta is calculated in practice PH Taking the value as a fixed value;
(2) Establishing a relation between the maximum power generation amount and the minimum power generation amount of the hydropower station unit:
wherein ,is the minimum guaranteed power generation of the unit h, +.>The theoretical full power generation amount calculated by the installed capacity of the unit h;
(3) The water balance equation is established as follows:
wherein ,generating water quantity for i months of hydropower station, < >>Discarding water for i months of the hydropower station;
(4) The reservoir water storage capacity constraint is established as follows:
wherein ,Vi m Minimum water storage capacity of reservoir to be ensured for ith hydropower station, V i M The maximum water storage capacity allowed for the ith hydropower station;
(5) The reservoir water discharge amount constraint is established as follows:
wherein ,Vi discharge,M The maximum allowable drainage flow of the ith hydropower station;
(6) The water storage capacity constraint at the beginning and the end of the scheduling period is established as follows:
wherein ,Ωyear For a hydropower station number set with more than month adjustment capability,
the simulation module is further configured to:
(1) The step hydropower short-term operation simplified model is established as follows:
on the basis of completing water quantity and electric quantity distribution by medium-long term operation simulation, step hydropower in short term operation simulation adopts a simplified unit model, and only the electric power constraint part is considered so as to reduce calculation complexity;
wherein ,is the daily maximum power generation constraint of hydropower station i,/->The daily hydroelectric power generation capacity of each step is obtained through medium-term operation simulation calculation;
(2) The short-term operation model of other types of power supplies is established as follows:
the power system satisfies the source load power balance at any time as follows:
wherein ,is the local load at time t, +.>The power is the power sent by the power system at the moment t;
the positive and negative standby capacities of the power system are jointly provided by water power, light and heat and energy storage, and constraint conditions are as follows:
wherein , and />Up-regulating capacity of power system at time t respectivelyDown-regulating capacity demand;
the optimization objective of the power supply short-term operation model is to minimize the annual operation cost of the power system, wherein the optimization objective comprises the generation cost of each type of power supply and wind power, photovoltaic, hydroelectric and photo-thermal power discarding punishment, and the objective function of the power supply short-term operation model is as follows:
wherein ：CG Is the unit power generation cost of the thermal power in the power supply planning scheme containing the thermal power, C Water and CCSP Is the unit power generation cost of water electricity and photo-heat, C Cur Is the electricity discarding punishment cost of wind power, photovoltaic, hydroelectric and photo-thermal.
3. An electronic device, comprising:
a memory for storing computer-executable instructions;
a processor configured to perform any of the multi-energy power system timing operations simulations of claim 1.
4. A computer-readable storage medium, having stored thereon a computer program for causing the computer to perform the multi-energy power system time series operation simulation of claim 1.
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