CN110165699B - Photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation - Google Patents
Photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation Download PDFInfo
- Publication number
- CN110165699B CN110165699B CN201910359554.3A CN201910359554A CN110165699B CN 110165699 B CN110165699 B CN 110165699B CN 201910359554 A CN201910359554 A CN 201910359554A CN 110165699 B CN110165699 B CN 110165699B
- Authority
- CN
- China
- Prior art keywords
- photo
- power station
- thermal power
- capacity
- power
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000005457 optimization Methods 0.000 title claims abstract description 33
- 230000000295 complement effect Effects 0.000 claims abstract description 66
- 238000005338 heat storage Methods 0.000 claims abstract description 38
- 238000013439 planning Methods 0.000 claims abstract description 38
- 230000007613 environmental effect Effects 0.000 claims abstract description 14
- 238000004519 manufacturing process Methods 0.000 claims abstract description 13
- 238000004088 simulation Methods 0.000 claims abstract description 12
- 230000005611 electricity Effects 0.000 claims abstract description 9
- 238000010248 power generation Methods 0.000 claims description 36
- 230000009194 climbing Effects 0.000 claims description 12
- 239000000126 substance Substances 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 10
- 230000005540 biological transmission Effects 0.000 claims description 9
- 230000008901 benefit Effects 0.000 claims description 8
- 238000013461 design Methods 0.000 claims description 8
- 239000003344 environmental pollutant Substances 0.000 claims description 8
- 231100000719 pollutant Toxicity 0.000 claims description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 238000012423 maintenance Methods 0.000 claims description 6
- 238000012384 transportation and delivery Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 239000000356 contaminant Substances 0.000 claims description 4
- 238000009826 distribution Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 claims description 3
- 230000007774 longterm Effects 0.000 claims description 3
- 230000005855 radiation Effects 0.000 claims description 3
- 238000011084 recovery Methods 0.000 claims description 3
- 230000005622 photoelectricity Effects 0.000 claims description 2
- 238000010276 construction Methods 0.000 claims 1
- 238000011161 development Methods 0.000 description 4
- 230000014509 gene expression Effects 0.000 description 3
- 238000003860 storage Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000007728 cost analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000011234 economic evaluation Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000013468 resource allocation Methods 0.000 description 1
Images
Classifications
-
- H02J3/383—
-
- 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
-
- 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]
-
- 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
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
Abstract
The invention discloses a photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation, which is used for analyzing the capacity characteristic, the electric quantity characteristic, the economy, the reliability, the flexibility and the environmental protection performance of a photo-thermal power station facing to planning based on the energy flow relation of the photo-thermal power station and the technical indexes of the photo-thermal power station; then establishing an optimization target by taking the minimum normalized electricity consumption cost of the photo-thermal power station as a target function, and calculating the scale configuration of each subsystem of the photo-thermal power station according to the photo-electric capacity ratio and the heat storage hours of the photo-thermal power station obtained by simulation; and then constructing a complementary optimal configuration model of the photo-thermal power station with the aim of lowest total cost of the complementary system, constructing constraint conditions to generate configuration capacity of various power supplies in the complementary system, and guiding planning and production of various complementary power supplies in the actual system according to the determined capacity configuration result. The method can be applied to individual optimization configuration of the photo-thermal power station and capacity optimization configuration of a complementary system containing the photo-thermal power station, and provides guidance for power supply investment decision.
Description
Technical Field
The invention belongs to the technical field of power supply planning, and particularly relates to a photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation.
Background
With the continuous maturity of various new forms of energy power generation technologies, new forms of energy installation proportion promotes by a wide margin, and the power structure is continuously optimized. The photo-thermal power station serving as a new renewable energy source has flexible regulation capacity and good complementary benefits with other power sources, but the high investment cost of the photo-thermal power station becomes a main factor influencing the development of the photo-thermal power station. The photothermal power station is generally composed of a light-gathering and heat-collecting system, a heat storage system and a power generation system, and in order to maintain continuous and stable operation of the photothermal power station, a backup system is also provided for some photothermal power stations. The reasonable individual optimization configuration of the photo-thermal power station has important significance on the economy and the operation characteristics of the photo-thermal power station. In addition, the power generation system of the photo-thermal power station has the capability of quick start-stop and climbing, and natural resources such as wind, light, water and the like have natural complementarity. The capacity of the photo-thermal and complementary power supply is optimized, so that effective resource utilization can be realized, and the complementary benefits of the system can be brought into play.
Referring to fig. 1, the conventional individual optimal configuration method for the optical-thermal power station generally uses the normalized power cost of the photo-thermal power station as an economic evaluation index, and mainly focuses on analyzing the influence of material selection, site selection and configuration of each subsystem scale on the characteristics of the optical-thermal power station. However, the influence of the external characteristics of the photo-thermal power station facing system planning on the individual optimal configuration of the power station is rarely considered in the method. With the continuous maturity of the photo-thermal power generation technology, large-scale photo-thermal grid connection becomes a development trend. The research on the influence of the external characteristics of the photo-thermal power station facing system planning on the individual optimization configuration of the photo-thermal power station is of great significance.
The traditional complementary power supply capacity optimal configuration method mainly takes a wind-photovoltaic-storage and wind-photovoltaic-water complementary system as a main part, and the capacity of various power supplies is optimally configured by establishing a complementary mechanism, so that the maximum complementary benefit of the system is realized. The complementary system optimization configuration of the plant containing the photo-thermal power station is researched by a few methods.
Disclosure of Invention
The invention aims to solve the technical problem of providing an optimal configuration method of a photo-thermal power station based on individual optimization and system multi-energy complementation, overcomes the defects of the traditional method and has important significance for configuration and planning of the photo-thermal power station.
The invention adopts the following technical scheme:
the method comprises the steps of obtaining regional resource data, system basic technical data, photo-thermal power station planning data and complementary system planning data based on an individual optimization and system multi-energy complementary photo-thermal power station optimization configuration method; analyzing planning-oriented capacity characteristics, electric quantity characteristics, economy, reliability, flexibility and environmental protection of the photo-thermal power station based on the energy flow relation of the photo-thermal power station and the technical indexes of the photo-thermal power station; then establishing an optimization target by taking the minimum normalized kilowatt-hour cost of the photo-thermal power station as an objective function, establishing a constraint condition, and obtaining the photoelectric capacity ratio SM of the photo-thermal power station according to the simulationSFAnd number of heat storage hours HTESCalculating the scale configuration of each subsystem of the photo-thermal power station; and then constructing a complementary optimal configuration model of the photo-thermal power station with the aim of lowest total cost of the complementary system, constructing constraint conditions to generate configuration capacity of various power supplies in the complementary system, and guiding planning and production of various complementary power supplies in the actual system according to the determined capacity configuration result.
In particular, capacity characteristics
The method is used for evaluating the capacity of the power supply to provide output, and specifically comprises the following steps:
electric quantity characteristic: annual energy production E of power supplyCSPThe method is used for the electric quantity balance analysis of system planning, and specifically comprises the following steps:
the economic efficiency is as follows: and evaluating the economy by adopting the LCOE (normalized electricity consumption cost), wherein the specific calculation is as follows:
reliability: establishing a shutdown probability model based on the long-term statistical characteristics of the photo-thermal unit, and specifically calculating as follows:
flexibility: the operation interval, the climbing rate and the start and stop of the unit are specifically calculated as follows:
environmental protection property: pollutant discharge amount and discharge cost of photo-thermal power station
The specific calculation is as follows:
wherein χ is a capacity factor of the photothermal power station; capCSPRated capacity of the photothermal power station; CRF is the capital recovery factor;
the investment cost of the photo-thermal power station is reduced;
the annual operation and maintenance cost of the photo-thermal power station is reduced; y is a state probability function of the photo-thermal power station; xCSPThe output state variable of the photo-thermal power station;
the ith output state of the photo-thermal power station is set;
the probability of the photothermal power station being in the ith output state is obtained;
the state variable of the photo-thermal power station at the time h is 1, namely the photo-thermal power station is in operation, and 0 represents the photo-thermal power station is out of operation;
respectively representing the minimum and maximum output of the photo-thermal power station;
the output of the photo-thermal power station at h moment; RDCSP、RUCSPThe maximum downward climbing speed and the maximum upward climbing speed of the photo-thermal power station are respectively set; x is the type of contaminant; rhoxThe discharge cost per unit mass of the pollutant x;
is the emission equivalent of the pollutant x.
Specifically, the method comprises the following steps of establishing an optimized target min f by taking the minimum normalized kilowatt-hour cost of the photo-thermal power station as a target function:
min f＝LCOE
wherein, LCOE is the leveling degree cost of the photo-thermal power station.
Specifically, the constructed constraint conditions include resource constraints of the photothermal power station; operating constraints of the photothermal power station; external property constraints of the photothermal power station;
the resource constraints of the photothermal power station are:
wherein A isSFThe heat collection area of the photo-thermal power station;
the planning area of the photo-thermal power station;
the operational constraints of the photothermal power station are:
wherein the content of the first and second substances,
for photo-thermal power station to transmit at h momentThe amount of heat input; etaSFThe photo-thermal conversion efficiency is achieved; DNIhThe direct solar radiation quantity at the moment h;
the light abandon amount at the h moment;
the heat transmitted to the power generation system by the light-gathering and heat-collecting system at the h moment is obtained;
the heat energy transferred to the power generation system by the light-gathering and heat-collecting system at the h moment is obtained;
the heat storage amount of the heat storage system at the moment h; etaHeatIs the heat loss coefficient of the heat storage system; etaSTThe heat storage efficiency of the heat storage system;
the heat energy transferred to the power generation system by the heat storage system at the moment h; etaPBEfficiency of the power generation system; etaTPThe heat release efficiency of the heat storage system;
heat provided for backup system at time h;
external property constraints for photothermal power stations include the following:
the confidence capacity constraint is:
the annual energy production is constrained as follows:
the reliability constraints are:
the environmental protection constraints are:
wherein tau is the peak load time period; t isτIs the duration of the peak load period; t is the simulation duration; χ is a capacity factor of the photothermal power station; kappa is the maximum power generation ratio of the backup system; t isminThe minimum power generation time of the photo-thermal power station; AUHCSPThe number of hours of year design utilization for the photo-thermal power station;
is the confidence capacity of the photothermal power station; eCSPIs the annual energy production of the photo-thermal power station.
Specifically, the scale configuration of each subsystem of the photothermal power station is calculated as follows:
CapSF＝SMSFCapCSP/ηPB
wherein, CapSFThe capacity of the light-gathering and heat-collecting system;
is the capacity of the heat storage system; SMSFThe ratio of the photo-electricity capacity to the photo-thermal power station; hTESThe number of heat storage hours; etaPBEfficiency of the power generation system; etaTPThe heat release efficiency of the heat storage system; etaHeatIs the heat loss coefficient of the heat storage system; capCSPThe rated capacity of the photothermal power station.
Specifically, the objective function of constructing the complementary optimal configuration model of the photothermal power station with the aim of minimizing the total cost of the complementary system is as follows:
wherein N is the type number of the complementary power supply; knThe number of the units of the nth power supply;
the investment cost of a single unit of the nth power supply is saved;
the operation and maintenance cost of the nth type power supply unit is obtained;
and
the output and input power of the tie line at the h moment; rhoSEAnd ρBERespectively selling electricity and buying electricity price; cspillThe cost is abandoned for new energy.
Specifically, the constraint conditions for generating the configuration capacity of each power supply in the complementary system include system power backup and balance constraint, operation constraint of each power supply, system resource constraint, system new energy power generation capacity ratio constraint and system external area power transmission constraint.
Further, the system power backup and balance constraints are:
wherein, χnThe capacity factor of the nth power supply; capnRated capacity of the nth type power supply; omegaRAnd ΩCRespectively integrating new energy and conventional energy;
is the maximum load;
and
respectively representing the load power at the h moment and the power of an nth power supply;
intermittent power sources such as wind power, photovoltaic and the like are as follows:
wherein the content of the first and second substances,
the output power at the intermittent power supply h moment; kw/sThe number of intermittent units; zhThe output of a single unit at the moment h;
discarding power for the intermittent power source at the h moment;
the operating constraints of a conventional power supply are:
wherein the content of the first and second substances,
the number of the conventional units in transportation;
the minimum maximum power of the conventional unit;
the output of the conventional unit at the h moment is obtained; RU (RU)c、RDcThe distribution represents the up-down climbing rate of the conventional unit;
the system resource constraints are:
wherein the content of the first and second substances,
respectively representing the minimum and maximum configuration numbers of the nth power supply;
the new energy generated energy is constrained by the following ratio:
the delivery electrical constraint of the system outer region is:
wherein, CaplineIs the transmission capacity of the junctor.
Specifically, the configuration capacity pi of the nth power supply in the complementary systemnThe following were used:
Πn＝KnCapn
wherein, KnThe number of the units of the nth power supply; capnThe rated capacity of the nth type power supply.
Specifically, the regional resource data comprises historical wind speed data, historical illumination data and historical water inflow data; the basic technical data of the system comprises load data and technical economic data of various power suppliesData, tie line data, and environmental economics data; the photothermal power plant planning data includes the annual design utilization hours AUH of the photothermal power plantCSPConfidence capacity of photothermal power station
Minimum power generation time length T of photo-thermal power stationminAnd the maximum power generation ratio kappa of the backup system; the complementary system planning data comprises a system spare rate D, a minimum utilization rate gamma of a connecting line, a minimum occupation ratio xi of the new energy generating capacity of the system and a proportion epsilon of the maximum allowable outgoing power conversion amount in unit time to the transmission capacity.
Compared with the prior art, the invention has at least the following beneficial effects:
the invention provides a photothermal power station optimal configuration method based on individual optimization and system multi-energy complementation, which can effectively solve the problems of photothermal power station individual optimal configuration and complementary optimal configuration in a system, and compared with the traditional photothermal power station configuration method, the photothermal power station optimal configuration method comprehensively considers the external characteristics of the photothermal power station facing the planning, and the individual optimal configuration model better meets the design requirements of power supply planning in the form of large-scale development of the photothermal power station in the future by analyzing the two-quantity four-character of the photothermal power station and considering the external characteristic constraint in the individual optimal configuration model, and the optimal configuration model of the complementary system power supply capacity containing the photothermal power station provided by the invention is established with the optimal system economy as the target, and a complementary mechanism meeting the requirements of the power generation capacity of the new energy in the region and the transmission of the connecting line outside the region is realized, and the complementary benefit maximization of the system power supply is realized. The problem that the photo-thermal power station is difficult to plan and put into production due to too high cost can be effectively solved, the resource allocation is optimized, and the utilization rate of new energy of the system is improved.
Furthermore, the external characteristics of the photo-thermal power station facing the planning can be effectively captured by analyzing the 'two-quantity four-property' of the photo-thermal power station, so that the individual and complementary optimization configuration of the photo-thermal power station can better meet the actual requirements of the planning.
Further, the optimization goal of minimizing the standardized kilowatt-hour cost is to achieve optimal individual economy of the photothermal power station.
Furthermore, resource constraint, operation constraint and external characteristic constraint of the photo-thermal power station are comprehensively considered, so that the simulation of the photo-thermal power station is more in line with the actual situation.
Furthermore, the optimal economic performance of the individual optimal configuration of the photo-thermal power station is realized by calculating the scale configuration of each subsystem according to the photo-electric capacity ratio and the heat storage hours obtained by simulation under the condition of meeting various constraints of the photo-thermal power station.
Further, the aim is to achieve an optimal economy of the complementary system with a minimum total cost of the complementary system.
Furthermore, the power reserve and balance constraint of the complementary system, the operation constraint of various power supplies, the resource constraint, the new energy power generation capacity ratio constraint and the outer region power transmission constraint are comprehensively considered, so that the operation of the complementary system meets the actual condition and the complementary requirement.
Furthermore, the capacity of the complementary system is configured according to the number of the units of various power supplies obtained through simulation, and the complementary benefit maximization of the complementary system is realized.
Further, the data obtained from the power system planning department are the original calculation parameters required for obtaining the proposed method.
In conclusion, the method disclosed by the invention is suitable for the reality of rapid development of photo-thermal power generation in China, can be applied to individual optimization configuration of a photo-thermal power station and capacity optimization configuration of a complementary system of the photo-thermal power station, and provides guidance for power supply investment decision.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 is a graph of the energy flow relationships within a photothermal power station;
fig. 2 is a flow chart of the method for optimizing configuration of the photothermal power plant based on individual optimization and system multi-energy complementation according to the present invention.
Detailed Description
The invention provides a photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation.
Referring to fig. 2, the method for optimizing configuration of a photo-thermal power station based on individual optimization and system multi-energy complementation of the present invention includes the following steps:
s1, acquiring regional resource data, system basic technical data and photo-thermal power station planning data from a power system planning department;
regional resource data: historical wind speed data; historical lighting data; historical incoming water volume data;
basic technical data of the system: load data; technical and economic data of various power supplies; tie line data; environmental economics data.
Photothermal power station planning data: annual design utilization hours AUH of photo-thermal power stationCSP(ii) a Confidence capacity of photothermal power station
Minimum power generation time length T of photo-thermal power stationmin(ii) a The backup system has a maximum power generation ratio k.
Complementary system planning data: a system standby rate D; minimum utilization rate gamma of tie lines; the lowest ratio xi of the generated energy of the new energy of the system; the maximum allowed outgoing power conversion per unit time is the ratio epsilon of the transmission capacity.
S2, analyzing external characteristics of the photo-thermal power station facing planning based on energy flow relation of the photo-thermal power station and technical indexes of the photo-thermal power station, wherein the external characteristics mainly refer to two-component four-property: capacity characteristics, electric quantity characteristics, economy, reliability, flexibility and environmental protection;
capacity characteristic
The capacity characteristic is used for evaluating the capacity of the power supply for providing output, and for the photo-thermal power station, the confidence capacity is mainly used, and the specific calculation is as follows:
electric quantity characteristic ECSP: the annual generated energy of the power supply is used for electric quantity balance analysis of system planning, and the specific calculation is as follows:
ECSP＝CapCSPAUHCSP (2)
economic LCOE: a cost analysis method is mostly adopted to evaluate the economy of the power supply, and the solar-thermal power station adopts the levelization electric cost to evaluate the economy, and the specific calculation is as follows:
reliability: establishing a shutdown probability model based on the long-term statistical characteristics of the photo-thermal unit, and specifically calculating as follows:
flexibility: mainly indicate that the running section of unit, climbing speed and unit open and stop, the light and heat power station is as a flexibility power, can regard light and heat unit to open and stop in a flexible way, and concrete calculation is as follows:
environmental protection property
Mainly refers to the pollutant discharge amount and the discharge cost of the photo-thermal power station, and the specific calculation is as follows:
wherein χ is the capacity of the photothermal power stationA factor; capCSPRated capacity of the photothermal power station; eCSPThe annual energy generation capacity of the photo-thermal power station; LCOE is the standard kilowatt-hour cost of the photo-thermal power station; CRF is the capital recovery factor;
the investment cost of the photo-thermal power station is reduced;
the annual operation and maintenance cost of the photo-thermal power station is reduced; y is a state probability function of the photo-thermal power station; xCSPThe output state variable of the photo-thermal power station;
the ith output state of the photo-thermal power station is set;
the probability of the photothermal power station being in the ith output state is obtained;
the state variable of the photo-thermal power station at the time h is 1, namely the photo-thermal power station is in operation, and 0 represents the photo-thermal power station is out of operation;
respectively representing the minimum and maximum output of the photo-thermal power station;
the output of the photo-thermal power station at h moment; RDCSP、RUCSPThe maximum downward climbing speed and the maximum upward climbing speed of the photo-thermal power station are respectively set;
the pollution discharge cost for the photo-thermal power station consuming fuel of unit mass; x is the type of contaminant; rhoxThe discharge cost per unit mass of the pollutant x;
is a row of contaminant xAnd (5) discharging the equivalent.
S3, constructing an individual optimization configuration model of the photo-thermal power station according to the external characteristics facing the planning of the photo-thermal power station;
s301, constructing an optimization target of the individual optimization configuration of the photo-thermal power station: establishing an optimization target min f by taking the minimum normalized kilowatt-hour cost of the photo-thermal power station as a target function, wherein the optimization target min f is as follows:
min f＝LCOE (8)；
s302, constructing constraint conditions including resource constraint of the photo-thermal power station; operating constraints of the photothermal power station; external property constraints of the photothermal power station;
1) the resource constraints of the photothermal power station are:
wherein A isSFThe heat collection area of the photo-thermal power station;
the planning area of the photo-thermal power station;
2) the operational constraints of the photothermal power station are:
wherein, the expressions (10) and (11) are input energy flow constraints, the expression (12) is heat storage constraint, and the expression (13) is output energyFlow constraint;
the heat is transferred into the photo-thermal power station at the moment h; etaSFThe photo-thermal conversion efficiency is achieved; DNIhThe direct solar radiation quantity at the moment h;
the light abandon amount at the h moment;
the heat transmitted to the power generation system by the light-gathering and heat-collecting system at the h moment is obtained;
the heat energy transferred to the power generation system by the light-gathering and heat-collecting system at the h moment is obtained;
the heat storage amount of the heat storage system at the moment h; etaHeatIs the heat loss coefficient of the heat storage system; etaSTThe heat storage efficiency of the heat storage system;
the heat energy transferred to the power generation system by the heat storage system at the moment h; etaPBEfficiency of the power generation system; etaTPThe heat release efficiency of the heat storage system;
the heat provided for backup system at time h.
3) External characteristic constraints of the photo-thermal power station comprise confidence capacity constraints, annual energy production constraints, reliability constraints and environmental protection constraints;
the confidence capacity constraint is:
the annual energy production is constrained as follows:
the reliability constraints are:
the environmental protection constraints are:
wherein tau is the peak load time period; t isτIs the duration of the peak load period; and T is the simulation time length.
S303, calculating the photoelectric capacity ratio SM of the photo-thermal power station according to the second step of simulationSFAnd number of heat storage hours HTESCalculating the scale configuration of each subsystem of the photo-thermal power station as follows:
CapSF＝SMSFCapCSP/ηPB (18)
wherein, CapSFThe capacity of the light-gathering and heat-collecting system;
is the capacity of the thermal storage system.
S4, configuring the photo-thermal power station according to the result of S3 and establishing a power supply capacity optimal configuration model of the photo-thermal power station complementary system;
s401, constructing an objective function of the complementary optimal configuration model of the photo-thermal power station by taking the lowest total cost of the complementary system as a target as follows:
wherein N is the type number of the complementary power supply; knThe number of the units of the nth power supply;
the investment cost of a single unit of the nth power supply is saved;
the operation and maintenance cost of the nth type power supply unit is obtained;
and
the output and input power of the tie line at the h moment; rhoSEAnd ρBERespectively selling electricity and buying electricity price; cspillThe cost is abandoned for new energy;
s402, constructing constraint conditions including system power backup and balance constraint; operating constraints of various power supplies; system resource constraints; the system new energy generated energy is subjected to ratio constraint; an out-of-system delivery electrical constraint;
1) the system power backup and balance constraints are:
wherein, χnThe capacity factor of the nth power supply; capnRated capacity of the nth type power supply; omegaRAnd ΩCRespectively integrating new energy and conventional energy;
is the maximum load;
and
respectively representing the load power at the h moment and the power of the nth power supply.
2) Various power supply operation constraints;
intermittent power sources such as wind power, photovoltaic and the like are as follows:
wherein the content of the first and second substances,
the output power at the intermittent power supply h moment; kw/sThe number of intermittent units; zhThe output of a single unit at the moment h;
power is discarded for the intermittent power source at time h.
The constraints of light and heat are shown in formulas (10) to (13).
The operating constraints of a conventional power supply are:
wherein the content of the first and second substances,
the number of the conventional units in transportation;
the minimum maximum power of the conventional unit;
the output of the conventional unit at the h moment is obtained; RU (RU)c、RDcThe distribution represents the up and down ramp rate of a conventional unit.
3) The system resource constraints are:
wherein the content of the first and second substances,
respectively representing the minimum and maximum configuration numbers of the nth type power supply.
4) The new energy generated energy is constrained by the following ratio:
5) the delivery electrical constraint of the system outer region is:
wherein, CaplineIs the transmission capacity of the junctor.
And S403, simulating and generating the configuration capacity of each power supply in the complementary system according to the complementary optimization configuration model established in the S4, and guiding the planning and production of each complementary power supply in the actual system according to the obtained capacity configuration result so that the system meets the capacity configuration requirement.
Πn＝KnCapn (30)
Therein, IInTo complement the configured capacity of the class n power supply in the system.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
1) Brief description of the embodiments
The practical resource condition of the northwest energy base of China is taken as an example for analysis, and the energy base is rich in light energy, wind energy and water resources. Acquiring wind and light resource data and load data of a region from a planning department, wherein the annual average direct sunlight irradiation quantity of the region is 2200kWh/m2The average wind speed was 4.5 m/s. The maximum load of the area where the energy base is located is 100MW, and the capacity of the external area connecting line is 200 MW. The complementary system mainly comprises three types of power supplies of a wind turbine generator set, a photo-thermal set and a hydroelectric generating set, and the basic parameters of the power supplies are shown in a table 1:
TABLE 1 basic parameters of the various types of power supplies
2) Photo-thermal power station individual optimization configuration result
According to the method, the individual optimization configuration is carried out on the photo-thermal power station, and the external planning characteristics of the photo-thermal power station are comprehensively considered, wherein the annual design power generation amount of the photo-thermal power station is 3500h, the design capacity factor is 0.6, and the annual minimum power generation hours is 4000 h. The external characteristic indexes of the photothermal power station shown in table 2 can be obtained by simulation:
TABLE 2 external Property index of photothermal Power station
It can be seen that the simulation results of the photothermal power station satisfy the external characteristic requirements for planning, and the individual optimization configuration results of the photothermal power station are: the optical capacitance ratio (SM) was 1.44, and the number of heat storage hours was 4.36. The capacity of the corresponding light-gathering and heat-collecting system is 144MW, and the capacity of the heat storage system is 582.24 MWh.
3) Complementary optimal configuration result of photo-thermal power station
Based on the result of the individual optimal configuration of the photo-thermal power station, the required complementary system requires that the non-water renewable energy power generation proportion at least reaches 30 percent, the utilization rate of a tie line reaches 80 percent, and the hourly fluctuation of the outgoing electric energy does not exceed 30 percent of the outgoing capacity. The results can be configured with complementary power sources as shown in table 3:
TABLE 3 optimal configuration of photothermal complementation system
It can be seen that the configured complementary system can meet the complementary requirement of the system, and the benefit maximization of the complementary system is realized.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (8)
1. The photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation is characterized by comprising the steps of obtaining regional resource data, system basic technical data, photo-thermal power station planning data and complementary system planning data; energy flow relation based on photo-thermal power station and technology of photo-thermal power stationThe capacity characteristic, the electric quantity characteristic, the economical efficiency, the reliability, the flexibility and the environmental protection performance of the photo-thermal power station facing the planning are analyzed by indexes; then establishing an optimized target min f (LCOE) by taking the minimum leveling electric cost of the photo-thermal power station as an objective function, establishing a constraint condition by taking the LCOE as the leveling electric cost of the photo-thermal power station, and establishing a photoelectric capacity ratio SM (minimum electric capacity ratio) of the photo-thermal power station according to the simulationSFAnd number of heat storage hours HTESCalculating the scale configuration of each subsystem of the photo-thermal power station; then constructing a complementary optimal configuration model of the photo-thermal power station with the aim of lowest total cost of the complementary system, constructing constraint conditions to generate configuration capacity of various power supplies in the complementary system, and guiding planning and production of various complementary power supplies in an actual system according to a determined capacity configuration result;
capacity characteristic
The method is used for evaluating the capacity of the power supply to provide output, and specifically comprises the following steps:
electric quantity characteristic: annual energy production E of power supplyCSPThe method is used for the electric quantity balance analysis of system planning, and specifically comprises the following steps:
ECSP＝CapCSPAUHCSP
the economic efficiency is as follows: and evaluating the economy by adopting the LCOE (normalized electricity consumption cost), wherein the specific calculation is as follows:
reliability: establishing a shutdown probability model based on the long-term statistical characteristics of the photo-thermal unit, and specifically calculating as follows:
flexibility: the operation interval, the climbing rate and the start and stop of the unit are specifically calculated as follows:
environmental protection property: pollutant discharge amount and discharge cost of photo-thermal power station
The specific calculation is as follows:
wherein χ is a capacity factor of the photothermal power station; capCSPRated capacity of the photothermal power station; CRF is the capital recovery factor;
the investment cost of the photo-thermal power station is reduced;
the annual operation and maintenance cost of the photo-thermal power station is reduced; y is a state probability function of the photo-thermal power station; xCSPThe output state variable of the photo-thermal power station;
the ith output state of the photo-thermal power station is set;
the probability of the photothermal power station being in the ith output state is obtained;
the state variable of the photo-thermal power station at the time h is 1, namely, the power station is in operation, and 0 represents the power station is stopped;
respectively representing the minimum and maximum output of the photo-thermal power station;
the output of the photo-thermal power station at h moment; RDCSP、RUCSPThe maximum downward climbing speed and the maximum upward climbing speed of the photo-thermal power station are respectively set; x is the type of contaminant; rhoxThe discharge cost per unit mass of the pollutant x;
is the emission equivalent of the pollutant x.
2. The method of claim 1, wherein the constraints for establishing the optimization objective construction with respect to the objective function of minimizing the levelization cost of the photothermal power station comprise resource constraints of the photothermal power station; operating constraints of the photothermal power station; external property constraints of the photothermal power station;
the resource constraints of the photothermal power station are:
wherein A isSFThe heat collection area of the photo-thermal power station;
the planning area of the photo-thermal power station;
the operational constraints of the photothermal power station are:
wherein the content of the first and second substances,
the heat is transferred into the photo-thermal power station at the moment h; etaSFThe photo-thermal conversion efficiency is achieved; DNIhThe direct solar radiation quantity at the moment h;
the light abandon amount at the h moment;
the heat transmitted to the power generation system by the light-gathering and heat-collecting system at the h moment is obtained;
the heat energy transferred to the power generation system by the light-gathering and heat-collecting system at the h moment is obtained;
the heat storage amount of the heat storage system at the moment h; etaHeatIs the heat loss coefficient of the heat storage system; etaSTThe heat storage efficiency of the heat storage system;
the heat energy transferred to the power generation system by the heat storage system at the moment h; etaPBFor power generation systemsEfficiency; etaTPThe heat release efficiency of the heat storage system;
heat provided for backup system at time h;
external property constraints for photothermal power stations include the following:
the confidence capacity constraint is:
the annual energy production is constrained as follows:
the reliability constraints are:
the environmental protection constraints are:
wherein tau is the peak load time period; t isτIs the duration of the peak load period; t is the simulation duration; χ is a capacity factor of the photothermal power station; kappa is the maximum power generation ratio of the backup system; t isminThe minimum power generation time of the photo-thermal power station; AUHCSPThe number of hours of year design utilization for the photo-thermal power station;
is the confidence capacity of the photothermal power station; eCSPIs the annual energy production of the photo-thermal power station.
3. The method of claim 1 wherein the configuration of the scale of each subsystem of the photothermal power station is calculated as follows:
CapSF＝SMSFCapCSP/ηPB
wherein, CapSFThe capacity of the light-gathering and heat-collecting system;
is the capacity of the heat storage system; SMSFThe ratio of the photo-electricity capacity to the photo-thermal power station; hTESThe number of heat storage hours; etaPBEfficiency of the power generation system; etaTPThe heat release efficiency of the heat storage system; etaHeatIs the heat loss coefficient of the heat storage system; capCSPThe rated capacity of the photothermal power station.
4. The method of claim 1, wherein the objective function for constructing the complementary optimal configuration model for the plant with photothermal power with the goal of minimizing the total cost of the complementary system is as follows:
wherein N is the type number of the complementary power supply; knThe number of the units of the nth power supply;
the investment cost of a single unit of the nth power supply is saved;
the operation and maintenance cost of the nth type power supply unit is obtained;
and
the output and input power of the tie line at the h moment; rhoSEAnd ρBERespectively selling electricity and buying electricity price; cspillThe cost is abandoned for new energy.
5. The method of claim 1, wherein the constraints for generating the configuration capacity of each type of power supply in the complementary system include system power backup and balance constraints, operation constraints of each type of power supply, system resource constraints, system new energy power generation capacity proportion constraints, and system out-of-system power delivery constraints.
6. The method of claim 5, wherein the system power backup and balancing constraints are:
wherein, χnThe capacity factor of the nth power supply; capnRated capacity of the nth type power supply; omegaRAnd ΩCRespectively integrating new energy and conventional energy;
is the maximum load;
and
respectively representing the load power at the h moment and the power of an nth power supply;
intermittent power sources such as wind power, photovoltaic and the like are as follows:
wherein the content of the first and second substances,
the output power at the intermittent power supply h moment; kw/sThe number of intermittent units; zhThe output of a single unit at the moment h;
discarding power for the intermittent power source at the h moment;
the operating constraints of a conventional power supply are:
wherein the content of the first and second substances,
the number of the conventional units in transportation;
the minimum maximum power of the conventional unit;
the output of the conventional unit at the h moment is obtained; RU (RU)c、RDcThe distribution represents the up-down climbing rate of the conventional unit;
the system resource constraints are:
wherein the content of the first and second substances,
respectively representing the minimum and maximum configuration numbers of the nth power supply;
the new energy generated energy is constrained by the following ratio:
wherein;
the delivery electrical constraint of the system outer region is:
wherein, CaplineIs the transmission capacity of the junctor.
7. The method of claim 1, wherein the configured capacity Π of class n power supplies in the complementary systemnThe following were used:
Πn＝KnCapn
wherein, KnThe number of the units of the nth power supply; capnThe rated capacity of the nth type power supply.
8. The method of claim 1, wherein the regional resource data comprises historical wind speed data, historical lighting data, and historical water inflow data; the basic technical data of the system comprise load data, technical and economic data of various power supplies, tie line data and environmental and economic data; the photothermal power station planning data includes the annual design benefit of the photothermal power stationHours of use AUHCSPConfidence capacity of photothermal power station
Minimum power generation time length T of photo-thermal power stationminAnd the maximum power generation ratio kappa of the backup system; the complementary system planning data comprises a system spare rate D, a minimum utilization rate gamma of a connecting line, a minimum occupation ratio xi of the new energy generating capacity of the system and a proportion epsilon of the maximum allowable outgoing power conversion amount in unit time to the transmission capacity.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910359554.3A CN110165699B (en) | 2019-04-30 | 2019-04-30 | Photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910359554.3A CN110165699B (en) | 2019-04-30 | 2019-04-30 | Photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110165699A CN110165699A (en) | 2019-08-23 |
| CN110165699B true CN110165699B (en) | 2021-09-07 |
Family
ID=67633240
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910359554.3A Active CN110165699B (en) | 2019-04-30 | 2019-04-30 | Photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110165699B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115879746A (en) * | 2023-02-23 | 2023-03-31 | 国网江西省电力有限公司经济技术研究院 | Planning strategy analysis method and system for park comprehensive energy and electronic equipment |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8903561B1 (en) * | 2009-07-29 | 2014-12-02 | Lockheed Martin Corporation | Method for thermal energy dispatch |
| CN107453379A (en) * | 2017-09-18 | 2017-12-08 | 中国电力工程顾问集团西北电力设计院有限公司 | A kind of analysis method for determining photo-thermal power station and participating in optimal heat accumulation duration after peak regulation |
| CN108336765A (en) * | 2018-01-19 | 2018-07-27 | 华北电力大学（保定） | A kind of wind-power electricity generation and solar-thermal generating system capacity ratio optimization method |
| CN108494014A (en) * | 2018-02-08 | 2018-09-04 | 能金云（北京）信息技术有限公司 | A kind of energy mix cogeneration of heat and power economy optimum management method |
| CN109086943A (en) * | 2018-08-27 | 2018-12-25 | 华北电力大学 | Wind-powered electricity generation photo-thermal power station association system capacity optimization method based on wind light mutual complementing characteristic |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103065197A (en) * | 2012-12-12 | 2013-04-24 | 中国能源建设集团广东省电力设计研究院 | Optimal configuration method of distributed combined cooling heating and power system |
-
2019
- 2019-04-30 CN CN201910359554.3A patent/CN110165699B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8903561B1 (en) * | 2009-07-29 | 2014-12-02 | Lockheed Martin Corporation | Method for thermal energy dispatch |
| CN107453379A (en) * | 2017-09-18 | 2017-12-08 | 中国电力工程顾问集团西北电力设计院有限公司 | A kind of analysis method for determining photo-thermal power station and participating in optimal heat accumulation duration after peak regulation |
| CN108336765A (en) * | 2018-01-19 | 2018-07-27 | 华北电力大学（保定） | A kind of wind-power electricity generation and solar-thermal generating system capacity ratio optimization method |
| CN108494014A (en) * | 2018-02-08 | 2018-09-04 | 能金云（北京）信息技术有限公司 | A kind of energy mix cogeneration of heat and power economy optimum management method |
| CN109086943A (en) * | 2018-08-27 | 2018-12-25 | 华北电力大学 | Wind-powered electricity generation photo-thermal power station association system capacity optimization method based on wind light mutual complementing characteristic |
Non-Patent Citations (3)
| Title |
|---|
| ,The Capacity Joint Optimization of Energy Storage and Renewable Generation Based on Simulation;Zhaodi Shi等，;《2018 International Conference on Power System Technology (POWERCON)》;20190107;全文 * |
| 古浪10万千瓦槽式光热电站系统方案研究;阚斌;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20190215;第2页-第35页 * |
| 计及综合成本的风电-光伏-光热联合出力调度策略;崔杨等;《高电压技术》;20190131;第45卷(第1期);第269-275页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110165699A (en) | 2019-08-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109103926B (en) | Photovoltaic power generation receiving capacity calculation method based on multi-radiation characteristic annual meteorological scene | |
| CN105048516B (en) | A kind of honourable extreme misery multi-source complementation Optimization Scheduling | |
| CN106099993B (en) | A kind of power source planning method for adapting to new energy and accessing on a large scale | |
| CN106786799B (en) | Power stepped power generation plan optimization method for direct current connecting line | |
| CN109449993B (en) | Multi-time scale production simulation method for multi-energy complementary power system | |
| CN106485352A (en) | A kind of multiclass power supply generation schedule combination decision-making method | |
| CN103259262A (en) | Method for optimizing maintenance plan of electric power system comprising large-scale wind power | |
| CN104578183B (en) | Tie-line power transmission plan optimization method for improving low-carbon level of electric system | |
| CN110661301B (en) | Capacity allocation optimization method for water-light-storage multi-energy complementary power generation system | |
| CN110994606B (en) | Multi-energy power supply capacity configuration method based on complex adaptation system theory | |
| CN116667395B (en) | Capacity allocation method for water-wind-solar-energy-storage complementary pump station based on cascade hydropower transformation | |
| CN108876026A (en) | Take into account the electricity optimization configuration method sent a telegram here outside extra-high voltage grid and area | |
| CN111445107A (en) | Multi-objective optimization configuration method for cold-heat-power combined supply type micro-grid | |
| CN112671035A (en) | Virtual power plant energy storage capacity configuration method based on wind power prediction | |
| CN112234604A (en) | Multi-energy complementary power supply base optimal configuration method, storage medium and equipment | |
| CN110932261A (en) | Multi-energy system combined installation planning method based on global benefit maximization | |
| CN115577929A (en) | Random optimization scheduling method for rural comprehensive energy system based on multi-scene analysis | |
| CN109993345A (en) | A kind of isolated operation towards garden is provided multiple forms of energy to complement each other system dynamic economic dispatch method | |
| CN105656026A (en) | Equipment construction resource configuration method and system of renewable energy sources | |
| CN108847661B (en) | Annual production simulation operation method and system for regional power system | |
| CN114301089A (en) | Energy storage capacity configuration optimization method for wind-solar combined power generation system | |
| CN110165699B (en) | Photo-thermal power station optimal configuration method based on individual optimization and system multi-energy complementation | |
| CN110247392A (en) | More standby resources robust Optimal methods of meter and wind-powered electricity generation marginal capacity and Demand Side Response | |
| CN116826726A (en) | Micro-grid power generation amount prediction method, device and storage medium | |
| CN112183839A (en) | Medium-term and long-term optimized scheduling method for cascade-containing hydroelectric wind-solar-water complementary power generation system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |