CN106372448A - Feasibility assessment method for cross-regional consumption of clean energy - Google Patents
Feasibility assessment method for cross-regional consumption of clean energy Download PDFInfo
- Publication number
- CN106372448A CN106372448A CN201610943204.8A CN201610943204A CN106372448A CN 106372448 A CN106372448 A CN 106372448A CN 201610943204 A CN201610943204 A CN 201610943204A CN 106372448 A CN106372448 A CN 106372448A
- Authority
- CN
- China
- Prior art keywords
- clean energy
- consumption
- capacity
- obtaining
- trans
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 31
- 230000006855 networking Effects 0.000 claims abstract description 21
- 238000011156 evaluation Methods 0.000 claims abstract description 20
- 239000003245 coal Substances 0.000 claims description 39
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 28
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 claims description 28
- 230000005540 biological transmission Effects 0.000 claims description 16
- 229910002092 carbon dioxide Inorganic materials 0.000 claims description 14
- 239000001569 carbon dioxide Substances 0.000 claims description 14
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 14
- 230000005611 electricity Effects 0.000 claims description 9
- 230000009466 transformation Effects 0.000 claims description 9
- 238000005265 energy consumption Methods 0.000 claims description 6
- 238000009434 installation Methods 0.000 claims description 6
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 5
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 5
- 229910052799 carbon Inorganic materials 0.000 claims description 5
- 229910052717 sulfur Inorganic materials 0.000 claims description 5
- 239000011593 sulfur Substances 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 4
- 230000005622 photoelectricity Effects 0.000 claims description 4
- 238000010248 power generation Methods 0.000 claims description 4
- 238000006477 desulfuration reaction Methods 0.000 claims description 3
- 230000023556 desulfurization Effects 0.000 claims description 3
- 238000011084 recovery Methods 0.000 claims description 3
- 230000015572 biosynthetic process Effects 0.000 claims 1
- 239000002699 waste material Substances 0.000 abstract description 10
- 238000010521 absorption reaction Methods 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 230000000875 corresponding effect Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2219/00—Indexing scheme relating to application aspects of data processing equipment or methods
- G06F2219/10—Environmental application, e.g. waste reduction, pollution control, compliance with environmental legislation
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a feasibility assessment method for cross-regional consumption of clean energy, relates to the technical field of energy, and solves the technical problem that the cross-regional consumption feasibility of the clean energy cannot be comprehensively assessed to cause waste of the clean energynet(ii) a According to the comprehensive evaluation coefficient R and the annual average networking net economic benefit B of the regional consumption of the clean energynetAnd evaluating the feasibility of the regional consumption of the clean energy. The method is applied to evaluating the feasibility of the cross-regional consumption of the clean energy.
Description
Technical Field
The invention relates to the technical field of energy, in particular to a feasibility assessment method for cross-regional consumption of clean energy.
Background
At present, along with the aggravation of environmental pollution, more and more traditional fossil energy sources are replaced by clean energy sources such as wind energy, solar energy and the like, so that the power consumption requirements of people are met, and meanwhile, the pollution to the environment is reduced.
However, in many areas with large power consumption and concentrated grid load, the clean energy resources are relatively deficient and cannot meet the power consumption requirements of the local area, and meanwhile, in many areas with relatively small power consumption, the clean energy resources are relatively abundant, so that the local clean energy is difficult to be consumed, and the problem of local clean energy waste is further caused. In order to avoid the waste of clean energy and realize the optimal configuration of the clean energy, a comprehensive clean energy cross-region consumption scheme needs to be formulated. Therefore, there is a need for a method for evaluating the feasibility of cross-regional consumption of clean energy, which is used to comprehensively evaluate the feasibility of cross-regional consumption of clean energy, and provide technical support and guidance for new projects for cross-regional consumption of clean energy, so as to avoid waste of clean energy and achieve optimal configuration of clean energy.
Disclosure of Invention
The invention aims to provide a method for evaluating the feasibility of the trans-regional consumption of clean energy, which is used for comprehensively evaluating the feasibility of the trans-regional consumption of the clean energy so as to avoid the waste of the clean energy and realize the optimal configuration of the clean energy.
In order to achieve the purpose, the invention provides a feasibility evaluation method for the cross-regional consumption of clean energy, which adopts the following technical scheme:
the feasibility assessment method for the cross-regional consumption of the clean energy comprises the following steps:
acquiring a correlation coefficient r of wind power output characteristics of a sending end in the cross-regional consumption of the clean energy and load characteristics of a receiving end in the cross-regional consumption of the clean energy;
acquiring the power abandoning proportion of the clean energy at the sending end;
acquiring the capacity proportion eta of the clean energy accessed in a centralized manner in the sending end;
obtaining the power supply installation ratio of the peak regulation depth in the receiving end to be more than 50%;
obtaining a comprehensive evaluation coefficient R of the regional consumption of the clean energy according to the correlation coefficient R, the proportion of the electric quantity abandoned by the clean energy, the proportion η of the capacity of the clean energy accessed in a centralized manner and the proportion of the installed power supply with the peak regulation depth of more than 50 percent, wherein R is omega1×r+ω2×+ω3×η+ω4×, wherein ω is1Is a weight coefficient, ω, of the correlation coefficient r2A weight coefficient, omega, for the proportion of the clean energy curtailment3A weighting factor, ω, of the ratio η of the clean energy capacity for the centralized access4The weight coefficient is the power installation proportion of the peak regulation depth of more than 50 percent;
adding a connecting line between the sending end and the receiving end, and obtaining the theoretical outgoing required capacity C of the sending end through analog calculationout；
Delivering a required capacity C according to the theoryoutObtaining the total quantity E of the discarded electric quantity of the clean energy reduced in the sending endreduce；
According to the total quantity E of the discarded electric quantity of the clean energyreduceAnd said theoretical delivery demand capacity CoutObtaining the annual average networking net economic benefit B of the regional consumption of the clean energynet；
According to the comprehensive evaluation coefficient R and the annual average networking net economic benefit B of the regional consumption of the clean energynetAnd evaluating the feasibility of the regional consumption of the clean energy.
Compared with the prior art, the feasibility evaluation method for the cross-regional consumption of the clean energy provided by the invention has the following beneficial effects:
in the feasibility evaluation method for the trans-regional consumption of the clean energy provided by the invention, on one hand, a comprehensive evaluation coefficient R for the trans-regional consumption of the clean energy can be obtained through a correlation coefficient R between the wind power output characteristic of a sending end in a trans-regional consumption scheme of the clean energy and the load characteristic of a receiving end in the trans-regional consumption of the clean energy, the ratio of the electric quantity of the clean energy in the sending end, the capacity of the clean energy in centralized access η and the installed ratio of a power supply with the peak regulation depth of the receiving end of more than 50%, so that the feasibility of the trans-regional consumption scheme of the clean energy in the aspect of energy configuration can be comprehensively evaluated according to the comprehensive evaluation coefficient R, the waste of the clean energy is avoided, and on the other hand, the theoretical outgoing demand capacity C of the sending end is obtainedoutAnd reduced total amount of discarded clean energy EreduceThen, the required capacity C can be sent out through the theory of the sending endoutAnd reduced total amount of discarded clean energy EreduceObtaining the annual average net economic benefit B of the cross-regional consumption of the clean energynetTherefore, the feasibility of the clean energy cross-regional consumption scheme is further evaluated in the aspect of economy, guidance is provided for selecting the clean energy cross-regional consumption scheme, and the optimal configuration of the clean energy is realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is a flowchart of a feasibility assessment method for cross-regional consumption of clean energy according to an embodiment of the present invention.
Detailed Description
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, not all, embodiments of the present 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.
An embodiment of the present invention provides a feasibility assessment method for cross-regional consumption of clean energy, and specifically, as shown in fig. 1, the feasibility assessment method for cross-regional consumption of clean energy includes:
and step S1, obtaining a correlation coefficient r of the wind power output characteristic of the sending end in the cross-regional consumption of the clean energy and the load characteristic of the receiving end in the cross-regional consumption of the clean energy.
For example, the correlation coefficient r between the wind power output characteristic of the sending end and the load characteristic of the receiving end can be obtained by fitting the wind power output characteristic curve of the sending end and the load characteristic curve of the receiving end, and it should be noted that, for a specific method for obtaining the correlation coefficient r between the wind power output characteristic of the sending end and the load characteristic of the receiving end by fitting the wind power output characteristic curve of the sending end and the load characteristic curve of the receiving end, a person skilled in the art may refer to the existing method for obtaining the correlation coefficient by curve fitting, and details are not repeated here.
If the value of r is positive, the wind power output characteristic of the sending end is positively correlated with the load characteristic of the receiving end; if the value of r is negative, the wind power output characteristic of the sending end is inversely related to the load characteristic of the receiving end; if the absolute value of r is equal to 1, the wind power output characteristic of the sending end is completely related to the load characteristic of the receiving end; and if the value of r is zero, the correlation between the wind power output characteristic of the sending end and the load characteristic of the receiving end is zero.
When r is greater than 0 and less than 1, and the larger the value of r is, the better the correlation between the wind power at the sending end and the load at the receiving end is, the relatively smaller the influence on the peak load regulation at the receiving end is, and the method is more suitable for being used as the sending end for the cross-regional consumption of clean energy.
And step S2, obtaining the ratio of the clean energy electricity abandonment amount of the sending end.
When the ratio of the electric quantity discarded by the clean energy is larger, the sending end system has weaker capacity of consuming the clean energy, has larger delivery demand, and is more suitable to be used as a sending end for consuming the clean energy across areas.
And step S3, acquiring the clean energy capacity ratio eta of centralized access in the sending end.
It should be noted that "centralized access" in the embodiment of the present invention refers to: and the voltage class of more than 10kv is switched in.
When the value of the clean energy capacity ratio η of the centralized access is larger, it means that the access ratio of the large capacity of the transmitting end system is higher, and the transmitting end system is more suitable for consuming the clean energy across the region.
And step S4, acquiring the power supply installed ratio of the peak shaving depth in the receiving end above 50%.
When the value of the power supply installed proportion of the peak shaving depth of more than 50% is larger, the power supply with stronger peak shaving capacity of the receiving end is higher, and the receiving end is more suitable for receiving clean energy transmitted by the transmitting end.
Step S5, obtaining a comprehensive evaluation coefficient R of the trans-regional consumption of the clean energy according to the correlation coefficient R, the proportion coefficient of the electric quantity discarded by the clean energy, the proportion coefficient η of the capacity of the centrally accessed clean energy and the installed proportion of the power supply with the peak shaving depth of more than 50%, wherein R is omega1×r+ω2×+ω3×η+ω4×, wherein ω is1Is a weight coefficient, ω, of the correlation coefficient r2Weight coefficient, omega, of the proportion of the amount of electricity discarded for clean energy3Weight coefficient, ω, of ratio of clean energy capacity to η for centralized access4The weight coefficient of the power supply installed proportion with the peak regulation depth of more than 50 percent.
It is necessary to supplement that for ω mentioned above1、ω2、ω3And ω4The specific value of (a) can be set by a person skilled in the art according to actual needs, and the embodiment of the present invention is not limited.
Step S6, adding a connecting line between the sending end and the receiving end, and obtaining the theoretical outgoing required capacity C of the sending end through simulation calculationout。
Illustratively, a capacity C can be added between the sending end and the receiving end in the cross-regional consumption of the clean energylineThe connecting line of (1) first order ClineWhen the power is equal to zero, the water abandoning electric quantity, the wind abandoning electric quantity and the light abandoning electric quantity of the sending end are obtained through software simulation calculation, and then C is gradually increasedlineUntil the water-abandoning electric quantity, the wind-abandoning electric quantity and the light-abandoning electric quantity of the sending end are not reduced, the connecting line capacity C obtained at the momentlineI.e. the theoretical delivery required capacity C of the delivery endout。
Step S7, delivering the required capacity C according to theoryoutObtaining the total amount E of the discarded clean energy in the sending endreduce。
Step S8, according to the total quantity E of the discarded electric quantity of the reduced clean energyreduceAnd theoretical delivery demand capacity CoutAnd obtaining the annual average net economic benefit B of the regional consumption of clean energynet。
Step S9, according to the comprehensive evaluation coefficient R and the annual average networking net economic benefit B of the regional consumption of the clean energynetAnd evaluating the feasibility of the regional consumption of the clean energy.
In the technical solution of this embodiment, on the one hand, the wind power output characteristic of the sending end in the clean energy transregional consumption scheme and the load characteristic of the receiving end in the clean energy transregional consumption scheme are mutually matchedThe comprehensive evaluation coefficient R of the cross-regional consumption of the clean energy can be obtained according to the relation coefficient R, the ratio of the electric quantity of the clean energy abandoned at the transmitting end, the ratio η of the capacity of the centrally-accessed clean energy and the ratio of the installed power supply with the peak regulation depth of the receiving end of more than 50 percent, so that the feasibility of the cross-regional consumption scheme of the clean energy in the aspect of energy configuration can be comprehensively evaluated according to the comprehensive evaluation coefficient R, the waste of the clean energy is avoided, and on the other hand, the theoretical required delivery capacity C of the transmitting end is obtainedoutAnd reduced total amount of discarded clean energy EreduceThen, the required capacity C can be sent out through the theory of the sending endoutAnd reduced total amount of discarded clean energy EreduceObtaining the annual average net economic benefit B of the cross-regional consumption of the clean energynetTherefore, the feasibility of the clean energy cross-regional consumption scheme is further evaluated in the aspect of economy, guidance is provided for selecting the clean energy cross-regional consumption scheme, and the optimal configuration of the clean energy is realized.
Exemplarily, the specific step of obtaining the correlation coefficient r between the wind power output characteristic of the sending end in the clean energy transregional absorption and the load characteristic of the receiving end in the clean energy transregional absorption in step S1 includes:
step S11, acquiring a monthly characteristic correlation coefficient r of wind power output characteristic of the sending end and load characteristic of the receiving endmonth。
Specifically, the monthly characteristic correlation coefficient r of the wind power output characteristic of the sending end and the load characteristic of the receiving end can be obtained by fitting the historical wind power output monthly characteristic curve of the sending end and the load monthly characteristic curve of the receiving endmonth。
Step S12, obtaining the abundance typical day characteristic correlation coefficient r of the wind power output characteristic of the sending end and the load characteristic of the receiving endday-1。
Specifically, the wind power output characteristic of the sending end and the load characteristic of the receiving end can be obtained by fitting the historical wind power output characteristic curve of the sending end and the load characteristic curve of the receiving end in the rich periodCharacteristic correlation coefficient r of typical days of full seasonday-1。
Step S13, obtaining a correlation coefficient r of typical day characteristics of the dead time of wind power output characteristics of the sending end and load characteristics of the receiving endday-2。
Specifically, a typical day characteristic correlation coefficient r of the wind power output characteristic of the sending end and the load characteristic of the receiving end in the dry period can be obtained by fitting a typical day characteristic curve of the historical wind power output of the sending end in the dry period and a typical day characteristic curve of the load of the receiving end in the dry periodday-2。
Step S14, according to the month characteristic correlation coefficient rmonthTypical daily characteristic correlation coefficient r of abundanceday-1Correlation coefficient r with typical day characteristics of withering periodday-2Obtaining a correlation coefficient r, wherein r ═ rmonth+rday-1+rday-2。
For example, the specific step of obtaining the ratio of the power discarded by the clean energy at the sending end in step S2 includes:
step S21, obtaining the water-abandoning electric quantity proportion of the hydropower in the delivery endhydro，Wherein E ishydroAvailable electric quantity for water and electricity, Ehydro-abanThe electric quantity of the water is the electric quantity of the water abandoned by the hydropower.
Step S22, obtaining the wind curtailment electric quantity proportion of the wind power in the sending endwind，Wherein E iswindAvailable electricity for wind power, Ewind-abanThe electric quantity of the abandoned wind of the wind power is obtained.
Step S23, obtaining the photoelectric discarding light quantity proportion of the photoelectricity in the sending endsolar，Wherein E issolarIs photoelectricAvailable electric quantity of Esolar-abanIs the photoelectric discarding quantity of the photoelectricity.
Optionally, a year-round system operation simulation of 8760 hours of the planning year of the regional consumption of the clean energy can be performed through software, so that the available electric quantity E of the hydropower station can be obtainedhydroWater-electricity-discarding electric quantity E of water and electricityhydro-abanAvailable electric quantity E of wind powerwindWind power water-abandoning electric quantity Ewind-abanPhotoelectric available electric quantity EsolarAnd photoelectric discarding power Esolar-aban。
Step S24, according to the electric quantity proportion of the water discardhydroRatio of wind power to abandonedwindRatio of light to electricitysolarObtaining the proportion coefficient of the electric quantity discarded by the clean energy, whereinhydro+wind+solar。
For example, in step S3, the specific step of obtaining the clean energy capacity ratio η of the centralized access in the sending end includes:
step S31, capacity ratio η of hydropower station accessed in centralized mode in sending terminal is obtainedhydro，Wherein, Chydro-disCapacity of a centrally accessed hydroelectric power station, ChydroIs the total capacity of the hydropower station in the delivery end.
Step S32, capacity ratio η of centrally accessed wind power plant in sending end is obtainedwind，Wherein, Cwind-disCapacity of wind farms for centralized access, CwindIs the total capacity of the wind field at the delivery end.
Step S33, capacity ratio η of centrally accessed photovoltaic power station in sending end is obtainedsolar，Wherein, Csolar-disCapacity of photovoltaic power station for centralized access, CsolarIs the total capacity of the photovoltaic power station in the transmitting end.
Step S34, capacity ratio η according to hydropower station with centralized accesshydroCapacity ratio η of centralized access wind farmwindCapacity ratio η of photovoltaic power station with centralized accesssolarObtaining a clean energy capacity ratio η of centralized access, wherein η is ηhydro+ηwind+ηsolar。
Illustratively, in step S8, the total amount of electric energy discarded E according to the reduced clean energy is reducedreduceAnd theoretical delivery demand capacity CoutAnd obtaining the annual average net economic benefit B of the regional consumption of clean energynetThe method comprises the following specific steps:
step S81, according to the total quantity E of the discarded electric quantity of the reduced clean energyreduceAnd obtain the annual networking consumption reduction and emission reduction economic benefit B of the cross-regional consumption of clean energytotal。
Step S82, delivering the required capacity C according to theoryoutLine investment I for obtaining clean energy consumption in different areaslineMain transformer investment I absorbed by clean energy in cross-regiontrans。
Step S83, according to the line investment IlineAnd main transformation investment ItransTotal engineering investment I for obtaining clean energy consumption in different areastotalWherein, Itotal＝Iline+Itrans。
Step S84, according to the total project investment ItotalObtaining the annual value I of the engineering investment of the regional consumption of the clean energyyealy，Wherein Y is the years of the project investment recovery period of the regional consumption of the clean energy, mu is the project investment reduction rate of the regional consumption of the clean energy, and sigma istransTransformation operating cost ratio, sigma, for regional consumption of clean energylineLine operating cost ratios are taken over the area for clean energy.
Step S85, networking according to the year, reducing consumption and emission and economic benefit BtotalAnd the annual value of engineering investment IyealyTo obtain net economic benefit B of annual average networkingnetWherein B isnet＝Btotal-Iyealy。
Exemplarily, the annual networking consumption reduction and emission reduction economic benefit BtotalCan include coal consumption reduction annual economic benefit BcoalAnd the annual economic benefit of carbon dioxide emission reductionAnd the annual economic benefit of sulfur dioxide emission reduction
Specifically, in the step S81, the total amount of the discarded clean energy E is decreasedreduceAnd obtain the annual networking consumption reduction and emission reduction economic benefit B of the cross-regional consumption of clean energytotalThe method comprises the following specific steps:
step S811, according to the total quantity E of the discarded clean energyreduceObtaining coal consumption reduction annual economic benefit Bcoal，Bcoal＝α×Ereduce×PcoalWherein α is average power generation coal consumption of receiving end region of clean energy across region consumption, PcoalIs the unit coal price of the region where the receiving end is located.
Step S812, according to the reduced total quantity E of the discarded electric quantity of the clean energyreduceAnd obtain the annual economic benefit of carbon dioxide emission reductionWherein,the carbon content of the standard coal is shown as the carbon content,in order to obtain a high carbon dioxide generation rate,is the price per carbon dioxide emission.
Step S813, according to the reduced total quantity E of the discarded electric quantity of the clean energyreduceObtaining the annual economic benefit of sulfur dioxide emission reductionWherein,the sulfur content of the standard coal is shown as the standard coal sulfur content,is the generation rate of sulfur dioxide, chi is the desulfurization rate,is the unit sulfur dioxide emission price.
Step S814, according to coal consumption reduction annual economic benefit BcoalAnd the annual economic benefit of carbon dioxide emission reductionAnd the annual economic benefit of sulfur dioxide emission reductionObtain annual networking consumption reduction and emission reduction economic benefit BtotalWherein
illustratively, in the step S82, the required capacity C is delivered according to the theoryoutLine investment I for obtaining clean energy consumption in different areaslineThe detailed steps ofThe method comprises the following steps:
capacity according to theoretical delivery requirement CoutAnd obtaining the number N of channel loops required by the trans-regional consumption of the clean energy by combining the single-loop power transmission capacity of the power transmission line in the trans-regional consumption of the clean energy.
And acquiring the length L of the power transmission corridor in the cross-regional consumption of the clean energy.
For example, the length L of the power transmission corridor in the clean energy transregional absorption can be obtained by combining the geographical positions of the drop points of the transmitting end and the receiving end in the clean energy transregional absorption.
Obtaining line investment I according to the number N of channel loops and the length L of the power transmission corridorline，Iline＝Pline× L × N, wherein PlineThe cost of the transmission line per unit length is low.
Illustratively, in the step S82, the required capacity C is delivered according to the theoryoutAnd obtaining the main transformation investment I of the clean energy resource which is consumed in a cross-region waytransThe method comprises the following specific steps:
capacity according to theoretical delivery requirement CoutCapacity C of single main transformer in transformer engineering combined with clean energy transregional consumptiontransAnd obtaining the number M of the single-side main transformers required by the regional consumption of the clean energy.
According to the capacity C of a single main transformer in power transmission engineeringtransAnd the number M of the single-side main transformers to obtain the investment I of the main transformerstrans，Itrans＝Ptrans×2×M×CtransWherein P istransThe unit capacity cost of the power transformation project.
To facilitate understanding and implementation for those skilled in the art, the following embodiments of the present invention will provide specific application examples of evaluation of two clean energy trans-regional consumption schemes by using the feasibility evaluation method for clean energy trans-regional consumption.
Suppose that in the first clean energy transregional consumption scheme, the sending end A-1 has wind in 2020The electric total installed machine is 9000MW, wherein the installed capacity of the centrally-connected wind power is 6000MW, and the capacity ratio η of the centrally-connected wind power generation field can be obtainedwind66 percent, the total photovoltaic installation is 1500MW, wherein, the installed capacity of the centrally accessed photovoltaic is 1000MW, the capacity ratio η of the centrally accessed photovoltaic power station can be obtainedsolar66 percent of the total installed power of the hydropower station is 40000MW, wherein, the installed capacity of the centrally-accessed hydropower station is 30000MW, the capacity ratio of the centrally-accessed hydropower station is ηhydro75%, the ratio of the clean energy capacity of the centralized access in the first scheme is obtained η1Is 201%; the local load of the sending end A-1 is 35000 MW; the load of the receiving end B-1 is 120000MW, the receiving end B-1 has rich power supply types and strong peak regulation capability, and the peak regulation depth of the receiving end B-1 exceeds 50 percent of the installed ratio of the power supply1Is 50%.
Firstly, a correlation coefficient r of wind power output characteristics of a sending end A-1 and load characteristics of a receiving end B-1 is obtained1。
Specifically, the historical wind power output monthly characteristic curve of the sending end A-1 and the load monthly characteristic curve of the receiving end B-1 are fitted to obtain a monthly characteristic correlation coefficient r of the historical wind power output characteristic of the sending end A-1 and the load characteristic of the receiving end B-1month-1＝-0.84。
The characteristic curve of the historical wind power output rich period typical day of the sending end A-1 and the characteristic curve of the load rich period typical day of the receiving end B-1 are fitted to obtain the characteristic coefficient r of the correlation between the historical wind power output characteristic of the sending end A-1 and the rich period typical day characteristic of the load characteristic of the receiving end B-1day-11＝-0.6。
The characteristic curve of the typical day of the dead period of the historical wind power output of the sending end A-1 and the characteristic curve of the typical day of the load of the receiving end B-1 are fitted to obtain a correlation coefficient r of the typical day of the dead period of the historical wind power output characteristic of the sending end A-1 and the load characteristic of the receiving end B-1day-12＝-0.79。
In conclusion, the correlation coefficient r of the wind power output characteristic of the sending end A-1 and the load characteristic of the receiving end B-1 can be obtained1＝rmonth-1+rday-11+rday-12＝-2.23。
Then, the ratio of the water-to-electricity discard capacity of the water and electricity in the sending end A-1 was obtained by simulationhydro10 percent of the wind power and the wind power abandon power ratiowind15% of the photoelectric discarding light quantity ratiosolar13%, the ratio coefficient of the clean energy power discard in the sending end A-1 can be obtained1The content was 38%.
By comprehensively considering the characteristics of the transmitting terminal A-1 and the receiving terminal B-1, respectively taking omega1Is 15%, omega2Is 30%, omega330%, and ω4The content was 25%.
In conclusion, a comprehensive evaluation coefficient R of the first clean energy transregional consumption scheme can be obtained1，R1＝ω1×r1+ω2×1+ω3×η1+ω4×1＝0.525。
In the second clean energy transregional consumption scheme, the total installed wind power of the sending-end region a-2 in 2020 is 5000MW, wherein the installed wind power capacity of the centralized access is 3000MW, and the capacity occupation ratio of the centralized access wind power plant is ηwind60 percent, the total photovoltaic installation is 3000MW, wherein, the installed capacity of the centrally accessed photovoltaic is 1000MW, the capacity ratio η of the centrally accessed photovoltaic power station can be obtainedsolar33 percent, the total installed capacity of the hydropower station is 20000MW, wherein, the installed capacity of the centrally-accessed hydropower station is 10000MW, and the capacity ratio of the centrally-accessed hydropower station is ηhydro50%, the ratio of the clean energy capacity of the centralized access is η2Is 143%; the local load of area A-2 is 30000 MW; the load of the receiving end B-2 is 90000MW, but the receiving end B-2 has single power supply structure and weak peak regulation capability, and the installed ratio of the power supply with the peak regulation depth exceeding 50 percent2The content was 35%.
Firstly, a correlation coefficient r of wind power output characteristics of a sending end A-2 and load characteristics of a receiving end B-2 is obtained2。
Specifically, the historical wind power output monthly characteristic curve of the sending end A-2 and the load monthly characteristic curve of the receiving end B2 are fitted to obtain a monthly characteristic correlation coefficient r of the historical wind power output characteristic of the sending end A-2 and the load characteristic of the receiving end B-2month-2＝-0.56。
The characteristic curve of the historical wind power output rich period typical day of the sending end A-2 and the characteristic curve of the load rich period typical day of the receiving end B-2 are fitted to obtain a correlation coefficient r of the historical wind power output characteristic of the sending end A-2 and the rich period typical day characteristic of the load characteristic of the receiving end B-2day-21＝-0.75。
The characteristic curve of the typical day of the historical wind power output in the dry period of the sending end A-2 and the characteristic curve of the typical day of the load in the dry period of the receiving end B-2 are fitted to obtain a correlation coefficient r of the typical day of the dry period of the historical wind power output characteristic of the sending end A-2 and the load characteristic of the receiving end B-1day-22＝0.59。
In conclusion, the correlation coefficient r of the wind power output characteristic of the transmitting end A-2 and the load characteristic of the receiving end B-2 can be obtained2＝rmonth-2+rday-21+rday-22＝-0.72。
Then, the ratio of the water-to-electricity discard capacity of the hydropower in the sending end A-2 was obtained by simulationhydro5 percent of the wind power and the wind power abandon power ratiowindThe ratio of photoelectric waste to light is 6 percentsolarWhen the ratio is 8 percent, the proportion coefficient of the clean energy power abandonment in the transmitting end A-2 can be obtained2The content was 19%.
Similarly, by comprehensively considering the characteristics of the sending terminal A-2 and the receiving terminal B-2, respectively taking omega1Is 15%, omega2Is 30%, omega330%, and ω4The content was 25%.
In conclusion, a comprehensive evaluation coefficient R of the second clean energy transregional consumption scheme can be obtained2，R2＝ω1×r2+ω2×2+ω3×η2+ω4×2＝0.465。
By comprehensively evaluating the coefficient R of the first clean energy cross-regional consumption scheme1Comprehensive evaluation coefficient R of cross-regional consumption scheme of second clean energy2Compared with the prior art, the comprehensive evaluation coefficient of the first clean energy transregional consumption scheme is higher, the transmitting end A-1 and the receiving end B-1 are more suitable for performing the clean energy transregional consumption, and the feasibility of the first clean energy transregional consumption scheme in the aspect of energy configuration is higher.
The first clean energy cross-regional consumption scenario was further evaluated economically for feasibility as follows.
Illustratively, the water abandon proportion, the wind abandon proportion and the light abandon proportion of the sending end A-1 and the corresponding connecting line capacity C between the sending end A1 and the receiving end B-1 can be obtained by using GOPT software simulationlineSpecifically, as shown in table 1, the link capacity C between the transmitting terminal a1 and the receiving terminal B-1lineAt 9000MW, the water abandoning ratio, wind abandoning ratio and light abandoning ratio of the sending end A-1 are not reduced, and the connecting line capacity C between the sending end A1 and the receiving end B-1lineThe value of (A) is the theoretical outgoing required capacity C of the sending end A1outI.e. Cout＝9000MW。
TABLE 1 water abandon proportion, wind abandon proportion, light abandon proportion of sending end A-1 and corresponding sending end A1 and receiving end
Junctor capacity C between terminals B-1lineValue of (A)
| 0MW | 3000MW | 5000MW | 7000MW | 9000MW | 11000MW | |
| Water reject ratio | 10％ | 5％ | 3％ | 1％ | 1％ | 1％ |
| Air abandon ratio | 15％ | 10％ | 8％ | 6％ | 2％ | 2％ |
| Waste light ratio | 13％ | 11％ | 9％ | 6％ | 3％ | 3％ |
According to the theoretical delivery required capacity C of the delivery end A1outThe total quantity E of the electric quantity abandoned by the clean energy reduced by the sending end A1 in the cross-regional consumption scheme of the clean energy can be obtainedreduce1860 hundred million kilowatt-hours.
Firstly, the meterCalculating the annual value I of the engineering investment of the regional consumption of the clean energyyealy。
Specifically, the length L of a power transmission corridor between a transmitting end A-1 and a receiving end B-1 is 1600km, the number N of channel loops of a power transmission line is 3, and the unit length manufacturing cost P of the power transmission linelineCapacity C of single main transformer of 370 ten thousand yuan/kilometer power transformation engineeringtrans5000MW, the number M of single-side main transformers is 2, and the unit capacity cost P of the power transformation projecttrans640 yuan/kilowatt, the years Y of the engineering investment recovery period of the regional consumption of the clean energy is 25 years, the reduction rate mu of the engineering investment is 8 percent, and the operation cost ratio sigma of the power transformation istrans2.5%, line running cost ratio σlineIs 2%, then:
(1) line investment I of the clean energy cross-regional consumption schemelineComprises the following steps:
Iline＝Pline× L × N (370L 370 × 1600 × 3 (1776000 in ten thousand yuan).
(2) Main transformer investment I of the clean energy cross-region consumption schemetransComprises the following steps:
Itrans＝Ptrans×2×M×Ctrans640 × 5000 × 2 ÷ 10 ÷ 640000 (ten thousand yuan).
(3) Engineering total investment I of the clean energy cross-regional consumption schemetotalComprises the following steps:
Itotal＝Iline+Itrans1776000+640000 2416000 (ten thousand yuan).
(4) The annual value I of engineering investment of the clean energy transregional consumption schemeyealyComprises the following steps:
then, calculating annual networking consumption reduction and emission reduction economic benefit B of the cross-regional consumption of the clean energytotal。
Specifically, the annual networking consumption reduction and emission reduction economic benefit BtotalCan include coal consumption reduction annual economic benefit BcoalAnd the annual economic benefit of carbon dioxide emission reductionAnd the annual economic benefit of sulfur dioxide emission reduction
Price per coal P in receiving end B-1 regioncoal600 yuan/ton, power generation coal consumption α of 0.325 kg/kilowatt hour, standard coal carbon content0.725, carbon dioxide generation rate3.67, price per carbon dioxide emission32 yuan/ton, standard coal sulfur content0.012, the sulfur dioxide generation rate1.6, desulfurization rate χ of 0.96, unit sulfur dioxide emission priceIs 1200 yuan/ton. Then:
(1) coal consumption reduction annual economic benefit BcoalComprises the following steps:
Bcoal＝α×Ereduce×Pcoal361140 (ten thousand yuan).
(2) Carbon dioxide emission reduction annual channelEconomic benefitComprises the following steps:
(3) annual economic benefit of sulfur dioxide emission reductionComprises the following steps:
(4) annual networking consumption reduction and emission reduction economic benefit BtotalComprises the following steps:
finally, the economic benefits B of consumption reduction and emission reduction can be networked according to the yeartotalAnd the annual value of engineering investment IyealyObtaining the net economic benefit B of the annual average networking of the first clean energy consumed across areasnet＝Btotal-Iyealy122350 (ten thousand yuan).
Therefore, the clean energy transregional consumption scheme with the A-1 as the sending end and the B-1 as the receiving end has high feasibility in the aspect of energy configuration, can avoid the waste of clean energy, has high economic benefit and high feasibility in the aspect of economy, and can realize the optimal configuration of the clean energy.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (9)
1. A feasibility assessment method for clean energy trans-regional consumption is characterized by comprising the following steps:
acquiring a correlation coefficient r of wind power output characteristics of a sending end in the cross-regional consumption of the clean energy and load characteristics of a receiving end in the cross-regional consumption of the clean energy;
acquiring the power abandoning proportion of the clean energy at the sending end;
acquiring the capacity proportion eta of the clean energy accessed in a centralized manner in the sending end;
obtaining the power supply installation ratio of the peak regulation depth in the receiving end to be more than 50%;
obtaining a comprehensive evaluation coefficient R of the regional consumption of the clean energy according to the correlation coefficient R, the proportion of the electric quantity abandoned by the clean energy, the proportion η of the capacity of the clean energy accessed in a centralized manner and the proportion of the installed power supply with the peak regulation depth of more than 50 percent, wherein R is omega1×r+ω2×+ω3×η+ω4×, wherein ω is1Is a weight coefficient, ω, of the correlation coefficient r2A weight coefficient, omega, for the proportion of the clean energy curtailment3A weighting factor, ω, of the ratio η of the clean energy capacity for the centralized access4The weight coefficient is the power installation proportion of the peak regulation depth of more than 50 percent;
adding a connecting line between the sending end and the receiving end, and obtaining the theoretical outgoing required capacity C of the sending end through analog calculationout；
Delivering a required capacity C according to the theoryoutObtaining the total quantity E of the discarded electric quantity of the clean energy reduced in the sending endreduce；
According to the total quantity E of the discarded electric quantity of the clean energyreduceAnd said theoretical delivery demand capacity CoutObtaining the annual average networking net economic benefit B of the regional consumption of the clean energynet；
According to the comprehensive evaluation coefficient R and the annual average networking net economic benefit B of the regional consumption of the clean energynetAnd evaluating the feasibility of the regional consumption of the clean energy.
2. The feasibility assessment method for the trans-regional consumption of clean energy according to claim 1, wherein the specific step of obtaining the correlation coefficient r between the wind power output characteristic of the sending end in the trans-regional consumption of clean energy and the load characteristic of the receiving end in the trans-regional consumption of clean energy comprises:
acquiring a monthly characteristic correlation coefficient r of the wind power output characteristic of the sending end and the load characteristic of the receiving endmonth；
Acquiring the wind power output characteristic of the sending end and the load characteristic of the receiving endCharacteristic correlation coefficient r of typical days of full seasonday-1；
Obtaining a correlation coefficient r of typical day characteristics in the dry period of the wind power output characteristics of the sending end and the load characteristics of the receiving endday-2；
According to the month characteristic correlation coefficient rmonthThe correlation coefficient r of typical daily characteristics of the abundance periodday-1And the correlation coefficient r of typical daily characteristics of the withering periodday-2Obtaining the correlation coefficient r, wherein r ═ rmonth+rday-1+rday-2。
3. The feasibility assessment method of clean energy trans-regional consumption according to claim 1, wherein the specific step of obtaining the ratio of the clean energy electricity discard amount of the sending end comprises:
obtaining the power consumption proportion of the water and electricity in the delivery endhydro，Wherein E ishydroTo the available electric quantity of said water and electricity, Ehydro-abanThe water-abandoning electric quantity of the hydropower station is obtained;
obtaining the wind power abandoning electric quantity proportion of the wind power in the sending endwind，Wherein E iswindFor the available electric quantity of the wind power, Ewind-abanThe abandoned wind electric quantity of the wind power is obtained;
obtaining the photoelectric light abandoning electric quantity proportion of the photoelectric in the sending endsolar，Wherein E issolarIs the amount of electricity available to the photoelectricity, Esolar-abanThe photoelectric discarding power of the photoelectricity is obtained;
according to the electric quantity proportion of the abandoned waterhydroThe ratio of the wind power to the abandoned wind powerwindAnd the ratio of the light abandoning electric quantitysolarObtainingThe ratio of the electric quantity discarded by the clean energy is equal tohydro+wind+solar。
4. The method for assessing feasibility of clean energy consumption across a region according to claim 1, wherein the step of obtaining the clean energy capacity fraction η of the centralized access in the sending end comprises:
obtaining capacity ratio of hydropower station accessed in centralized mode in sending endηhydro，Wherein, Chydro-disCapacity of said centrally accessed hydroelectric power station, ChydroIs the total capacity of the hydropower station;
obtaining the capacity ratio of the wind power station accessed in the centralized way in the sending terminalηwind，Wherein, Cwind-disCapacity of said centrally accessed wind farm, CwindIs the total capacity of the wind farm;
η capacity ratio of the centrally accessed photovoltaic power station in the sending terminal is obtainedsolar，Wherein, Csolar-disCapacity of the centrally accessed photovoltaic plant, CsolarIs the total capacity of the photovoltaic power plant;
η according to capacity ratio of the centrally accessed hydropower stationhydroCapacity fraction η of the centrally accessed wind farmwindAnd capacity ratio η of the centrally connected photovoltaic power plantsolarObtaining a clean energy capacity ratio η of the centralized access, wherein η is ηhydro+ηwind+ηsolar。
5. According to claim1 the feasibility assessment method for the trans-regional consumption of clean energy, characterized in that the total quantity E of the discarded electric energy of the clean energy is reducedreduceAnd said theoretical delivery demand capacity CoutObtaining the annual average networking net economic benefit B of the regional consumption of the clean energynetThe method comprises the following specific steps:
according to the total quantity E of the discarded electric quantity of the clean energyreduceObtaining the annual networking consumption reduction and emission reduction economic benefit B of the cross-regional consumption of the clean energytotal；
Delivering a required capacity C according to the theoryoutObtaining line investment I of said clean energy consumption across arealineAnd main transformer investment I of the regional consumption of the clean energytrans；
According to the line investment IlineAnd the main transformation investment ItransObtaining total engineering investment I of the regional consumption of the clean energytotalWherein, Itotal＝Iline+Itrans；
According to the total investment I of the projecttotalObtaining the equivalent annual value I of the engineering investment of the regional consumption of the clean energyyealy，Wherein Y is the years of the project investment recovery period of the regional consumption of the clean energy, mu is the project investment reduction rate of the regional consumption of the clean energy, and sigma istransTransformation operating cost ratio, σ, for regional consumption of said clean energylineA line operating cost ratio for the clean energy cross-regional budget;
according to the annual networking consumption reduction and emission reduction economic benefit BtotalAnd said engineering investment equal annual value IyealyObtaining said annual average net economic benefit BnetWherein B isnet＝Btotal-Iyealy。
6. Feasibility assessment of clean energy trans-regional consumption according to claim 5The estimation method is characterized in that the annual networking consumption reduction and emission reduction economic benefit BtotalIncluding coal consumption reduction annual economic benefit BcoalAnd the annual economic benefit of carbon dioxide emission reductionAnd the annual economic benefit of sulfur dioxide emission reduction
7. The method of claim 6, wherein the total amount of energy rejected from clean energy E is based on the total amount of energy rejected from clean energy EreduceObtaining the annual networking consumption reduction and emission reduction economic benefit B of the cross-regional consumption of the clean energytotalThe method comprises the following specific steps:
according to the total quantity E of the discarded electric quantity of the clean energyreduceObtaining the coal consumption reduction annual economic benefit Bcoal，Bcoal＝α×Ereduce×PcoalWherein α is the average power generation coal consumption of the receiving end region of the cross-regional consumption of the clean energy, PcoalThe unit coal price of the region where the receiving end is located;
according to the total quantity E of the discarded electric quantity of the clean energyreduceObtaining the annual economic benefit of carbon dioxide emission reduction Wherein,the carbon content of the standard coal is shown as the carbon content,as the rate of carbon dioxide formation，Is the carbon dioxide emission price per unit;
according to the total quantity E of the discarded electric quantity of the clean energyreduceObtaining the annual economic benefit of sulfur dioxide emission reduction Wherein,the sulfur content of the standard coal is shown as the standard coal sulfur content,in order to obtain the sulfur dioxide generation rate,χin order to obtain the desulfurization rate,is the unit sulfur dioxide emission price;
according to the coal consumption reduction annual economic benefit BcoalThe annual economic benefit of carbon dioxide emission reductionAnd the annual economic benefit of sulfur dioxide emission reductionObtaining the annual networking consumption reduction and emission reduction economic benefit BtotalWherein
8. the feasibility assessment method of clean energy trans-regional consumption according to claim 5,characterized in that the capacity C required for delivery is determined according to said theoryoutObtaining line investment I of said clean energy consumption across arealineThe method comprises the following specific steps:
delivering a required capacity C according to the theoryoutObtaining the number N of channel loops required by the trans-regional consumption of the clean energy by combining the single-loop power transmission capacity of the power transmission line in the trans-regional consumption of the clean energy;
acquiring the length L of a power transmission corridor in the regional consumption of the clean energy;
obtaining the line investment I according to the number N of the channel loops and the length L of the power transmission corridorline，Iline＝Pline× L × N, wherein PlineThe cost of the transmission line per unit length is reduced.
9. A feasibility assessment method of clean energy trans-regional consumption according to claim 5, characterized in that it is based on said theoretical delivery demand capacity CoutObtaining the main transformation investment I of the regional consumption of the clean energytransThe method comprises the following specific steps:
delivering a required capacity C according to the theoryoutCombining the capacity C of a single main transformer of the transformer engineering in the regional consumption of the clean energytransObtaining the number M of single-side main transformers required by the regional consumption of the clean energy;
according to the capacity C of a single main transformer in the power transmission projecttransAnd the number M of the single-side main transformers to obtain the investment I of the main transformerstrans，Itrans＝Ptrans×2×M×CtransWherein P istransThe unit capacity cost of the power transformation project.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610943204.8A CN106372448A (en) | 2016-11-01 | 2016-11-01 | Feasibility assessment method for cross-regional consumption of clean energy |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610943204.8A CN106372448A (en) | 2016-11-01 | 2016-11-01 | Feasibility assessment method for cross-regional consumption of clean energy |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106372448A true CN106372448A (en) | 2017-02-01 |
Family
ID=57894421
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610943204.8A Pending CN106372448A (en) | 2016-11-01 | 2016-11-01 | Feasibility assessment method for cross-regional consumption of clean energy |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106372448A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107256436A (en) * | 2017-05-05 | 2017-10-17 | 国家电网公司 | The prediction and matching and control method of dissolving of thermal storage electric boiler and clean energy resource |
| CN108764728A (en) * | 2018-05-29 | 2018-11-06 | 云南电网有限责任公司 | A kind of clean energy resource sends assessment and methods of comparison and selection and the device of scheme outside |
| CN110350521A (en) * | 2019-07-09 | 2019-10-18 | 国网江苏省电力有限公司经济技术研究院 | A kind of the receiving end Network congestion prediction technique and device of the transregional interaction consumption of high proportion renewable energy |
| CN114372650A (en) * | 2020-10-15 | 2022-04-19 | 中国南方电网有限责任公司 | Feasibility assessment method for cross-regional consumption of clean energy |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102013701A (en) * | 2010-12-06 | 2011-04-13 | 青海电力科学试验研究院 | Method for calculating photovoltaic power generation accepting capability of power grid of high-altitude region |
| CN105305435A (en) * | 2015-11-13 | 2016-02-03 | 国网江西省电力科学研究院 | Carbon reduction quantity calculation method of regional power |
| CN105807633A (en) * | 2016-05-10 | 2016-07-27 | 大连理工大学 | Thermoelectric combined system scheduling method for achieving wind power absorption based on energy storage of centralized heat supply pipe network and buildings |
-
2016
- 2016-11-01 CN CN201610943204.8A patent/CN106372448A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102013701A (en) * | 2010-12-06 | 2011-04-13 | 青海电力科学试验研究院 | Method for calculating photovoltaic power generation accepting capability of power grid of high-altitude region |
| CN105305435A (en) * | 2015-11-13 | 2016-02-03 | 国网江西省电力科学研究院 | Carbon reduction quantity calculation method of regional power |
| CN105807633A (en) * | 2016-05-10 | 2016-07-27 | 大连理工大学 | Thermoelectric combined system scheduling method for achieving wind power absorption based on energy storage of centralized heat supply pipe network and buildings |
Non-Patent Citations (7)
| Title |
|---|
| DONGHUI ZHANG等: "A Study on HVDC User-Defined Modeling in PSS/E", 《PREPRINTS OF THE 5TH INTERNATIONAL CONFERENCE ON ELECTRIC UTILITY DEREGULATION AND RESTRUCTURING AND POWER TECHNOLOGIES》 * |
| LIU HAI-BO等: "The Synergistic Scheduling Optimization Model for Wind Power and Thermal Power with Energy Storage System Under the Carbon Emission Trade", 《THE OPEN FUELS & ENERGY SCIENCE JOURNAL》 * |
| 刘畅: "风电消纳能力分析方法的研究", 《电力系统保护与控制》 * |
| 刘聪等: "高载能负荷参与的电网消纳风/光电能力定量预评估方法", 《电网技术》 * |
| 卢斯煜等: "南方电网"西电东送"特性对送受端电网新能源消纳能力影响分析", 《电力建设》 * |
| 张运洲等: ""三北"地区风电开发、输送及消纳研究", 《中国电力》 * |
| 汪宁渤等: "酒泉风电跨区消纳模式及其外送方案", 《电力系统自动化》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107256436A (en) * | 2017-05-05 | 2017-10-17 | 国家电网公司 | The prediction and matching and control method of dissolving of thermal storage electric boiler and clean energy resource |
| CN107256436B (en) * | 2017-05-05 | 2022-07-22 | 国家电网公司 | Predictive matching and consumption control method for heat storage electric boiler and clean energy |
| CN108764728A (en) * | 2018-05-29 | 2018-11-06 | 云南电网有限责任公司 | A kind of clean energy resource sends assessment and methods of comparison and selection and the device of scheme outside |
| CN110350521A (en) * | 2019-07-09 | 2019-10-18 | 国网江苏省电力有限公司经济技术研究院 | A kind of the receiving end Network congestion prediction technique and device of the transregional interaction consumption of high proportion renewable energy |
| CN114372650A (en) * | 2020-10-15 | 2022-04-19 | 中国南方电网有限责任公司 | Feasibility assessment method for cross-regional consumption of clean energy |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Amutha et al. | Techno-economic evaluation of various hybrid power systems for rural telecom | |
| CN107634518B (en) | Source-network-load coordinated active power distribution network economic dispatching method | |
| Schaber et al. | Managing temporary oversupply from renewables efficiently: Electricity storage versus energy sector coupling in germany | |
| Ali et al. | Impact of high penetration level of grid-connected photovoltaic systems on the UK low voltage distribution network | |
| Zhu et al. | Renewable energy consumption technology under energy internet environment | |
| CN106372448A (en) | Feasibility assessment method for cross-regional consumption of clean energy | |
| Liu et al. | Impacts of distributed renewable energy generations on smart grid operation and dispatch | |
| CN102904289A (en) | Island new energy system optimal capacity allocation method based on drosophila optimization algorithm | |
| Li et al. | Modeling and multi-objective optimization of a stand-alone photovoltaic-wind turbine-hydrogen-battery hybrid energy system based on hysteresis band | |
| Martínez et al. | Wind Power Curtailment Analysis under generation flexibility requirements: The Spanish case study | |
| Dellosa | Potential Effect and Analysis of High Residential Solar Photovoltaic (PV) Systems Penetration to an Electric Distribution Utility (DU). | |
| CN112053255B (en) | CART pruning algorithm-based power grid energy component decomposition and energy tracing method | |
| Nehrir et al. | Impact of wind power distributed generation on distribution systems | |
| CN212627177U (en) | Hydrogen production and energy storage system for offshore wind power energy base | |
| Schwarz et al. | Integration of renewable energies, flexible loads and storages into the German power grid: Actual situation in German change of power system | |
| CN109861272B (en) | Multi-voltage-level power grid distributed power supply optimal configuration method considering electric quantity delivery | |
| Oladeji et al. | Electrical load survey and forecast for a decentralized hybrid power system at Elebu, Kwara State, Nigeria | |
| Vitale | Renewable energies–Future perspectives | |
| Sakagami et al. | Performance of a DC-based microgrid system in Okinawa | |
| Khalid et al. | Optimal hybrid wind-solar system for matching renewable power generation with demand | |
| CN113962827A (en) | Power transmission network double-layer extension planning method based on clear results of main and auxiliary energy markets | |
| CN104065073B (en) | Electric power system | |
| Pazheri et al. | Global renewable electricity potential | |
| Ali et al. | Using electric vehicles to mitigate imbalance requirements associated with high penetration level of grid-connected photovoltaic systems | |
| CN105990845A (en) | Direct-current power curve determination method of delivery system of wind-power base |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170201 |
|
| RJ01 | Rejection of invention patent application after publication |