CN116418020A - Energy storage configuration method for improving new energy consumption capability of provincial area - Google Patents
Energy storage configuration method for improving new energy consumption capability of provincial area Download PDFInfo
- Publication number
- CN116418020A CN116418020A CN202310424922.4A CN202310424922A CN116418020A CN 116418020 A CN116418020 A CN 116418020A CN 202310424922 A CN202310424922 A CN 202310424922A CN 116418020 A CN116418020 A CN 116418020A
- Authority
- CN
- China
- Prior art keywords
- energy storage
- power
- new energy
- energy
- load
- 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
- 238000004146 energy storage Methods 0.000 title claims abstract description 157
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000005265 energy consumption Methods 0.000 title claims description 32
- 238000010206 sensitivity analysis Methods 0.000 claims abstract description 18
- 238000009434 installation Methods 0.000 claims abstract description 13
- 230000000903 blocking effect Effects 0.000 claims abstract description 10
- 238000011156 evaluation Methods 0.000 claims abstract description 10
- 238000004364 calculation method Methods 0.000 claims description 25
- 230000005611 electricity Effects 0.000 claims description 18
- 230000009194 climbing Effects 0.000 claims description 11
- 238000010248 power generation Methods 0.000 claims description 10
- 238000004088 simulation Methods 0.000 claims description 9
- 238000012937 correction Methods 0.000 claims description 7
- 230000035945 sensitivity Effects 0.000 claims description 5
- 239000000446 fuel Substances 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 claims description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 18
- 230000000694 effects Effects 0.000 description 13
- 230000035699 permeability Effects 0.000 description 6
- 239000002699 waste material Substances 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 4
- 235000017399 Caesalpinia tinctoria Nutrition 0.000 description 3
- 241000388430 Tara Species 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 239000012267 brine Substances 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 230000003749 cleanliness Effects 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000003631 expected effect Effects 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- XOFYZVNMUHMLCC-ZPOLXVRWSA-N prednisone Chemical compound O=C1C=C[C@]2(C)[C@H]3C(=O)C[C@](C)([C@@](CC4)(O)C(=O)CO)[C@@H]4[C@@H]3CCC2=C1 XOFYZVNMUHMLCC-ZPOLXVRWSA-N 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- HPALAKNZSZLMCH-UHFFFAOYSA-M sodium;chloride;hydrate Chemical compound O.[Na+].[Cl-] HPALAKNZSZLMCH-UHFFFAOYSA-M 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
Images
Classifications
-
- 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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
-
- 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]
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention relates to an energy storage configuration method for improving the energy storage capacity of a provincial area, which comprises the steps of researching and judging main factors influencing the energy storage of the provincial area, establishing a new energy storage model considering the constraint of peak regulation capacity, combining factors such as the blocking power rejection rate of a section, the peak regulation power rejection rate and the like, establishing an energy storage capacity configuration model and evaluation indexes for improving the energy storage capacity of the provincial area so as to analyze the influence on a power grid after energy storage is added, and performing sensitivity analysis between the factors and the energy storage capacity configuration by combining the factors such as the utilization rate of the new energy, the hydrology year, the installation ratio of the new energy and the like; the invention comprehensively considers the factors such as new energy characteristics, provincial load, peak regulation resources, inter-provincial tie line peak regulation mutual aid capability, direct current external delivery capability and the like, and uses new energy data in Qinghai region for demonstration, and the result shows the effectiveness and stability of the method.
Description
Technical Field
The invention belongs to the technical field of energy storage, and particularly relates to an energy storage configuration method for improving the new energy consumption capability of a provincial domain.
Background
In recent years, the contradiction of water, wind and light discarding is prominent due to the restriction of the uncoordinated network source planning, insufficient cross-region conveying channel and peak regulation capacity, unhealthy marketing mechanism and the like. In the future, under the driving of double 50% targets, with the continuous increase of the installed scale of new energy, part of conventional power supplies are replaced by renewable energy, the system flexibility is insufficient in adjusting capacity, and the intermittent and anti-peak shaving properties of the new energy lead to the problems of system peak shaving and energy consumption of a future power system.
The energy storage can utilize the characteristics of peak clipping and valley filling, smoothing the fluctuation of new energy output, improving the average utilization rate of a power transmission channel, providing flexible peak regulation capacity, realizing the cooperative regulation and control of new energy power and thermoelectric power, and the like, and has great effects on improving the operation efficiency of a power system, improving the energy structure and reducing the carbon emission. The energy storage system has extremely high response speed and is particularly suitable for participating in power grid frequency modulation. The energy storage such as pumped storage, compressed air and the like has large-scale energy throughput capacity and is suitable for power grid peak shaving. The energy storage can participate in various links of the power system, such as power generation, power transmission, power distribution and power utilization sides, has quick adjustment capability, and can provide 2-4 times of adjustment depth compared with a conventional unit with the same capacity; the power in the 4 quadrants can be provided, and the power supply is a good power quality regulating power supply. Therefore, in the research of power grid work, it is necessary to find an energy storage configuration for improving the new energy consumption capability of the provincial area.
Disclosure of Invention
According to the energy storage capacity configuration method, the energy storage capacity is configured by comprehensively considering the factors such as the new energy utilization rate, the new energy characteristics, the power saving load, the peak regulation resources and the like, so that the peak regulation and frequency regulation requirements of a power grid can be met, and the new energy consumption level in the power saving area is further improved; the invention discloses an energy storage configuration method for improving the new energy consumption capability of a provincial domain, which comprises the following steps:
step one, researching and judging main factors influencing new energy consumption in provincial areas;
step two, a new energy consumption model considering peak regulation capacity constraint is established;
step three, combining factors such as a section blocking power rejection rate, a peak shaving power rejection rate and the like, and establishing an energy storage capacity configuration model and an evaluation index for improving the new energy consumption capacity of the provincial area so as to analyze the influence on a power grid after energy storage is added;
and fourthly, combining the factors such as the new energy utilization rate, hydrologic year, new energy installation ratio and the like, and carrying out sensitivity analysis between the factors and the energy storage capacity configuration.
Further, the first step includes the following procedures:
determining an evaluation level year, extracting a load curve and a power supply structure of each day of the year, and analyzing by peak regulation capacity to obtain a space value of a new energy generator set accepted by a power grid of each time period of each day;
simulating new energy power output curves of each day, comparing new energy power space values accepted by the power grid of each time period of each day with the new energy power output curves to obtain power discarding power of each time period of each day, forming a annual power discarding power timing curve, and counting annual power discarding data;
taking planned overhaul, load reserve and accident reserve of each power station in the power system as constraint conditions, simulating the operation mode and power generation curve of each power station in 365 days of the power system all the year round, analyzing the consumption capability of new energy based on a peak regulation level, and analyzing the consumption capability of the power system under minute-level new energy power fluctuation in an hour time scale; dividing the annual generator set combination into four quarter set combination models, and marking seasons with strong output of the traditional generator set;
the unit maintenance plan is obtained through an equal reliability principle, and the method comprises the following steps:
(1) Taking 4 hours as intervals throughout the day, and solving a monthly unit combination plan, wherein the average month is 180 time nodes;
(2) According to the monthly unit combination plan, the problem of insufficient renewable energy utilization caused by insufficient unit peak regulation capacity under the time scales of 30 minutes, 15 minutes and 5 minutes due to fluctuation of renewable energy is analyzed.
Further, the second step includes the following procedures:
(1) Establishing a unit combination calculation model:
and preparing a power supply overhaul plan based on an equal risk method, and constructing a unit combination calculation model based on the minimum total running cost as a target, wherein the unit combination calculation model is expressed as a formula 1:
wherein: alpha j ,β j ,γ j Respectively fuel cost coefficient, S t Gj For starting up the machine, U t Gj For the unit voltage, P t Gj For the active power of the unit, D t Gj Is the shutdown cost;
wherein S is t Gj By comparing T using a two-state model t Gj,off Determining whether to start the unit by cold start or hot start with the minimum cold start time limit, S t Gj Expressed as formula 2:
wherein: c cj ,c hj The cold and hot start-up cost of the unit j is respectively;
minimum downtime limit for unit j;
the cold start time of the unit; t (T) t Gj,off For continuous downtime;
constraint conditions of the unit combination calculation model comprise constraints such as electric power and electricity balance, upper and lower unit output limits, rotation standby, minimum unit starting and stopping time, unit climbing and the like;
(2) Establishing a new energy power-off proportion calculation model of peak regulation constraint:
calculating to obtain annual unit combination, and further calculating to obtain sigma P gmin ；∑P gmin The minimum output of the conventional power supply is the minimum output of the conventional power supply at every moment in the whole year;
the payload is defined, expressed as equation 3:
load net ＝load o +load s -P PV -P wind (equation 3)
Wherein: load net Load as payload o Load is the original load curve s For system outgoing power, P wind For wind power output, P PV Is photovoltaic output;
an hour-by-hour payload curve is obtained, and at this time Σp gmin A comparison is made in which:
1) When no energy is stored, a specific calculation flow is shown in fig. 2:
if load net ＞∑P gmin The machine set climbing is not out of limit, so that renewable energy sources can be completely consumed, and no wind and light are abandoned;
if load net ＜∑P gmin And the machine set climbs without out-of-limit, the renewable energy source is abandoned to be Sigma P gmin -load net ；
On a small time scaleIn the method, renewable energy source fluctuation is larger, the unit climbing rate is limited, when the equivalent load fluctuation rate is larger than the unit out-of-limit, and the climbing limit value of all the units is marked as P', the newly added abandoned wind and abandoned light quantity is
2) When stored energy is contained, based on fig. 3, the correction method is as follows:
using stored energy e=l 2 Delta E corrects the net load curve to obtain the comprehensive net load of the system at the t period on the d day;
let d-th day payload curve low valley value P min,d Applying the stored energy E to r time periods near the trough, r taking the empirical value, as shown in the shaded portion of FIG. 3, the trough of the payload is then taken from P min,d To P min′d Thereby reducing peak-to-valley differences for the daily net load;
according to the principle that the capacity of stored energy is equal to the area of a shadow part, the corrected net load low valley value is expressed as a formula 4:
wherein: Δt is the time interval, 15min; p (P) netload,d,t1 A payload value that is a period of time near the trough; l (L) 2 Δe represents the capacity of energy storage in the current scenario;
using the net load curve after the energy storage correction, called the integrated net load curve P comload,d,t 。
Further, the third step includes the following steps:
(1) After the section blockage is configured on the energy storage, substituting the energy storage into PEBL software for time sequence simulation;
(2) Obtaining the section blocking power rejection rate and the peak shaving power rejection rate, if the power rejection rate sum is less than 5%, no energy storage is needed to be configured, and the energy storage configuration scale is output; otherwise, further analyzing the peak-to-peak power-off curve;
(3) Analyzing peak shaving and power discarding curves of different areas, configuring energy storage for 5% of target with total power discarding rate, searching suitable energy storage configuration combination, and traversing all areas;
(4) And (3) re-distributing the peak regulation energy storage and the section energy storage configured in all areas into PEBL software, calculating the total power rejection rate sum, if the total power rejection rate sum is not more than 5%, completing the energy storage configuration, otherwise continuing according to the steps (1) - (3).
Further, the fourth step includes the following steps:
(1) Based on a sensitivity analysis basis between the section energy storage configuration scale and the new energy utilization rate, analyzing sensitivity between the provincial energy storage configuration scale and the new energy utilization rate;
(2) Performing sensitivity analysis of hydrologic year and provincial energy storage capacity configuration;
(3) And performing sensitivity analysis on the installation ratio of the new energy in the provincial area and the energy storage capacity configuration.
The implementation of the invention has the beneficial effects that: according to the principle of safety, cleanliness and economy, starting from the overall benefit of the power system, according to the technical and economic characteristics of various power supplies in the power system, including operations of hydropower, thermal power, wind power, photovoltaic and the like, the conventional power supply operation modes of hydropower, thermal power and the like are optimized, the high-efficiency utilization of wind power and photovoltaic power generation is promoted, and a specific process is provided for establishing a new energy power generation consumption analysis method; secondly, a new energy consumption model considering peak regulation capacity constraint is established, wherein the new energy consumption model comprises a new energy power-off proportion calculation method considering a unit start-stop plan and the peak regulation constraint, a specific calculation flow is given when energy storage is not considered, and a correction method for ensuring correct result of calculation comprehensive net load is given when energy storage is considered; then, an energy storage capacity configuration method for improving the new energy consumption capacity of the provincial area is established, and a specific calculation flow is given; and finally, correcting the energy storage configuration scale, and performing sensitivity analysis between factors and the energy storage configuration by comprehensively considering factors such as new energy utilization rate, hydrology, new energy installation ratio and the like, so that a specific calculation method and a specific flow are provided, and the rationality and the effectiveness of the energy storage configuration method for improving the new energy consumption capability are further ensured.
The invention provides an energy storage configuration method for improving the new energy consumption capacity of a provincial area, which is based on production simulation software. The configuration method comprehensively considers factors such as new energy characteristics, regional load, peak regulation resources, inter-provincial tie line peak regulation mutual aid capability, direct current external delivery capability and the like of Qinghai province, and uses new energy data of Qinghai regions for demonstration, and results show the effectiveness and stability of the method.
Drawings
FIG. 1 is a new energy consumption frame diagram, establishing a new energy power generation consumption analysis method;
FIG. 2 is a flow chart of calculation of the new energy power rejection ratio without energy storage under consideration of peak shaving constraint;
FIG. 3 is a schematic diagram of a composite payload curve after energy storage is introduced;
FIG. 4 is a flow chart of energy storage configuration to establish an energy storage capacity configuration method for improving the energy storage capacity of the new energy storage area;
FIG. 5 is a graph of sensitivity analysis between the Qinghai energy storage configuration scale and new energy utilization in an example;
FIG. 6 is a graph showing a sensitivity analysis between the peak shaving energy storage configuration scale and the new energy utilization in Qinghai province;
FIG. 7 is a graph showing the sensitivity analysis between the peak shaving energy storage configuration scale and the new energy utilization of 70% of the new energy in the year of the brine in the example.
Detailed Description
The invention is further described below with reference to the accompanying drawings; the invention is capable of other and different embodiments and its several details are capable of modifications in various obvious respects, all without departing from the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive.
The energy storage configuration method for improving the new energy consumption capability of the provincial domain in the embodiment comprises the following steps:
step one: the main factors influencing the new energy consumption of provincial areas are researched and judged;
and aiming at a specific evaluation level year, obtaining a load curve and a power supply structure of each day of the year, and obtaining a power grid wind power receiving space of each day and each time period through peak regulation capacity analysis.
If the new energy electric output curve of each day can also be obtained through simulation, the electric power of each day in each period can be obtained by comparing the new energy receiving space of the electric network of each day in each period with the new energy output, a annual electric power discarding time sequence curve is formed, and then annual electric power discarding condition indexes are obtained through statistics.
The overall flow of the new energy power generation and absorption analysis method is shown in figure 1.
According to the principle of safety, cleanness and economy, the operation modes of conventional power supplies such as hydroelectric power and thermal power are optimized according to the technical and economic characteristics of various power supplies in the power system, such as hydroelectric power, thermal power, wind power and photovoltaic power, and the like, and the high-efficiency utilization of wind power and photovoltaic power generation is promoted. Considering constraint conditions such as planned overhaul, load reserve, accident reserve and the like of each power station in the system, simulating the operation mode and the power generation curve of each power station in 365 days of the system all the year round, analyzing the capacity of the renewable energy source from a peak regulation level, and then analyzing the capacity of the system under the fluctuation of the renewable energy source of the minute level in the hour time scale. Here, in order to simplify the scale of the solution, it is also considered that the output of a part of power sources such as hydroelectric power units, thermoelectric power units and the like has strong seasonality, so that the annual unit combination can be divided into four quarter unit combination problems. Regarding the crew overhaul plan in fig. 1, it can be obtained by the equal reliability principle. The specific flow is as follows:
(1) When the system is subjected to unit combination solving under a long time scale, the number of units is large, the time scale is long, the solving difficulty of the mixed integers with high dimension is high, the time is long, and the balance of the whole computing platform is not facilitated, so that 4 hours are taken as intervals throughout the day, 180 time nodes are averaged every month, and a monthly unit combination plan is solved;
(2) According to the set combination result obtained by solving, the problem of insufficient renewable energy utilization caused by insufficient set peak regulation capacity under finer time scales, such as hour, 30 minutes, 15 minutes and 5 minutes time scales, is analyzed.
Step two: the principle of improving the peak regulation capacity of the system by analyzing the energy storage is established, the basic thought of provincial large-scale new energy consumption evaluation is established, a new energy consumption model considering the constraint of the peak regulation capacity is established, and the specific flow is as follows:
(1) Considering unit start-stop plan
The power supply overhaul plan is formulated based on equal risk method calculation, the unit combination scheme is formulated based on an optimization model constructed by taking the minimum total running cost as a target, and the optimization model is expressed by adopting a formula 1:
wherein: alpha j ,β j ,γ j Fuel cost coefficients, respectively; s is S t Gj Is the starting cost; u (U) t Gj Is the unit voltage; p (P) t Gj The active power of the unit; d (D) t Gj Is the shutdown cost;
S t Gj the starting cost adopts a two-state model by comparing the continuous shutdown time T t Gj,off And determining whether to start the unit in a cold start or hot start mode according to the minimum cold start time limit, wherein the starting cost is expressed by adopting a formula 2:
wherein: c cj ,c hj The cold and hot start-up cost of the unit j is respectively;
for the minimum downtime limit of the unit j,
is the cold start time of the unit.
Constraint conditions considered by the unit combination calculation model comprise constraints such as electric power and electric quantity balance, upper and lower unit output limits, rotation standby, minimum unit starting and stopping time, unit climbing and the like.
(2) New energy power-off proportion calculation method considering peak regulation constraint
The unit combination of the whole year is calculated, and then the minimum output of the conventional power supply at every moment of the whole year can be calculated and calculated as sigma P g min 。
Defining the payload as represented by equation 3:
load net ＝load o +load s -P PV -P wind (equation 3)
Wherein: load net Load as payload o Load is the original load curve s For system outgoing power, P wind For wind power output, P PV Is a photovoltaic output.
Obtaining an hour-by-hour payload curve, based on which the sum of the minimum output of all the starting units at that time, ΣP, is calculated g min Comparison is performed:
1) Assuming no stored energy, a specific calculation flow is shown in fig. 2:
if load net ＞∑P gmin And the machine set climbs without exceeding the limit, the renewable energy sources can be completely consumed, and no wind and light are abandoned.
If load net ＜∑P g min And the machine set climbs without out-of-limit, the renewable energy source is abandoned to be Sigma P g min -load net 。
In a small time scale, renewable energy source fluctuation can be larger, and the unit climbing rate is limited, when the equivalent load fluctuation rate is larger than the unit out-of-limit, and the climbing limit value of all the units is marked as P', the newly increased abandoned wind abandoned light quantity is
2) Assuming that the stored energy is contained, the correction method is as shown in fig. 3:
using stored energy e=l 2 The delta E modifies the payload curve to obtain the integrated payload for the system day d and time t. Assuming the net load curve low valley on day d is Pmin,d By applying the stored energy E to r periods (r takes empirical values) around the valley, as shown in the shaded portion of fig. 3. The low valley of the payload is then from P min,d To P min,′d Thereby (a)The peak-to-valley difference of the daily net load is reduced.
The corrected payload valley value is expressed as formula 4 according to the principles of the capacity of stored energy, the area of the shaded portion, and the like:
wherein: Δt is the time interval, 15min; p (P) netload,d,t1 A payload value that is a period of time near the trough; l (L) 2 Δe represents the capacity of the stored energy in the current scenario.
Using the net load curve after the energy storage correction, called the integrated net load curve P comload,d,t 。
Step three: the energy storage capacity configuration method for improving the new energy consumption capacity of the provincial area is established, the flow chart is shown in fig. 4, and the specific flow is as follows:
(1) After the section blocking energy storage configuration is completed, substituting the energy storage into PEBL software for time sequence simulation.
(2) Obtaining the section blocking power rejection rate and the peak shaving power rejection rate, if the power rejection rate sum is less than 5%, no energy storage is needed to be configured, and the energy storage configuration scale is output; otherwise, the peak-to-peak power-off curve is further analyzed.
(3) And analyzing peak shaving and power discarding curves of different areas, configuring energy storage according to the total power discarding rate and a target of 5%, searching for a proper energy storage configuration combination, and traversing all areas.
(4) And (3) re-distributing the peak regulation energy storage and the section energy storage configured in all areas into PEBL software, calculating the electricity rejection rate sum, if the electricity rejection rate sum is not more than 5%, completing the energy storage configuration, otherwise continuing according to the flow.
Based on the third step, the energy storage capacity configuration result for improving the capacity of the Qinghai province is counted, and the effect evaluation index and the effect after the energy storage is additionally installed are analyzed.
Taking Qinghai as an example, the hydrologic year is the plain water year, 2021 year data are built in production simulation software, when the mutual economy outside the area is 100% and the mutual economy in the area can be completely realized, the electric power and electric quantity balance of the Qinghai in 2021 year is calculated under the no energy storage configuration, and the result is shown in table 1:
table 1: power and electricity balance result of 2021 Qinghai current power grid
From Table 1, it is found that the new energy source has 43 hundred million degrees of waste energy due to insufficient peak shaving, and the waste energy rate due to insufficient peak shaving resource is 10.64%. The energy storage for improving the capacity of the local area outside is configured into a Qinghai power grid, the energy storage required to be configured in the province area is calculated according to the third step, the energy storage for improving the capacity of the local area outside is distributed into PEBL simulation data, and at the moment, the new energy consumption capacity in the Qinghai province area (including the sending) is calculated according to the fact that the peripheral areas are not mutually used up and all the subareas in the Qinghai are fully mutually used up; the calculation results are shown in Table 2, and the results show that after the energy storage is added, the section blocking rejection rate is less than 5%, and the effectiveness of the section energy storage is verified. When the peak regulation energy storage is considered, some new energy sources are actually abandoned due to insufficient peak regulation resources, so that the section blocking electric abandoning rate can be obviously reduced. The energy storage peak shaving power rejection rate of the section calculated when the mutual power rejection rate is 100% outside the region and the mutual power rejection rate can be calculated when the mutual power rejection rate is completely within the region, the peak shaving power rejection rate of three regions of Hai xi, qing nan and Tara can be seen to be more than 5%, the full power rejection rate of Qing Hai province is 8.79%, therefore, the energy storage needs to be additionally arranged, and the expected value of the peak shaving power rejection rate is the last column on the right side in order to reduce the Qing Hai province power rejection rate to 5%.
Table 2: energy storage scale configuration due to section blockage in 2021 and effect after configuration
| Region of | Section energy storage | Section blocking power rejection rate | Peak regulation and power rejection rate | Peak shaving and power discarding expected value |
| Haixi (a Chinese character of Haixi) | 2000MW/3h | 2.82％ | 7.46％ | 2.18％ |
| Qingnan province (Qingnan province) | 300MW/3h | 0.09％ | 9.76％ | 4.91％ |
| Ta La | - | 0.7％ | 10.29％ | 4.3％ |
| Qinghai main network | - | - | 0.82％ | - |
| (Qinghai) | - | - | 8.79％ | 5％ |
And analyzing the new energy power-off curve caused by insufficient peak regulation resources. The optimal configuration scheme of the stored energy is shown in table 3:
table 3:2021 peak shaving energy storage configuration combination and preliminary expected effect
From Table 3, it is known that the peak shaving energy storage of 2GW/3h, 2GW/3h and 1.5GW/3h are configured in the three areas of Haifeng, qing nan and Tara, so that the peak shaving and power discarding rate can be reduced to the expected target value.
The peak shaving energy storage is continuously distributed into PEBL simulation data, 8760-point simulation operation is carried out all the year round, and the electricity rejection rate of each partition is statistically analyzed to basically meet the assessment requirement of the electricity rejection rate, and particularly, the electricity rejection rate is close to 5% from the whole province, and the table 4 is shown.
Table 4: full-network energy storage configuration scale and effect of Qinghai-cause in 2021
Table 4 shows that under the current power grid of year 2021 (60% of new energy installation ratio), the peak regulation energy storage (5.5 GW/3h in the minor) of 2GW/3h, 2GW/3h and 1.5GW/3h are respectively configured in the sea, qing nan and Tara, the section energy storage (2.3 GW/3h in the minor) of 2GW/3h and 300MW/3h are respectively configured in the sea, qing nan, and the total 7.8GW/3h can reduce the total waste power rate of Qinghai province to 5%.
The method comprises the steps of establishing relevant evaluation indexes for analyzing the influence of energy storage on the Qinghai power grid after adding, wherein the indexes mainly comprise 3 indexes, namely the electric power deficiency, the new energy electric quantity permeability and the renewable energy electric quantity permeability, and the specific formulas are as follows:
table 5: evaluation of key indexes after energy storage of whole network configuration of Qinghai in 2021
| Index (I) | Before additional installation of energy storage | After the energy storage is additionally arranged |
| Probability of |
0 | 0 |
| New energy electric quantity permeability | 44.40％ | 47.32％ |
| Electric quantity permeability of renewable energy | 91.01％ | 93.94％ |
The data in table 5 are obtained through calculation, and the new energy electric quantity permeability and the renewable energy electric quantity permeability are obviously improved after the energy storage is additionally arranged, so that the effectiveness of the configuration method is fully shown.
Step four: the energy storage configuration is further reasonable, the energy storage configuration meets the development requirement of provincial domains, the factors such as the new energy utilization rate, hydrologic years, the new energy installation ratio and the like are comprehensively considered, the sensitivity analysis between the factors and the energy storage configuration is carried out, and the specific flow is as follows:
(1) And on the basis of sensitivity analysis between the section energy storage configuration scale and the new energy utilization rate, sensitivity between the provincial energy storage configuration scale and the new energy utilization rate is analyzed. Table 6 shows the energy storage configuration scale for each section and region of Qinghai at 90% and 95% new energy utilization. As can be seen from Table 6, when the new energy utilization rate is reduced from 95% to 90%, the energy storage capacity configuration scale is reduced from 7800MW/3h to 1400MW/3h, and the energy storage capacity configuration scale is reduced by more than 5 times. Tables 7 to 12 show the detailed energy storage configuration scale and the effect calculation results.
Table 6: full-network configuration energy storage scale for 2021 Qinghai when new energy utilization rate is 90% and 95%
The new energy utilization rate is reduced successively, and the energy storage configuration scale can be reduced by 1GW/3h every time the new energy utilization rate is reduced under the current power grid of the Qinghai 2021 year, and the energy storage utilization hours are increased, so that the energy storage utilization rate is gradually increased from 750 hours to 1516 hours, as shown in fig. 5. The configuration of peak shaving energy storage in the sea, green south and tala is shown in figure 6.
Table 7: energy storage configuration scale and effect (hundred million degrees and hour) of 2021 Qinghai when new energy utilization rate is 95 percent
Table 8: energy storage configuration scale and effect (hundred million degrees and hour) of 2021 Qinghai when new energy utilization rate is 94 percent
Table 9: energy storage configuration scale and effect (hundred million degrees and hour) of 2021 Qinghai when new energy utilization rate is 93 percent
Table 10: energy storage configuration scale and effect (hundred million degrees and hour) of 2021 Qinghai when new energy utilization rate is 92 percent
Table 11: energy storage configuration scale and effect (hundred million degrees and hour) of 2021 Qinghai when new energy utilization rate is 91 percent
Table 12: energy storage configuration scale and effect (hundred million degrees and hour) of 2021 Qinghai when new energy utilization rate is 90 percent
(2) And performing sensitivity analysis of hydrologic year and provincial energy storage capacity configuration. From table 13, it is known that the generation amount of water and electricity is about 121 hundred million degrees more than that of plain water due to the large generation of water and electricity in the year of high water, and the electricity rejection rate (including section electricity rejection and peak shaving electricity rejection) of new energy sources is increased from 12.9 to 14.25% because water and electricity are preferentially used, as shown in table 13.
Table 13: effect of different hydrologic years of Qinghai 2021 on power rejection rate
| Year of flat water | Year of full water | |
| Load electric quantity | 805 | 805 |
| Direct current delivery | 346.7 | 346.7 |
| New energy source | 357.4 | 351.4 |
| Conventional power supply | 112.7 | 106.8 |
| Hydroelectric power generation | 375.2 | 486.5 |
| Qinghai power rejection rate | 12.90％ | 14.25％ |
Table 14 shows the simulation results of the power and electricity balance of the current power grid of the Qinghai 2021 in the year of the high water, and the significant drop of the power received by Qinghai from the ac section can be seen from the table due to the great occurrence of water and electricity. The waste energy of new energy is also increased sharply from 43 hundred million to 49 hundred million.
Table 14: power and electricity balance simulation result of current power grid in 2021 of Qinghai in year of high water
On the basis of energy storage capacity configuration for improving the new energy consumption capability of the provincial area in the plain water year, the sensitivity between the energy storage configuration scale and the hydrologic year is explored. As can be seen from table 15: compared with the plain water year, the new energy electricity rejection rate is improved, and if the new energy utilization rate is ensured to be unchanged, the new energy storage capacity is required to be increased. If the energy is stored in a large-scale in a water year, the new energy utilization rate is reduced by 1%.
Table 15: sensitivity analysis of energy storage configuration scale, new energy utilization rate and hydrologic year of Qinghai 2021
(3) And performing sensitivity analysis on the installation ratio of the new energy in the provincial area and the energy storage capacity configuration. And under the condition that the new energy source in the year of the high water is 70 percent and other boundaries are unchanged, calculating the energy storage configuration scale in the Qinghai province area. With the improvement of the new energy duty ratio, the waste electric quantity of the new energy is obviously improved under the condition that the peak shaving resource in the province is unchanged. In order to meet the requirement of 5% of the existing power rejection rate, 19.35GW/4h energy storage is configured in the Qinghai province range under the condition of 70% new energy duty ratio, as shown in a table 16, and 7.8GW/3h energy storage is configured in the province range under the condition of 60% new energy duty ratio, as shown in a table 15, the energy storage configuration scale is increased to 3.3 times; the cost and the scale of the energy storage configuration are obviously improved, the energy storage capacity accounts for 54.5% of the installed scale of the new energy (the energy storage time is 4 hours), and the energy storage capacity accounts for 30% of the installed scale of the new energy (the energy storage time is 3 hours) under the 60% of the new energy. The sensitivity of the energy storage configuration scale under different utilization rates of new energy is studied, and is shown in table 17 and fig. 7.
Table 16: energy storage configuration scale and utilization rate under different utilization rates of new energy in Qinghai province in high-water year under 70% new energy ratio
Table 17: compared with the new energy consumption in the provincial area under the different new energy installation duty ratios in the year of the high water without energy storage (ten thousands kilowatts, hundred million degrees)
| 60% new energy duty ratio | 70% new energy duty ratio | |
| New energy installation | 2415 | 3534 |
| New energy generating capacity | 404 | 584.5 |
| New energy waste amount | 57.57 | 150.15 |
| New energy power rejection rate | 14.25％ | 25.69％ |
As is known from table 17 and fig. 7, at 70% of the installed ratio of the new energy, when the new energy utilization rate assessment index is adjusted down to 90%, the energy storage configuration scale is reduced to 45% when the utilization rate is 95%, the energy storage configuration scale is reduced by about 1000 ten thousand megawatts/4 hours, and the utilization rate of the energy storage is also significantly improved. Therefore, when the new energy installation ratio is increased, new energy utilization rate assessment indexes should be further established so that the energy storage configuration scale is more reasonable, responsibility steps of all parties can be balanced, and the effectiveness and rationality of the energy storage configuration method are further improved.
Claims (5)
1. The invention provides an energy storage configuration method for improving the new energy consumption capability of a provincial area, which is characterized by comprising the following steps:
step one, researching and judging main factors influencing new energy consumption in provincial areas;
step two, a new energy consumption model considering peak regulation capacity constraint is established;
step three, combining factors such as a section blocking power rejection rate, a peak shaving power rejection rate and the like, and establishing an energy storage capacity configuration model and an evaluation index for improving the new energy consumption capacity of the provincial area so as to analyze the influence on a power grid after energy storage is added;
and fourthly, combining the factors such as the new energy utilization rate, hydrologic year, new energy installation ratio and the like, and carrying out sensitivity analysis between the factors and the energy storage capacity configuration.
2. The energy storage configuration method for improving new energy consumption capability in provincial regions according to claim 1, wherein the first step comprises the following steps:
determining an evaluation level year, extracting a load curve and a power supply structure of each day of the year, and analyzing by peak regulation capacity to obtain a space value of a new energy generator set accepted by a power grid of each time period of each day;
simulating new energy power output curves of each day, comparing new energy power space values accepted by the power grid of each time period of each day with the new energy power output curves to obtain power discarding power of each time period of each day, forming a annual power discarding power timing curve, and counting annual power discarding data;
taking planned overhaul, load reserve and accident reserve of each power station in the power system as constraint conditions, simulating the operation mode and power generation curve of each power station in 365 days of the power system all the year round, analyzing the consumption capability of new energy based on a peak regulation level, and analyzing the consumption capability of the power system under minute-level new energy power fluctuation in an hour time scale; dividing the annual generator set combination into four quarter set combination models, and marking seasons with strong output of the traditional generator set;
the unit maintenance plan is obtained through an equal reliability principle, and the method comprises the following steps:
(1) Taking 4 hours as intervals throughout the day, and solving a monthly unit combination plan, wherein the average month is 180 time nodes;
(2) According to the monthly unit combination plan, the problem of insufficient renewable energy utilization caused by insufficient unit peak regulation capacity under the time scales of 30 minutes, 15 minutes and 5 minutes due to fluctuation of renewable energy is analyzed.
3. The energy storage configuration method for improving the new energy consumption capability of the provincial domain according to claim 1, wherein the second step comprises the following steps:
(1) Establishing a unit combination calculation model:
and preparing a power supply overhaul plan based on an equal risk method, and constructing a unit combination calculation model based on the minimum total running cost as a target, wherein the unit combination calculation model is expressed as a formula 1:
wherein: alpha j ,β j ,γ j Respectively fuel cost coefficient, S t Gj For starting up the machine, U t Gj For the unit voltage, P t Gj For the active power of the unit, D t Gj Is the shutdown cost;
wherein S is t Gj By comparing T using a two-state model t Gj,off Determining whether to start the unit by cold start or hot start with the minimum cold start time limit, S t Gj Expressed as formula 2:
wherein: c (C) cj ,C hj The cold and hot start-up cost of the unit j is respectively;
minimum downtime limit for unit j; />
The cold start time of the unit; t (T) t Gj,off For continuous downtime;
constraint conditions of the unit combination calculation model comprise constraints such as electric power and electricity balance, upper and lower unit output limits, rotation standby, minimum unit starting and stopping time, unit climbing and the like;
(2) Establishing a new energy power-off proportion calculation model of peak regulation constraint:
calculating to obtain annual unit combination, and further calculating to obtain sigma P gmin ；∑P gmin The minimum output of the conventional power supply is the minimum output of the conventional power supply at every moment in the whole year;
the payload is defined, expressed as equation 3:
load net ＝load o +load s -P PV -P wind
(equation 3)
Wherein: load net Load as payload o Load is the original load curve s For system outgoing power, P wind For wind power output, P PV Is photovoltaic output;
an hour-by-hour payload curve is obtained, and at this time Σp gmin A comparison is made in which:
1) When no energy is stored, a specific calculation flow is shown in fig. 2:
if load net ＞∑P gmin The machine set climbing is not out of limit, so that renewable energy sources can be completely consumed, and no wind and light are abandoned;
if load net ＜∑P gmin And the machine set climbs without out-of-limit, the renewable energy source is abandoned to be Sigma P gmin -load net ；
In a small time scale, renewable energy source fluctuation can be larger, and the unit climbing rate is limited, when the equivalent load fluctuation rate is larger than the unit out-of-limit, and the climbing limit value of all the units is marked as P', the newly increased abandoned wind abandoned light quantity is
2) When stored energy is contained, based on fig. 3, the correction method is as follows:
using stored energy e=l 2 Delta E corrects the net load curve to obtain the comprehensive net load of the system at the t period on the d day;
let d-th day payload curve low valley value P min,d Applying the stored energy E to r time periods near the trough, r taking the empirical value, as shown in the shaded portion of FIG. 3, the trough of the payload is then taken from P min,d To P min′d Thereby reducing peak-to-valley differences for the daily net load;
according to the principle that the capacity of stored energy is equal to the area of a shadow part, the corrected net load low valley value is expressed as a formula 4:
wherein: Δt is the time interval，15min；P netload,d,t1 A payload value that is a period of time near the trough; l (L) 2 Δe represents the capacity of energy storage in the current scenario;
using the net load curve after the energy storage correction, called the integrated net load curve P comload,d,t 。
4. The energy storage configuration method for improving the new energy consumption capability of a provincial area according to claim 1, wherein the third step comprises the following steps:
(1) After the section blockage is configured on the energy storage, substituting the energy storage into PEBL software for time sequence simulation;
(2) Obtaining the section blocking power rejection rate and the peak shaving power rejection rate, if the power rejection rate sum is less than 5%, no energy storage is needed to be configured, and the energy storage configuration scale is output; otherwise, further analyzing the peak-to-peak power-off curve;
(3) Analyzing peak shaving and power discarding curves of different areas, configuring energy storage for 5% of target with total power discarding rate, searching suitable energy storage configuration combination, and traversing all areas;
(4) And (3) re-distributing the peak regulation energy storage and the section energy storage configured in all areas into PEBL software, calculating the total power rejection rate sum, if the total power rejection rate sum is not more than 5%, completing the energy storage configuration, otherwise continuing according to the steps (1) - (3).
5. The energy storage configuration method for improving the new energy consumption capability of the provincial domain according to claim 1, wherein the fourth step comprises the following steps:
(1) Based on a sensitivity analysis basis between the section energy storage configuration scale and the new energy utilization rate, analyzing sensitivity between the provincial energy storage configuration scale and the new energy utilization rate;
(2) Performing sensitivity analysis of hydrologic year and provincial energy storage capacity configuration;
(3) And performing sensitivity analysis on the installation ratio of the new energy in the provincial area and the energy storage capacity configuration.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310424922.4A CN116418020A (en) | 2023-04-20 | 2023-04-20 | Energy storage configuration method for improving new energy consumption capability of provincial area |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310424922.4A CN116418020A (en) | 2023-04-20 | 2023-04-20 | Energy storage configuration method for improving new energy consumption capability of provincial area |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116418020A true CN116418020A (en) | 2023-07-11 |
Family
ID=87056137
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310424922.4A Pending CN116418020A (en) | 2023-04-20 | 2023-04-20 | Energy storage configuration method for improving new energy consumption capability of provincial area |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116418020A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116976521A (en) * | 2023-08-14 | 2023-10-31 | 水电水利规划设计总院 | Power system peak regulation energy storage capacity demand prediction method with different time scales |
| CN117852927A (en) * | 2024-03-06 | 2024-04-09 | 中能智新科技产业发展有限公司 | Source network charge storage integrated planning production simulation method, system and storage medium |
| CN117852927B (en) * | 2024-03-06 | 2024-06-04 | 中能智新科技产业发展有限公司 | Source network charge storage integrated planning production simulation method, system and storage medium |
-
2023
- 2023-04-20 CN CN202310424922.4A patent/CN116418020A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116976521A (en) * | 2023-08-14 | 2023-10-31 | 水电水利规划设计总院 | Power system peak regulation energy storage capacity demand prediction method with different time scales |
| CN116976521B (en) * | 2023-08-14 | 2024-01-16 | 水电水利规划设计总院 | Power system peak regulation energy storage capacity demand prediction method with different time scales |
| CN117852927A (en) * | 2024-03-06 | 2024-04-09 | 中能智新科技产业发展有限公司 | Source network charge storage integrated planning production simulation method, system and storage medium |
| CN117852927B (en) * | 2024-03-06 | 2024-06-04 | 中能智新科技产业发展有限公司 | Source network charge storage integrated planning production simulation method, system and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109599861B (en) | Power supply structure planning method of power supply of transmission-end power grid considering local load peak regulation capacity | |
| Yin et al. | Economic and environmental effects of peak regulation using coal-fired power for the priority dispatch of wind power in China | |
| CN107732949B (en) | Energy storage, distribution and constant volume method integrating multi-season characteristics of wind power all year round | |
| Pamshetti et al. | Coordinated allocation of BESS and SOP in high PV penetrated distribution network incorporating DR and CVR schemes | |
| CN109636674B (en) | Large-scale hydropower station group monthly transaction electric quantity decomposition and checking method | |
| CN104578176A (en) | Method for making power generation plan in consideration of direct current interaction | |
| CN105006844A (en) | Electric power system day-ahead robust scheduling system on intermittent power generation grid connected condition | |
| Yuan et al. | Cross-regional integrated transmission of wind power and pumped-storage hydropower considering the peak shaving demands of multiple power grids | |
| CN108039737A (en) | One introduces a collection net lotus coordinated operation simulation system | |
| CN112016747A (en) | Optimization method suitable for source-load-storage flexible resource overall planning and operation | |
| CN116418020A (en) | Energy storage configuration method for improving new energy consumption capability of provincial area | |
| CN109687534B (en) | Power system generator set active power control method based on step water quantity matching | |
| CN104636824A (en) | Distributed photovoltaic siting and sizing method for determining minimum permeability | |
| Hu et al. | Adaptive time division power dispatch based on numerical characteristics of net loads | |
| CN103679284A (en) | Accommodated wind power accessed fixed interval rolling scheduling method | |
| CN116579115B (en) | System planning method and device for cooperative interaction of electricity and hydrogen | |
| Jing et al. | Benefit compensation of hydropower-wind-photovoltaic complementary operation in the large clean energy base | |
| CN113240546B (en) | Monthly scheduling method for units in dense hydropower region | |
| CN115760188A (en) | Medium-and-long-term contract electric quantity decomposition method considering carbon emission balance | |
| Zhang et al. | Auxiliary service market model considering the participation of pumped-storage power stations in peak shaving | |
| CN105514985B (en) | Method for constructing power grid aggregation model | |
| CN114884135A (en) | Day-ahead coordination control method suitable for regional level source network load storage | |
| CN116316865A (en) | Full-link coordination planning optimization method for high-proportion new energy regional power system | |
| CN114447990A (en) | Real-time scheduling method for promoting clean energy consumption of power grid | |
| Li et al. | Optimal Planning Model of Renewable Energy and Energy Storage System Considering Load Characteristics |
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 |