CN113725912A - Multi-region power system planning method and system considering cross-region power grid peak shaving - Google Patents

Multi-region power system planning method and system considering cross-region power grid peak shaving Download PDF

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CN113725912A
CN113725912A CN202110805564.2A CN202110805564A CN113725912A CN 113725912 A CN113725912 A CN 113725912A CN 202110805564 A CN202110805564 A CN 202110805564A CN 113725912 A CN113725912 A CN 113725912A
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planned
power
region
area
peak
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张宁
孔维政
代红才
赵龙
田鑫
曹相阳
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State Grid Energy Research Institute Co Ltd
Economic and Technological Research Institute of State Grid Shandong Electric Power Co Ltd
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State Grid Energy Research Institute Co Ltd
Economic and Technological Research Institute of State Grid Shandong Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • 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
    • H02J3/003—Load forecast, e.g. methods or systems for forecasting future load 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
    • 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
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • 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
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

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Abstract

The invention provides a multi-region power system planning method and system considering cross-region power grid peak shaving, which comprises the following steps: determining key peak shaving parameters required by the planning of the power system based on each region to be planned; establishing a multi-region power system planning model considering key peak regulation parameters and considering cross-region power grid peak regulation; planning the power system of each to-be-planned area based on the value of the key peak shaving parameter and the value of the necessary power parameter of each to-be-planned area and the multi-area power system planning model considering the cross-area power grid peak shaving; the multi-region power system planning model considering the cross-region power grid peak shaving is established according to the peak shaving capacity constraint of each to-be-planned region power system and the cross-region power grid peak shaving coefficient constraint. The method includes the steps that peak shaving parameters of all areas to be planned are brought into a planning model, and the overall peak shaving capacity of the power system is accurately and comprehensively depicted; the method is beneficial to determining the reasonable development scale of the new energy, and better supports the construction of the power system taking the new energy as the main body.

Description

Multi-region power system planning method and system considering cross-region power grid peak shaving
Technical Field
The invention belongs to the field of power system planning, and particularly relates to a multi-region power system planning method and system considering cross-region power grid peak shaving.
Background
The traditional power system planning takes power and electric quantity balance as core constraints, and peak regulation constraints are not considered. The interconnected power grid is also a flexible resource, and the peak shaving value is not effectively exerted because the transmission power of the trans-regional transmission channel is fixed and the real-time fluctuation optimization is insufficient at present. With the continuous improvement of the permeability of the fluctuating new energy, the matching between the system peak regulation capacity and the peak regulation demand needs to be ensured in the planning stage of the power system, and the coordinated development of the power system and the new energy needs to be ensured, so that the peak regulation capacity constraint is considered in part of power system planning model methods in recent years.
Currently, peak shaving resources in the existing peak shaving capacity constraint are limited to various adjustable power supplies, demand response and energy storage, so that a planning method considering the peak shaving of a power grid comprehensively needs to be provided.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a multi-region power system planning method considering cross-region power grid peak shaving, which is characterized by comprising the following steps of:
determining key peak shaving parameters required by the planning of the power system based on each region to be planned;
establishing a multi-region power system planning model considering key peak regulation parameters and considering cross-region power grid peak regulation;
planning the power system of each to-be-planned area based on the value of the key peak shaving parameter and the value of the necessary power parameter of each to-be-planned area and the multi-area power system planning model considering the cross-area power grid peak shaving;
the multi-region power system planning model considering the cross-region power grid peak shaving is established according to the peak shaving capacity constraint of each to-be-planned region power system and the cross-region power grid peak shaving coefficient constraint.
Preferably, the establishing a multi-region power system planning model considering peak shaving of the cross-region power grid in consideration of the key peak shaving parameters includes:
establishing a target function by taking the minimum net present value of the total cost of the power system in a set planning period as a target based on the key peak regulation parameters;
based on the key peak shaving parameters, the target function is constrained by using the peak shaving capacity of the power system of each to-be-planned area, the peak shaving coefficient of the cross-regional power grid, the power balance of each to-be-planned area, the electric quantity balance of each to-be-planned area, the power transmission capacity of each channel between each to-be-planned area, the power transmission electric quantity of each channel between each to-be-planned area, the regulating rate of the system of each to-be-planned area, the expansion scale of various power sources of each to-be-planned area, the expansion scale of each power transmission channel between each to-be-planned area, the total renewable energy target, the total carbon dioxide emission amount, the total sulfur dioxide emission amount and the total nitrogen oxide emission amount as constraint conditions, and a multi-region power system planning model considering the peak shaving of the cross-regional power grid is established.
Preferably, the peak shaving capacity constraint of the power system of the area to be planned is determined according to the following formula:
Figure BDA0003166391160000021
in the formula, omegasprFor a set of power supplies with peak shaving capability in the region r to be planned, mus,rThe average peak regulation depth, Cs, of the class-rs power supply of the region to be planneds,r,tCumulative installed capacity, Ω, of the s power type for the t-th region r to be plannedx2rSet of power transmission channels, mu, for the region r to be planned to receive power from the region x to be plannedg,rFor the peak-shaving coefficient, Pt, of the transmission channel g in the region r to be plannedg,tIs the transmission capacity, omega, of the transmission channel g of the year tr2xSet of power transmission channels, Ω, for transmitting power from the region r to be planned to the region x to be planneddprFor a demand response set, Cd, with peak shaving capability in an area r to be plannedd,r,tFor the d-th class demand response capacity, omega, of the t-th to-be-planned area rcprFor the energy storage set with peak regulation capability in the region r to be planned, Ccc,r,tInstalled capacity, lambda, for storing energy of class c of the area r to be planned in the t-th yearr,tA predicted value of load peak-valley difference rate, Fp, of the t-th to-be-planned area rr,tIs the predicted value of the maximum load of the t-th area r to be planned, omegasvFor fluctuating power supply sets, vsThe peak regulation demand coefficient of the s-th type fluctuating power supply.
Preferably, the cross-regional power grid peak regulation coefficient constraint is determined according to the following formula:
0≤μg,r+μg,x≤Ug(g∈Ωx2r,Ωr2x)
in the formula, mug,rIs the peak regulation coefficient mu of the transregional power transmission channel g in the region r to be plannedg,xFor the peak regulation coefficient, U, of the transregional power transmission channel g in the region x to be plannedgIs the maximum peak regulation coefficient, omega, of the cross-region power transmission channel gx2rSet of power transmission channels, Ω, for the region r to be planned to receive power from the region x to be plannedr2xA power transmission channel set for transmitting power to an area x to be planned for an area r to be planned;
wherein, the maximum peak regulation depth U of the cross-region power transmission channel ggCalculated as follows:
Figure BDA0003166391160000022
in the formula, AgThe maximum peak shaving depth of the cross-region power transmission channel g;
maximum peak shaving depth A of cross-region power transmission channel ggCalculated as follows:
Ag＝πMAX,g-πMIN,g
in the formula, piMIN，gIs the minimum transmission power coefficient, pi, of the transregional transmission channel gMAX，gIs the maximum transmission power coefficient of the trans-regional transmission channel g.
Preferably, the objective function is determined according to the following formula:
Figure BDA0003166391160000031
wherein F is the net present value of the total cost of the power system in the planning period, T is the year, T is the time length of the planning period, A1For the cost of power supply construction, A2For the cost of the grid construction, A3To demand side resource utilization cost, A4For storing installation costs, A5For the system running cost, A6For system emission cost, R is the discount rate;
wherein, the power supply construction cost A1Calculated as follows:
Figure BDA0003166391160000032
in the formula, omegarFor planning the set of regions to be planned, ΩsIs a collection of power source species, Css,r,tCumulative installed capacity, Q, for the s power type of the t year to be planned area rs,r,tRetired capacity for the s power type of the t-th region r to be plannedsThe installed cost per unit capacity of the power supply of the s-th type;
cost of power grid construction A2Calculated as follows:
Figure BDA0003166391160000033
in the formula, omegagFor cross-regional collection of power transmission channels, Cgg,tCapacity of the g-th power transmission channel in the t year, PgThe unit capacity expansion cost of the g-th power transmission channel is obtained;
cost of demand side resource utilization A3Calculated as follows:
Figure BDA0003166391160000034
in the formula, omegaeFor energy-efficient plant species collections, Cee,r,tInstalled capacity, P, of energy efficient power plant of type e for area r to be planned in year teThe unit capacity expansion cost, omega, of the class e energy efficiency power plantdFor demand response class set, Cdd,r,tClass d demand response capacity for the t-th to-be-planned area r, EdIncentive costs for class d demand responses;
cost of energy storage installation A4Calculated as follows:
Figure BDA0003166391160000035
in the formula, omegacFor a set of energy storage categories, Ccc,r,tInstalled capacity, P, for storing energy of class c of area r to be planned in the t yearcThe unit capacity expansion cost of the class c energy storage;
system running cost a5Calculated as follows:
Figure BDA0003166391160000036
in the formula, HsAnnual utilization hours for the s power supply, EsThe operation cost of the power supply of the s-th type is the unit electric quantity operation cost;
system emission cost a6Calculated as follows:
Figure BDA0003166391160000041
in the formula, Mcs,tIs the carbon emission coefficient, Pr, of the s power supply of the t yearCWhich is a carbon emission cost.
Preferably, the acquiring of the area to be planned includes:
and calculating an inter-region net load complementation effect value, and taking the region of which the inter-region net load complementation effect value is greater than a preset inter-region power networking complementarity value as a region to be planned.
Preferably, the inter-region net load complementation effect value is calculated according to the following formula:
ΔV＝VNLr,m+VNLx,m-VSNLm
in the formula,. DELTA.VFor net load complementary effect values between the region r to be planned and the region x to be planned, VNLr,mThe average daily peak-to-valley difference of the net load average power curve of the mth month of the region to be planned, VNLx,mIs the average daily peak-to-valley difference, VSNL, of the net load average power curve of the mth month of the area x to be plannedmAnd adding the average daily peak-valley difference of the net load average power curve for the m th month of the region r to be planned and the region x to be planned.
Preferably, the key peak shaving parameters include:
the maximum power transmission power coefficient of each power transmission channel, the minimum power transmission power coefficient of each power transmission channel, the accumulated installed capacity of each power supply at the preset time of each region to be planned, each demand response capacity at the preset time of each region to be planned, the installed capacity of each energy storage at the preset time of each region to be planned, the line capacity at the preset time of each power transmission channel, the power transmission capacity at the preset time of each power transmission channel, the peak regulation coefficient of each power transmission channel at each region to be planned, the maximum peak regulation effect coefficient of each power transmission channel, the average peak regulation depth of each power supply at each region to be planned, the load peak-valley difference prediction value at the preset time of each region to be planned, the maximum load prediction value at the preset time of each region to be planned and the peak regulation demand coefficient of each power supply.
Preferably, the necessary power parameters of each area to be planned include:
retired capacity of various power supplies in preset time of each to-be-planned area, installed capacity of various energy efficiency power plants in preset time of each to-be-planned area, annual utilization hours of various power supplies in each to-be-planned area, peak-to-load output confidence coefficient of various power supplies in each to-be-planned area, power transmission support coefficient of each power transmission channel at maximum load moment of each to-be-planned area, power transmission line loss rate of each power transmission channel, average power transmission and distribution line loss rate in each to-be-planned area, charge and discharge efficiency of various stored energy, electric quantity demand predicted value in preset time of each to-be-planned area, annual maximum utilization hours of each power transmission channel, output regulation rate of various power supplies in each to-be-planned area, output regulation rate of various demand response resources in each to-planned area, output regulation rate of various stored energy in each to-planned area, load demand change rate in unit time of each to-planned area, output regulation rate of various to-planned areas, output regulation rate of various energy storage capacity of each to-planned area, and load demand change rate in unit time of each to-planned area, The method comprises the steps of obtaining the maximum construction capacity of various power supplies in preset time of each to-be-planned area, the maximum expansion capacity of each power transmission channel in preset time, the renewable power supply ratio target value in preset time of each to-be-planned area, the carbon emission coefficient of various power supplies in preset time of each to-be-planned area, the carbon dioxide emission upper limit in preset time of each to-be-planned area, the sulfur dioxide emission coefficient of various power supplies in preset time of each to-be-planned area, the sulfur dioxide emission upper limit in preset time of each to-be-planned area, the nitrogen oxide emission coefficient of various power supplies in preset time of each to-be-planned area and the nitrogen oxide emission upper limit in preset time of each to-be-planned area.
Based on the same inventive concept, the invention also provides a multi-region power system planning system considering cross-region power grid peak shaving, which comprises: the system comprises a calculation module, a model module and a planning module;
the calculation module is used for determining key peak shaving parameters required by the planning of the power system based on each region to be planned;
the model module is used for establishing a multi-region power system planning model considering key peak regulation parameters and considering cross-region power grid peak regulation;
the planning module plans the power system of each to-be-planned area based on the value of the key peak shaving parameter and the value of the necessary power parameter of each to-be-planned area and the multi-area power system planning model considering the cross-area power grid peak shaving;
the multi-region power system planning model considering the cross-region power grid peak shaving is established according to the peak shaving capacity constraint of each to-be-planned region power system and the cross-region power grid peak shaving coefficient constraint.
Compared with the closest prior art, the invention has the following beneficial effects:
the invention provides a multi-region power system planning method and system considering cross-region power grid peak shaving, which comprises the following steps: determining key peak shaving parameters required by the planning of the power system based on each region to be planned; establishing a multi-region power system planning model considering key peak regulation parameters and considering cross-region power grid peak regulation; planning the power system of each to-be-planned area based on the value of the key peak shaving parameter and the value of the necessary power parameter of each to-be-planned area and the multi-area power system planning model considering the cross-area power grid peak shaving; the multi-region power system planning model considering the cross-region power grid peak shaving is established according to the peak shaving capacity constraint of each to-be-planned region power system and the cross-region power grid peak shaving coefficient constraint. The invention brings the peak regulation parameters of each region to be planned into the planning model, and can more accurately and comprehensively depict the whole peak regulation capability of the power system.
According to the method and the system provided by the invention, the peak regulation constraint is introduced into the power system planning, so that the reasonable development scale of the new energy can be determined, and the construction of a novel power system taking the new energy as a main body can be better supported.
Drawings
Fig. 1 is a schematic flow chart of a multi-region power system planning method considering cross-region power grid peak shaving according to the present invention;
fig. 2 is a schematic diagram of a basic structure of a multi-region power system planning system considering cross-region power grid peak shaving provided in the present invention.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Example 1:
the flow diagram of the multi-region power system planning method considering cross-region power grid peak shaving provided by the invention is shown in fig. 1, and comprises the following steps:
step 1: determining key peak shaving parameters required by the planning of the power system based on each region to be planned;
step 2: establishing a multi-region power system planning model considering key peak regulation parameters and considering cross-region power grid peak regulation;
and step 3: planning the power system of each to-be-planned area based on the value of the key peak shaving parameter and the value of the necessary power parameter of each to-be-planned area and the multi-area power system planning model considering the cross-area power grid peak shaving;
the multi-region power system planning model considering the cross-region power grid peak shaving is established according to the peak shaving capacity constraint of each to-be-planned region power system and the cross-region power grid peak shaving coefficient constraint.
Before step 1, the payload complementarity between the regions needs to be analyzed, and each region to be planned is determined, which specifically includes:
(1) calculating the average power curve of the load demand of the single area
The main fluctuation of the new energy power generation output and the load demand is reflected in different time periods in a day, so a typical daily load curve is mainly adopted in the power analysis. Considering that the new energy generation output and the load demand have great difference in different seasons and months of the year, the average daily power curve of each month is generated by taking the month as a basic unit, and the following is the same.
Based on 8760-hour whole-sample actual operation data in each region, load demand daily average power curve in each month in each region is collated and calculated:
Figure BDA0003166391160000061
in the formula, La,m,tIs the average load demand of region a at mth month t, La,m,d,tThe load demand at D, t, D, of the mth month, D, of the region amDay m month.
(2) Calculating the average power curve of wind power output of a single region
Based on 8760-hour full-sample actual operation data in each region, wind power output daily average power curve in each month in each region is collated and calculated:
Figure BDA0003166391160000062
in the formula, Pwa,m,tMean wind power output Pw of mth month and tth month in a region aa,m,d,tThe wind power output is the wind power output of the region a at the mth month, the tth day and the tth day.
(3) Calculating the average power curve of the photovoltaic power generation output of a single region
Based on 8760-hour full-sample actual operation data in each region, the average power curve of the photovoltaic power generation output day in each month in each region is calculated in an arranging manner:
Figure BDA0003166391160000071
in the formula, Psa,m,tIs the average photovoltaic power generation output, Ps, of the mth month and the tth month of the a regiona,m,d,tThe photovoltaic power generation output is at mth month, tth day and tth day of a region a.
(4) Calculating a single region payload average power curve
Calculating a net load daily average power curve in each month of each region based on a daily average power curve of load demands of each region, a daily average power curve of wind power output and a daily average power curve of photovoltaic power generation output:
NLa,m,t＝La,m,t-Pwa,m,t-Psa,m,t
in the formula, NLa,m,tIs the net load at the mth month t of the a region.
(5) Calculating the average daily peak-valley difference of the net load average power curve of a single region
Calculating the average daily peak-valley difference based on the net load average power curve of each region to depict the peak regulation pressure of the power system in each region:
VNLa,m＝max(NLa,m,t)-min(NLa,m,t)
in the formula, VNLa,mThe average daily peak-to-valley difference of the m-th month net load average power curve of the a region.
(6) Calculating a two-region aggregate payload average power curve
Calculating an aggregate curve of two areas with the possibility of power networking by summing the net load average power curves of the two areas, wherein the influence of time zone difference between the two areas is considered:
SNLm,t＝NLa,m,t+NLb,m,t+T
in the formula, SNLm,tThe total net load at the mth month and the tth time of the two regions, and T is the time difference between the two regions a and b.
(7) Calculating the average daily peak-valley difference of the total net load average power curve of the two regions
Calculating the average daily peak-valley difference based on the total net load average power curve of the two regions to depict the total peak regulation pressure of the power system after the two regions fully realize power networking:
VSNLm＝max(SNLm,t)-min(SNLm,t)
in the formula, VSNLmThe average daily peak-to-valley difference of the payload average power curve is summed for the two region month m.
(8) Calculating the net load complementation effect between the areas: comparing the sum of the average daily peak-to-valley differences of the individual region net load average power curves with the average daily peak-to-valley difference of the two region aggregate net load average power curves:
ΔV＝VNLa,m+VNLb,m-VSNLm
in the formula,. DELTA.VThe difference between the sum of the average daily peak-valley differences of the net load average power curves of two single areas and the average daily peak-valley difference of the net load average power curves of two areas can be used for analyzing the peak shaving value of the networking of the two areas. If ΔVA positive number indicates that the two regions have power networking complementarity, ΔVA larger value of (a) indicates a greater networking complementarity.
According to the above steps, converting DeltaVThe area with a large value of (2) is determined as the area to be planned.
The step 1 specifically comprises the following steps:
determining key peak shaving parameters required by planning according to each region to be planned, which specifically comprises the following steps: the method is used for determining the peak shaving coefficient upper limit of the cross-regional interconnected power grid and determining the total peak shaving capacity of various peak shaving resources of the system to meet the peak shaving capacity requirement of the system.
The determination process of the peak regulation coefficient upper limit of the cross-region interconnected power grid is as follows:
(a) defining maximum and minimum transmission power coefficients (relative to the transmission channel capacity, such as 100% and 20%) of the trans-regional transmission channel, and calculating the maximum peak regulation depth of the trans-regional transmission channel:
πMIN,g·Cgg,t≤Ptg,t≤πMAX,g·Cgg,t
Ag＝πMAX,g-πMIN,g
in the formula, piMIN，gIs the minimum transmission power coefficient, pi, of the transregional transmission channel gMAX，gIs the maximum power transmission power coefficient, Cg, of the cross-region power transmission channel gg,tLine capacity, Pt, of transregional transmission channel g of year tg,tIs the transmission capacity of the transregional transmission channel g of the t year, AgIs the maximum peak shaver depth of the trans-regional power transmission channel g.
(b) The networking peaking effect of the cross-regional networking channel should not exceed the inter-regional net load complementary effect:
Ag·Cgg,t≤ΔV。
(c) judging whether the cross-regional networking channel is unidirectional or bidirectional power transmission, and determining that the channel is the upper limit (maximum peak regulation effect coefficient) of the sum of peak regulation coefficients of the two end regions of the line:
0≤μg,r+μg,x≤Ug(g∈Ωx2r,Ωr2x)
Figure BDA0003166391160000081
in the formula, mug,rIs the peak regulation coefficient mu of the transregional power transmission channel g in the region r to be plannedg,xFor the peak regulation coefficient, U, of the transregional power transmission channel g in the region x to be plannedgIs the maximum peak regulation coefficient, omega, of the cross-region power transmission channel gx2rFor the region r to be plannedSet of power transmission channels, omega, for power reception in planning region xr2xAnd the power transmission channel set is used for transmitting power to the area x to be planned for the area r to be planned.
The following is to make clear that the total peak regulation capacity of various peak regulation resources of the system needs to meet the peak regulation capacity requirement of the system:
the total peak regulation capacity of various peak regulation resources of the system needs to meet the peak regulation capacity requirement of the system. The peak shaving resources comprise various power supplies, trans-regional power grids, demand response and energy storage. The peak regulation capacity of the system depends on the fluctuation of load and the fluctuation of the output of a fluctuating power supply (mainly wind power and photovoltaic power generation).
Figure BDA0003166391160000091
In the formula, omegasprFor a set of power supplies with peak shaving capability in the region r to be planned, mus,rThe average peak regulation depth, Cs, of the class-rs power supply of the region to be planneds,r,tCumulative installed capacity, Ω, of the s power type for the t-th region r to be plannedx2rSet of power transmission channels, mu, for the region r to be planned to receive power from the region x to be plannedg,rFor the peak-shaving coefficient, Pt, of the transmission channel g in the region r to be plannedg,tIs the transmission capacity, omega, of the transmission channel g of the year tr2xSet of power transmission channels, Ω, for transmitting power from the region r to be planned to the region x to be planneddprFor a demand response set, Cd, with peak shaving capability in an area r to be plannedd,r,tFor the d-th class demand response capacity, omega, of the t-th to-be-planned area rcprFor the energy storage set with peak regulation capability in the region r to be planned, Ccc,r,tInstalled capacity, lambda, for storing energy of class c of the area r to be planned in the t-th yearr,tA predicted value of load peak-valley difference rate, Fp, of the t-th to-be-planned area rr,tIs the predicted value of the maximum load of the t-th area r to be planned, omegasvFor fluctuating power supply sets, vsThe peak regulation demand coefficient of the s-th type fluctuating power supply.
The step 2 specifically comprises the following steps:
establishing a target function by taking the minimum net present value of the total cost of the power system in a set planning period as a target based on the key peak regulation parameters;
the objective function of the model is to minimize the net present value of the total system cost in the planning period, including power supply construction cost, power grid construction cost, demand side resource utilization cost, energy storage installation cost, system operation cost and emission cost.
The objective function is determined as follows:
Figure BDA0003166391160000092
wherein F is the net present value of the total cost of the power system in the planning period, T is the year, T is the time length of the planning period, A1For the cost of power supply construction, A2For the cost of the grid construction, A3To demand side resource utilization cost, A4For storing installation costs, A5For the system running cost, A6For system emission cost, R is the discount rate;
wherein, the power supply construction cost A1Calculated as follows:
Figure BDA0003166391160000093
in the formula, omegarFor planning the set of regions to be planned, ΩsIs a collection of power source species, Css,r,tCumulative installed capacity, Q, for the s power type of the t year to be planned area rs,r,tRetired capacity for the s power type of the t-th region r to be plannedsThe installed cost per unit capacity of the power supply of the s-th type;
cost of power grid construction A2Calculated as follows:
Figure BDA0003166391160000101
in the formula, omegagFor cross-regional collection of power transmission channels, Cgg,tCapacity of the g-th power transmission channel in the t year, PgFor the g-th power transmissionPer unit capacity expansion cost of the track;
cost of demand side resource utilization A3Calculated as follows:
Figure BDA0003166391160000102
in the formula, omegaeFor energy-efficient plant species collections, Cee,r,tInstalled capacity, P, of energy efficient power plant of type e for area r to be planned in year teThe unit capacity expansion cost, omega, of the class e energy efficiency power plantdFor demand response class set, Cdd,r,tClass d demand response capacity for the t-th to-be-planned area r, EdIncentive costs for class d demand responses;
cost of energy storage installation A4Calculated as follows:
Figure BDA0003166391160000103
in the formula, omegacFor a set of energy storage categories, Ccc,r,tInstalled capacity, P, for storing energy of class c of area r to be planned in the t yearcThe unit capacity expansion cost of the class c energy storage;
system running cost a5Calculated as follows:
Figure BDA0003166391160000104
in the formula, HsAnnual utilization hours for the s power supply, EsThe operation cost of the power supply of the s-th type is the unit electric quantity operation cost;
system emission cost a6Calculated as follows:
Figure BDA0003166391160000105
in the formula, Mcs,tIs the carbon emission coefficient, Pr, of the s power supply of the t yearCTo carbon emissionAnd (4) cost.
Based on the key peak shaving parameters, the target function is constrained by using the peak shaving capacity of the power system of each to-be-planned area, the peak shaving coefficient of the cross-regional power grid, the power balance of each to-be-planned area, the electric quantity balance of each to-be-planned area, the power transmission capacity of each channel between each to-be-planned area, the power transmission electric quantity of each channel between each to-be-planned area, the regulating rate of the system of each to-be-planned area, the expansion scale of various power sources of each to-be-planned area, the expansion scale of each power transmission channel between each to-be-planned area, the total renewable energy target, the total carbon dioxide emission amount, the total sulfur dioxide emission amount and the total nitrogen oxide emission amount as constraint conditions, and a multi-region power system planning model considering the peak shaving of the cross-regional power grid is established.
The method is mainly used for determining the peak shaving capacity constraint of the power system of each region to be planned and the peak shaving coefficient constraint of the trans-regional power grid.
The peak regulation capacity constraint expression of the power system of the area to be planned is determined according to the following formula:
Figure BDA0003166391160000106
in the formula, omegasprFor a set of power supplies with peak shaving capability in the region r to be planned, mus,rThe average peak regulation depth, Cs, of the class-rs power supply of the region to be planneds,r,tCumulative installed capacity, Ω, of the s power type for the t-th region r to be plannedx2rSet of power transmission channels, mu, for the region r to be planned to receive power from the region x to be plannedg,rFor the peak-shaving coefficient, Pt, of the transmission channel g in the region r to be plannedg,tIs the transmission capacity, omega, of the transmission channel g of the year tr2xSet of power transmission channels, Ω, for transmitting power from the region r to be planned to the region x to be planneddprFor a demand response set, Cd, with peak shaving capability in an area r to be plannedd,r,tFor the d-th class demand response capacity, omega, of the t-th to-be-planned area rcprFor the energy storage set with peak regulation capability in the region r to be planned, Ccc,r,tInstalled capacity, lambda, for storing energy of class c of the area r to be planned in the t-th yearr,tFor the area r to be planned in the t-th yearLoad peak-to-valley difference rate prediction value, Fpr,tIs the predicted value of the maximum load of the t-th area r to be planned, omegasvFor fluctuating power supply sets, vsThe peak regulation demand coefficient of the s-th type fluctuating power supply.
The method for establishing the cross-regional power grid peak regulation coefficient constraint expression comprises the following steps:
0≤μg,r+μg,x≤Ug(g∈Ωx2r,Ωr2x)
in the formula, mug,rIs the peak regulation coefficient mu of the transregional power transmission channel g in the region r to be plannedg,xFor the peak regulation coefficient, U, of the transregional power transmission channel g in the region x to be plannedgIs the maximum peak regulation coefficient, omega, of the cross-region power transmission channel gx2rSet of power transmission channels, Ω, for the region r to be planned to receive power from the region x to be plannedr2xAnd the power transmission channel set is used for transmitting power to the area x to be planned for the area r to be planned.
And power balance constraint of each region to be planned:
the constraint aims to ensure the balance of power supply and demand of each region to be planned, wherein trans-regional power transmission and power transmission line loss are considered, and the constraint is determined according to the following formula:
Figure BDA0003166391160000111
in the formula, Confs,rThe peak load output confidence coefficient, lambda, of the s-th power supply in the region r to be plannedg,rIs the transmission support coefficient l of the transregional transmission channel g at the time of the maximum load of the region r to be plannedgIs the transmission line loss rate of the transregional transmission channel grThe average transmission and distribution line loss rate in the area r to be planned is represented by eta, which is a standby coefficient.
And electric quantity balance constraint of each region to be planned:
the constraint aims to ensure the balance of the power supply and demand of the electric quantity of each region to be planned, wherein the trans-regional power transmission and the power transmission line loss are considered, and the constraint is determined according to the following formula:
Figure BDA0003166391160000112
in the formula, Etg,tThe value of the electric quantity, Fe, transmitted for the transregional transmission channel g of the t yearr,tThe predicted value of the electric quantity demand of the t-th to-be-planned area r, picThe charge-discharge efficiency of the class c stored energy.
And (3) transmission capacity constraint:
the constraint aims to ensure that the transmission power of each trans-regional transmission channel is within a reasonable range, and is determined according to the following formula:
πMIN,g·Cgg,t≤Ptg,t≤πMAX,g·Cgg,t。
and (3) transmission electric quantity constraint:
the constraint aims to ensure that the annual electric quantity transmitted by each trans-regional power transmission channel does not exceed the annual maximum electric quantity transmitted by the trans-regional power transmission channel, and is determined according to the following formula:
Etg,t≤Cgg,t·Hg
in the formula, HgThe maximum annual utilization hours of the trans-regional transmission channel g.
And (3) system regulation rate constraint of each region to be planned:
the total regulation rate of various flexible resources of the system needs to meet the requirements of load fluctuation and uncertain power output fluctuation on the regulation rate of the system, and is determined according to the following formula:
Figure BDA0003166391160000121
in the formula, deltas,rAdjusting the output power of the class-rs power supply of the region to be planned, deltad,rAdjusting the output rate, delta, of the class rd demand response resource for the area to be planned rc,rRegulating the output of class rC energy storage in the region to be planned by a rate deltal,rAnd the change rate of the load demand of the region r to be planned in unit time.
And power supply expansion scale constraint:
considering factors such as the endowment of various resources of each region to be planned, the power supply construction speed and the like, setting various power supply expansion scale constraints of each region to be planned, and determining according to the following formula:
0≤Css,r,t-Css,r,t-1+Qs,r,t≤Csms,r,t
in the formula, Csms,r,tThe maximum construction capacity of the class s power supply of the area r to be planned in the t year.
And (3) power transmission channel expansion scale constraint:
considering factors such as available power transmission corridors, line construction speed and the like, setting expansion scale constraints of each power transmission channel, and determining according to the following formula:
0≤Cgg,t-Cgg,t-1≤Cgmg,t
in the formula, Cgmg,tThe maximum expansion capacity of the transregional power transmission channel g in the t year.
Renewable energy target constraints:
setting the constraint according to the set target of each region to be planned for the development of the renewable energy sources, and determining according to the following formula:
Figure BDA0003166391160000131
in the formula, omegasrFor a set of renewable power types, αr,tThe proportion target value of the renewable power source is the t year of the area r to be planned.
Carbon dioxide emission constraint:
in order to reduce carbon emission of the power system and promote low-carbon development of the power system, the upper limit constraint of the total carbon dioxide emission of the system is set and determined according to the following formula:
Figure BDA0003166391160000132
in the formula, Ecr,tThe upper limit of the carbon dioxide emission of the electric power system in the t year of the area r to be planned.
And (3) sulfur dioxide emission restriction:
in order to reduce the pollutant emission of the power system, the upper limit constraint of the total sulfur dioxide emission amount of the system is set and is determined according to the following formula:
Figure BDA0003166391160000133
in the formula, Mss,tIs the sulfur dioxide emission coefficient of the s power supply in the t yearr,tThe upper limit of the sulfur dioxide emission of the electric power system in the t year of the area r to be planned.
Nitrogen oxide emission constraints:
in order to reduce pollutant emission of the power system, setting an upper limit constraint of total nitrogen oxide emission of the system, and determining according to the following formula:
Figure BDA0003166391160000134
in the formula, Mns,tThe nitrogen oxide emission coefficient of the s power supply in the t year, Enr,tThe upper limit of the emission of nitrogen oxides of the electric power system in the t year of the region r to be planned.
After the cross-regional power grid peak shaving is considered, the selection of peak shaving resources in system planning is enriched, the whole peak shaving capacity of the system can be accurately and comprehensively depicted, the reasonable development scale of new energy can be determined, and the construction of a novel power system taking the new energy as a main body can be better supported.
Example 2:
based on the same inventive concept, the present invention further provides a multi-region power system planning system considering cross-region power grid peak shaving, as shown in fig. 2, including: the system comprises a calculation module, a model module and a planning module;
the calculation module is used for determining key peak shaving parameters required by the planning of the power system based on each region to be planned;
the model module is used for establishing a multi-region power system planning model considering key peak regulation parameters and considering cross-region power grid peak regulation;
the planning module plans the power system of each to-be-planned area based on the value of the key peak shaving parameter and the value of the necessary power parameter of each to-be-planned area and the multi-area power system planning model considering the cross-area power grid peak shaving;
the multi-region power system planning model considering the cross-region power grid peak shaving is established according to the peak shaving capacity constraint of each to-be-planned region power system and the cross-region power grid peak shaving coefficient constraint.
Wherein, the model module includes: an objective function unit and a constraint unit;
the target function unit is used for establishing a target function by taking the minimum net present value of the total cost of the power system in a set planning period as a target on the basis of the key peak shaving parameters;
and the constraint unit is used for constraining the target function by using the peak regulation capacity of the power system of each to-be-planned area, the peak regulation coefficient of the cross-regional power grid, the power balance of each to-be-planned area, the power transmission capacity of each channel between each to-be-planned area, the system regulation rate of each to-be-planned area, the expansion scale of each power supply of each to-be-planned area, the expansion scale of each power transmission channel between each to-be-planned area, the total target of renewable energy, the total amount of carbon dioxide emission, the total amount of sulfur dioxide emission and the total amount of nitrogen oxide emission as constraint conditions based on the key peak regulation parameters, and establishing a multi-region power system planning model considering the peak regulation of the cross-regional power grid.
The peak regulation capacity constraint of the power system of the area to be planned is determined according to the following formula:
Figure BDA0003166391160000141
in the formula, omegasprFor a set of power supplies with peak shaving capability in the region r to be planned, mus,rThe average peak regulation depth, Cs, of the class-rs power supply of the region to be planneds,r,tCumulative installed capacity, Ω, of the s power type for the t-th region r to be plannedx2rSet of power transmission channels, mu, for the region r to be planned to receive power from the region x to be plannedg,rFor the peak-shaving coefficient, Pt, of the transmission channel g in the region r to be plannedg,tIs the transmission capacity, omega, of the transmission channel g of the year tr2xA set of power transmission channels for transmitting power to an area x to be planned for an area r to be planned,Ωdprfor a demand response set, Cd, with peak shaving capability in an area r to be plannedd,r,tFor the d-th class demand response capacity, omega, of the t-th to-be-planned area rcprFor the energy storage set with peak regulation capability in the region r to be planned, Ccc,r,tInstalled capacity, lambda, for storing energy of class c of the area r to be planned in the t-th yearr,tA predicted value of load peak-valley difference rate, Fp, of the t-th to-be-planned area rr,tIs the predicted value of the maximum load of the t-th area r to be planned, omegasvFor fluctuating power supply sets, vsThe peak regulation demand coefficient of the s-th type fluctuating power supply.
And (3) restraining the peak shaving coefficient of the trans-regional power grid, and determining according to the following formula:
0≤μg,r+μg,x≤Ug(g∈Ωx2r,Ωr2x)
in the formula, mug,rIs the peak regulation coefficient mu of the transregional power transmission channel g in the region r to be plannedg,xFor the peak regulation coefficient, U, of the transregional power transmission channel g in the region x to be plannedgIs the maximum peak regulation coefficient, omega, of the cross-region power transmission channel gx2rSet of power transmission channels, Ω, for the region r to be planned to receive power from the region x to be plannedr2xAnd the power transmission channel set is used for transmitting power to the area x to be planned for the area r to be planned.
Wherein, the maximum peak regulation depth U of the cross-region power transmission channel ggCalculated as follows:
Figure BDA0003166391160000151
in the formula, AgThe maximum peak shaving depth of the cross-region power transmission channel g;
maximum peak shaving depth A of cross-region power transmission channel ggCalculated as follows:
Ag＝πMAX,g-πMIN,g
in the formula, piMIN，gIs the minimum transmission power coefficient, pi, of the transregional transmission channel gMAX，gIs the maximum transmission power coefficient of the trans-regional transmission channel g.
The objective function is determined as follows:
Figure BDA0003166391160000152
wherein F is the net present value of the total cost of the power system in the planning period, T is the year, T is the time length of the planning period, A1For the cost of power supply construction, A2For the cost of the grid construction, A3To demand side resource utilization cost, A4For storing installation costs, A5For the system running cost, A6For system emission cost, R is the discount rate;
wherein, the power supply construction cost A1Calculated as follows:
Figure BDA0003166391160000153
in the formula, omegarFor planning the set of regions to be planned, ΩsIs a collection of power source species, Css,r,tCumulative installed capacity, Q, for the s power type of the t year to be planned area rs,r,tRetired capacity for the s power type of the t-th region r to be plannedsThe installed cost per unit capacity of the power supply of the s-th type;
cost of power grid construction A2Calculated as follows:
Figure BDA0003166391160000154
in the formula, omegagFor cross-regional collection of power transmission channels, Cgg,tCapacity of the g-th power transmission channel in the t year, PgThe unit capacity expansion cost of the g-th power transmission channel is obtained;
cost of demand side resource utilization A3Calculated as follows:
Figure BDA0003166391160000155
in the formula, omegaeFor energy-efficient plant species collections, Cee,r,tInstalled capacity, P, of energy efficient power plant of type e for area r to be planned in year teThe unit capacity expansion cost, omega, of the class e energy efficiency power plantdFor demand response class set, Cdd,r,tClass d demand response capacity for the t-th to-be-planned area r, EdIncentive costs for class d demand responses;
cost of energy storage installation A4Calculated as follows:
Figure BDA0003166391160000161
in the formula, omegacFor a set of energy storage categories, Ccc,r,tInstalled capacity, P, for storing energy of class c of area r to be planned in the t yearcThe unit capacity expansion cost of the class c energy storage;
system running cost a5Calculated as follows:
Figure BDA0003166391160000162
in the formula, HsAnnual utilization hours for the s power supply, EsThe operation cost of the power supply of the s-th type is the unit electric quantity operation cost;
system emission cost a6Calculated as follows:
Figure BDA0003166391160000163
in the formula, Mcs,tIs the carbon emission coefficient, Pr, of the s power supply of the t yearCWhich is a carbon emission cost.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the scope of protection thereof, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: after reading this disclosure, those skilled in the art will be able to make various changes, modifications and equivalents to the embodiments of the invention, which fall within the scope of the appended claims.

Claims (10)

1. A multi-region power system planning method considering cross-region power grid peak shaving is characterized by comprising the following steps:
determining key peak shaving parameters required by the planning of the power system based on each region to be planned;
establishing a multi-region power system planning model considering key peak regulation parameters and considering cross-region power grid peak regulation;
planning the power system of each to-be-planned area based on the value of the key peak shaving parameter and the value of the necessary power parameter of each to-be-planned area and the multi-area power system planning model considering the cross-area power grid peak shaving;
the multi-region power system planning model considering the cross-region power grid peak shaving is established according to the peak shaving capacity constraint of each to-be-planned region power system and the cross-region power grid peak shaving coefficient constraint.
2. The method of claim 1, wherein the establishing a multi-zone power system planning model that accounts for cross-zone grid peaking in view of key peaking parameters comprises:
establishing a target function by taking the minimum net present value of the total cost of the power system in a set planning period as a target based on the key peak regulation parameters;
based on the key peak shaving parameters, the target function is constrained by using the peak shaving capacity of the power system of each to-be-planned area, the peak shaving coefficient of the cross-regional power grid, the power balance of each to-be-planned area, the electric quantity balance of each to-be-planned area, the power transmission capacity of each channel between each to-be-planned area, the power transmission electric quantity of each channel between each to-be-planned area, the regulating rate of the system of each to-be-planned area, the expansion scale of various power sources of each to-be-planned area, the expansion scale of each power transmission channel between each to-be-planned area, the total renewable energy target, the total carbon dioxide emission amount, the total sulfur dioxide emission amount and the total nitrogen oxide emission amount as constraint conditions, and a multi-region power system planning model considering the peak shaving of the cross-regional power grid is established.
3. The method of claim 2, wherein the peak shaving capacity constraint of the power system of the area to be planned is determined according to the following equation:
Figure FDA0003166391150000011
in the formula, omegasprFor a set of power supplies with peak shaving capability in the region r to be planned, mus,rThe average peak regulation depth, Cs, of the class-rs power supply of the region to be planneds,r,tCumulative installed capacity, Ω, of the s power type for the t-th region r to be plannedx2rSet of power transmission channels, mu, for the region r to be planned to receive power from the region x to be plannedg,rFor the peak-shaving coefficient, Pt, of the transmission channel g in the region r to be plannedg,tIs the transmission capacity, omega, of the transmission channel g of the year tr2xSet of power transmission channels, Ω, for transmitting power from the region r to be planned to the region x to be planneddprFor a demand response set, Cd, with peak shaving capability in an area r to be plannedd,r,tFor the d-th class demand response capacity, omega, of the t-th to-be-planned area rcprFor the energy storage set with peak regulation capability in the region r to be planned, Ccc,r,tInstalled capacity, lambda, for storing energy of class c of the area r to be planned in the t-th yearr,tA predicted value of load peak-valley difference rate, Fp, of the t-th to-be-planned area rr,tIs the predicted value of the maximum load of the t-th area r to be planned, omegasvFor fluctuating power supply sets, vsThe peak regulation demand coefficient of the s-th type fluctuating power supply.
4. The method of claim 2, wherein the cross-regional grid peaking factor constraint is determined according to the following equation:
0≤μg,r+μg,x≤Ug(g∈Ωx2r,Ωr2x)
in the formula, mug,rFor peak regulation of transregional power transmission channel g in region r to be plannedCoefficient, μg,xFor the peak regulation coefficient, U, of the transregional power transmission channel g in the region x to be plannedgIs the maximum peak regulation coefficient, omega, of the cross-region power transmission channel gx2rSet of power transmission channels, Ω, for the region r to be planned to receive power from the region x to be plannedr2xA power transmission channel set for transmitting power to an area x to be planned for an area r to be planned;
wherein, the maximum peak regulation depth U of the cross-region power transmission channel ggCalculated as follows:
Figure FDA0003166391150000021
in the formula, AgThe maximum peak shaving depth of the cross-region power transmission channel g;
maximum peak shaving depth A of cross-region power transmission channel ggCalculated as follows:
Ag＝πMAX,g-πMIN,g
in the formula, piMIN，gIs the minimum transmission power coefficient, pi, of the transregional transmission channel gMAX，gIs the maximum transmission power coefficient of the trans-regional transmission channel g.
5. The method of claim 2, wherein the objective function is determined according to the following equation:
Figure FDA0003166391150000022
wherein F is the net present value of the total cost of the power system in the planning period, T is the year, T is the time length of the planning period, A1For the cost of power supply construction, A2For the cost of the grid construction, A3To demand side resource utilization cost, A4For storing installation costs, A5For the system running cost, A6For system emission cost, R is the discount rate;
wherein, the power supply construction cost A1Calculated as follows:
Figure FDA0003166391150000023
in the formula, omegarFor planning the set of regions to be planned, ΩsIs a collection of power source species, Css,r,tCumulative installed capacity, Q, for the s power type of the t year to be planned area rs,r,tRetired capacity for the s power type of the t-th region r to be plannedsThe installed cost per unit capacity of the power supply of the s-th type;
cost of power grid construction A2Calculated as follows:
Figure FDA0003166391150000024
in the formula, omegagFor cross-regional collection of power transmission channels, Cgg,tCapacity of the g-th power transmission channel in the t year, PgThe unit capacity expansion cost of the g-th power transmission channel is obtained;
cost of demand side resource utilization A3Calculated as follows:
Figure FDA0003166391150000031
in the formula, omegaeFor energy-efficient plant species collections, Cee,r,tInstalled capacity, P, of energy efficient power plant of type e for area r to be planned in year teThe unit capacity expansion cost, omega, of the class e energy efficiency power plantdFor demand response class set, Cdd,r,tClass d demand response capacity for the t-th to-be-planned area r, EdIncentive costs for class d demand responses;
cost of energy storage installation A4Calculated as follows:
Figure FDA0003166391150000032
in the formula，ΩcFor a set of energy storage categories, Ccc,r,tInstalled capacity, P, for storing energy of class c of area r to be planned in the t yearcThe unit capacity expansion cost of the class c energy storage;
system running cost a5Calculated as follows:
Figure FDA0003166391150000033
in the formula, HsAnnual utilization hours for the s power supply, EsThe operation cost of the power supply of the s-th type is the unit electric quantity operation cost;
system emission cost a6Calculated as follows:
Figure FDA0003166391150000034
in the formula, Mcs,tIs the carbon emission coefficient, Pr, of the s power supply of the t yearCWhich is a carbon emission cost.
6. The method of claim 1, wherein the obtaining of the area to be planned comprises:
and calculating an inter-region net load complementation effect value, and taking the region of which the inter-region net load complementation effect value is greater than a preset inter-region power networking complementarity value as a region to be planned.
7. The method of claim 6, wherein the inter-region payload complementation effect value is calculated as:
ΔV＝VNLr,m+VNLx,m-VSNLm
in the formula,. DELTA.VFor net load complementary effect values between the region r to be planned and the region x to be planned, VNLr,mThe average daily peak-to-valley difference of the net load average power curve of the mth month of the region to be planned, VNLx,mIs the average daily peak-to-valley difference, VSNL, of the net load average power curve of the mth month of the area x to be plannedmAnd adding the average daily peak-valley difference of the net load average power curve for the m th month of the region r to be planned and the region x to be planned.
8. The method of claim 1, wherein the key peak shaver parameters comprise:
the maximum power transmission power coefficient of each power transmission channel, the minimum power transmission power coefficient of each power transmission channel, the accumulated installed capacity of each power supply at the preset time of each region to be planned, each demand response capacity at the preset time of each region to be planned, the installed capacity of each energy storage at the preset time of each region to be planned, the line capacity at the preset time of each power transmission channel, the power transmission capacity at the preset time of each power transmission channel, the peak regulation coefficient of each power transmission channel at each region to be planned, the maximum peak regulation effect coefficient of each power transmission channel, the average peak regulation depth of each power supply at each region to be planned, the load peak-valley difference prediction value at the preset time of each region to be planned, the maximum load prediction value at the preset time of each region to be planned and the peak regulation demand coefficient of each power supply.
9. The method of claim 1, wherein the necessary power parameters for each area to be planned include:
retired capacity of various power supplies in preset time of each to-be-planned area, installed capacity of various energy efficiency power plants in preset time of each to-be-planned area, annual utilization hours of various power supplies in each to-be-planned area, peak-to-load output confidence coefficient of various power supplies in each to-be-planned area, power transmission support coefficient of each power transmission channel at maximum load moment of each to-be-planned area, power transmission line loss rate of each power transmission channel, average power transmission and distribution line loss rate in each to-be-planned area, charge and discharge efficiency of various stored energy, electric quantity demand predicted value in preset time of each to-be-planned area, annual maximum utilization hours of each power transmission channel, output regulation rate of various power supplies in each to-be-planned area, output regulation rate of various demand response resources in each to-planned area, output regulation rate of various stored energy in each to-planned area, load demand change rate in unit time of each to-planned area, output regulation rate of various to-planned areas, output regulation rate of various energy storage capacity of each to-planned area, and load demand change rate in unit time of each to-planned area, The method comprises the steps of obtaining the maximum construction capacity of various power supplies in preset time of each to-be-planned area, the maximum expansion capacity of each power transmission channel in preset time, the renewable power supply ratio target value in preset time of each to-be-planned area, the carbon emission coefficient of various power supplies in preset time of each to-be-planned area, the carbon dioxide emission upper limit in preset time of each to-be-planned area, the sulfur dioxide emission coefficient of various power supplies in preset time of each to-be-planned area, the sulfur dioxide emission upper limit in preset time of each to-be-planned area, the nitrogen oxide emission coefficient of various power supplies in preset time of each to-be-planned area and the nitrogen oxide emission upper limit in preset time of each to-be-planned area.
10. A multi-zone power system planning system that accounts for cross-zone power grid peak shaving, comprising: the system comprises a calculation module, a model module and a planning module;
the calculation module is used for determining key peak shaving parameters required by the planning of the power system based on each region to be planned;
the model module is used for establishing a multi-region power system planning model considering key peak regulation parameters and considering cross-region power grid peak regulation;
the planning module plans the power system of each to-be-planned area based on the value of the key peak shaving parameter and the value of the necessary power parameter of each to-be-planned area and the multi-area power system planning model considering the cross-area power grid peak shaving;
the multi-region power system planning model considering the cross-region power grid peak shaving is established according to the peak shaving capacity constraint of each to-be-planned region power system and the cross-region power grid peak shaving coefficient constraint.
CN202110805564.2A 2021-07-16 2021-07-16 Multi-region power system planning method and system considering cross-region power grid peak shaving Pending CN113725912A (en)

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