WO2023179118A1 - Method and system for optimizing direct-current power transmission curve of multi-energy complementary integrated external transmission base - Google Patents
Method and system for optimizing direct-current power transmission curve of multi-energy complementary integrated external transmission base Download PDFInfo
- Publication number
- WO2023179118A1 WO2023179118A1 PCT/CN2022/139573 CN2022139573W WO2023179118A1 WO 2023179118 A1 WO2023179118 A1 WO 2023179118A1 CN 2022139573 W CN2022139573 W CN 2022139573W WO 2023179118 A1 WO2023179118 A1 WO 2023179118A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- power
- power transmission
- curve
- peak
- receiving end
- Prior art date
Links
- 230000005540 biological transmission Effects 0.000 title claims abstract description 220
- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000000295 complement effect Effects 0.000 title claims abstract description 25
- 230000033228 biological regulation Effects 0.000 claims abstract description 27
- 238000005457 optimization Methods 0.000 claims description 23
- 230000008859 change Effects 0.000 claims description 17
- 238000012384 transportation and delivery Methods 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 4
- 238000009826 distribution Methods 0.000 claims description 4
- 230000006835 compression Effects 0.000 claims description 3
- 238000007906 compression Methods 0.000 claims description 3
- 238000009434 installation Methods 0.000 claims description 3
- 238000010248 power generation Methods 0.000 abstract description 10
- 238000004146 energy storage Methods 0.000 abstract 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 13
- 238000011161 development Methods 0.000 description 7
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 5
- 229910052799 carbon Inorganic materials 0.000 description 5
- 238000011160 research Methods 0.000 description 5
- 238000004088 simulation Methods 0.000 description 5
- 238000004422 calculation algorithm Methods 0.000 description 4
- 230000007423 decrease Effects 0.000 description 4
- 230000005611 electricity Effects 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 4
- 230000000877 morphologic effect Effects 0.000 description 4
- 238000005265 energy consumption Methods 0.000 description 3
- 238000003860 storage Methods 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 230000001186 cumulative effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000035515 penetration Effects 0.000 description 2
- 238000013439 planning Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000004308 accommodation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003245 coal Substances 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000004660 morphological change Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000000844 transformation 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
- H02J3/38—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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- 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
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
-
- 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
- H02J3/36—Arrangements for transfer of electric power between ac networks via a high-tension dc link
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based 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
- 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
-
- 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
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/60—Arrangements for transfer of electric power between AC networks or generators via a high voltage DC link [HVCD]
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
Disclosed in the present invention are a method and system for optimizing a direct-current power transmission curve of a multi-energy complementary integrated external transmission base. The method comprises: according to direct-current annual power transmission curves based on resource matching and load matching under the same number of direct-current utilization hours, and in combination with a clean energy curtailment rate and the load matching degree of a receiving end, determining an optimal annual power transmission curve; according to the optimal annual power transmission curve and typical daily load curves of a receiving-end power grid, determining an optimal daily power transmission curve which matches a power demand of the receiving end; on the basis of the typical daily load curves of the receiving-end power grid, obtaining a peak regulation slope timing sequence; according to the peak regulation slope timing sequence, and in combination with a slope sequence-mode sequence comparison table, obtaining a peak regulation mode sequence; on the basis of the peak regulation mode sequence, calculating a peak regulation timing power transmission upper limit; and on the basis of the peak regulation timing power transmission upper limit, correcting the optimal daily power transmission curve. By means of the present invention, in a power generation system having a high percentage of clean power, such as a large-scale hydro-wind-photovoltaic integrated power generation system and a wind-photovoltaic-thermal energy storage integrated power generation system, a direct-current external transmission curve can be effectively optimized by means of taking the demands of both a transmission end and a receiving end into consideration.
Description
本发明涉及一种基于趋势模式匹配，兼顾送端资源匹配、受端负荷特性与调峰需求的多能互补一体化外送基地直流输电曲线优化方法及系统，属于新型电力系统设计领域。The invention relates to a multi-energy complementary integrated transmission base DC transmission curve optimization method and system that is based on trend pattern matching and takes into account transmission end resource matching, receiving end load characteristics and peak load regulation requirements, and belongs to the field of new power system design.
随着我国经济发展进入新常态，能源行业发展态势发生深刻转变，为实现“30.60”双碳目标，非化石能源消费在终端能源消费的占比中亟需提升。同时，为加快构建以新能源为主体的新型电力系统，新能源渗透率将不断提升，如何合理配置新能源规模，提升电网消纳能力，在满足电网安全稳定的前提下降低新能源弃电率，成为亟待解决的重要问题。As my country's economic development enters a new normal, the development trend of the energy industry has undergone profound changes. In order to achieve the "30.60" dual carbon goal, the proportion of non-fossil energy consumption in terminal energy consumption urgently needs to be increased. At the same time, in order to speed up the construction of a new power system with new energy as the main body, the penetration rate of new energy will continue to increase. How to rationally allocate the scale of new energy, improve the consumption capacity of the power grid, and reduce the rate of new energy power abandonment while ensuring the security and stability of the power grid? , has become an important issue that needs to be solved urgently.
因此，针对在风光水火储大型电源基地的多能互补领域，国内外都已开展了深入的研究，主要集中在多电源机组的优化调度、电源容量配置方法以及时序生产模拟等方面。首先，对于多电源机组的优化调度，通过建立清洁能源时空多尺度模型、优化协同调度算法以及建立综合运行管控机制这三个方面来实现，例如针对风光水多能源电力系统，提出了基于随机规划的短期优化调度方法或者通过POS算法，求解最小弃水和最低煤耗的优化目标函数；其次，对于电源规模配比，提出了利用粒子群算法与混合整数线性规划算法求解混合发电系统的容量最优配置。但是，针对以上的研究多是选择风电光伏出力的典型场景，无法对于系统运行的复杂情况进行全面的模拟，因此结合新能源特性进行时序生产模拟逐渐成为研究重点，例如通过考虑水风光出力特性、负荷特性、机组调峰能力以及电网网络传输等约束，建立清洁能源时序生产模拟模型，或者采用时序运行模拟技术验证我国某地区的联网效益。Therefore, in-depth research has been carried out at home and abroad in the field of multi-energy complementation in large-scale wind, solar, hydrothermal and thermal storage power bases, mainly focusing on the optimal dispatch of multi-power units, power capacity configuration methods, and sequential production simulation. First of all, the optimal dispatch of multi-power units is achieved through three aspects: establishing a spatio-temporal multi-scale model of clean energy, optimizing collaborative dispatch algorithms, and establishing a comprehensive operation management and control mechanism. For example, for wind, solar, and water multi-energy power systems, a stochastic planning-based method is proposed The short-term optimal dispatch method or POS algorithm is used to solve the optimization objective function of minimum water abandonment and minimum coal consumption. Secondly, for the power supply scale ratio, the particle swarm algorithm and mixed integer linear programming algorithm are proposed to solve the capacity optimization of the hybrid power generation system. configuration. However, the above studies mostly select typical scenarios of wind power and photovoltaic output, and cannot comprehensively simulate the complex conditions of system operation. Therefore, time-series production simulation based on the characteristics of new energy has gradually become a research focus, for example, by considering the output characteristics of water, wind and solar, Based on constraints such as load characteristics, unit peak shaving capacity, and power grid network transmission, a clean energy time series production simulation model can be established, or time series operation simulation technology can be used to verify the interconnection benefits in a certain region of my country.
综上可知，大规模多能互补开发的研究领域，主要聚焦在机组建模与优化调度模型的研究，以及基于刚性约束的时序生产模拟。然而，大规模多能互补基地通常通过特高压交直流通道送往负荷中心，如何兼顾送端资源特性与受端负荷、调峰特性，优化电源配比与送电曲线，成为影响多能互补基地清洁能源消纳水平与外送电力品质的关键。In summary, it can be seen that the research field of large-scale multi-energy complementary development mainly focuses on the research of unit modeling and optimal dispatch model, as well as the timing production simulation based on rigid constraints. However, large-scale multi-energy complementary bases are usually sent to load centers through UHV AC and DC channels. How to take into account the resource characteristics of the sending end and the load and peak regulation characteristics of the receiving end, and optimize the power supply ratio and power transmission curve will become an important factor affecting the multi-energy complementary bases. The key to the level of clean energy consumption and the quality of external power.
发明内容Contents of the invention
本发明的目的在于提供一种多能互补一体化外送基地直流输电曲线优化方法及系统，以解决在高比例清洁电量占比的多能互补发电系统中没有考虑送端资源匹配、受端负荷特性和调峰需求三者之间的关系的问题。The purpose of the present invention is to provide a multi-energy complementary integrated outbound transmission base DC power transmission curve optimization method and system to solve the problem that the multi-energy complementary power generation system with a high proportion of clean electricity does not consider the matching of sending end resources and the receiving end load. The relationship between characteristics and peak shaving requirements.
为实现上述目的，本发明采用如下技术方案：In order to achieve the above objects, the present invention adopts the following technical solutions:
一方面，一种多能互补一体化外送基地直流输电曲线优化方法，包括：On the one hand, a multi-energy complementary integrated delivery base DC transmission curve optimization method includes:
根据相同直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线，结合清洁能源弃电率与受端负荷匹配度，确定最优年送电曲线；Based on the DC annual power transmission curve based on resource matching and load matching under the same DC utilization hours, combined with the clean energy power abandonment rate and the matching degree of the receiving end load, the optimal annual power transmission curve is determined;
根据所述最优年送电曲线和受端电网典型日负荷曲线，确定匹配受端电力需求的最优日送电曲线；According to the optimal annual power transmission curve and the typical daily load curve of the receiving end power grid, determine the optimal daily power transmission curve that matches the receiving end power demand;
基于所述受端电网典型日负荷曲线，计算受端电网调峰平衡序列，并通过计算所述调峰平衡序列的斜率，获得调峰斜率时序序列；根据所述调峰斜率时序序列，结合斜率序列与模式序列对照表，获得调峰模式序列；Based on the typical daily load curve of the receiving end power grid, calculate the peaking balance sequence of the receiving end power grid, and obtain the peaking slope time series by calculating the slope of the peaking balance sequence; according to the peaking slope time series, combine the slope Compare the sequence and mode sequence to obtain the peak-shaving mode sequence;
基于所述调峰模式序列，计算调峰时序送电上限；基于所述调峰时序送电上限，对所述最优日送电曲线进行修正，得到兼顾受端电力需求与调峰需求的最优日送电曲线。Based on the peak shaving mode sequence, the upper limit of peak shaving timing power transmission is calculated; based on the upper limit of peak shaving timing power transmission, the optimal daily power transmission curve is corrected to obtain the optimal daily power transmission curve that takes into account both the receiving end power demand and the peak shaving demand. Excellent power transmission curve.
进一步地，所述根据相同直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线，结合清洁能源弃电率与受端负荷匹配度，确定最优年送电曲线，包括：Further, based on the DC annual power transmission curve based on resource matching and load matching under the same DC utilization hours, combined with the clean energy power abandonment rate and the matching degree of the receiving end load, the optimal annual power transmission curve is determined, including:
建立包括清洁能源弃电率与受端负荷匹配度的目标函数：Establish an objective function including the matching degree of clean energy power curtailment rate and receiving end load:
minR
g,k+λ
kR
l,k (1)
minR g,k +λ k R l,k (1)
式中，λ
k为权重因子，R
g,k为第k个月清洁能源弃电率，R
l,k为第k个月的受端负荷匹配度；
In the formula, λ k is the weighting factor, R g,k is the clean energy power curtailment rate in the kth month, R l,k is the receiving end load matching degree in the kth month;
所述目标函数的约束条件为：The constraints of the objective function are:
0≤R
g,k≤R
g,kmax (4)
0≤R g,k ≤R g,kmax (4)
式中，E
g,k、E
l,k分别为在相同直流利用小时数下第k个月依据送端资源分布的送电电量和依据受端负荷需求的送电电量，E
o,k为优化后的第k个月直流外 送送电量，ω(k)为第k个月的资源弃电指示函数，E
c,k为估算的送端电网第k个月的电量空间，R
g,kmax为第k个月的清洁能源弃电率限定值，T
dc为相同直流利用小时数，P
o max为直流外送通道的额定容量；
In the formula, E g,k and E l,k are respectively the power transmission amount based on the resource distribution of the sending end and the power transmission amount based on the load demand of the receiving end in the kth month under the same DC utilization hours. E o,k is The optimized DC external transmission power in the kth month, ω(k) is the resource curtailment indicator function in the kth month, E c,k is the estimated power space of the sending end grid in the kth month, R g, kmax is the limit value of the clean energy power abandonment rate in the kth month, T dc is the same number of DC utilization hours, and P o max is the rated capacity of the DC external transmission channel;
基于所述约束条件，对所述目标函数进行求解，得到最优年送电曲线E
o＝[E
o,1,E
o,2,...,E
o,k,...,E
o,12]。
Based on the constraints, the objective function is solved to obtain the optimal annual power transmission curve E o =[E o,1 ,E o,2 ,...,E o,k ,...,E o ,12 ].
进一步地，所述送端电网第k个月的电量空间E
c,k根据以下方法估算：
Further, the power space E c,k of the kth month of the sending end power grid is estimated according to the following method:
根据以下公式计算送端电网第k个月t时刻的电力平衡盈亏
Calculate the power balance profit and loss of the sending end power grid at time t in the kth month according to the following formula
式中，
分别代表送端电网第k个月t时刻电源出力与负荷；
In the formula, Represent the power output and load of the sending end power grid at time t in the kth month respectively;
选取
中的最小值作为第k个月装机控制时刻的电力盈亏P
c,k，则该区域内的第k个月的电量空间E
c,k，通过下式进行估算：
Select The minimum value in is taken as the power profit and loss P c,k at the installation control time of the kth month. Then the power space E c,k of the kth month in the area is estimated by the following formula:
式中，N
k代表第k个月的天数，ΔT为时段时长，T
d为一天计算总时长。
In the formula, N k represents the number of days in the kth month, ΔT is the duration of the period, and T d is the total duration of one day.
进一步地，所述根据所述最优年送电曲线和受端电网典型日负荷曲线，确定匹配受端电力需求的最优日送电曲线，包括：Further, determining the optimal daily power transmission curve that matches the power demand of the receiving end based on the optimal annual power transmission curve and the typical daily load curve of the receiving end power grid includes:
根据所述最优年送电曲线，确定第k个月的直流日送电曲线
其中T
d为一天计算总时长；
According to the optimal annual power transmission curve, the DC daily power transmission curve of the kth month is determined. Among them, T d is the total calculation time of one day;
根据第k个月的受端电网典型日负荷曲线
确定全天各时段的送电权重
According to the typical daily load curve of the receiving end power grid in the kth month Determine the power delivery weight for each time period throughout the day
式中，
代表第k个月t时刻受端电网的负荷水平，L
o,kmax、L
o,kmin分别为L
o,k中的最大值与最小值；
In the formula, Represents the load level of the receiving power grid at time t in the kth month, L o,kmax and Lo ,kmin are the maximum and minimum values in Lo ,k respectively;
基于第k个月的受端电网典型日负荷曲线和全天各时段的送电权重，建立目标函数：Based on the typical daily load curve of the receiving power grid in the kth month and the power transmission weight at each time period throughout the day, the objective function is established:
式中，
为第k个月t时刻的直流送电电量，P
o max为直流外送通道的额定 容量，N
k为第k个月的天数；
In the formula, is the DC power transmission amount at time t in the kth month, P o max is the rated capacity of the DC transmission channel, and N k is the number of days in the kth month;
所述目标函数的约束条件为：The constraints of the objective function are:
式中，ΔT为时段时长，E
o,k为第k个月的直流送电电量；
In the formula, ΔT is the period length, E o,k is the DC power transmission amount in the kth month;
基于所述约束条件，对所述目标函数进行迭代求解，获得匹配受端电力需求的最优日送电曲线
Based on the constraints, the objective function is iteratively solved to obtain the optimal daily power transmission curve that matches the power demand at the receiving end.
进一步地，所述受端电网调峰平衡序列
根据以下公式计算：
Further, the receiving end power grid peak load balancing sequence Calculated according to the following formula:
式中，
为t时刻受端电网常规电源机组的最小出力，
分别为t时刻受端电网的风电及光伏出力。
In the formula, is the minimum output of the conventional power supply unit of the receiving end power grid at time t, are respectively the wind power and photovoltaic output of the receiving end grid at time t.
进一步地，所述调峰斜率时序序列根据以下公式计算：Further, the peak shaving slope time series is calculated according to the following formula:
式中，C′
o,k为调峰斜率时序序列，
为
的变化斜率，C
o,k max为序列C
o,k中绝对值最大值，
为压缩因子。
In the formula, C′ o,k is the peak shaving slope time series, for The change slope of C o,k max is the maximum absolute value in the sequence C o,k , is the compression factor.
进一步地，调峰模式序列
根据下表获得：
Further, the peak shaving mode sequence Obtain according to the following table:
斜率序列与模式序列对照表Slope sequence and pattern sequence comparison table
其中，
为斜率模式序列变化的低阈值，
为斜率模式序列变化的中阈值，
为斜率模式序列变化的高阈值，ε
c为调峰模式序列的单位变化量。
in, is the low threshold for the slope pattern sequence change, is the mid-threshold of the slope pattern sequence change, is the high threshold for changes in the slope mode sequence, and ε c is the unit change amount of the peaking mode sequence.
进一步地，所述调峰时序送电上限根据以下公式计算得到：Further, the upper limit of power transmission in the peak regulation timing is calculated according to the following formula:
式中，
为t时刻的调峰送电上限。
In the formula, is the upper limit of peak power transmission at time t.
进一步地，所述基于所述调峰时序送电上限，对所述最优日送电曲线进行修正，包括：Further, the correction of the optimal daily power transmission curve based on the upper limit of power transmission in the peak-shaving timing sequence includes:
日送电曲线
应满足调峰送电约束：
Daily power transmission curve Peak regulation power transmission constraints should be met:
式中，
为t时刻的调峰送电上限；
In the formula, is the upper limit of peak power transmission at time t;
结合式(9)与式(14)对日送电曲线
进行迭代优化，获得兼顾受端电力需求与调峰需求的最优日送电曲线
Combining Equation (9) and Equation (14) for the Japanese power transmission curve Carry out iterative optimization to obtain the optimal daily power transmission curve that takes into account the power demand of the receiving end and the peak load regulation demand.
另一方面，一种多能互补一体化外送基地直流输电曲线优化系统，包括：On the other hand, a multi-energy complementary integrated delivery base DC transmission curve optimization system includes:
最优年送电曲线确定模块，配置为根据相同直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线，结合清洁能源弃电率与受端负荷匹配度，确定最优年送电曲线；The optimal annual power transmission curve determination module is configured to determine the optimal annual power transmission based on the DC annual power transmission curve based on resource matching and load matching under the same DC utilization hours, combined with the clean energy power abandonment rate and the matching degree of the receiving end load. curve;
最优日送电曲线确定模块，配置为根据所述最优年送电曲线和受端电网典型日负荷曲线，确定匹配受端电力需求的最优日送电曲线；The optimal daily power transmission curve determination module is configured to determine the optimal daily power transmission curve that matches the receiving end power demand based on the optimal annual power transmission curve and the typical daily load curve of the receiving end power grid;
调峰模式序列确定模块，配置为基于所述受端电网典型日负荷曲线，计算受端电网调峰平衡序列，并通过计算所述调峰平衡序列的斜率，获得调峰斜率时序序列；根据所述调峰斜率时序序列，结合斜率序列与模式序列对照表，获得调峰模式序列；The peak-shaving mode sequence determination module is configured to calculate the peak-shaving balance sequence of the receiving-end power grid based on the typical daily load curve of the receiving-end power grid, and obtain the peak-shaving slope time series by calculating the slope of the peak-shaving balance sequence; according to the required Describe the peak-shaving slope time series, and combine the slope sequence and the mode sequence comparison table to obtain the peak-shaving mode sequence;
最优日送电曲线修正模块，配置为基于所述调峰模式序列，计算调峰时序送电上限；基于所述调峰时序送电上限，对所述最优日送电曲线进行修正，得到兼顾受端电力需求与调峰需求的最优日送电曲线。The optimal daily power transmission curve correction module is configured to calculate the upper limit of peak shaving timing power transmission based on the peak shaving mode sequence; based on the upper limit of peak shaving timing power transmission, correct the optimal daily power transmission curve to obtain The optimal daily power transmission curve takes into account the power demand of the receiving end and the peak load regulation demand.
与现有技术相比，本发明所达到的有益效果是：Compared with the prior art, the beneficial effects achieved by the present invention are:
本发明在大型水风光、风光火储等高比例清洁电量占比的发电系统中，可以有效地兼顾送受端需求优化直流外送曲线，合理地优化清洁能源基地的电源配比，改善高比例新能源外送的电力品质。当前随着“碳达峰”、“碳中和”目标的提出，电力系统面临结构性的转变,以新能源为主体的电力系统将对传统电网的供电结构、电源配比、电力流向、电网拓扑等造成革命性的改变，本发明在评估直流送电系统送端电源方案时可以基于送端资源、受端负荷、受端调峰需求对直流送电曲线进行合理的设计，从而为直流运行方式、电源组织提供支撑性参考。In power generation systems with a high proportion of clean electricity, such as large-scale water, wind, solar, wind, solar, and thermal storage, the invention can effectively optimize the DC transmission curve by taking into account the needs of the sending and receiving ends, rationally optimize the power supply ratio of the clean energy base, and improve the efficiency of high-proportion new power generation. Power quality for energy delivery. With the current goals of "carbon peaking" and "carbon neutrality" being proposed, the power system is facing structural changes. The power system with new energy as the main body will change the power supply structure, power supply ratio, power flow, and power grid of the traditional power grid. topology, etc., the present invention can reasonably design the DC power transmission curve based on the resources of the sending end, the load of the receiving end, and the peak load regulation demand of the receiving end when evaluating the power supply scheme of the sending end of the DC power transmission system, thereby providing better conditions for DC operation. Provide supporting reference for methods and power organization.
图1为本发明方法总体流程图；Figure 1 is an overall flow chart of the method of the present invention;
图2为金沙江流域水电平水年出力曲线；Figure 2 shows the water level annual output curve of the Jinsha River Basin;
图3为金沙江流域风电与光伏的典型出力特性，(a)风电全年平均出力，(b)风 电四季典型出力特性，(c)光伏全年平均出力，(d)光伏四季典型出力曲线；Figure 3 shows the typical output characteristics of wind power and photovoltaic in the Jinsha River Basin, (a) the annual average output of wind power, (b) the typical output characteristics of wind power in four seasons, (c) the average annual output of photovoltaic, (d) the typical output curve of photovoltaic in four seasons;
图4为四川省电力盈亏趋势；Figure 4 shows the power profit and loss trend in Sichuan Province;
图5为白鹤滩送江苏最优年送电曲线，(a)年送电曲线优化(低方案)，(b)不同利用小时数下的年送电曲线；Figure 5 shows the optimal annual power transmission curve of Baihetan power supply to Jiangsu, (a) annual power transmission curve optimization (low plan), (b) annual power transmission curve under different utilization hours;
图6为江苏省四季典型日的负荷以及新能源出力曲线，(a)高负荷场景，(b)反调峰场景；Figure 6 shows the load and new energy output curves of typical days in four seasons in Jiangsu Province, (a) high load scenario, (b) reverse peak load scenario;
图7为各季节典型调峰时序曲线；Figure 7 shows typical peaking timing curves in each season;
图8为四季典型日最优送电曲线，(a)春季，(b)夏季，(c)秋季，(d)冬季；Figure 8 shows the typical daily optimal power transmission curve in four seasons, (a) spring, (b) summer, (c) autumn, (d) winter;
图9为时间序列的形态模式示意图。Figure 9 is a schematic diagram of the morphological model of the time series.
下面结合具体实施例对本发明作进一步描述。以下实施例仅用于更加清楚地说明本发明的技术方案，而不能以此来限制本发明的保护范围。The present invention will be further described below in conjunction with specific embodiments. The following examples are only used to more clearly illustrate the technical solutions of the present invention, but cannot be used to limit the scope of the present invention.
如图1所示，一种多能互补一体化外送基地直流输电曲线优化方法，包括以下步骤：As shown in Figure 1, a multi-energy complementary integrated transmission base DC transmission curve optimization method includes the following steps:
步骤S1，根据相同直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线，结合清洁能源弃电率与受端负荷匹配度，确定最优年送电曲线；Step S1, determine the optimal annual power transmission curve based on the DC annual power transmission curve based on resource matching and load matching under the same DC utilization hours, combined with the clean energy power abandonment rate and the matching degree of the receiving end load;
结合现有的外送直流通道送电情况，考虑充分消纳送端资源的基础上，参考已有直流外送的利用小时数水平，进行直流利用小时数的框选，确定配套直流利用小时数。Combined with the existing power transmission situation of external DC channels, taking into account the full consumption of the transmission end resources, and referring to the utilization hours level of the existing DC external transmission, the DC utilization hours are selected to determine the supporting DC utilization hours. .
针对送端电网第k个月，根据以下公式计算在t时刻的电力平衡盈亏
For the kth month of the sending power grid, calculate the power balance profit and loss at time t according to the following formula
式中，
分别代表送端电网第k个月t时刻电源出力与负荷。
In the formula, Respectively represent the power output and load of the sending end power grid at time t in the kth month.
选取
中的最小值作为第k个月装机控制时刻的电力盈亏P
c,k，则该区域内的第k个月的电量空间E
c,k，可以通过下式进行估算：
Select The minimum value in is taken as the power profit and loss P c,k at the installation control time of the kth month. Then the power space E c,k of the kth month in the area can be estimated by the following formula:
式中，N
k代表第k个月的天数，ΔT为时段时长，T
d为一天计算总时长。E
c,k>0表示送端电网有余量空间可以消纳多能互补发电系统的富余电力；E
c,k<0表示送端电网有富余电力可以利用直流通道外送。
In the formula, N k represents the number of days in the kth month, ΔT is the duration of the period, and T d is the total duration of one day. E c,k >0 means that the sending-end power grid has margin space to absorb the surplus power of the multi-energy complementary power generation system; E c,k <0 means that the sending-end power grid has surplus power that can be sent out through the DC channel.
年送电曲线的优化主要在考虑匹配负荷曲线变化趋势的基础上，进一步匹配 送端的水风光资源。The optimization of the annual power transmission curve is mainly based on matching the changing trend of the load curve and further matching the water, wind and solar resources at the transmission end.
为此，建立包括清洁能源弃电率与受端负荷匹配度的目标函数：To this end, an objective function including the matching degree of clean energy curtailment rate and receiving end load is established:
min R
g,k+λ
kR
l,k (3)
min R g,k +λ k R l,k (3)
式中，λ
k为权重因子，R
g,k为第k个月清洁能源弃电率，R
l,k为第k个月的受端负荷匹配度。
In the formula, λ k is the weighting factor, R g,k is the clean energy power curtailment rate in the kth month, and R l,k is the receiving end load matching degree in the kth month.
清洁能源弃电率R
g,k与受端负荷匹配度R
l,k的估算方法如下：
The estimation method of the clean energy power curtailment rate R g,k and the receiving end load matching degree R l,k is as follows:
式中，E
g,k、E
l,k分别为在相同直流利用小时数下第k个月依据送端资源分布的送电电量和依据受端负荷需求的送电电量，E
o,k为优化后的第k个月直流外送送电量，ω(k)为第k个月的资源弃电指示函数，E
c,k为估算的送端电网第k个月的电量空间。
In the formula, E g,k and E l,k are respectively the power transmission amount based on the resource distribution of the sending end and the power transmission amount based on the load demand of the receiving end in the kth month under the same DC utilization hours. E o,k is The optimized DC external transmission power in the kth month, ω(k) is the resource curtailment indicator function in the kth month, and E c,k is the estimated power space of the sending end power grid in the kth month.
清洁能源弃电率R
g,k不应超过弃电率限定值，即
The clean energy power curtailment rate R g,k should not exceed the power curtailment rate limit value, that is
0≤R
g,k≤R
g,kmax (6)
0≤R g,k ≤R g,kmax (6)
式中，R
g,kmax为第k个月的清洁能源弃电率限定值。
In the formula, R g,kmax is the limit value of clean energy power curtailment rate in the kth month.
E
o,k还应满足相同直流利用小时数下的全年送电量的约束，即：
E o,k should also satisfy the constraints of annual power transmission under the same DC utilization hours, that is:
式中，T
dc为相同直流利用小时数，P
o max为直流外送通道的额定容量。
In the formula, T dc is the number of hours of DC utilization, and P o max is the rated capacity of the DC outgoing channel.
因此，目标函数的约束条件为：Therefore, the constraints of the objective function are:
基于式(3)目标函数，在满足上述约束条件下优化迭代，得到最优年送电曲线E
o＝[E
o,1,E
o,2,...,E
o,k,...,E
o,12]。
Based on the objective function of equation (3) and optimizing iterations while satisfying the above constraints, the optimal annual power transmission curve E o =[E o,1 ,E o,2 ,...,E o,k ,... ,E o,12 ].
步骤S2，根据所述最优年送电曲线和受端电网典型日负荷曲线，确定匹配受端电力需求的最优日送电曲线；Step S2, determine the optimal daily power transmission curve that matches the power demand of the receiving end based on the optimal annual power transmission curve and the typical daily load curve of the receiving end power grid;
通过步骤S1确定了最优全年送电曲线，从而确定了每个月的送电电量E
o,k。在此基础上，直流日送电曲线
应与受端日负荷特性相匹配，同时也应考虑到受端地区配套新能源的反调峰特性，以减轻受端消纳压力。
The optimal annual power transmission curve is determined through step S1, thereby determining the monthly power transmission amount E o,k . On this basis, the DC daily power transmission curve It should match the daily load characteristics of the receiving end, and at the same time, the anti-peaking characteristics of supporting new energy sources in the receiving end area should also be taken into account to reduce the consumption pressure on the receiving end.
对于第k个月的受端电网典型日负荷曲线
受送端电量资源限制，难以完全按照负荷变化趋势送电，但应重点保障负荷高峰期的电力需求，因此设定不同时段的送电权重
如下式所示：
Typical daily load curve of the receiving end power grid for the kth month Due to the limitation of power resources at the transmission end, it is difficult to deliver power completely in accordance with the load change trend. However, the focus should be on ensuring the power demand during peak load periods, so power delivery weights are set for different periods. As shown in the following formula:
式中，
代表第k个月t时刻受端电网的负荷水平，L
o,kmax、L
o,kmin分别为L
o,k中的最大值与最小值。
In the formula, Represents the load level of the receiving power grid at time t of the kth month, L o,kmax and Lo ,kmin are the maximum and minimum values in Lo ,k respectively.
为了匹配受端电力需求，对日送电曲线进一步优化，建立目标函数如下：In order to match the power demand at the receiving end, the daily power transmission curve is further optimized and the objective function is established as follows:
式中，
为第k个月t时刻的直流送电电量，N
k为第k个月的天数。
In the formula, is the DC power transmission amount at time t in the kth month, and N k is the number of days in the kth month.
优化过程中应满足年送电曲线的电量约束，即：During the optimization process, the power constraints of the annual power transmission curve should be met, namely:
式中，ΔT为时段时长，E
o,k为第k个月的直流送电电量。
In the formula, ΔT is the duration of the period, and E o,k is the DC power transmission amount in the kth month.
基于式(10)约束条件，对式(9)目标函数进行迭代求解，获得匹配受端电力需求的最优日送电曲线
Based on the constraints of equation (10), the objective function of equation (9) is iteratively solved to obtain the optimal daily power transmission curve that matches the power demand of the receiving end.
步骤S3，基于所述受端电网典型日负荷曲线，计算受端电网调峰平衡序列，并通过计算所述调峰平衡序列的斜率，获得调峰斜率时序序列；根据所述调峰斜率时序序列，结合斜率序列与模式序列对照表，获得调峰模式序列；Step S3, based on the typical daily load curve of the receiving end power grid, calculate the peaking balance sequence of the receiving end power grid, and obtain the peaking slope time series by calculating the slope of the peaking balance sequence; according to the peaking slope time series , combine the slope sequence and the pattern sequence comparison table to obtain the peak-shaving pattern sequence;
在获得匹配受端电力需求的最优日送电曲线
后，该曲线应进一步满足受端电网的调峰约束。
Obtaining the optimal daily power transmission curve that matches the power demand of the receiving end Finally, the curve should further satisfy the peak load regulation constraints of the receiving end power grid.
根据以下公式计算第k个月的受端调峰平衡序列
Calculate the peak-shaving balancing sequence of the kth month according to the following formula
式中，
为t时刻受端电网常规电源机组的最小出力，
分别为t时刻受端电网的风电及光伏出力。
表示受端电网风光调峰困难，直流送电应降低出力参与调峰。
In the formula, is the minimum output of the conventional power supply unit of the receiving end power grid at time t, are respectively the wind power and photovoltaic output of the receiving end grid at time t. It means that wind and solar peak shaving is difficult for the receiving end power grid, and DC power transmission should reduce its output to participate in peak shaving.
序列C
o,k体现了受端电网新能源出力与负荷的变化趋势。为了能够细致地反映调峰变化的趋势，将其趋势分为7种情况：快速上升、迅速上升、缓慢上升、持平、缓慢下降、迅速下降、快速下降，分别用{3ε
c,2ε
c,ε
c,0,-ε
c,-2ε
c,-3ε
c}的模式序列加以描述，ε
c为模式序列的单位变化量。序列的形态变化趋势及模式描述如图9所示。
The sequence C o,k reflects the changing trend of new energy output and load of the receiving end power grid. In order to reflect the trend of peak regulation changes in detail, the trend is divided into 7 situations: rapid rise, rapid rise, slow rise, flat, slow decline, rapid decline, rapid decline, respectively {3ε c , 2ε c , ε The pattern sequence of c ,0,-ε c ,-2ε c ,-3ε c } is described, and ε c is the unit variation of the pattern sequence. The morphological change trend and pattern description of the sequence are shown in Figure 9.
斜率是反映曲线变化快慢的变量，为了能准确刻画调峰序列的形态模式，根据以下调峰平衡序列的斜率计算方法，计算得到调峰斜率时序序列：The slope is a variable that reflects the speed of the curve change. In order to accurately depict the morphological pattern of the peak-shaving sequence, the peak-shaving slope time series is calculated according to the following slope calculation method of the peak-shaving balance sequence:
式中，C'
o,k为调峰斜率时序序列，
为
的变化斜率，C
o,kmax为序列C
o,k中绝对值最大值，
为压缩因子。
In the formula, C' o,k is the peak shaving slope time series, for The change slope of C o,kmax is the maximum absolute value in the sequence C o,k , is the compression factor.
获得调峰斜率时序序列C'
o,k后，参考表1可以获取斜率序列与模式序列的关系。模式序列
的值可以通过表1对照获得，表中
为斜率模式序列变化的低阈值，
为斜率模式序列变化的中阈值，
为斜率模式序列变化的高阈值，ε
c为调峰模式序列的单位变化量。
After obtaining the peak-shaving slope time series C' o,k , refer to Table 1 to obtain the relationship between the slope sequence and the mode sequence. pattern sequence The value of can be obtained by comparing Table 1. In the table is the low threshold for the slope pattern sequence change, is the mid-threshold of the slope pattern sequence change, is the high threshold for changes in the slope mode sequence, and ε c is the unit change amount of the peaking mode sequence.
表1 斜率序列与模式序列对照表Table 1 Comparison table of slope sequence and pattern sequence
若调峰时序序列
说明此时调峰序列处于快速上升的状态，形态序列
若调峰时序序列
说明此时调峰序列处于快速下降的状态，形态序列
其他形态可以类推得到。
If the peak shaving timing sequence It shows that the peak-shaving sequence is in a rapidly rising state at this time, and the morphological sequence If the peak shaving timing sequence It shows that the peak-shaving sequence is in a state of rapid decline at this time, and the morphological sequence Other forms can be derived by analogy.
步骤S4，基于所述调峰模式序列，计算调峰时序送电上限；基于所述调峰时序送电上限，对所述最优日送电曲线进行修正，得到兼顾受端电力需求与调峰需求的最优日送电曲线。Step S4: Calculate the upper limit of power transmission in peak shaving timing based on the sequence of peak shaving modes; correct the optimal daily power transmission curve based on the upper limit of power transmission in peak shaving timing to obtain a solution that takes into account the power demand of the receiving end and peak shaving The optimal daily power delivery curve for demand.
基于步骤S3得到的调峰模式序列，根据以下公式计算t时刻的调峰送电上限
Based on the peak shaving mode sequence obtained in step S3, calculate the upper limit of peak shaving power transmission at time t according to the following formula
日送电曲线
应满足调峰送电约束，即：
Daily power transmission curve Peak regulation power transmission constraints should be met, that is:
结合式(9)与式(14)对日送电曲线
进行迭代优化，获得兼顾受端电力需求与调峰需求的最优日送电曲线
Combining Equation (9) and Equation (14) for the Japanese power transmission curve Carry out iterative optimization to obtain the optimal daily power transmission curve that takes into account the power demand of the receiving end and the peak load regulation demand.
下面给出具体实施案例：Specific implementation cases are given below:
以金沙江流域多能互补外送系统为例，验证本发明方法的合理性。本实施案例以单个直流外送通道为核心，考虑联合调节金沙江流域金上7级电站、金下乌东德、白鹤滩、溪洛渡电站，未将金沙江流域内的向家坝水电站纳入研究范畴。其中金沙江流域金上7级电站、金下乌东德、白鹤滩、溪洛渡电站的平水年平均出力曲线如图2所示，金沙江流域风电与光伏的典型出力特性如图3所示。Taking the multi-energy complementary delivery system in the Jinsha River Basin as an example, the rationality of the method of the present invention is verified. This implementation case focuses on a single direct current transmission channel and considers the joint regulation of the Jinshang 7-level power station, Jinxiawudongde, Baihetan, and Xiluodu power stations in the Jinsha River Basin. The Xiangjiaba Hydropower Station in the Jinsha River Basin is not included in the research scope. . Among them, the flat-water annual average output curves of Jinshang Level 7 Power Station, Jinxia Wudongde, Baihetan, and Xiluodu Power Stations in the Jinsha River Basin are shown in Figure 2. The typical output characteristics of wind power and photovoltaics in the Jinsha River Basin are shown in Figure 3.
不考虑向家坝水电站，金沙江流域水电站配套外送直流总容量为5500千瓦，结合现有外送直流通道送电情况，考虑充分消纳水电基础上，适当提高风电光伏送电电量，考虑拟定不同利用小时数下各直流的高中低年送电量方案，具体见表2。Excluding Xiangjiaba Hydropower Station, the total supporting external DC capacity of hydropower stations in the Jinsha River basin is 5,500 kilowatts. Combined with the existing external DC channel power transmission situation, and considering fully absorbing hydropower, appropriately increasing the amount of wind power and photovoltaic power transmission is considered to be formulated. The power transmission plans for each DC in different utilization hours are shown in Table 2 for details.
表2Table 2
以白鹤滩左岸送电江苏为例，该直流送端为四川省，受端为江苏省。根据金沙江流域白鹤滩左岸送端资源的出力特性和受端江苏省电网的负荷特性，获取相同的直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线。其中E
g,k、E
l,k分别为在相同直流利用小时数下依据白鹤滩左岸送端资源分布的送电电量与江苏省受端负荷需求的送电电量。
Taking the Baihetan left bank power transmission to Jiangsu as an example, the DC sending end is Sichuan Province and the receiving end is Jiangsu Province. Based on the output characteristics of the resources at the sending end on the left bank of Baihetan in the Jinsha River Basin and the load characteristics of the power grid in Jiangsu Province at the receiving end, the annual DC power transmission curve based on resource matching and load matching under the same DC utilization hours is obtained. Among them, E g,k and E l,k are respectively the power transmission power based on the resource distribution of the sending end on the left bank of Baihetan and the power transmission power required by the receiving end load in Jiangsu Province under the same DC utilization hours.
四川省电力供需具有以水为主、丰枯结构性矛盾突出的特点。从需求方面来看，丰枯比约50％：50％；从供给方面来看，装机结构以水电为主，由于水电整体出力特性具有丰多枯少的特点，其中丰枯电量比约为60％：40％，水电出力特性与负荷特性的不匹配，造成了四川容易出现“丰余枯缺”的结构性问题。随着三大流域后续水电开发，四川整体水电外送规模进一步扩大，叠加自身负荷的发展，四川省逐步发展至“丰枯均缺”、同时丰水期弃水问题并存的形势。四川省的电力盈亏发展趋势如图4所示。The power supply and demand in Sichuan Province is characterized by water-based supply and demand, with prominent structural contradictions between abundance and dryness. From the demand side, the ratio of good times to bad times is about 50%:50%; from the perspective of supply, the installed capacity structure is dominated by hydropower. Since the overall output characteristics of hydropower are characterized by abundant and short periods, the ratio of good to dry electricity is about 60 %: 40%. The mismatch between hydropower output characteristics and load characteristics has caused Sichuan to be prone to structural problems of “abundance and shortage”. With the subsequent hydropower development in the three major river basins, Sichuan's overall hydropower transmission scale has further expanded, and combined with the development of its own load, Sichuan Province has gradually developed into a situation of "both high and low water shortages", and the problem of water abandonment in high water periods coexists. The development trend of power profit and loss in Sichuan Province is shown in Figure 4.
由图4中可知，四川省在2025年出现季节性缺口，最大缺口达到353万千瓦，基于上述电力盈亏结果依据式(2)估算四川电网可消纳的电量空间，进一步结合清洁能源弃电率R
g,k与受端负荷匹配度R
l,k对白鹤滩左岸送电江苏的年送电曲线进行迭代优化，其中，控制参数R
g,kmax＝10％，，λ
k＝0.2得到白鹤滩左岸至江苏最优年送电曲线，如图5所示。
As can be seen from Figure 4, Sichuan Province will experience a seasonal gap in 2025, with the maximum gap reaching 3.53 million kilowatts. Based on the above power profit and loss results, the power space that can be accommodated by the Sichuan power grid is estimated according to Equation (2), and further combined with the clean energy curtailment rate R g,k and the receiving end load matching degree R l,k are used to iteratively optimize the annual power transmission curve of Baihetan left bank power transmission in Jiangsu. Among them, the control parameters R g,kmax = 10%, λ k = 0.2 are obtained in Baihetan. The optimal annual power transmission curve from the left bank to Jiangsu is shown in Figure 5.
从图5中可以看出，为保障送端水风光多能互补发电系统的弃电率，优化曲线主要考虑送端的资源禀赋。考虑到四川水电在丰期有富余水电可以组织外送，送电曲线适当上调以满足受端电力支撑需求；枯期送端本地电力亏缺而受端春秋季电力需求不足，送电曲线适当下调以满足送端本地需求。As can be seen from Figure 5, in order to ensure the power curtailment rate of the hydro-wind-solar multi-energy complementary power generation system at the transmission end, the optimization curve mainly considers the resource endowment at the transmission end. Taking into account that Sichuan Hydropower has surplus hydropower in the peak season and can organize external transmission, the power transmission curve is appropriately adjusted upward to meet the power support needs of the receiving end; in the dry season, the local power at the sending end is insufficient and the receiving end has insufficient power demand in spring and autumn, and the power transmission curve is appropriately adjusted down. To meet the local needs of the sending end.
进一步的，日送电曲线需要兼顾受端地区的不同场景，主要包括高负荷场景与反调峰场景两类。在高负荷场景下直流日送电曲线应确保电力支撑，在反调峰场景时应配合调峰控制。Furthermore, the daily power transmission curve needs to take into account different scenarios in the receiving area, mainly including high load scenarios and anti-peaking scenarios. The DC daily power transmission curve should ensure power support in high-load scenarios, and should cooperate with peak shaving control in anti-peak shaving scenarios.
在全国“碳达峰、碳中和”的战略背景下，受端省份的新能源也将进一步迅猛发展，新能源渗透率的提高将为电网消纳带来显著压力。选择受端地区四季典型日的负荷及新能源出力曲线，如图6所示。Against the background of the national strategy of “carbon peaking and carbon neutrality”, new energy in the receiving provinces will also further develop rapidly, and the increase in the penetration rate of new energy will bring significant pressure on power grid consumption. Select the load and new energy output curves of typical days in four seasons in the receiving end area, as shown in Figure 6.
以江苏省为例，受端电网负荷高峰主要集中在夏冬两季，春秋季负荷较低。负荷高峰场景下，夏季江风电出力较低、冬季出力较高，光伏则呈现相反的变化趋势；在反调峰场景下，春秋季风光大发的概率较高，同时风电的出力变率较高，对于送端直流的调峰深度提出要求。对受端地区典型风电与光伏的全年出力数据进行统计分析，结果如表3所示。Taking Jiangsu Province as an example, the load peaks of the receiving power grid are mainly concentrated in summer and winter, and the load is lower in spring and autumn. Under the load peak scenario, the output of river wind power is lower in summer and higher in winter, while photovoltaics show the opposite trend; in the reverse peak load scenario, the probability of peak power in spring and autumn is higher, and at the same time, the output variability of wind power is high. Put forward requirements for the peak shaving depth of DC at the sending end. Statistical analysis was conducted on the annual output data of typical wind power and photovoltaic power in the receiving end area, and the results are shown in Table 3.
表3table 3
基于受端地区的新能源出力统计结果及典型风光出力曲线，对受端地区开展调峰平衡时序计算，生成调峰平衡序列，各季节典型调峰时序曲线如图7所示。Based on the statistical results of new energy output and typical wind and solar output curves in the receiving area, the peaking balance timing calculation was carried out in the receiving area to generate a peaking balance sequence. Typical peaking timing curves in each season are shown in Figure 7.
由表3和图7可知，夏季负荷高峰风电、光伏累积概率95％的出力率仅为27％、40％，受端地区调峰存在较大裕度，日送电曲线应以保障电力需求为主；冬季高峰风电出力较高，在风电大发时段日送电负荷应积极参与调峰；春季调峰压力最大，风电、光伏累积概率95％的出力率达到66％与50％，应尽量压低送电曲线减轻受端压力。It can be seen from Table 3 and Figure 7 that the output rate of wind power and photovoltaic with a 95% cumulative probability of summer load peak is only 27% and 40%. There is a large margin for peak regulation in the receiving end area. The daily power transmission curve should be to ensure the power demand. Mainly; the peak wind power output in winter is relatively high, and the daily power transmission load should actively participate in peak regulation during the peak period of wind power; in spring, the peak regulation pressure is the greatest, and the output rates of wind power and photovoltaic cumulative probability of 95% reach 66% and 50%, which should be kept as low as possible The power transmission curve reduces the pressure on the receiving end.
取
ε
c＝0.1，生成调峰时序序列的模式匹配序列。兼顾调峰时序模式匹配与受端负荷曲线拟合，对受端地区各典型时刻下的日送电曲线进行优化，以白鹤滩～江苏的低方案为例，其四季典型日的日送电曲线优化过程如图8所示。
Pick ε c =0.1, generate the pattern matching sequence of the peak shaving timing sequence. Taking into account peak-shaving timing pattern matching and receiving-end load curve fitting, the daily power transmission curve at each typical time in the receiving-end area is optimized. Taking the low-level scheme from Baihetan to Jiangsu as an example, its daily power transmission curve on typical days in four seasons The optimization process is shown in Figure 8.
从图8中可以看出，在夏季高峰时刻，受端系统调峰裕度大，直流可以满容量送电，受制于送端水风光资源量，利用送电权重系数加权，保障负荷高峰时期的电力电量；在春秋低谷时刻，直流应充分考虑风电光伏出力影响，在风电易大发的夜间与光伏大发的正午时刻参与调峰，限制直流出力。It can be seen from Figure 8 that during the summer peak hours, the receiving end system has a large peak shaving margin, and DC can transmit power at full capacity. Subject to the amount of water, wind and solar resources at the transmitting end, the power transmission weight coefficient is used to weight the load during the peak period. Electric power: During the trough moments in spring and autumn, DC should fully consider the impact of wind power and photovoltaic output, and participate in peak regulation at night when wind power is likely to be strong and at noon when photovoltaic power is strong to limit DC output.
本发明方法基于送端电网的负荷特性与电力电量平衡结果，估算送端电网对清洁电源的消纳空间；进一步基于送端清洁电源的可开发量、出力特性与受端电网的负荷特性、电力电量需求，通过计算清洁能源弃电率与受端负荷匹配度，建立优化目标函数，获取在同等直流通道利用小时数水平下基于送端资源匹配和受端负荷匹配的最优直流年送电曲线。The method of the present invention estimates the accommodation space of the sending-end power grid for clean power based on the load characteristics and power balance results of the sending-end power grid. It is further based on the developable amount and output characteristics of the sending-end clean power supply and the load characteristics and power of the receiving-end power grid. For power demand, by calculating the matching degree between the clean energy power abandonment rate and the receiving end load, an optimization objective function is established to obtain the optimal DC annual power transmission curve based on the sending end resource matching and the receiving end load matching at the same level of DC channel utilization hours. .
在获得了最优直流年送电曲线后，考虑日送电曲线应与受端日负荷特性相匹配，同时兼顾受端地区配套新能源的反调峰特性，减轻受端消纳压力。通过计算受端电网的典型日负荷曲线，获得在典型日不同时刻的最优送电权重，并结合送端电网的调峰平衡建立调峰变化模式序列，获取典型日每个时段考虑受端调峰需求的直流送电上限。结合每个时刻的最优送电权重与送电上限得到典型日最优直流日送电曲线。After obtaining the optimal DC annual power transmission curve, it is considered that the daily power transmission curve should match the daily load characteristics of the receiving end, while taking into account the anti-peaking characteristics of supporting new energy sources in the receiving end area to reduce the consumption pressure of the receiving end. By calculating the typical daily load curve of the receiving-end power grid, the optimal power transmission weight at different times on a typical day is obtained, and combined with the peak-shaving balance of the sending-end power grid, a peak-shaving change pattern sequence is established to obtain the peak-shaving change pattern sequence for each period of a typical day. DC power transmission limit for peak demand. Combining the optimal power transmission weight and the power transmission upper limit at each moment, the optimal DC daily power transmission curve for a typical day is obtained.
本发明方法在大型水风光、风光火储等高比例清洁电量占比的发电系统中，可以有效地兼顾送受端需求优化直流外送曲线，可为应用于实际电网的地区新能源开发建设与直流输电规划提供决策基础。In power generation systems with a high proportion of clean electricity, such as large-scale water, wind, solar, wind, solar, and thermal storage, the method of the present invention can effectively optimize the DC transmission curve by taking into account the needs of the sending and receiving ends, and can be used in the development and construction of regional new energy and DC in actual power grids. Transmission planning provides the basis for decision-making.
在另一实施例中，一种多能互补一体化外送基地直流输电曲线优化系统，包括：In another embodiment, a multi-energy complementary integrated direct current transmission curve optimization system for a delivery base includes:
最优年送电曲线确定模块，配置为根据相同直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线，结合清洁能源弃电率与受端负荷匹配度，确定最优年送电曲线；The optimal annual power transmission curve determination module is configured to determine the optimal annual power transmission based on the DC annual power transmission curve based on resource matching and load matching under the same DC utilization hours, combined with the clean energy power abandonment rate and the matching degree of the receiving end load. curve;
最优日送电曲线确定模块，配置为根据所述最优年送电曲线和受端电网典型日负荷曲线，确定匹配受端电力需求的最优日送电曲线；The optimal daily power transmission curve determination module is configured to determine the optimal daily power transmission curve that matches the receiving end power demand based on the optimal annual power transmission curve and the typical daily load curve of the receiving end power grid;
调峰模式序列确定模块，配置为基于所述受端电网典型日负荷曲线，计算受端电网调峰平衡序列，并通过计算所述调峰平衡序列的斜率，获得调峰斜率时序序列；根据所述调峰斜率时序序列，结合斜率序列与模式序列对照表，获得调峰模式序列；The peak-shaving mode sequence determination module is configured to calculate the peak-shaving balance sequence of the receiving-end power grid based on the typical daily load curve of the receiving-end power grid, and obtain the peak-shaving slope time series by calculating the slope of the peak-shaving balance sequence; according to the required Describe the peak-shaving slope time series, and combine the slope sequence and the mode sequence comparison table to obtain the peak-shaving mode sequence;
最优日送电曲线修正模块，配置为基于所述调峰模式序列，计算调峰时序送电上限；基于所述调峰时序送电上限，对所述最优日送电曲线进行修正，得到兼顾受端电力需求与调峰需求的最优日送电曲线。The optimal daily power transmission curve correction module is configured to calculate the upper limit of peak shaving timing power transmission based on the peak shaving mode sequence; based on the upper limit of peak shaving timing power transmission, correct the optimal daily power transmission curve to obtain The optimal daily power transmission curve takes into account the power demand of the receiving end and the peak load regulation demand.
以上已以较佳实施例公布了本发明，然其并非用以限制本发明，凡采取等同替换或等效变换的方案所获得的技术方案，均落在本发明的保护范围内。The present invention has been disclosed above with preferred embodiments, but they are not intended to limit the present invention. Any technical solutions obtained by adopting equivalent substitutions or equivalent transformations fall within the protection scope of the present invention.
Claims (10)
- 一种多能互补一体化外送基地直流输电曲线优化方法，其特征在于，包括：A method for optimizing the DC transmission curve of a multi-energy complementary integrated outbound transmission base, which is characterized by including:根据相同直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线，结合清洁能源弃电率与受端负荷匹配度，确定最优年送电曲线；Based on the DC annual power transmission curve based on resource matching and load matching under the same DC utilization hours, combined with the clean energy power abandonment rate and the matching degree of the receiving end load, the optimal annual power transmission curve is determined;根据所述最优年送电曲线和受端电网典型日负荷曲线，确定匹配受端电力需求的最优日送电曲线；According to the optimal annual power transmission curve and the typical daily load curve of the receiving end power grid, determine the optimal daily power transmission curve that matches the receiving end power demand;基于所述受端电网典型日负荷曲线，计算受端电网调峰平衡序列，并通过计算所述调峰平衡序列的斜率，获得调峰斜率时序序列；根据所述调峰斜率时序序列，结合斜率序列与模式序列对照表，获得调峰模式序列；Based on the typical daily load curve of the receiving end power grid, calculate the peaking balance sequence of the receiving end power grid, and obtain the peaking slope time series by calculating the slope of the peaking balance sequence; according to the peaking slope time series, combine the slope Compare the sequence and mode sequence to obtain the peak-shaving mode sequence;基于所述调峰模式序列，计算调峰时序送电上限；基于所述调峰时序送电上限，对所述最优日送电曲线进行修正，得到兼顾受端电力需求与调峰需求的最优日送电曲线。Based on the peak shaving mode sequence, the upper limit of peak shaving timing power transmission is calculated; based on the upper limit of peak shaving timing power transmission, the optimal daily power transmission curve is corrected to obtain the optimal daily power transmission curve that takes into account both the receiving end power demand and the peak shaving demand. Excellent power transmission curve.
- 根据权利要求1所述的一种多能互补一体化外送基地直流输电曲线优化方法，其特征在于，所述根据相同直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线，结合清洁能源弃电率与受端负荷匹配度，确定最优年送电曲线，包括：A method for optimizing the DC power transmission curve of a multi-energy complementary integrated outbound transmission base according to claim 1, characterized in that the annual DC power transmission curve based on resource matching and load matching under the same DC utilization hours is combined with The matching degree between the clean energy power abandonment rate and the receiving end load determines the optimal annual power transmission curve, including:建立包括清洁能源弃电率与受端负荷匹配度的目标函数：Establish an objective function including the matching degree of clean energy power curtailment rate and receiving end load:min R g,k+λ kR l,k (1) min R g,k +λ k R l,k (1)式中，λ k为权重因子，R g,k为第k个月清洁能源弃电率，R l,k为第k个月的受端负荷匹配度； In the formula, λ k is the weighting factor, R g,k is the clean energy power curtailment rate in the kth month, R l,k is the receiving end load matching degree in the kth month;所述目标函数的约束条件为：The constraints of the objective function are:
0≤R g,k≤R g,k max (4) 0≤R g,k ≤R g,k max (4)
式中，E g,k、E l,k分别为在相同直流利用小时数下第k个月依据送端资源分布的送电电量和依据受端负荷需求的送电电量，E o,k为优化后的第k个月直流外送送电量，ω(k)为第k个月的资源弃电指示函数，E c,k为估算的送端电网第k个月的电量空间，R g,k max为第k个月的清洁能源弃电率限定值，T dc为相同直流利用小时数，P omax为直流外送通道的额定容量； In the formula, E g,k and E l,k are respectively the power transmission amount based on the resource distribution of the sending end and the power transmission amount based on the load demand of the receiving end in the kth month under the same DC utilization hours. E o,k is The optimized DC external transmission power in the kth month, ω(k) is the resource curtailment indicator function in the kth month, E c,k is the estimated power space of the sending end grid in the kth month, R g, k max is the limit value of the clean energy power abandonment rate in the kth month, T dc is the same number of DC utilization hours, and P omax is the rated capacity of the DC external transmission channel;基于所述约束条件，对所述目标函数进行求解，得到最优年送电曲线E o＝[E o,1,E o,2,…,E o,k,…,E o,12]。 Based on the constraints, the objective function is solved to obtain the optimal annual power transmission curve E o =[E o,1 ,E o,2 ,…,E o,k ,…,E o,12 ]. - 根据权利要求2所述的多能互补一体化外送基地直流输电曲线优化方法，其特征在于，所述送端电网第k个月的电量空间E c,k根据以下方法估算： The method for optimizing the DC transmission curve of a multi-energy complementary integrated outbound transmission base according to claim 2, characterized in that the power space E c,k of the kth month of the transmission end power grid is estimated according to the following method:根据以下公式计算送端电网第k个月t时刻的电力平衡盈亏Calculate the power balance profit and loss of the sending end power grid at time t in the kth month according to the following formula
式中，分别代表送端电网第k个月t时刻电源出力与负荷； In the formula,
Represent the power output and load of the sending end power grid at time t in the kth month respectively;选取中的最小值作为第k个月装机控制时刻的电力盈亏P c,k，则该区域内的第k个月的电量空间E c,k，通过下式进行估算： Select
The minimum value in is taken as the power profit and loss P c,k at the installation control time of the kth month. Then the power space E c,k of the kth month in the area is estimated by the following formula:
式中，N k代表第k个月的天数，ΔT为时段时长，T d为一天计算总时长。 In the formula, N k represents the number of days in the kth month, ΔT is the duration of the period, and T d is the total duration of one day. - 根据权利要求1所述的多能互补一体化外送基地直流输电曲线优化方法，其特征在于，所述根据所述最优年送电曲线和受端电网典型日负荷曲线，确定匹配受端电力需求的最优日送电曲线，包括：The multi-energy complementary integrated outgoing transmission base DC power transmission curve optimization method according to claim 1, characterized in that the matching receiving end power is determined based on the optimal annual power transmission curve and the typical daily load curve of the receiving end power grid. The optimal daily power delivery curve for demand includes:根据所述最优年送电曲线，确定第k个月的直流日送电曲线其中T d为一天计算总时长； According to the optimal annual power transmission curve, the DC daily power transmission curve of the kth month is determined.
Among them, T d is the total calculation time of one day;根据第k个月的受端电网典型日负荷曲线确定全天各时段的送电权重
According to the typical daily load curve of the receiving end power grid in the kth month
Determine the power delivery weight for each time period throughout the day
式中，代表第k个月t时刻受端电网的负荷水平，L o,k max、L o,k min分别为L o,k中的最大值与最小值； In the formula,
Represents the load level of the receiving end power grid at time t of the kth month, L o,k max and Lo ,k min are the maximum and minimum values in Lo ,k respectively;基于第k个月的受端电网典型日负荷曲线和全天各时段的送电权重，建立目标函数：Based on the typical daily load curve of the receiving power grid in the kth month and the power transmission weight at each time period throughout the day, the objective function is established:
式中，为第k个月t时刻的直流送电电量，P omax为直流外送通道的额定容量，N k为第k个月的天数； In the formula,
is the DC power transmission amount at time t in the kth month, P omax is the rated capacity of the DC transmission channel, and N k is the number of days in the kth month;所述目标函数的约束条件为：The constraints of the objective function are:
式中，ΔT为时段时长，E o,k为第k个月的直流送电电量； In the formula, ΔT is the period length, E o,k is the DC power transmission amount in the kth month;基于所述约束条件，对所述目标函数进行迭代求解，获得匹配受端电力需求的最优日送电曲线Based on the constraints, the objective function is iteratively solved to obtain the optimal daily power transmission curve that matches the power demand at the receiving end.
- 根据权利要求4所述的多能互补一体化外送基地直流输电曲线优化方法，其特征在于，所述受端电网调峰平衡序列根据以下公式计算： The multi-energy complementary integrated outbound transmission base DC power transmission curve optimization method according to claim 4, characterized in that the receiving end power grid peak regulation balancing sequence
Calculated according to the following formula:
式中，为t时刻受端电网常规电源机组的最小出力，
分别为t时刻受端电网的风电及光伏出力。 In the formula,
is the minimum output of the conventional power supply unit of the receiving end power grid at time t,are respectively the wind power and photovoltaic output of the receiving end grid at time t. - 根据权利要求5所述的多能互补一体化外送基地直流输电曲线优化方法，其特征在于，所述调峰斜率时序序列根据以下公式计算：The method for optimizing the DC transmission curve of a multi-energy complementary integrated outbound transmission base according to claim 5, characterized in that the peak-shaving slope time series is calculated according to the following formula:
式中，C′ o,k为调峰斜率时序序列，为
的变化斜率，C o,k max为序列C o,k中绝对值最大值，
为压缩因子。 In the formula, C′ o,k is the peak shaving slope time series,
forThe change slope of C o,k max is the maximum absolute value in the sequence C o,k ,is the compression factor. - 根据权利要求6所述的多能互补一体化外送基地直流输电曲线优化方法，其特征在于，调峰模式序列根据下表获得： The multi-energy complementary integrated delivery base DC transmission curve optimization method according to claim 6, characterized in that the peak shaving mode sequence
Obtain according to the following table:斜率序列与模式序列对照表Slope sequence and pattern sequence comparison table
其中，为斜率模式序列变化的低阈值，
为斜率模式序列变化的中阈值，
为斜率模式序列变化的高阈值，ε c为调峰模式序列的单位变化量。 in,
is the low threshold for the slope pattern sequence change,is the mid-threshold of the slope pattern sequence change,is the high threshold for changes in the slope mode sequence, and ε c is the unit change amount of the peaking mode sequence. - 根据权利要求7所述的多能互补一体化外送基地直流输电曲线优化方法，其特征在于，所述调峰时序送电上限根据以下公式计算得到：The DC power transmission curve optimization method of a multi-energy complementary integrated external transmission base according to claim 7, characterized in that the upper limit of the peak-shaving timing power transmission is calculated according to the following formula:
式中，为t时刻的调峰送电上限。 In the formula,
is the upper limit of peak power transmission at time t. - 根据权利要求4所述的多能互补一体化外送基地直流输电曲线优化方法，其特征在于，所述基于所述调峰时序送电上限，对所述最优日送电曲线进行修正，包括：The DC power transmission curve optimization method of a multi-energy complementary integrated external transmission base according to claim 4, characterized in that the optimal daily power transmission curve is corrected based on the peak-shaving timing power transmission upper limit, including :日送电曲线应满足调峰送电约束： Daily power transmission curve
Peak regulation power transmission constraints should be met:
式中，为t时刻的调峰送电上限； In the formula,
is the upper limit of peak power transmission at time t;结合式(9)与式(14)对日送电曲线进行迭代优化，获得兼顾受端电力需求与调峰需求的最优日送电曲线
Combining Equation (9) and Equation (14) for the Japanese power transmission curve
Carry out iterative optimization to obtain the optimal daily power transmission curve that takes into account the power demand of the receiving end and the peak load regulation demand. - 一种多能互补一体化外送基地直流输电曲线优化系统，其特征在于，包括：A multi-energy complementary integrated DC transmission curve optimization system for outbound transmission bases, which is characterized by including:最优年送电曲线确定模块，配置为根据相同直流利用小时数下基于资源匹配与负荷匹配的直流年送电曲线，结合清洁能源弃电率与受端负荷匹配度，确定最优年送电曲线；The optimal annual power transmission curve determination module is configured to determine the optimal annual power transmission based on the DC annual power transmission curve based on resource matching and load matching under the same DC utilization hours, combined with the clean energy power abandonment rate and the matching degree of the receiving end load. curve;最优日送电曲线确定模块，配置为根据所述最优年送电曲线和受端电网典型日负荷曲线，确定匹配受端电力需求的最优日送电曲线；The optimal daily power transmission curve determination module is configured to determine the optimal daily power transmission curve that matches the receiving end power demand based on the optimal annual power transmission curve and the typical daily load curve of the receiving end power grid;调峰模式序列确定模块，配置为基于所述受端电网典型日负荷曲线，计算受端电网调峰平衡序列，并通过计算所述调峰平衡序列的斜率，获得调峰斜率时序序列；根据所述调峰斜率时序序列，结合斜率序列与模式序列对照表，获得调峰模式序列；The peak-shaving mode sequence determination module is configured to calculate the peak-shaving balance sequence of the receiving-end power grid based on the typical daily load curve of the receiving-end power grid, and obtain the peak-shaving slope time series by calculating the slope of the peak-shaving balance sequence; according to the required Describe the peak-shaving slope time series, and combine the slope sequence and the mode sequence comparison table to obtain the peak-shaving mode sequence;最优日送电曲线修正模块，配置为基于所述调峰模式序列，计算调峰时序送电上限；基于所述调峰时序送电上限，对所述最优日送电曲线进行修正，得到兼顾受端电力需求与调峰需求的最优日送电曲线。The optimal daily power transmission curve correction module is configured to calculate the upper limit of peak shaving timing power transmission based on the peak shaving mode sequence; based on the upper limit of peak shaving timing power transmission, correct the optimal daily power transmission curve to obtain The optimal daily power transmission curve takes into account the power demand of the receiving end and the peak load regulation demand.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210287336.5 | 2022-03-23 | ||
| CN202210287336.5A CN114914948A (en) | 2022-03-23 | 2022-03-23 | Method and system for optimizing direct-current transmission curve of multi-energy complementary integrated delivery base |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2023179118A1 true WO2023179118A1 (en) | 2023-09-28 |
Family
ID=82763529
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2022/139573 WO2023179118A1 (en) | 2022-03-23 | 2022-12-16 | Method and system for optimizing direct-current power transmission curve of multi-energy complementary integrated external transmission base |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN114914948A (en) |
| WO (1) | WO2023179118A1 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117277444A (en) * | 2023-11-17 | 2023-12-22 | 中国电力科学研究院有限公司 | New energy base power capacity optimal configuration method and device |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114914948A (en) * | 2022-03-23 | 2022-08-16 | 中国能源建设集团江苏省电力设计院有限公司 | Method and system for optimizing direct-current transmission curve of multi-energy complementary integrated delivery base |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180294649A1 (en) * | 2017-04-07 | 2018-10-11 | Nexant, Inc. | Systems and methods for optimally delivering electrical energy in a network |
| CN111353654A (en) * | 2020-03-13 | 2020-06-30 | 郑州大学 | Direct-current transmitting-end hydropower station optimal scheduling method compatible with peak regulation requirements of receiving-end power grid |
| CN111799778A (en) * | 2020-06-11 | 2020-10-20 | 国网山东省电力公司经济技术研究院 | Wind power-containing power system energy storage capacity optimization method considering peak shaving requirements |
| CN112508402A (en) * | 2020-12-04 | 2021-03-16 | 国网湖北省电力有限公司电力科学研究院 | Method for generating DC power transmission curve scene, electronic device, and medium |
| CN114914948A (en) * | 2022-03-23 | 2022-08-16 | 中国能源建设集团江苏省电力设计院有限公司 | Method and system for optimizing direct-current transmission curve of multi-energy complementary integrated delivery base |
-
2022
- 2022-03-23 CN CN202210287336.5A patent/CN114914948A/en active Pending
- 2022-12-16 WO PCT/CN2022/139573 patent/WO2023179118A1/en unknown
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180294649A1 (en) * | 2017-04-07 | 2018-10-11 | Nexant, Inc. | Systems and methods for optimally delivering electrical energy in a network |
| CN111353654A (en) * | 2020-03-13 | 2020-06-30 | 郑州大学 | Direct-current transmitting-end hydropower station optimal scheduling method compatible with peak regulation requirements of receiving-end power grid |
| CN111799778A (en) * | 2020-06-11 | 2020-10-20 | 国网山东省电力公司经济技术研究院 | Wind power-containing power system energy storage capacity optimization method considering peak shaving requirements |
| CN112508402A (en) * | 2020-12-04 | 2021-03-16 | 国网湖北省电力有限公司电力科学研究院 | Method for generating DC power transmission curve scene, electronic device, and medium |
| CN114914948A (en) * | 2022-03-23 | 2022-08-16 | 中国能源建设集团江苏省电力设计院有限公司 | Method and system for optimizing direct-current transmission curve of multi-energy complementary integrated delivery base |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117277444A (en) * | 2023-11-17 | 2023-12-22 | 中国电力科学研究院有限公司 | New energy base power capacity optimal configuration method and device |
| CN117277444B (en) * | 2023-11-17 | 2024-03-19 | 中国电力科学研究院有限公司 | New energy base power capacity optimal configuration method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114914948A (en) | 2022-08-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2023179118A1 (en) | Method and system for optimizing direct-current power transmission curve of multi-energy complementary integrated external transmission base | |
| CN109980685B (en) | Uncertainty-considered active power distribution network distributed optimization operation method | |
| CN109919478B (en) | Comprehensive energy microgrid planning method considering comprehensive energy supply reliability | |
| CN110365013B (en) | Capacity optimization method of photo-thermal-photovoltaic-wind power combined power generation system | |
| CN107634518B (en) | Source-network-load coordinated active power distribution network economic dispatching method | |
| CN108767895B (en) | Method for optimizing capacity of water-wind-solar matched power supply of sending-end system by considering resource constraint | |
| CN113850474B (en) | Thermoelectric hydrogen multi-energy flow comprehensive energy system and optimal scheduling method thereof | |
| CN114069687B (en) | Distributed photovoltaic planning method considering reactive power regulation effect of inverter | |
| CN115689233A (en) | Wind, light, water, fire and storage system complementary coordination optimization scheduling method considering peak regulation initiative | |
| CN115841396A (en) | Watershed cascade water-wind-solar complementary capacity stowage optimization and economic evaluation method | |
| CN111969591B (en) | Off-grid hybrid energy system optimization method based on complementation of optical energy storage hydropower station | |
| CN112803567A (en) | Parameter optimization design method and system based on intelligent building optical storage power supply equipment | |
| CN111917137A (en) | Regulation and control method for multiple distributed energy sources in regional power grid | |
| CN109873419B (en) | Water-light storage system operation optimization method considering similarity and economic benefits | |
| Wang et al. | Analysis of Coordinated Operation of the Clean Energy System Based on the Multiobjective Optimization Model | |
| CN114530848B (en) | Multi-time scale dynamic partitioning method for optical storage virtual power plant | |
| CN114336703B (en) | Automatic cooperative control method for large-scale wind-solar energy storage station | |
| CN114398777A (en) | Power system flexibility resource allocation method based on Bashi game theory | |
| CN114825381A (en) | Capacity configuration method for photo-thermal power station of wind-solar new energy base | |
| Heo et al. | Energy resource capacity optimization for zero-energy housing complex | |
| CN111786419A (en) | Regional power grid energy configuration system | |
| Ge et al. | The wind-PV-hydro-thermal multi-source cleaning dispatch with the influence of super-power thermal storage boiler | |
| CN113507134B (en) | Optimal planning method for planning target year new energy power supply installed capacity | |
| Wang et al. | Comparisons of Different Dispatches to Promote the Consumption of Renewable Energy | |
| Feng et al. | Research on Multi-energy Complementary Clean DC Delivery Considering Sending-End Resources and the Matching Mode of Receiving-End Peak Load Regulation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 22933167 Country of ref document: EP Kind code of ref document: A1 |