CN112103955A - Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system - Google Patents

Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system Download PDF

Info

Publication number
CN112103955A
CN112103955A CN202010974491.5A CN202010974491A CN112103955A CN 112103955 A CN112103955 A CN 112103955A CN 202010974491 A CN202010974491 A CN 202010974491A CN 112103955 A CN112103955 A CN 112103955A
Authority
CN
China
Prior art keywords
grid
power
energy
energy storage
equipment
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010974491.5A
Other languages
Chinese (zh)
Other versions
CN112103955B (en
Inventor
李欣然
刘小龙
杨徉
刘志谱
卢颖华
罗真
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hunan University
Original Assignee
Hunan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hunan University filed Critical Hunan University
Priority to CN202010974491.5A priority Critical patent/CN112103955B/en
Publication of CN112103955A publication Critical patent/CN112103955A/en
Application granted granted Critical
Publication of CN112103955B publication Critical patent/CN112103955B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • 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
    • H02J3/008—Circuit arrangements for AC mains or AC distribution networks involving trading of energy or energy transmission rights
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention discloses an optimal utilization method of electric energy storage accident reserve capacity of a comprehensive energy system, which comprises the following steps: respectively constructing an energy model for each device of the comprehensive energy system of the battery production park; constructing a grid-connected expected income model and a grid-disconnected expected loss model based on demand response of a battery production park to the comprehensive energy system and the grid-disconnected risk of the battery production park; the offline risk of the battery production park is obtained by comprehensively considering the probability of unplanned offline and important load loss for quantification; synthesizing the grid-connected expected yield and the off-grid expected loss, and establishing a comprehensive energy system optimization scheduling model considering off-grid risk and grid-connected yield; and solving the comprehensive energy system optimization scheduling model. According to the invention, under the condition of considering both the off-grid risk and the grid-connected income, the accident capacity of the energy storage equipment is fully utilized, and the grid-connected operation economy of the comprehensive energy system in the battery production park is improved.

Description

一种综合能源系统的电储能事故备用容量优化利用方法A method for optimal utilization of reserve capacity for electric energy storage accident in an integrated energy system

技术领域technical field

本发明涉及一种综合能源系统的电储能事故备用容量优化利用方法。The invention relates to a method for optimizing the utilization of an electric energy storage accident reserve capacity of an integrated energy system.

背景技术Background technique

具有快速响应能力以及短时高倍率放电等优点的电储能，是综合能源系统理想的备用电源。然而，与之矛盾的是，受益于目前大电网极高的安全性和稳定性，综合能源系统在实际运行过程中，配置的电储能事故备用基本处于闲置状态，在一定程度上造成了资源的浪费。Electric energy storage, which has the advantages of fast response capability and short-term high-rate discharge, is an ideal backup power source for integrated energy systems. However, it is paradoxical that, benefiting from the extremely high safety and stability of the current large power grid, in the actual operation process of the integrated energy system, the configured electric energy storage accident backup is basically in an idle state, which to a certain extent causes resources of waste.

因此，在承担一定风险的情况下，可考虑以下几个因素优化利用电储能备用，进一步提高系统运行的经济性：1)考虑系统各时段重要负荷需求差异；2)考虑系统所处区域不同状态(特别是天气状态，负载状态等)下发生事故的概率差异；3)考虑不同事故发生后损失的差异。另一方面，柔性负荷的调节是缓解供需侧矛盾的重要手段之一。随着手机、智能无线设备和电动汽车的快速发展，电池的市场需求越来越广。电池生产过程中的分容测试逐渐采用能量回馈的形式以实现节能环保。目前，厂商对分容工序充放电参数设置过于简单，通过需求响应手段优化分容工序，不仅可以提高并网运行的经济性，同时，可以满足脱网情况下部分重要负荷的供电需求，进一步优化利用电储能事故备用容量。系统中若含有温控负荷，可利用其柔性特征，在许可范围内降低舒适度，起到短时缓冲供能不足的作用。Therefore, under the condition of taking certain risks, the following factors can be considered to optimize the use of electric energy storage backup to further improve the economy of the system operation: 1) Consider the difference in the demand for important loads in different periods of the system; 2) Consider the different regions where the system is located The difference in the probability of accidents occurring under different conditions (especially weather conditions, load conditions, etc.); 3) Consider the difference in losses after different accidents occur. On the other hand, the adjustment of flexible load is one of the important means to alleviate the contradiction between supply and demand. With the rapid development of mobile phones, smart wireless devices and electric vehicles, the market demand for batteries is getting wider and wider. The capacity distribution test in the battery production process gradually adopts the form of energy feedback to achieve energy saving and environmental protection. At present, the setting of the charging and discharging parameters of the capacity sharing process is too simple. By optimizing the capacity sharing process by means of demand response, it can not only improve the economy of grid-connected operation, but also meet the power supply demand of some important loads in the case of off-grid, and further optimize the Utilize electric energy storage accident reserve capacity. If the system contains temperature-controlled loads, its flexibility can be used to reduce comfort within the permitted range, and play a role in short-term buffering of insufficient energy supply.

基于此，本发明兼顾脱网风险与并网收益，并考虑分容电池与温控负荷的柔性特征，提出一种基于风险量化与需求侧响应的电储能事故备用容量优化利用方法。对于含有较大规模电储能事故备用的电池生产园区综合能源系统来说，本发明具有很好的经济应用价值。Based on this, the present invention takes into account off-grid risk and grid-connected benefits, and considers the flexible characteristics of capacity-sharing batteries and temperature-controlled loads, and proposes an optimal utilization method of electric energy storage accident reserve capacity based on risk quantification and demand-side response. For the comprehensive energy system of the battery production park with large-scale electric energy storage accident backup, the invention has good economical application value.

发明内容SUMMARY OF THE INVENTION

本发明要解决的技术问题是，针对电池生产园区综合能源系统并网运行过程中储能设备的事故容量利用率不高的问题，提供一种综合能源系统的电储能事故备用容量优化利用方法，在兼顾脱网风险与并网收益的情况下，充分利用储能设备的事故容量，以进一步提高电池生产园区综合能源系统并网运行的经济性。The technical problem to be solved by the present invention is to provide a method for optimizing the utilization of electric energy storage accident reserve capacity of an integrated energy system, aiming at the problem that the accident capacity utilization rate of the energy storage equipment is not high during the grid-connected operation of the integrated energy system of the battery production park. , in the case of taking into account the risk of off-grid and the benefits of grid-connected, make full use of the accident capacity of energy storage equipment to further improve the economics of grid-connected operation of the integrated energy system of the battery production park.

为实现上述技术目的，本发明采用如下技术方案：For realizing the above-mentioned technical purpose, the present invention adopts following technical scheme:

基于风险量化与需求侧响应的综合能源系统优化利用方法，包括：Integrated energy system optimization and utilization methods based on risk quantification and demand side response, including:

步骤1，对电池生产园区的综合能源系统各设备分别构建能量模型，包括储能模型、热电联产模型、制冷设备模型、水泵模型；Step 1: Build energy models for each device of the comprehensive energy system in the battery production park, including energy storage models, cogeneration models, refrigeration equipment models, and water pump models;

步骤2，基于电池生产园区对综合能源系统的需求响应，以及电池生产园区的脱网风险，构建并网期望收益模型和脱网期望损失模型；Step 2: Based on the demand response of the battery production park to the integrated energy system and the off-grid risk of the battery production park, construct the grid-connected expected benefit model and the off-grid expected loss model;

其中，电池生产园区的脱网风险，通过综合考虑非计划脱网的概率和重要负荷损失进行量化得到；Among them, the off-grid risk of the battery production park is quantified by comprehensively considering the probability of unplanned off-grid and important load losses;

步骤3，综合并网期望收益和脱网期望损失，建立兼顾脱网风险与并网收益的综合能源系统优化调度模型；Step 3, synthesizing the expected benefit of grid connection and the expected loss of off-grid, and establishing a comprehensive energy system optimization scheduling model that takes into account the risk of off-grid and the benefit of grid connection;

步骤4，求解综合能源系统优化调度模型，得到综合能源系统中储能设备的事故备用容量、综合能源系统中各设备的功率以及电池生成园区各重要环节负荷的投切状态。Step 4: Solve the optimal scheduling model of the integrated energy system, and obtain the emergency reserve capacity of the energy storage equipment in the integrated energy system, the power of each device in the integrated energy system, and the switching state of the load of each important link in the battery generation park.

进一步的，步骤4的求解方法为：通过线性化处理将综合能源系统优化调度模型转换为混合整数线性规划模型，然后调用MATLAB混合整数线性规划intlinprog函数进行求解。Further, the solution method of step 4 is: converting the integrated energy system optimal scheduling model into a mixed integer linear programming model through linearization processing, and then calling the MATLAB mixed integer linear programming intlinprog function to solve.

进一步的，储能设备的类型包括电储能设备、冷储能设备、热储能设备、生产性储能设备，同一类型电池作为一个生产性储能设备，针对每个储能模型构建的储能模型均可表示为：Further, the types of energy storage devices include electric energy storage devices, cold energy storage devices, thermal energy storage devices, and productive energy storage devices. The same type of battery is used as a productive energy storage device. The energy model can be expressed as:

对于

Figure BDA0002685296090000021
for
Figure BDA0002685296090000021

Figure BDA0002685296090000022
Figure BDA0002685296090000022

Figure BDA0002685296090000023
Figure BDA0002685296090000023

0≤Pt ESc≤PESn (1c)0≤P t ESc ≤P ESn (1c)

0≤Pt ESd≤PESn (1d)0≤P t ESd ≤P ESn (1d)

Pt ESdPt ESc＝0 (1e)P t ESd P t ESc =0 (1e)

Pt ES＝Pt ESd-Pt ESc (1f)P t ES =P t ESd -P t ESc (1f)

式中：t为运行时段；N为运行时段集合；ES为储能类型，可以为bes、ces、hes、ges，分别对应电、冷、热、生产性储能；

Figure BDA0002685296090000024
为储能设备所储存的容量与额定容量的比值；κES为能量自损耗率；
Figure BDA0002685296090000025
分别为储能设备的充、放能效率；Pt ESc、Pt ESd分别为储能设备的充、放能功率；WESn为储能设备的额定容量；Δt为调度周期；
Figure BDA0002685296090000026
分别为最小允许储能容量、最大允许储能容量与储能额定容量的比值；PESn为储能设备的额定功率；Pt ES为储能功率，规定放能为正，充能为负；In the formula: t is the operation period; N is the set of operation periods; ES is the energy storage type, which can be bes, ces, hes, and ges, corresponding to electricity, cold, heat, and productive energy storage respectively;
Figure BDA0002685296090000024
is the ratio of the stored capacity to the rated capacity of the energy storage device; κ ES is the energy self-loss rate;
Figure BDA0002685296090000025
are the charging and discharging efficiencies of the energy storage device, respectively; P t ESc and P t ESd are the charging and discharging power of the energy storage device, respectively; W ESn is the rated capacity of the energy storage device; Δt is the dispatch period;
Figure BDA0002685296090000026
are the ratio of the minimum allowable energy storage capacity, the maximum allowable energy storage capacity to the rated energy storage capacity, respectively; P ESn is the rated power of the energy storage device; P t ES is the energy storage power, and it is specified that the discharge energy is positive and the charging energy is negative;

针对热电联产设备构建的热电联产模型表示为：The cogeneration model constructed for cogeneration equipment is expressed as:

对于

Figure BDA0002685296090000027
for
Figure BDA0002685296090000027

Figure BDA0002685296090000028
Figure BDA0002685296090000028

Figure BDA0002685296090000031
Figure BDA0002685296090000031

Figure BDA0002685296090000032
Figure BDA0002685296090000032

Figure BDA0002685296090000033
Figure BDA0002685296090000033

Figure BDA0002685296090000034
Figure BDA0002685296090000034

Figure BDA0002685296090000035
Figure BDA0002685296090000035

式中：t为运行时段；N为运行时段集合；Pt chp、

Figure BDA0002685296090000036
分别为热电联产设备输出的电功率、热功率；
Figure BDA0002685296090000037
分别为热电联产设备输入热能的功率上下限；κchpp、κp为输入热能与输出电能间的转换系数和偏差；κchpq、κq为输入热能与输出热能间的转换系数和偏差；△U、△D分别为热电联产最大上爬坡出力、最大下爬坡出力；
Figure BDA0002685296090000038
为经余热回收设备回收利用的热功率；ηchpr为热能利用系数；Ft chp表示热电联产设备输入热能的功率；In the formula: t is the operating period; N is the set of operating periods; P t chp ,
Figure BDA0002685296090000036
are the electrical power and thermal power output by the cogeneration equipment, respectively;
Figure BDA0002685296090000037
are the upper and lower power limits of input thermal energy of cogeneration equipment, respectively; κ chpp , κ p are the conversion coefficient and deviation between input thermal energy and output electrical energy; κ chpq , κ q are the conversion coefficient and deviation between input thermal energy and output thermal energy; △ U and △D are the maximum up-slope output and the maximum down-slope output of cogeneration, respectively;
Figure BDA0002685296090000038
is the thermal power recovered by the waste heat recovery equipment; η chpr is the thermal energy utilization coefficient; F t chp represents the input thermal power of the cogeneration equipment;

制冷设备包括以热能为能源的吸收式冷温水机和以电能为能源的电制冷机，构建的制冷设备模型分别表示为：Refrigeration equipment includes absorption chiller with thermal energy as energy and electric refrigerator with electric energy as energy. The constructed refrigeration equipment models are expressed as:

Figure BDA0002685296090000039
Figure BDA0002685296090000039

Figure BDA00026852960900000310
Figure BDA00026852960900000310

式中：

Figure BDA00026852960900000311
分别为冷温水机的供冷功率、耗热功率；
Figure BDA00026852960900000312
Pt ec分别为电制冷机的供冷功率、耗电功率；ηac、ηec分别为吸收式制冷设备和电制冷设备的性能系数；
Figure BDA00026852960900000313
为制冷设备额定容量；where:
Figure BDA00026852960900000311
are the cooling power and heat consumption power of the cold and warm water machine respectively;
Figure BDA00026852960900000312
P t ec are the cooling power and power consumption of the electric refrigerator, respectively; η ac and η ec are the performance coefficients of the absorption refrigeration equipment and the electric refrigeration equipment, respectively;
Figure BDA00026852960900000313
is the rated capacity of the refrigeration equipment;

针对水泵设备构建的水泵设备模型表示为：The pump equipment model constructed for the pump equipment is expressed as:

Figure BDA00026852960900000314
Figure BDA00026852960900000314

式中，Pt pump为水泵耗电功率；

Figure BDA00026852960900000315
与λc、λh分别为输送冷、热能以及相应耗电系数。In the formula, P t pump is the power consumption of the pump;
Figure BDA00026852960900000315
and λ c , λ h are the transporting cold and heat energy and the corresponding power consumption coefficient, respectively.

进一步的，对非计划脱网的概率进行量化的计算公式为：Further, the calculation formula for quantifying the probability of unplanned disconnection is:

Figure BDA00026852960900000316
Figure BDA00026852960900000316

式中，s、w、i分别表示一天内的时段、天气类型、脱网类型，S、W、I分别一天内的时段数量、天气类型数量、脱网类型数量；Rs,w,i为s时段w类型天气发生i类型脱网的概率；ms,w,i为s时段w类型天气发生i类型脱网的段数；Ms,w为s时段w类型天气的总段数；In the formula, s, w, i represent the time period, weather type, and off-grid type in a day, respectively, S, W, and I respectively represent the number of time periods, weather types, and off-grid types in a day; R s, w, i are Probability of type i off-grid for type w weather in s period; m s,w,i is the number of segments of type w weather in s period when type i is off the grid; Ms s,w is the total number of segments of type w weather in s period;

非计划脱网的重要负荷损失包括电池生产园区的重要环节电负荷损失和重要温控负荷损失；Important load losses due to unplanned off-grid include electrical load losses in important links in the battery production park and important temperature control load losses;

对非计划脱网的重要环节电负荷损失进行量化的计算公式为：The calculation formula for quantifying the electrical load loss in important links of unplanned off-grid is:

假设τ时刻脱网，对于

Figure BDA0002685296090000041
Assuming that τ is off the grid, for
Figure BDA0002685296090000041

Figure BDA0002685296090000042
Figure BDA0002685296090000042

式中，Vs P为脱网后重要环节总损失；Δtoff为脱网时长；h表示第h个重要环节，H表示重要环节的数量；

Figure BDA0002685296090000043
为脱网后某时刻重要环节单位时间单位功率缺额产生的损失；
Figure BDA0002685296090000044
为脱网后某时刻重要环节需求功率；
Figure BDA0002685296090000045
为二进制变量，
Figure BDA0002685296090000046
取1和0分别表示某时刻供应与不供应重要环节负荷；In the formula, V s P is the total loss of important links after the off-grid; Δt off is the off-grid duration; h represents the h-th important link, and H represents the number of important links;
Figure BDA0002685296090000043
It is the loss caused by the unit time and unit power shortage of important links at a certain moment after disconnection;
Figure BDA0002685296090000044
Demand power for important links at a certain moment after off-grid;
Figure BDA0002685296090000045
is a binary variable,
Figure BDA0002685296090000046
Take 1 and 0 to represent the supply and non-supply of important link loads at a certain time;

对非计划脱网的重要温控负荷损失进行量化的的计算公式为：The calculation formula for quantifying the important temperature control load loss due to unplanned off-grid is:

假设τ时刻脱网，对于

Figure BDA0002685296090000047
Assuming that τ is off the grid, for
Figure BDA0002685296090000047

Figure BDA0002685296090000048
Figure BDA0002685296090000048

Figure BDA0002685296090000049
Figure BDA0002685296090000049

式中，Vs Q为脱网后温控负荷总损失；

Figure BDA00026852960900000410
为脱网后某时刻单位时间单位冷/热功率缺额产生的损失；
Figure BDA00026852960900000411
为某时刻重要温控负荷需求功率；Qt为某时刻温控设备输出功率；cair、mair为空气比热容、质量；Tt in、Tt out为某时刻室内、外温度；kq、Aq、Dq为墙体的热传导系数、面积和厚度。In the formula, V s Q is the total loss of temperature control load after off-grid;
Figure BDA00026852960900000410
It is the loss caused by the shortage of cooling/heating power per unit time and unit at a certain moment after the off-grid;
Figure BDA00026852960900000411
is the demand power of important temperature control loads at a certain time; Q t is the output power of the temperature control equipment at a certain time; c air and m air are the specific heat capacity and mass of the air; T t in and T t out are the indoor and outdoor temperatures at a certain time; k q , A q , D q are the thermal conductivity, area and thickness of the wall.

进一步的，构建得到的并网期望收益模型为：Further, the constructed grid-connected expected revenue model is:

Figure BDA00026852960900000412
Figure BDA00026852960900000412

式中，Ec为并网期望收益，C0、C分别为不利用储能备用与利用储能备用的并网运行成本；n为并网运行时段数；Ft chp、ft chp为某时刻燃气热功率与单位功率的成本；KQ为供冷/热设备数量，KP为综合能源系统中的供电设备数量，

Figure BDA00026852960900000413
为供冷/热设备出力，
Figure BDA00026852960900000414
为综合能源系统中的供冷/热设备单位出力的运行维护成本；Pt k和
Figure BDA00026852960900000415
为综合能源系统中的供电设备出力与单位出力的运行维护成本；Pt grid、ft grid分别为综合能源系统与电网交互功率、交互成本；In the formula, E c is the expected income of grid connection, C 0 and C are the operating costs of grid connection without using energy storage backup and using energy storage backup respectively; n is the number of grid-connected operation periods; F t chp , f t chp are certain Time gas heating power and cost per unit power; K Q is the number of cooling/heating equipment, K P is the number of power supply equipment in the integrated energy system,
Figure BDA00026852960900000413
Output for cooling/heating equipment,
Figure BDA00026852960900000414
Operation and maintenance costs per unit output of cooling/heating equipment in the integrated energy system; P t k and
Figure BDA00026852960900000415
is the operation and maintenance cost of power supply equipment output and unit output in the integrated energy system; P t grid and f t grid are the interaction power and interaction cost between the integrated energy system and the grid, respectively;

构建得到的脱网期望损失模型为：The constructed off-net expected loss model is:

Figure BDA0002685296090000051
Figure BDA0002685296090000051

式中，El为脱网期望损失，V为脱网运行成本与切负荷损失之和；τ、i为脱网时刻和类型；

Figure BDA0002685296090000052
为τ时刻脱网情形下某时刻的燃气热功率；
Figure BDA0002685296090000053
为τ时刻脱网情形下某时刻供冷/热设备出力、供电设备出力；
Figure BDA0002685296090000054
为二进制变量，
Figure BDA0002685296090000055
取1和0分别表示τ时刻脱网情形下某时刻供应与不供应第h个重要环节负荷；In the formula, E l is the expected loss of off-grid, V is the sum of off-grid operation cost and load shedding loss; τ and i are off-grid time and type;
Figure BDA0002685296090000052
is the thermal power of gas at a certain moment when the grid is disconnected at time τ;
Figure BDA0002685296090000053
For the output of cooling/heating equipment and power supply equipment at a certain time when the grid is disconnected at time τ;
Figure BDA0002685296090000054
is a binary variable,
Figure BDA0002685296090000055
Taking 1 and 0 respectively means that the load of the h-th important link is supplied or not supplied at a certain moment in the case of disconnection at time τ;

综合能源系统优化调度模型的目标函数为：The objective function of the optimal dispatch model of the integrated energy system is:

maxE＝Ec-El (10)maxE=E c -E l (10)

式中，E为目标期望收益；In the formula, E is the target expected return;

能源系统优化调度模型包括并网约束、脱网约束、并网与脱网关联约束以及生产性储能生产约束，分别表示为：The optimal scheduling model of the energy system includes grid-connection constraints, off-grid constraints, grid-connected and off-grid association constraints, and productive energy storage production constraints, which are expressed as:

对于

Figure BDA0002685296090000056
for
Figure BDA0002685296090000056

Figure BDA0002685296090000057
Figure BDA0002685296090000057

Figure BDA0002685296090000058
Figure BDA0002685296090000058

式(11a)为冷能或热能平衡约束，式(11b)为电能平衡约束；λ为水泵电耗系数；Pt l为并网电负荷；

Figure BDA0002685296090000059
为电制冷/热功率；
Figure BDA00026852960900000510
为并网冷/热负荷；
Figure BDA00026852960900000511
为第d个生产性储能出力；D为生产性储能个数；Equation (11a) is the cooling energy or heat energy balance constraint, Equation (11b) is the electric energy balance constraint; λ is the power consumption coefficient of the pump; P t l is the grid-connected power load;
Figure BDA0002685296090000059
is the electrical cooling/heating power;
Figure BDA00026852960900000510
for grid-connected cooling/heating loads;
Figure BDA00026852960900000511
is the output of the d-th productive energy storage; D is the number of productive energy storages;

对于

Figure BDA00026852960900000512
for
Figure BDA00026852960900000512

Figure BDA00026852960900000513
Figure BDA00026852960900000513

式(12)中，第一项为重要环节连续供能约束；第二项为τ时刻脱网情形下电能平衡约束，Pt con为控制中心与消防负荷；第三、四项为τ时刻脱网情形下温控负荷柔性约束，Ts为标准温度；

Figure BDA0002685296090000061
为温控负荷舒适度范围下、上限；In formula (12), the first term is the continuous energy supply constraint of important links; the second term is the power balance constraint in the case of off-grid at time τ, and P t con is the control center and fire load; the third and fourth terms are off-grid at time τ. The flexible constraint of temperature control load under the network condition, T s is the standard temperature;
Figure BDA0002685296090000061
are the lower and upper limits of the temperature-controlled load comfort range;

对于

Figure BDA0002685296090000062
for
Figure BDA0002685296090000062

Figure BDA0002685296090000063
Figure BDA0002685296090000063

式(13)中，

Figure BDA0002685296090000064
为并网运行过程中τ时刻燃气机电功率，
Figure BDA0002685296090000065
为τ时刻脱网运行燃气机初始电功率；
Figure BDA0002685296090000066
为并网运行过程中τ时刻储能容量状态，
Figure BDA0002685296090000067
为τ时刻脱网运行储能初始容量状态；In formula (13),
Figure BDA0002685296090000064
is the gas-electric motor power at time τ during grid-connected operation,
Figure BDA0002685296090000065
is the initial electric power of the gas turbine running off-grid at time τ;
Figure BDA0002685296090000066
is the state of energy storage capacity at time τ during grid-connected operation,
Figure BDA0002685296090000067
is the initial capacity state of energy storage for off-grid operation at time τ;

对于

Figure BDA0002685296090000068
for
Figure BDA0002685296090000068

Figure BDA0002685296090000069
Figure BDA0002685296090000069

Figure BDA00026852960900000610
Figure BDA00026852960900000610

Figure BDA00026852960900000611
Figure BDA00026852960900000611

式中，Kr为预留时段数，

Figure BDA00026852960900000612
和
Figure BDA00026852960900000613
为充放电倍率上限值。In the formula, K r is the number of reserved periods,
Figure BDA00026852960900000612
and
Figure BDA00026852960900000613
is the upper limit of the charge-discharge rate.

进一步的，综合能源系统优化调度模型的求解变量包括：综合能源系统在并网运行时与电网的交互功率、储能设备的备用容量、储能设备的充放能功率、热电联产设备输入热能的功率、吸收式冷温水机的功率、电制冷机的功率，以及综合能源系统在脱网运行时，储能设备的充放能功率、热电联产设备输入热能的功率、吸收式冷温水机的功率、电制冷机的功率、电池生产园区各重要环节负荷的投切状态。Further, the solution variables of the integrated energy system optimal dispatch model include: the interactive power between the integrated energy system and the grid when the integrated energy system is connected to the grid, the reserve capacity of the energy storage device, the charging and discharging power of the energy storage device, and the input thermal energy of the cogeneration device. The power of the absorption chiller, the power of the electric refrigerator, and the charging and discharging power of the energy storage equipment, the power of the heat input of the cogeneration equipment, the power of the absorption chiller when the integrated energy system is running off-grid The power of the electric refrigerator, the power of the electric refrigerator, and the switching state of the load of each important link in the battery production park.

有益效果beneficial effect

本发明考虑不同状态下的非计划脱网概率以及重要负荷损失，将脱网风险进行量化，在此基础上，兼顾脱网风险与并网收益，并考虑分容电池与温控负荷柔性特征，构建基于风险量化与需求侧响应的综合能源系统优化调度模型。根据现有预测技术，提前判断天气状态，实现不同状态下电储能事故备用容量的最优化利用以及电池分容工序的最优化安排。The invention considers the unplanned off-grid probability and important load loss in different states, and quantifies the off-grid risk. A comprehensive energy system optimal dispatch model based on risk quantification and demand-side response is constructed. According to the existing prediction technology, the weather state is judged in advance, and the optimal utilization of the backup capacity of the electric energy storage accident under different states and the optimal arrangement of the battery capacity distribution process are realized.

本发明的有益效果是：The beneficial effects of the present invention are:

(1)本发明的非计划脱网概率计算方法考虑了天气状态、负载率水平以及脱网类型多种因素，能够较为准确地预判脱网风险。(1) The unplanned off-grid probability calculation method of the present invention takes into account various factors such as weather conditions, load rate levels and off-grid types, and can more accurately predict off-grid risks.

(2)本发明兼顾脱网风险与并网收益，并利用分容电池与温控负荷的柔性特征，构建了基于风险量化与需求侧响应的综合能源系统经济优化调度模型。该方法能够实现不同状态下电储能事故备用容量的最优化利用以及电池分容工序的最优化安排，可在承担较小风险的情况下提高系统运行的经济性，具有较好的实用性和经济性。(2) The present invention takes both off-grid risk and grid-connected benefits into consideration, and utilizes the flexible features of split-capacity batteries and temperature-controlled loads to construct an economic optimal dispatch model for a comprehensive energy system based on risk quantification and demand-side response. The method can realize the optimal utilization of the backup capacity of the electric energy storage accident in different states and the optimal arrangement of the battery capacity sharing process, which can improve the economy of the system operation under the condition of less risk, and has good practicability and efficiency. economical.

附图说明Description of drawings

图1为本发明实施例所述方法的流程框图；Fig. 1 is a flowchart of the method according to an embodiment of the present invention;

图2为本发明实施例所述电池生产园区的能流图；2 is an energy flow diagram of a battery production park according to an embodiment of the present invention;

图3为本发明实施例所述电池生产园区的电池生产环节示意图。FIG. 3 is a schematic diagram of a battery production process in a battery production park according to an embodiment of the present invention.

具体实施方式Detailed ways

本实施例以本发明的技术方案为依据开展，给出了详细的实施方式和具体的操作过程，对本发明的技术方案作进一步解释说明。This embodiment is carried out based on the technical solution of the present invention, and provides a detailed implementation manner and a specific operation process, and further explains the technical solution of the present invention.

本发明实施例公开的是一种综合能源系统的电储能事故备用容量优化利用方法，如图1所示，包括以下步骤：The embodiment of the present invention discloses a method for optimizing the utilization of an electric energy storage accident reserve capacity of an integrated energy system. As shown in FIG. 1 , the method includes the following steps:

步骤1，对电池生产园区的综合能源系统各设备分别构建能量模型，包括储能模型、热电联产模型、制冷设备模型、水泵模型。本实施例中的电池生产园区的能流图参考图2所示。Step 1: Build an energy model for each device of the comprehensive energy system in the battery production park, including an energy storage model, a cogeneration model, a refrigeration equipment model, and a water pump model. The energy flow diagram of the battery production park in this embodiment is shown with reference to FIG. 2 .

综合能源系统中的储能设备类型包括电储能、冷储能、热储能、生产性储能，生产园区有A/B/C/D四种类型的电池，同一类型电池作为一个生产性储能设备，所有储能设备可建立统一模型，表示为：The types of energy storage equipment in the integrated energy system include electric energy storage, cold energy storage, thermal energy storage, and productive energy storage. There are four types of batteries A/B/C/D in the production park. Energy storage equipment, all energy storage equipment can establish a unified model, which is expressed as:

对于

Figure BDA0002685296090000071
for
Figure BDA0002685296090000071

Figure BDA0002685296090000072
Figure BDA0002685296090000072

Figure BDA0002685296090000073
Figure BDA0002685296090000073

0≤Pt ESc≤PESn (1c)0≤P t ESc ≤P ESn (1c)

0≤Pt ESd≤PESn (1d)0≤P t ESd ≤P ESn (1d)

Pt ESdPt ESc＝0 (1e)P t ESd P t ESc =0 (1e)

Pt ES＝Pt ESd-Pt ESc (1f)P t ES =P t ESd -P t ESc (1f)

其中，式(1a)表示储能运行相邻时段能量平衡关系；式(1b)表示储能容量状态上下限约束；式(1c)-(1e)表示储能出力限制及充/放能互补约束；式(1f)表示储能输出功率；Among them, Equation (1a) represents the energy balance relationship between the adjacent periods of energy storage operation; Equation (1b) represents the upper and lower limit constraints of the energy storage capacity state; Equations (1c)-(1e) represent the energy storage output limit and charge/discharge complementary constraints ; Formula (1f) represents the output power of energy storage;

式(1)中：t为运行时段；N为运行时段集合；ES为储能类型，可以为bes、ces、hes、ges，分别对应电、冷、热、生产性储能；

Figure BDA0002685296090000081
为储能设备所储存的容量与额定容量的比值；κES为能量自损耗率；
Figure BDA0002685296090000082
分别为储能设备的充、放能效率；Pt ESc、Pt ESd分别为储能设备的充、放能功率；WESn为储能设备的额定容量；Δt为调度周期；
Figure BDA0002685296090000083
分别为最小允许储能容量、最大允许储能容量与储能额定容量的比值；PESn为储能设备的额定功率；Pt ES为储能功率，规定放能为正，充能为负。In formula (1): t is the operation period; N is the set of operation periods; ES is the energy storage type, which can be bes, ces, hes, and ges, corresponding to electricity, cold, heat, and productive energy storage respectively;
Figure BDA0002685296090000081
is the ratio of the stored capacity to the rated capacity of the energy storage device; κ ES is the energy self-loss rate;
Figure BDA0002685296090000082
are the charging and discharging efficiencies of the energy storage device, respectively; P t ESc and P t ESd are the charging and discharging power of the energy storage device, respectively; W ESn is the rated capacity of the energy storage device; Δt is the dispatch period;
Figure BDA0002685296090000083
are the ratio of the minimum allowable energy storage capacity, the maximum allowable energy storage capacity to the rated energy storage capacity, respectively; P ESn is the rated power of the energy storage device; P t ES is the energy storage power, and it is specified that discharge is positive and charging is negative.

热电联产设备主要为燃气机。当输入热能达到一定程度时燃气机同时输出电能和热能，其模型描述为式(2)。式(2a)-(2e)为热电联产出力及爬坡约束；式(2f)表示燃气机产生的热量一部分经余热回收设备回收，另一部分未被利用成为弃热。The cogeneration equipment is mainly gas turbine. When the input thermal energy reaches a certain level, the gas turbine simultaneously outputs electric energy and thermal energy, and its model is described as formula (2). Equations (2a)-(2e) are the cogeneration capacity and ramp constraints; Equation (2f) indicates that part of the heat generated by the gas turbine is recovered by the waste heat recovery equipment, and the other part is not used as waste heat.

对于

Figure BDA0002685296090000084
for
Figure BDA0002685296090000084

Figure BDA0002685296090000085
Figure BDA0002685296090000085

Figure BDA0002685296090000086
Figure BDA0002685296090000086

Figure BDA0002685296090000087
Figure BDA0002685296090000087

Figure BDA0002685296090000088
Figure BDA0002685296090000088

Figure BDA0002685296090000089
Figure BDA0002685296090000089

Figure BDA00026852960900000810
Figure BDA00026852960900000810

式(2)中：t为运行时段；N为运行时段集合；Pt chp、

Figure BDA00026852960900000811
分别为热电联产设备输出的电功率、热功率；
Figure BDA00026852960900000812
分别为热电联产设备输入热能的功率上下限；κchpp、κp为输入热能与输出电能间的转换系数和偏差；κchpq、κq为输入热能与输出热能间的转换系数和偏差；△U、△D分别为热电联产最大上爬坡出力、最大下爬坡出力；
Figure BDA00026852960900000813
为经余热回收设备回收利用的热功率；ηchpr为热能利用系数，Ft chp表示热电联产设备输入热能的功率。In formula (2): t is the operating period; N is the set of operating periods; P t chp ,
Figure BDA00026852960900000811
are the electrical power and thermal power output by the cogeneration equipment, respectively;
Figure BDA00026852960900000812
are the upper and lower power limits of input thermal energy of cogeneration equipment, respectively; κ chpp , κ p are the conversion coefficient and deviation between input thermal energy and output electrical energy; κ chpq , κ q are the conversion coefficient and deviation between input thermal energy and output thermal energy; △ U and △D are the maximum up-slope output and the maximum down-slope output of cogeneration, respectively;
Figure BDA00026852960900000813
is the thermal power recovered by the waste heat recovery equipment; η chpr is the thermal energy utilization coefficient, and F t chp represents the input thermal power of the cogeneration equipment.

制冷设备包括以热能为能源的吸收式冷温水机和以电能为能源的电制冷机，构建的制冷设备模型分别表示为：Refrigeration equipment includes absorption chiller with thermal energy as energy and electric refrigerator with electric energy as energy. The constructed refrigeration equipment models are expressed as:

Figure BDA0002685296090000091
Figure BDA0002685296090000091

Figure BDA0002685296090000092
Figure BDA0002685296090000092

式中：

Figure BDA0002685296090000093
分别为冷温水机的供冷功率、耗热功率；
Figure BDA0002685296090000094
Pt ec分别为电制冷机的供冷功率、耗电功率；ηac、ηec分别为吸收式制冷设备和电制冷设备的性能系数；
Figure BDA0002685296090000095
为制冷设备额定容量；where:
Figure BDA0002685296090000093
are the cooling power and heat consumption power of the cold and warm water machine respectively;
Figure BDA0002685296090000094
P t ec are the cooling power and power consumption of the electric refrigerator, respectively; η ac and η ec are the performance coefficients of the absorption refrigeration equipment and the electric refrigeration equipment, respectively;
Figure BDA0002685296090000095
is the rated capacity of the refrigeration equipment;

水泵是冷热联供系统中输送冷热能的设备，由耗电功率与输送冷热能关系构成的水泵设备模型表示为：The water pump is the equipment for conveying cold and heat energy in the combined cooling and heating system. The pump equipment model composed of the relationship between power consumption and conveying cold and heat energy is expressed as:

Figure BDA0002685296090000096
Figure BDA0002685296090000096

式中，Pt pump为水泵耗电功率；

Figure BDA0002685296090000097
与λc、λh分别为输送冷、热能以及相应耗电系数。In the formula, P t pump is the power consumption of the pump;
Figure BDA0002685296090000097
and λ c , λ h are the transporting cold and heat energy and the corresponding power consumption coefficient, respectively.

步骤2，基于电池生产园区对综合能源系统的需求响应，以及电池生产园区的脱网风险，构建并网期望收益模型和脱网期望损失模型；Step 2: Based on the demand response of the battery production park to the integrated energy system and the off-grid risk of the battery production park, construct the grid-connected expected benefit model and the off-grid expected loss model;

其中，电池生产园区的脱网风险，关键在于计算事件发生的概率以及事件带来的后果，因此可通过综合考虑非计划脱网的概率和重要负荷损失进行量化得到。Among them, the key to the off-grid risk of battery production parks is to calculate the probability of the event and the consequences of the event. Therefore, it can be quantified by comprehensively considering the probability of unplanned off-grid and the loss of important loads.

对非计划脱网的概率进行量化的计算公式为：The formula to quantify the probability of unplanned disconnection is:

Figure BDA0002685296090000098
Figure BDA0002685296090000098

式中，s、w、i分别表示一天内的时段、天气类型、脱网类型，S、W、I分别一天内的时段数量、天气类型数量、脱网类型数量；Rs,w,i为s时段w类型天气发生i类型脱网的概率；ms,w,i为s时段w类型天气发生i类型脱网的段数；Ms,w为s时段w类型天气的总段数；本实施例中，S＝3、W＝3、I＝3。In the formula, s, w, i represent the time period, weather type, and off-grid type in a day, respectively, S, W, and I respectively represent the number of time periods, weather types, and off-grid types in a day; R s, w, i are The probability that the type i type is disconnected from the network in the s period of the type w weather; m s ,w,i is the number of sections of the type w type of weather in the s period of Among them, S=3, W=3, I=3.

非计划脱网的重要负荷损失包括电池生产园区的重要环节电负荷损失和重要温控负荷损失；Important load losses due to unplanned off-grid include electrical load losses in important links in the battery production park and important temperature control load losses;

如图3所示的电池生产环节，其中阶段1和阶段2内部的方框为重要环节电负荷，共4个，阶段3的化成环节通过给电池充电以激活电池，分容环节通过充放电测试电池容量。非计划脱网后，需要维持重要环节正常工作一段时间以处理完当前批次剩余材料。处理材料的数量与所消耗电能基本成正比，以重要环节单位时间单位功率缺额产生的经济损失与缺额电能的乘积表示重要环节电负荷损失，即，对非计划脱网的重要环节电负荷损失进行量化的计算公式为：As shown in Figure 3, the battery production process is shown in Figure 3, in which the boxes inside Stage 1 and Stage 2 are the electrical loads of important links, a total of 4. The formation process of Stage 3 activates the battery by charging the battery, and the capacity distribution process passes the charge-discharge test. battery capacity. After unplanned off-grid, it is necessary to maintain the normal operation of important links for a period of time to process the remaining materials of the current batch. The amount of processing materials is basically proportional to the electric energy consumed, and the electrical load loss of the important links is expressed by the product of the economic loss caused by the unit time and unit power shortage of the important links and the lack of electric energy, that is, the electrical load loss of the important links that are not planned to be disconnected from the grid. The calculation formula for quantification is:

假设τ时刻脱网，对于

Figure BDA0002685296090000101
Assuming that τ is off the grid, for
Figure BDA0002685296090000101

Figure BDA0002685296090000102
Figure BDA0002685296090000102

式中，Vs P为脱网后重要环节总损失；Δtoff为脱网时长；h表示第h个重要环节，H表示重要环节的数量，本实施例中H＝4；

Figure BDA0002685296090000103
为脱网后某时刻重要环节单位时间单位功率缺额产生的损失；
Figure BDA0002685296090000104
为脱网后某时刻重要环节需求功率；
Figure BDA0002685296090000105
为二进制变量，
Figure BDA0002685296090000106
取1和0分别表示某时刻供应与不供应重要环节负荷。In the formula, V s P is the total loss of important links after off-grid; Δt off is the off-grid duration; h represents the h-th important link, H represents the number of important links, and H=4 in this embodiment;
Figure BDA0002685296090000103
It is the loss caused by the unit time and unit power shortage of important links at a certain moment after disconnection;
Figure BDA0002685296090000104
Demand power for important links at a certain moment after off-grid;
Figure BDA0002685296090000105
is a binary variable,
Figure BDA0002685296090000106
Take 1 and 0 to represent the supply and non-supply of important link loads at a certain time, respectively.

在发生非计划脱网后，电池生产园区需维持在舒适温度范围内防止各生产环节材料损坏，在舒适范围内偏离标准温度会降低舒适度。因此，以温控负荷单位时间单位冷/热功率缺额产生的经济损失与缺额冷/热能的乘积表示舒适度降低引起的损失，即，对非计划脱网的重要温控负荷损失进行量化的的计算公式为：After an unplanned disconnection occurs, the battery production park needs to maintain a comfortable temperature range to prevent material damage in all production links. Deviation from the standard temperature within the comfortable range will reduce the comfort level. Therefore, the loss caused by the reduction of comfort is expressed as the product of the economic loss caused by the shortfall of cooling/heating power per unit time and unit of the temperature-controlled load and the shortfall of cooling/heating energy, that is, the loss of important temperature-controlled loads due to unplanned off-grid is quantified. The calculation formula is:

假设τ时刻脱网，对于

Figure BDA0002685296090000107
Assuming that τ is off the grid, for
Figure BDA0002685296090000107

Figure BDA0002685296090000108
Figure BDA0002685296090000108

Figure BDA0002685296090000109
Figure BDA0002685296090000109

式中，Vs Q为脱网后温控负荷总损失；

Figure BDA00026852960900001010
为脱网后某时刻单位时间单位冷/热功率缺额产生的损失；
Figure BDA00026852960900001011
为某时刻重要温控负荷需求功率；Qt为某时刻温控设备输出功率；cair、mair为空气比热容、质量；Tt in、Tt out为某时刻室内、外温度；kq、Aq、Dq为墙体的热传导系数、面积和厚度。In the formula, V s Q is the total loss of temperature control load after off-grid;
Figure BDA00026852960900001010
It is the loss caused by the shortage of cooling/heating power per unit time and unit at a certain moment after the off-grid;
Figure BDA00026852960900001011
is the demand power of important temperature control loads at a certain time; Q t is the output power of the temperature control equipment at a certain time; c air and m air are the specific heat capacity and mass of the air; T t in and T t out are the indoor and outdoor temperatures at a certain time; k q , A q , D q are the thermal conductivity, area and thickness of the wall.

电池生产园区的综合能源系统在并网运行时，基于电池生产园区对综合能源系统的需求响应以及电池生产园区的脱网风险，构建得到的并网期望收益模型为：When the integrated energy system of the battery production park is connected to the grid, based on the demand response of the battery production park to the integrated energy system and the off-grid risk of the battery production park, the expected income model of grid connection is constructed as follows:

Figure BDA00026852960900001012
Figure BDA00026852960900001012

式中，Ec为并网期望收益，C0、C分别为不利用储能备用与利用储能备用的并网运行成本；n为并网运行时段数；Ft chp、ft chp为某时刻燃气热功率与单位功率的成本；KQ为供冷/热设备数量，KP为供电设备数量，

Figure BDA00026852960900001013
为供冷/热设备出力，
Figure BDA00026852960900001014
为供冷/热设备单位出力的运行维护成本；Pt k和
Figure BDA0002685296090000111
为供电设备出力与单位出力的运行维护成本；Pt grid、ft grid分别为综合能源系统与电网交互功率、交互成本。若脱网发生在T1时段，恢复并网后储能仍然可以在剩余时段完成峰谷差套利，其收益与无脱网的收益相同。因此，计算Ec时s不用取1。In the formula, E c is the expected income of grid connection, C 0 and C are the operating costs of grid connection without using energy storage backup and using energy storage backup respectively; n is the number of grid-connected operation periods; F t chp , f t chp are certain Time gas heating power and cost per unit power; K Q is the number of cooling/heating equipment, K P is the number of power supply equipment,
Figure BDA00026852960900001013
Output for cooling/heating equipment,
Figure BDA00026852960900001014
Operation and maintenance cost per unit output of cooling/heating equipment; P t k and
Figure BDA0002685296090000111
It is the operation and maintenance cost of power supply equipment output and unit output; P t grid and ft grid are the interaction power and interaction cost between the integrated energy system and the grid , respectively. If the off-grid occurs in the T1 period, the energy storage can still complete the peak - valley difference arbitrage in the remaining period after the grid is restored, and the benefits are the same as those without off-grid. Therefore, s does not need to be 1 when calculating E c .

电池生产园区的综合能源系统在发生非计划脱时，基于电池生产园区对综合能源系统的需求响应以及电池生产园区的脱网风险，构建得到的脱网期望损失模型为：When the integrated energy system of the battery production park is unplanned, based on the demand response of the battery production park to the integrated energy system and the off-grid risk of the battery production park, the expected loss model for off-grid is constructed as follows:

Figure BDA0002685296090000112
Figure BDA0002685296090000112

式中，El为脱网期望损失，V为脱网运行成本与切负荷损失之和；τ、i为脱网时刻和类型；

Figure BDA0002685296090000113
为τ时刻脱网情形下某时刻的燃气热功率；
Figure BDA0002685296090000114
为τ时刻脱网情形下某时刻供冷/热设备出力、供电设备出力；
Figure BDA0002685296090000115
为二进制变量，
Figure BDA0002685296090000116
取1和0分别表示τ时刻脱网情形下某时刻供应与不供应第h个重要环节负荷。In the formula, E l is the expected loss of off-grid, V is the sum of off-grid operation cost and load shedding loss; τ and i are off-grid time and type;
Figure BDA0002685296090000113
is the thermal power of gas at a certain moment when the grid is disconnected at time τ;
Figure BDA0002685296090000114
For the output of cooling/heating equipment and power supply equipment at a certain time when the grid is disconnected at time τ;
Figure BDA0002685296090000115
is a binary variable,
Figure BDA0002685296090000116
Taking 1 and 0 respectively means that the h-th important link load is supplied or not supplied at a certain moment in the case of disconnection at time τ.

步骤3，综合并网期望收益和脱网期望损失，建立兼顾脱网风险与并网收益的综合能源系统优化调度模型，即由上述并网期望收益和脱网期望损失建立的目标函数：Step 3: Synthesize the expected income of grid connection and the expected loss of off-grid, and establish a comprehensive energy system optimization scheduling model that takes into account the risk of off-grid and the income of grid connection, that is, the objective function established by the above-mentioned expected income and expected loss of grid connection:

maxE＝Ec-El (10)maxE=E c -E l (10)

式中，E为目标期望收益；且该目标函数还包括并网约束、脱网约束、并网与脱网关联约束以及生产性储能生产约束。In the formula, E is the target expected income; and the objective function also includes grid-connection constraints, off-grid constraints, grid-connected and off-grid association constraints, and productive energy storage production constraints.

并网约束表示为：The grid-connected constraints are expressed as:

对于

Figure BDA0002685296090000117
for
Figure BDA0002685296090000117

Figure BDA0002685296090000118
Figure BDA0002685296090000118

Figure BDA0002685296090000119
Figure BDA0002685296090000119

式(11a)为冷能或热能平衡约束，式(11b)为电能平衡约束；λ为水泵电耗系数；Pt l为并网电负荷；

Figure BDA00026852960900001110
为电制冷/热功率；
Figure BDA00026852960900001111
为并网冷/热负荷；
Figure BDA00026852960900001112
为第d个生产性储能出力；D为生产性储能个数。Equation (11a) is the cooling energy or heat energy balance constraint, Equation (11b) is the electric energy balance constraint; λ is the power consumption coefficient of the pump; P t l is the grid-connected power load;
Figure BDA00026852960900001110
is the electrical cooling/heating power;
Figure BDA00026852960900001111
for grid-connected cooling/heating loads;
Figure BDA00026852960900001112
is the output of the d-th productive energy storage; D is the number of productive energy storages.

脱网约束表示为：The off-grid constraint is expressed as:

对于

Figure BDA00026852960900001113
for
Figure BDA00026852960900001113

Figure BDA0002685296090000121
Figure BDA0002685296090000121

式(12)中，第一项为重要环节连续供能约束；第二项为τ时刻脱网情形下电能平衡约束，Pt con为控制中心与消防负荷；第三、四项为τ时刻脱网情形下温控负荷柔性约束，Ts为标准温度；

Figure BDA0002685296090000122
为温控负荷舒适度范围下、上限。In formula (12), the first term is the continuous energy supply constraint of important links; the second term is the power balance constraint in the case of off-grid at time τ, and P t con is the control center and fire load; the third and fourth terms are off-grid at time τ. The flexible constraint of temperature control load under the network condition, T s is the standard temperature;
Figure BDA0002685296090000122
It is the lower and upper limit of the temperature control load comfort range.

并网与脱网关联约束表示为：The grid-connected and off-grid association constraints are expressed as:

对于

Figure BDA0002685296090000123
for
Figure BDA0002685296090000123

Figure BDA0002685296090000124
Figure BDA0002685296090000124

式(13)中，

Figure BDA0002685296090000125
为并网运行过程中τ时刻燃气机电功率，
Figure BDA0002685296090000126
为τ时刻脱网运行燃气机初始电功率；
Figure BDA0002685296090000127
为并网运行过程中τ时刻储能容量状态，
Figure BDA0002685296090000128
为τ时刻脱网运行储能初始容量状态。In formula (13),
Figure BDA0002685296090000125
is the gas-electric motor power at time τ during grid-connected operation,
Figure BDA0002685296090000126
is the initial electric power of the gas turbine running off-grid at time τ;
Figure BDA0002685296090000127
is the state of energy storage capacity at time τ during grid-connected operation,
Figure BDA0002685296090000128
It is the initial capacity state of energy storage for off-grid operation at time τ.

电池生产园区的生产性储能生产约束包括：a、全部电池自动装入分容柜需要预留一定时间；b、分容过程充放电倍率范围需根据客户要求设置；c、分容步骤需按照充满-放完-充至初始状态的顺序进行且必须在一天内完成全部步骤，分容过程中可静置。将以上约束条件表示如式(14)：The productive energy storage production constraints of the battery production park include: a. All batteries need to be automatically loaded into the sub-capacity cabinet for a certain period of time; b. The charging and discharging rate range in the sub-capacity process must be set according to customer requirements; c. The capacity sub-steps must be set according to the The sequence of filling-discharging-charging to the initial state is carried out, and all steps must be completed within one day, and it can be left to stand during the dividing process. The above constraints can be expressed as formula (14):

对于

Figure BDA0002685296090000129
for
Figure BDA0002685296090000129

Figure BDA00026852960900001210
Figure BDA00026852960900001210

Figure BDA00026852960900001211
Figure BDA00026852960900001211

Figure BDA00026852960900001212
Figure BDA00026852960900001212

式(14a)为满足第a、第b项约束，Kr为预留时段数，

Figure BDA0002685296090000131
和
Figure BDA0002685296090000132
为充放电倍率上限值；式(14b)、(14c)为满足第c项约束条件，其中，式(14b)为电池先充满后放完顺序约束，式(14c)为一个循环充放电过程且满充满放约束。Equation (14a) is to satisfy the constraints a and b, K r is the number of reserved periods,
Figure BDA0002685296090000131
and
Figure BDA0002685296090000132
is the upper limit of the charge-discharge rate; formulas (14b) and (14c) are to satisfy the constraint condition of item c, where formula (14b) is the sequence constraint of the battery being fully charged and discharged, and formula (14c) is a cyclic charge-discharge process And full of constraints.

步骤4，通过线性化处理将综合能源系统优化调度模型转换为混合整数线性规划模型，然后调用MATLAB混合整数线性规划intlinprog函数进行求解综合能源系统优化调度模型。Step 4: Convert the integrated energy system optimal dispatch model into a mixed integer linear programming model through linearization processing, and then call the MATLAB mixed integer linear programming intlinprog function to solve the integrated energy system optimal dispatch model.

综合能源系统优化调度模型的求解变量包括：综合能源系统在并网运行时与电网的交互功率、储能设备的备用容量、储能设备的充放能功率、热电联产设备输入热能的功率、吸收式冷温水机的功率、电制冷机的功率，以及综合能源系统在脱网运行时，储能设备的充放能功率、热电联产设备输入热能的功率、吸收式冷温水机的功率、电制冷机的功率、电池生产园区各重要环节负荷的投切状态。The solution variables of the integrated energy system optimal dispatch model include: the interactive power between the integrated energy system and the grid when the integrated energy system is connected to the grid, the reserve capacity of the energy storage device, the charging and discharging power of the energy storage device, the input heat power of the cogeneration device, The power of the absorption cold and warm water machine, the power of the electric refrigerator, and the charging and discharging power of the energy storage equipment when the integrated energy system is running off-grid, the power of the input heat energy of the cogeneration equipment, the power of the absorption cold and warm water machine, The power of the electric refrigerator and the switching state of the load of each important link in the battery production park.

该步骤4中，通过线性化处理将综合能源系统优化调度模型转换为混合整数线性规划模型，具体为式(15)-式(17)所示。In step 4, the integrated energy system optimal dispatch model is converted into a mixed integer linear programming model through linearization processing, which is specifically shown in equations (15)-(17).

由于公式(1)所示的储能设备模型为互补约束，因此可引用入二进制变量对该互补约束进行线性化处理，得到式(15)所示的互补约束线性处理：Since the energy storage device model shown in equation (1) is a complementary constraint, binary variables can be used to linearize the complementary constraint, and the linear processing of the complementary constraint shown in equation (15) can be obtained:

对于

Figure BDA0002685296090000133
for
Figure BDA0002685296090000133

Figure BDA0002685296090000134
Figure BDA0002685296090000134

式(15)中：

Figure BDA0002685296090000135
均为二进制变量，分别表示某一时刻储能的充能状态和放能状态。当储能充能时，
Figure BDA0002685296090000136
为1，
Figure BDA0002685296090000137
为0；当储能放能时，
Figure BDA0002685296090000138
为0，
Figure BDA0002685296090000139
为1。In formula (15):
Figure BDA0002685296090000135
Both are binary variables, which respectively represent the charging state and discharging state of the energy storage at a certain time. When the energy storage is charged,
Figure BDA0002685296090000136
is 1,
Figure BDA0002685296090000137
is 0; when the energy is discharged,
Figure BDA0002685296090000138
is 0,
Figure BDA0002685296090000139
is 1.

生产性储能约束公式(14c)含有max、min项约束，两种约束处理方法类似，以约束含min项为例，引入二进制变量进行线性化处理，表示为式(16)所示的max项线性化处理：The productive energy storage constraint formula (14c) contains constraints of max and min terms. The two constraint processing methods are similar. Taking the constraint containing the min term as an example, binary variables are introduced for linearization, which is expressed as the max term shown in equation (16). Linearization processing:

对于

Figure BDA00026852960900001310
for
Figure BDA00026852960900001310

Figure BDA00026852960900001311
Figure BDA00026852960900001311

Figure BDA00026852960900001312
Figure BDA00026852960900001312

Figure BDA00026852960900001313
Figure BDA00026852960900001313

Figure BDA00026852960900001314
Figure BDA00026852960900001314

式(16)中，

Figure BDA00026852960900001315
为二进制变量；
Figure BDA00026852960900001316
存在唯一的1，当其取1时，生产性储能
Figure BDA00026852960900001317
为满放约束。In formula (16),
Figure BDA00026852960900001315
is a binary variable;
Figure BDA00026852960900001316
There is a unique 1, when it takes 1, the productive energy storage
Figure BDA00026852960900001317
For full constraints.

公式(2)所示的热电联产设备模型中，热电联产设备出力存在分段点，引入二进制变量与连续变量进行处理的分段函数约束处理，表示为：In the cogeneration equipment model shown in formula (2), the output of cogeneration equipment has a segment point, and the segment function constraint processing of binary variables and continuous variables for processing is introduced, which is expressed as:

对于

Figure BDA0002685296090000141
for
Figure BDA0002685296090000141

Figure BDA0002685296090000142
Figure BDA0002685296090000142

Figure BDA0002685296090000143
Figure BDA0002685296090000143

Figure BDA0002685296090000144
Figure BDA0002685296090000144

Figure BDA0002685296090000145
Figure BDA0002685296090000145

Figure BDA0002685296090000146
Figure BDA0002685296090000146

Figure BDA0002685296090000147
Figure BDA0002685296090000147

Figure BDA0002685296090000148
Figure BDA0002685296090000148

式(17)中，

Figure BDA0002685296090000149
为燃气机可调功率下限与上限；
Figure BDA00026852960900001410
均为二进制变量；
Figure BDA00026852960900001411
为连续变量。
Figure BDA00026852960900001412
为0时，
Figure BDA00026852960900001413
一定为0，即输入热能未达到要求时，燃气机输出功率始终为0；
Figure BDA00026852960900001414
为1时，
Figure BDA00026852960900001415
可取[0,1]内连续值，即燃气机功率在上下限范围内连续可调。In formula (17),
Figure BDA0002685296090000149
Adjustable power lower limit and upper limit for gas engine;
Figure BDA00026852960900001410
are binary variables;
Figure BDA00026852960900001411
is a continuous variable.
Figure BDA00026852960900001412
When it is 0,
Figure BDA00026852960900001413
It must be 0, that is, when the input heat energy does not meet the requirements, the output power of the gas engine is always 0;
Figure BDA00026852960900001414
When it is 1,
Figure BDA00026852960900001415
A continuous value within [0,1] can be taken, that is, the power of the gas engine is continuously adjustable within the upper and lower limits.

以上实施例为本申请的优选实施例，本领域的普通技术人员还可以在此基础上进行各种变换或改进，在不脱离本申请总的构思的前提下，这些变换或改进都应当属于本申请要求保护的范围之内。The above embodiments are the preferred embodiments of the application, and those of ordinary skill in the art can also carry out various transformations or improvements on this basis. Without departing from the general concept of the application, these transformations or improvements should belong to the present application. within the scope of the application for protection.

Claims (6)

1. A method for optimally utilizing the electric energy storage accident reserve capacity of an integrated energy system is characterized by comprising the following steps:
step 1, respectively constructing energy models for all equipment of a comprehensive energy system of a battery production park, wherein the energy models comprise an energy storage model, a cogeneration model, a refrigeration equipment model and a water pump model;
step 2, constructing a grid-connected expected income model and a grid-disconnected expected loss model based on demand response of the battery production park to the comprehensive energy system and the grid-disconnected risk of the battery production park;
the offline risk of the battery production park is obtained by comprehensively considering the probability of unplanned offline and important load loss for quantification;
step 3, integrating the grid-connected expected yield and the off-grid expected loss, and establishing an integrated energy system optimization scheduling model considering the off-grid risk and the grid-connected yield;
and 4, solving the optimized scheduling model of the comprehensive energy system to obtain the accident reserve capacity of the energy storage equipment in the comprehensive energy system, the power of each equipment in the comprehensive energy system and the switching state of each important link load of the battery generation park.
2. The method of claim 1, wherein the solution method of step 4 is: and converting the comprehensive energy system optimization scheduling model into a mixed integer linear programming model through linearization treatment, and calling an MATLAB mixed integer linear programming intlinprog function to solve.
3. The method according to claim 1, wherein the types of energy storage devices comprise an electrical energy storage device, a cold energy storage device, a hot energy storage device, and a productive energy storage device, the same type of battery is used as one productive energy storage device, and the energy storage model constructed for each energy storage model can be represented as:
for the
Figure FDA0002685296080000011
Figure FDA0002685296080000012
Figure FDA0002685296080000013
0≤Pt ESc≤PESn (1c)
0≤Pt ESd≤PESn (1d)
Pt ESdPt ESc＝0 (1e)
Pt ES＝Pt ESd-Pt ESc (1f)
In the formula: t is the operation time period; n is a running time period set; ES is an energy storage type, can be bes, ces, hes, ges, respectively corresponding to electricity, cold, heat, productive energy storage;
Figure FDA0002685296080000014
the ratio of the capacity stored by the energy storage device to the rated capacity; kappaESIs the energy self-loss rate;
Figure FDA0002685296080000015
respectively being energy storage devicesEnergy charging and discharging efficiency; pt ESc、Pt ESdRespectively charging and discharging energy of the energy storage equipment; wESnIs the rated capacity of the energy storage device; Δ t is a scheduling period;
Figure FDA0002685296080000021
the ratio of the minimum allowed energy storage capacity, the maximum allowed energy storage capacity and the rated energy storage capacity is respectively; pESnThe rated power of the energy storage device; pt ESSetting the energy discharge as positive and the energy charging as negative for the energy storage power;
the cogeneration model constructed for a cogeneration plant is represented as:
for the
Figure FDA0002685296080000022
Figure FDA0002685296080000023
Figure FDA0002685296080000024
Figure FDA0002685296080000025
Figure FDA0002685296080000026
Figure FDA0002685296080000027
Figure FDA0002685296080000028
In the formula: t is the operation time period; n is a running time period set; pt chp、
Figure FDA0002685296080000029
Electric power and thermal power output by the cogeneration equipment are respectively;
Figure FDA00026852960800000210
respectively inputting the upper and lower power limits of heat energy for the cogeneration equipment; kappachpp、κpThe conversion coefficient and deviation between the input heat energy and the output electric energy; kappachpq、κqThe conversion coefficient and deviation between the input heat energy and the output heat energy are obtained; the delta U and the delta D are respectively the maximum climbing force and the maximum descending force of the cogeneration;
Figure FDA00026852960800000211
the heat power is recovered and utilized by waste heat recovery equipment; etachprThe heat energy utilization coefficient; ft chpPower representing input thermal energy of the cogeneration plant;
the refrigeration equipment comprises an absorption type cold and warm water machine taking heat energy as energy and an electric refrigerator taking electric energy as energy, and the constructed refrigeration equipment models are respectively expressed as follows:
Figure FDA00026852960800000212
Figure FDA00026852960800000213
in the formula:
Figure FDA00026852960800000214
respectively the cold supply power and the heat consumption power of the cold and warm water machine;
Figure FDA00026852960800000215
Pt ecrespectively the cooling power and the power consumption power of the electric refrigerator; etaac、ηecThe performance coefficients of the absorption refrigeration equipment and the electric refrigeration equipment are respectively;
Figure FDA00026852960800000216
rated capacity for refrigeration equipment;
the water pump equipment model constructed for the water pump equipment is represented as follows:
Figure FDA0002685296080000031
in the formula, Pt pumpThe power is consumed by the water pump;
Figure FDA0002685296080000032
and λc、λhRespectively for transporting cold and heat energy and corresponding power consumption coefficients.
4. The method of claim 3, wherein the formula for quantifying the probability of unplanned outages is:
Figure FDA0002685296080000033
in the formula, s, w and i respectively represent time periods, weather types and off-line types in one day, and S, W, I respectively represent the number of the time periods, the number of the weather types and the number of the off-line types in one day; rs,w,iThe probability of i-type offline for w-type weather in s time period; m iss,w,iThe number of sections of i-type off-line for w-type weather in s time period; ms,wTotal number of segments for type w weather in s period;
important load loss of unplanned offline includes important ring power saving load loss and important temperature control load loss of a battery production park;
the calculation formula for quantifying the important ring power-saving load loss of the unplanned offline is as follows:
assuming time τ is off-line, for
Figure FDA0002685296080000034
Figure FDA0002685296080000035
In the formula, Vs PThe loss is the total loss of important links after the net is disconnected; Δ toffThe offline duration is; h represents the H important link, and H represents the number of the important links;
Figure FDA0002685296080000036
loss generated by unit power shortage in unit time of an important link at a certain moment after offline;
Figure FDA0002685296080000037
power is required for an important link at a certain moment after the network is disconnected;
Figure FDA0002685296080000038
in the form of a binary variable, the variable,
Figure FDA0002685296080000039
taking 1 and 0 to respectively represent the load of supplying and not supplying important links at a certain time;
the calculation formula for quantifying the important temperature control load loss of the unplanned offline is as follows:
assuming time τ is off-line, for
Figure FDA00026852960800000310
Figure FDA00026852960800000311
Figure FDA00026852960800000312
In the formula, Vs QThe total loss of temperature control load after off-line;
Figure FDA00026852960800000313
loss generated by unit cold/heat power shortage at a certain time after the net is disconnected;
Figure FDA00026852960800000314
power is required for an important temperature control load at a certain time; qtOutputting power for the temperature control equipment at a certain time; c. Cair、mairAir specific heat capacity and mass; t ist in、Tt outIndoor and outdoor temperatures at a certain time; k is a radical ofq、Aq、DqThe heat conduction coefficient, area and thickness of the wall.
5. The method according to claim 4, wherein the grid-connected expected profit model is constructed by:
Figure FDA0002685296080000041
in the formula, EcFor expected revenue of grid connection, C0C is the grid-connected operation cost of the standby energy storage and the standby energy storage; n is the number of sections in grid-connected operation; ft chp、ft chpThe cost of the thermal power and the unit power of the fuel gas at a certain time; kQFor the number of cooling/heating units, KPFor the number of power supply devices in the integrated energy system,
Figure FDA0002685296080000042
in order to provide a force to the cold/hot equipment,
Figure FDA0002685296080000043
the operation and maintenance cost of the unit output of the cooling/heating equipment in the comprehensive energy system; pt kAnd
Figure FDA0002685296080000044
the operation and maintenance cost of the output of the power supply equipment and the unit output in the comprehensive energy system is saved; pt grid、ft gridRespectively the interaction power and the interaction cost of the comprehensive energy system and the power grid;
the off-line expected loss model is constructed as follows:
Figure FDA0002685296080000045
in the formula, ElThe expected loss of the offline is obtained, and V is the sum of the offline operation cost and the load shedding loss; tau and i are offline time and type;
Figure FDA0002685296080000046
the thermal power of the gas at a certain moment under the condition of tau moment offline;
Figure FDA0002685296080000047
the output of cold/hot supply equipment and the output of power supply equipment at a certain moment under the condition of tau moment offline;
Figure FDA0002685296080000048
in the form of a binary variable, the variable,
Figure FDA0002685296080000049
taking 1 and 0 to respectively represent the load of the h-th important link supplied and not supplied at a certain moment under the condition of tau moment offline;
the objective function of the comprehensive energy system optimization scheduling model is as follows:
max E＝Ec-El (10)
wherein E is the target expected yield;
the energy system optimization scheduling model comprises grid connection constraint, off-grid constraint, grid connection and off-grid association constraint and productive energy storage production constraint, which are respectively expressed as follows:
for the
Figure FDA00026852960800000410
Figure FDA00026852960800000411
Figure FDA00026852960800000412
Formula (11a) is cold energy or heat energy balance constraint, and formula (11b) is electric energy balance constraint; lambda is the power consumption coefficient of the water pump; pt lIs a grid-connected electrical load;
Figure FDA0002685296080000051
electrical cooling/heating power;
Figure FDA0002685296080000052
is a grid-connected cold/heat load;
Figure FDA0002685296080000053
outputting force for the d productive energy storage; d is the number of productive stored energy;
for the
Figure FDA0002685296080000054
Figure FDA0002685296080000055
In the formula (12), the first term is the continuous energy supply constraint of the important link; the second term is the electric energy balance constraint under the condition of tau moment off-line, Pt conIs used for controlling the center and the fire-fighting load; the third and fourth terms are temperature control load flexible constraint under the condition of T moment offline, TsIs the standard temperature;
Figure FDA0002685296080000056
the lower limit and the upper limit of the temperature control load comfort range;
for the
Figure FDA0002685296080000057
Figure FDA0002685296080000058
In the formula (13), the reaction mixture is,
Figure FDA0002685296080000059
for the electric power of the gas engine at the time tau in the grid-connected operation process,
Figure FDA00026852960800000510
the initial electric power of the gas engine is off-line for the time tau;
Figure FDA00026852960800000511
for the energy storage capacity state at the time tau in the grid-connected operation process,
Figure FDA00026852960800000512
the energy storage initial capacity state is operated for the tau moment offline;
for the
Figure FDA00026852960800000513
Figure FDA00026852960800000514
Figure FDA00026852960800000515
Figure FDA00026852960800000516
In the formula, KrIn order to reserve the number of time segments,
Figure FDA00026852960800000517
and
Figure FDA00026852960800000518
the upper limit of the charge/discharge rate is shown.
6. The method of claim 5, wherein the solution variables of the integrated energy system optimization scheduling model comprise: the comprehensive energy system is in interactive power with a power grid during grid-connected operation, the reserve capacity of the energy storage equipment, the charging and discharging power of the energy storage equipment, the power of heat energy input by the cogeneration equipment, the power of the absorption type cold and warm water machine, the power of the electric refrigerator, and the switching state of loads of important links in a battery production park during off-grid operation of the comprehensive energy system.
CN202010974491.5A 2020-09-16 2020-09-16 Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system Active CN112103955B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010974491.5A CN112103955B (en) 2020-09-16 2020-09-16 Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010974491.5A CN112103955B (en) 2020-09-16 2020-09-16 Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system

Publications (2)

Publication Number Publication Date
CN112103955A true CN112103955A (en) 2020-12-18
CN112103955B CN112103955B (en) 2022-02-08

Family

ID=73759326

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010974491.5A Active CN112103955B (en) 2020-09-16 2020-09-16 Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system

Country Status (1)

Country Link
CN (1) CN112103955B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113159380A (en) * 2021-03-18 2021-07-23 国网山东综合能源服务有限公司 Comprehensive energy system operation optimization method considering demand response

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102103720A (en) * 2011-01-31 2011-06-22 南京航空航天大学 Risk-based micro power grid distributed power generation standby optimized configuration method
CN104392286A (en) * 2014-12-02 2015-03-04 山东大学 Microgrid operation optimizing method by considering combined supply of cooling, heating and power with stored energy operation strategy
CN105337303A (en) * 2015-09-22 2016-02-17 贵州电网有限责任公司电网规划研究中心 Capacity optimization configuration method for combined heat and power generation micro grid containing heat pump
CN109659927A (en) * 2018-10-24 2019-04-19 国网天津市电力公司电力科学研究院 A kind of comprehensive energy microgrid energy accumulation capacity configuration considering energy storage participation
CN109921447A (en) * 2019-04-12 2019-06-21 湖南大学 An economic dispatch method for microgrid based on SOC dynamic constraints of energy storage devices
CN109995030A (en) * 2019-04-28 2019-07-09 湖南大学 An optimal setting method of SOC lower limit value of energy storage device considering off-grid risk
CN110533225A (en) * 2019-08-07 2019-12-03 华北电力大学 A kind of business garden integrated energy system Optimization Scheduling based on chance constrained programming

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102103720A (en) * 2011-01-31 2011-06-22 南京航空航天大学 Risk-based micro power grid distributed power generation standby optimized configuration method
CN104392286A (en) * 2014-12-02 2015-03-04 山东大学 Microgrid operation optimizing method by considering combined supply of cooling, heating and power with stored energy operation strategy
CN105337303A (en) * 2015-09-22 2016-02-17 贵州电网有限责任公司电网规划研究中心 Capacity optimization configuration method for combined heat and power generation micro grid containing heat pump
CN109659927A (en) * 2018-10-24 2019-04-19 国网天津市电力公司电力科学研究院 A kind of comprehensive energy microgrid energy accumulation capacity configuration considering energy storage participation
CN109921447A (en) * 2019-04-12 2019-06-21 湖南大学 An economic dispatch method for microgrid based on SOC dynamic constraints of energy storage devices
CN109995030A (en) * 2019-04-28 2019-07-09 湖南大学 An optimal setting method of SOC lower limit value of energy storage device considering off-grid risk
CN110533225A (en) * 2019-08-07 2019-12-03 华北电力大学 A kind of business garden integrated energy system Optimization Scheduling based on chance constrained programming

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
周霞等: "基于风险量化的事故备用容量协调分配方法", 《电工技术学报》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113159380A (en) * 2021-03-18 2021-07-23 国网山东综合能源服务有限公司 Comprehensive energy system operation optimization method considering demand response
CN113159380B (en) * 2021-03-18 2023-04-07 国网山东综合能源服务有限公司 Comprehensive energy system operation optimization method considering demand response

Also Published As

Publication number Publication date
CN112103955B (en) 2022-02-08

Similar Documents

Publication Publication Date Title
CN112464477A (en) Multi-energy coupling comprehensive energy operation simulation method considering demand response
CN104734168B (en) A microgrid operation optimization system and method based on combined electric and thermal dispatching
CN102710013B (en) Energy optimization management system of park energy network based on microgrid and its implementation method
CN111404183B (en) Method, program, system and application of multi-energy storage collaborative configuration in regional integrated energy system
CN111355265B (en) Micro-grid energy two-stage robust optimization method and system
CN102664401B (en) A Microgrid Control Method Based on Battery Life Model
CN110197312A (en) A kind of user class integrated energy system Optimization Scheduling based on Multiple Time Scales
CN112529244A (en) Comprehensive energy system collaborative optimization operation method considering electric load demand response
CN110991000B (en) Modeling method for energy hub considering solid oxide fuel cell and electric conversion gas
CN107742901B (en) Combination method and device of wind power grid-connected units considering compressed air energy storage
CN111541244B (en) Power grid side energy storage device capacity calculation method considering power consumption cost of energy storage device
CN102509175A (en) Reliability optimization method of distributed power supply system
CN112488363B (en) Generalized energy storage based optimal scheduling method for multi-energy power system
CN113256045A (en) Park comprehensive energy system day-ahead economic dispatching method considering wind and light uncertainty
CN110350512A (en) A kind of Itellectualized uptown generation of electricity by new energy station method for optimizing scheduling and system
CN113381403A (en) Photo-thermal-biomass hybrid power station capacity configuration method based on operation reliability
CN108736518B (en) Comprehensive energy supply system and method for urban complex and large public building group
CN117081143A (en) Method for promoting coordination and optimization operation of park comprehensive energy system for distributed photovoltaic on-site digestion
CN111522238A (en) A comfort-based building integrated energy system control method and control system
CN115293457A (en) Seasonal hydrogen storage optimization configuration method of comprehensive energy system based on distributed collaborative optimization strategy
CN112103955B (en) Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system
CN109995030A (en) An optimal setting method of SOC lower limit value of energy storage device considering off-grid risk
CN212277942U (en) Product stores up and uses integration comprehensive utilization system based on pressure energy electricity generation
CN109921447B (en) An economic dispatch method for microgrid based on SOC dynamic constraints of energy storage devices
CN117391764A (en) Comprehensive energy system optimal scheduling method and system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant