WO2022000700A1 - 一种气热惯性备用参与园区综合能源系统备用配置方法 - Google Patents

一种气热惯性备用参与园区综合能源系统备用配置方法 Download PDF

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WO2022000700A1
WO2022000700A1 PCT/CN2020/107349 CN2020107349W WO2022000700A1 WO 2022000700 A1 WO2022000700 A1 WO 2022000700A1 CN 2020107349 W CN2020107349 W CN 2020107349W WO 2022000700 A1 WO2022000700 A1 WO 2022000700A1
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backup
time
heat
thermal
gas
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孙维佳
王�琦
汤奕
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南京东博智慧能源研究院有限公司
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    • G06FELECTRIC DIGITAL DATA PROCESSING
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    • G06F30/20Design optimisation, verification or simulation
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
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    • G06COMPUTING; CALCULATING OR COUNTING
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    • G06F2111/00Details relating to CAD techniques
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  • the invention relates to a backup configuration method for a gas-heat inertial backup participating in a comprehensive energy system in a park, and belongs to the technical field of comprehensive energy.
  • the power system backup ensures the safe operation of the system and reserves a certain margin.
  • the backup is mainly used to deal with the problem of system power shortage caused by uncertain factors such as the uncertainty of new energy output forecast, the uncertainty of load forecast, and the failure and shutdown of units.
  • uncertain factors such as the uncertainty of new energy output forecast, the uncertainty of load forecast, and the failure and shutdown of units.
  • the reliability and economy of the integrated energy system are equally important. It is necessary to abandon the traditional conservative backup configuration method and study the backup configuration of the integrated energy system that integrates various backup forms.
  • the present invention proposes a method for the standby configuration of the gas-heat inertial reserve to participate in the comprehensive energy system of the park.
  • the present invention can make full use of the gas-heat inertial reserve in the comprehensive energy system of the park to participate in the optimal configuration of the backup, so as to cope with the problem of system power shortage, On the premise of ensuring the reliability of the system, improve the economy of system operation.
  • a method for the backup configuration of a gas-thermal inertial reserve participating in a comprehensive energy system of a park comprising the following steps:
  • a thermal system model is established by comprehensively considering the thermal time delay, thermal loss, and thermal inertia characteristics of the thermal system;
  • step (1) is specifically:
  • ⁇ , v, P are the density, flow rate, and pressure of natural gas, respectively, ⁇ , D, and ⁇ are the friction coefficient, inner diameter, and inclination angle of the pipeline and the horizontal plane, respectively, g is the acceleration of gravity, and x and t are time variables, respectively and spatial variables;
  • A, L and T are the cross-sectional area, length and temperature of the natural gas pipeline, respectively
  • R M is the natural gas gas constant
  • P out (t) are the pressure at the end of the natural gas pipeline and its first and second derivatives with time t, respectively
  • f out (t) are the flow rate at the end of the natural gas pipeline and its first derivative with time t, respectively;
  • t 1 t 2 are inertial backup gas supply and start and end time
  • G M is the heat value of natural gas, f 1, f 2, respectively, at time t 1 as conduit, t Terminal flow at time 2.
  • step (2) is specifically:
  • thermodynamic system model is:
  • ⁇ n (t) is the thermal time delay of the transmission pipe n corresponding to the heat load building m with time t
  • l n is the length of the transmission pipe n
  • v n (t) is the change of the transmission pipe n with time t.
  • the mathematical model of gas-heat inertia backup is as follows: a t and b t are the gas inertia and thermal inertia reserve capacity prices that change with time t, respectively, is the reserve capacity of gas inertia and thermal inertia input with time t; the backup mathematical model of power generation side is c t , d t are the reserve capacity price and electricity price that change with time t after the reserve market is cleared, R S , are the reserve transaction capacity of the power generation side and the reserve capacity actually invested with time t, respectively; the demand side reserve mathematical model is are the reserve capacity price and electricity compensation price of demand-side user i changing with time t, respectively, R D,i , are the demand-side user i’s demand-response transaction capacity and the actually invested spare capacity, which change with time t, respectively, and k is the number of demand-side users.
  • the present invention adopts the above technical scheme, and has the following technical effects:
  • the invention utilizes the gas-heat inertial reserve to participate in the backup configuration of the comprehensive energy system in the park, and integrates various backup forms to realize the complementarity of the gas-heat inertial reserve, the demand-side reserve, and the power-generation-side reserve. It can be configured to deal with the problem of system power shortage, and improve the economy of system operation on the premise of ensuring the reliability of the system.
  • Fig. 1 is the general flow chart of the inventive method
  • Figure 2 is a schematic diagram of a gas inertial system
  • Figure 3 is a schematic diagram of the gas inertial backup coping with the power shortage of the system, wherein (a) is the terminal flow, (b) is the terminal air pressure, and (c) is the gas backup power;
  • Figure 4 is a schematic diagram of a thermal inertial system
  • Figure 5 is a schematic diagram of the thermal inertia backup coping with the power shortage of the system, where (a) is the input power of the heat source, (b) is the power supplied by the heating network, (c) is the actual indoor temperature, and (d) is the output of the hot backup power.
  • a method for the standby configuration of gas-thermal inertial standby participating in the comprehensive energy system of the park includes the following steps:
  • the natural gas pipeline reserve has the characteristics of negative feedback regulation: when the power demand of the system increases, the flow at the end of the pipeline can be increased, and part of the pipeline reserve can be released to the gas unit, so as to alleviate the problem of system power shortage. , the flow at the end of the pipeline is restored, the transmission pipeline stores part of the natural gas supplied by the gas source, the pipeline pressure rises again, and the pipe storage returns to the normal value, as shown in Figure 2. Considering the inertia adjustment characteristics of natural gas pipeline storage, it can be regarded as a dynamic reserve for system power shortage.
  • ⁇ , v, P are the density, flow rate, and pressure of natural gas, respectively
  • ⁇ , D, and ⁇ are the friction coefficient, inner diameter, and inclination angle of the pipeline and the horizontal plane, respectively
  • g is the acceleration of gravity
  • x and t are time variables, respectively and spatial variables.
  • f out and f in are the outlet flow and inlet flow (kg/s) of the pipeline, respectively, and P out and P in are the outlet pressure and inlet pressure (Pa) of the pipeline, respectively.
  • A, L and T are the cross-sectional area, length and temperature of the natural gas pipeline, respectively
  • R M is the natural gas gas constant
  • P out (t) are the pressure at the end of the natural gas pipeline and its first and second derivatives with time t, respectively
  • f out (t) are the flow rate at the end of the natural gas pipeline and its first derivative with time t, respectively.
  • Time t 1 is provided a power system transient increase in vacancy, from the rose pipe ends instantaneous flow f 1 to f 2.
  • the pressure response process at the end of the natural gas pipeline is the linear superposition result of the step response and the impulse response, which can be solved by using Laplace transform. the release.
  • the gas pressure at the end of the natural gas pipeline shall not exceed its upper and lower operating limits:
  • the longest supply time of gas inertia backup can be defined as:
  • the gas backup power model R G (t) can be obtained as follows:
  • t 1 t 2 are inertial backup gas supply and start and end time
  • G M is the heat value of natural gas, f 1, f 2, respectively, at time t 1 as conduit, t Terminal flow at time 2.
  • the thermal system model is established by comprehensively considering the thermal time delay, thermal loss, and thermal inertia characteristics of the thermal system.
  • the transmission pipeline corresponding to the heat load building m is the n pipeline
  • the thermal time delay ⁇ n (t) of the transmission pipeline n with time t is proportional to the length l n of the transmission pipeline n, and is proportional to the hot water velocity v n (t ) is inversely proportional; the heat loss power in the transmission pipeline n during the heat transmission process vs.
  • Pipeline Heat Loss Rate is proportional to the pipe length l n ; considering the thermal inertia of the building itself, T m (t) represents the indoor temperature of the thermal load building m changing with time t, is the first derivative of T m (t), H m (t) is the heating power of the heat network to the heat load building m as a function of time t, and L m (t) is the heat load of the building m as a function of time t.
  • T out (t) represents the outdoor temperature of the heat-loaded building that changes with time t
  • m 1,2,. ..,z
  • z is the number of buildings with total heat load of the integrated energy system in the park.
  • T m,c is the normal comfortable temperature
  • T m,l is the minimum comfortable temperature
  • the indoor temperature of the heat load building m is a first-order step response, and the temperature decreases according to a negative exponential curve.
  • the heat load building has a limited time to input the hot standby power. If the maximum supply time of the thermal inertial standby is Defines i.e. time t 4, the thermal inertia of the system is stopped to fill the spare power shortage and building heat load will gradually rise to a comfortable temperature optimum heat after a certain time lag process.
  • t 5 represents the time when the building power of the heating network supply heat load changes considering the thermal time lag.
  • t 3 and t 4 are the start and end times of thermal inertia backup supply, respectively.
  • the thermal time delay can be calculated as:
  • the thermal power H m (t) of the heating network supply load, the temperature T m (t) in the building of the thermal load, the thermal backup power Schematic diagrams are shown in (b) to (d) of FIG. 5 .
  • a t and b t are the gas inertia and thermal inertia reserve capacity prices that change with time t, respectively, It is the spare capacity put in by the gas inertia and thermal inertia that change with time t.
  • the backup mathematical model on the power generation side is:
  • c t and d t are the reserve capacity price and electricity price that change with time t after the reserve market is cleared
  • R S are the reserve transaction capacity of the power generation side and the actually invested reserve capacity, respectively, which change with time t.
  • the demand-side standby mathematical model is:
  • R D,i are the demand-side user i’s demand-response transaction capacity and the actually invested spare capacity, which change with time t, respectively, and k is the number of demand-side users.
  • the objective function is to take the lowest total purchase cost of reserve during the study period as the objective function:

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Abstract

一种气热惯性备用参与园区综合能源系统备用配置方法,首先建立气惯性备用应对系统功率缺额的出力模型,然后建立热惯性备用应对系统功率缺额的出力模型,最后协同考虑气热惯性备用、发电侧备用、需求侧备用进行园区综合能源备用配置。可以充分利用园区综合能源系统内的气热惯性备用,进而综合多种备用形式,以应对系统功率缺额问题,在保证系统可靠性水平的前提下,提升系统运行经济性。

Description

一种气热惯性备用参与园区综合能源系统备用配置方法 技术领域
本发明涉及一种气热惯性备用参与园区综合能源系统备用配置方法,属于综合能源技术领域。
背景技术
作为电力系统重要的辅助服务,电力系统备用确保系统安全运行并留有一定的充裕度。园区级综合能源系统中,备用主要用于应对新能源出力预测不确定性、负荷预测不确定性、机组故障停运等不确定性因素引起的系统功率缺额问题。在目前电力市场改革的背景下,综合能源系统运行的可靠性和经济性同等重要,有必要摒弃传统的保守备用配置方法,研究综合多种备用形式的综合能源系统备用配置。
考虑到综合能源系统内部电气热多能耦合特性,除传统发电侧备用和需求侧备用外,气热惯性备用也可为系统提供功率支撑,为园区级综合能源系统的备用配置提供了新思路。其中,气惯性备用指气传输管道通过释放管存、降低管压为系统提供备用功率,热惯性备用指热负荷建筑通过牺牲运行舒适度、降低室温为系统提供备用功率。综合多种备用形式,充分考虑气热惯性备用、需求侧备用、发电侧备用的互补配置,在保证系统可靠性水平的前提下,能够提升系统运行经济性,以较小的成本代价优化系统应对系统功率缺额的备用配置。
发明内容
为解决上述问题,本发明提出了一种气热惯性备用参与园区综合能源系统备用配置方法,本发明可以充分利用园区综合能源系统内气热惯性备用参与备用优化配置,以应对系统功率缺额问题,在保证系统可靠性水平的前提下,提升系统运行经济性。
本发明为解决上述技术问题采用以下技术方案:
一种气热惯性备用参与园区综合能源系统备用配置方法,包括如下步骤:
(1)基于天然气管道暂态模型,建立气惯性备用应对系统功率缺额出力模型,具体包括:
1)基于动态天然气流的连续性方程和动量方程,建立天然气管道暂态模型;
2)基于有限元近似的思想,求解天然气管道末端压强响应模型;
3)考虑天然气系统运行约束,构建气惯性备用应对系统功率缺额出力模型;
(2)考虑热力系统热时滞、热损耗、热惯性特性,建立热惯性备用应对系统功率缺额出力模型,具体包括:
a)综合考虑热力系统热时滞、热损耗、热惯性特性,建立热力系统模型;
b)基于时频域变换,求解热负荷建筑室温响应模型;
c)考虑热力系统运行约束,构建热惯性备用应对系统功率缺额出力模型;
(3)综合考虑气热惯性备用、发电侧备用、需求侧备用,以最小化园区综合能源系统备用购买总成本为目标,构建园区综合能源备用模型,进行园区综合能源备用配置。
进一步,步骤(1)具体为:
1)天然气管道暂态模型为:
Figure PCTCN2020107349-appb-000001
式中,ρ、v、P分别为天然气的密度、流速、压强,λ、D、θ分别为管道的摩擦系数、内径、管道与水平面的倾角,g为重力加速度,x、t分别为时间变量和空间变量;
2)利用拉普拉斯变换求解天然气管道末端压强响应模型:
Figure PCTCN2020107349-appb-000002
式中,A、L、T分别为天然气管道的横截面积、长度和温度,R M为天然气气体常数,P out(t)、
Figure PCTCN2020107349-appb-000003
分别为随时间t变化的天然气管道末端压强及其一阶、二阶导数,f out(t)、
Figure PCTCN2020107349-appb-000004
分别为随时间t变化的天然气管道末端流量及其一阶导数;
3)气惯性备用应对系统功率缺额出力模型为:
Figure PCTCN2020107349-appb-000005
约束条件为:
Figure PCTCN2020107349-appb-000006
其中,
Figure PCTCN2020107349-appb-000007
Figure PCTCN2020107349-appb-000008
分别为P out(t)的上下限,t 1和t 2分别为气惯性备用供应的起始和截止时刻,G M为天然气热力值,f 1、f 2分别为管道在t 1时刻、t 2时刻的末端流量。
进一步,步骤(2)具体为:
a)热力系统模型为:
Figure PCTCN2020107349-appb-000009
式中,τ n(t)为热负荷建筑m对应的传输管道n随时间t变化的热时滞,l n为传输管道n的长度,v n(t)为传输管道n随时间t变化的热水流速,
Figure PCTCN2020107349-appb-000010
为热传输过程中传输管道n的热损耗功率,
Figure PCTCN2020107349-appb-000011
为传输管道n的管道热损率,T m(t)和
Figure PCTCN2020107349-appb-000012
分别为热负荷建筑m随时间t变化的室内温度和其一阶导数,H m(t)为随时间t变化的热网络对热负荷建筑m的供热功率,L m(t)为随时间t变化的热负荷建筑m的热损耗功率,C A为热负荷建筑的室内空气比热容,M A为热负荷建筑的室内空气质量,
Figure PCTCN2020107349-appb-000013
为热负荷建筑的散热系数,T out(t)表示随时间t变化的热负荷建筑的室外温度,m=1,2,...,z,z为园区综合能源系统总热负荷建筑数目;
2)利用拉普拉斯变换求解热负荷建筑室温响应模型:
Figure PCTCN2020107349-appb-000014
3)构建热惯性备用应对系统功率缺额的出力模型为:
Figure PCTCN2020107349-appb-000015
式中,T m,c为正常舒适温度,T m,l为最低舒适温度,
Figure PCTCN2020107349-appb-000016
为随时间t变化的热负荷建筑m的热惯性备用,,t 3、t 4分别为热惯性备用供应的起始和截止时刻。
进一步,园区综合能源备用模型为:
Figure PCTCN2020107349-appb-000017
其中,气热惯性备用数学模型为
Figure PCTCN2020107349-appb-000018
a t、b t分别为随时间t变化的气惯性、热惯性备用容量价格,
Figure PCTCN2020107349-appb-000019
为随时间t变化的气惯性、热惯性投入的备用容量;发电侧备用数学模型为
Figure PCTCN2020107349-appb-000020
c t、d t为备用市场出清后随时间t变化的备用容量价格 和电量价格,R S
Figure PCTCN2020107349-appb-000021
分别为随时间t变化的发电侧备用成交容量、实际所投入的备用容量;需求侧备用数学模型为
Figure PCTCN2020107349-appb-000022
分别为随时间t变化的需求侧用户i的备用容量价格、电量补偿价格,R D,i
Figure PCTCN2020107349-appb-000023
分别为随时间t变化的需求侧用户i需求响应成交容量、实际所投入的备用容量,k为需求侧用户数目。
本发明采用以上技术方案与现有技术相比,具有以下技术效果:
本发明在充分考虑综合能源气热系统惯性特性的基础上,利用气热惯性备用参与园区综合能源系统备用配置,综合多种备用形式,实现气热惯性备用、需求侧备用、发电侧备用的互补配置,以应对系统功率缺额问题,在保证系统可靠性水平的前提下,提升系统运行经济性。
附图说明
图1为本发明方法的总流程图;
图2为气惯性系统示意图;
图3为气惯性备用应对系统功率缺额示意图,其中,(a)为末端流量,(b)为末端气压,(c)为气备用功率;
图4为热惯性系统示意图;
图5为热惯性备用应对系统功率缺额示意图,其中,(a)为热源输入功率,(b)为热网供给功率,(c)为室内实际温度,(d)为热备用功率出力。
具体实施方式
以下将结合具体实施例对本发明提供的技术方案进行详细说明,应理解下述具体实施方式仅用于说明本发明而不用于限制本发明的范围。
一种气热惯性备用参与园区综合能源系统备用配置方法,如图1所示,包括如下步骤:
(1)基于天然气管道暂态模型,建立气惯性备用应对系统功率缺额模型
天然气管存备用具有负反馈调节特性:系统功率需求增加时,可增加管道末端流量,释放部分管存给燃气机组,缓解系统功率缺额问题,管道压强下降,管存减少;系统功率需求恢复正常时,管道末端流量恢复,传输管道把气源供给的部分天然气存储起来,管道压强重新上升,管存恢复到正常值,如图2所示。考虑到天然气管存的惯性调节特性,可将其视为系统功率缺额的动态备用。
1)基于动态天然气流的连续性方程和动量方程,建立天然气管道暂态模型。
天然气管道传输暂态过程可表征为:
Figure PCTCN2020107349-appb-000024
式中,ρ、v、P分别为天然气的密度、流速、压强,λ、D、θ分别为管道的摩擦系数、内径、管道与水平面的倾角,g为重力加速度,x、t分别为时间变量和空间变量。
2)基于有限元近似的思想,求解天然气管道末端压强响应模型。
基于有限元近似的思想,利用下面公式简化:
Figure PCTCN2020107349-appb-000025
Figure PCTCN2020107349-appb-000026
其中,f out、f in分别为管道出口流量、进口流量(kg/s),P out、P in分别为管道出口压强、进口压强(Pa)。
整理可得二阶方程:
Figure PCTCN2020107349-appb-000027
式中,A、L、T分别为天然气管道的横截面积、长度和温度,R M为天然气气体常数,P out(t)、
Figure PCTCN2020107349-appb-000028
分别为随时间t变化的天然气管道末端压强及其一阶、二阶导数,f out(t)、
Figure PCTCN2020107349-appb-000029
分别为随时间t变化的天然气管道末端流量及其一阶导数。
设t 1时刻系统功率缺额瞬时增加,管道末端流量瞬时从f 1上升到f 2。天然气管道末端压强响应过程为阶跃响应和冲激响应的线性叠加结果,可利用拉普拉斯变换求解得出,天然气管道末端流量瞬时增大时,末端气压按负指数曲线降低,管存随之释放。
3)考虑天然气系统运行约束,构建气惯性备用应对系统功率缺额出力模型。
实际运行中,天然气管道末端气压不得超过其运行上下限:
Figure PCTCN2020107349-appb-000030
一旦末端气压下降至t 2时刻低于运行下限,将无法为系统提供备用功率支撑,管道末端流量恢复,末端气压按负指数曲线上升至正常值。
气惯性备用最长供应时间
Figure PCTCN2020107349-appb-000031
可定义为:
Figure PCTCN2020107349-appb-000032
可得出气备用功率模型R G(t)如下:
Figure PCTCN2020107349-appb-000033
其中,
Figure PCTCN2020107349-appb-000034
Figure PCTCN2020107349-appb-000035
分别为P out(t)的上下限,t 1和t 2分别为气惯性备用供应的起始和截止时刻,G M为天然气热力值,f 1、f 2分别为管道在t 1时刻、t 2时刻的末端流量。
本发明的实施例中,若取参数分别为v=5m/s,R M=519.1J/(KG·K),T=25℃=273.15K,λ=0.05,D=0.5m,A=0.19635m 2,P in(t)=0.3MPa,
Figure PCTCN2020107349-appb-000036
G M=29.044MJ/kg
设t 1=1h时,系统负荷需求瞬时增加,管道末端流量瞬时从正常值f 1增加到f 2,其中,f 1=1.2kg/s,f 2=1.3kg/s。
将以上数据全部带入二阶方程,利用拉普拉斯变换求解可得:
P out(t)=173000-[25385-8e -0.04827(t-1*3600)+25393e -0.0008161(t-1*3600)]
Figure PCTCN2020107349-appb-000037
基于以上推导,为应对系统功率缺额,天然气管道末端流量瞬时增大,末端气压按负指数曲线降低,管存随之释放;一旦末端气压下降至t 2时刻低于运行下限,将无法为系统继续提供备用功率支撑,天然气管道末端流量恢复正常,末端气压按负指数曲线上升至正常值。可得出末端流量f out(t)、末端气压p out(t)、气备用功率R G(t)示意图如图3中的(a)至(c)所示。
(2)考虑热力系统热时滞、热损耗、热惯性,建立热惯性备用应对系统功率缺额模型
已知热网中热传递过程如图4。假设采用质调节方式,热源以采暖蒸汽形式向一级换热器传递能量,热源处仅改变热网络供水温度,不改变系统网络流量和流速。正常运行情况下,建筑物始终维持在最优舒适温度;系统发生功率缺额时,主动减少对建筑物供热,建筑物温度不断下降至最低舒适温度以提供功率支撑;热负荷建筑投入热备用时间到达上限时,系统立即恢复对建筑物正常供热,建筑物温度不断上升至最优舒适温度。考虑到热负荷建筑的惯性调节特性,可将其视为系统功率缺额的动态备用。
a)综合考虑热力系统热时滞、热损耗、热惯性特性,建立热力系统模型。
Figure PCTCN2020107349-appb-000038
Figure PCTCN2020107349-appb-000039
Figure PCTCN2020107349-appb-000040
Figure PCTCN2020107349-appb-000041
式中,热负荷建筑物m对应传输管道为n管道,传输管道n随时间t变化的热时滞τ n(t)与传输管道n的长度l n成正比、与热水流速v n(t)成反比;热传输过程中传输管道n存在的热损耗功率
Figure PCTCN2020107349-appb-000042
与管道热损率
Figure PCTCN2020107349-appb-000043
和管道长度l n成正比;考虑建筑物本身热惯性,T m(t)表示热负荷建筑m随时间t变化的室内温度,
Figure PCTCN2020107349-appb-000044
为T m(t)的一阶导数,H m(t)为随时间t变化的热网络对热负荷建筑m的供热功率,L m(t)为随时间t变化的热负荷建筑m的热损耗功率,C A为热负荷建筑的室内空气比热容,M A为热负荷建筑的室内空气质量,
Figure PCTCN2020107349-appb-000045
为热负荷建筑的散热系数(与建筑围护结构散热、冷风渗透散热、通风散热均有关),T out(t)表示随时间t变化的热负荷建筑的室外温度,m=1,2,...,z,z为园区综合能源系统总热负荷建筑数目。
b)基于时频域变换,求解热负荷建筑室温响应模型。
假设一定时间内室外温度T out不变,热力系统模型可简化得到得:
Figure PCTCN2020107349-appb-000046
t 4时刻,设热源供能功率瞬时从正常值H 1降为最低值H 2,则可推知:
Figure PCTCN2020107349-appb-000047
式中,T m,c为正常舒适温度,T m,l为最低舒适温度。
可得出热负荷建筑m室内温度为一阶阶跃响应,温度按负指数曲线下降。
c)考虑热力系统运行约束,构建热惯性备用应对系统功率缺额出力模型。
考虑到实际情况下,热负荷建筑投入热备用功率时间有限,若热惯性备用最长供应时间为
Figure PCTCN2020107349-appb-000048
则定义即t 4时刻,热惯性备用停止为系统填补功率缺额,热负荷建筑将在一定热时滞过程后逐步回升至最优舒适温度。
Figure PCTCN2020107349-appb-000049
t 5=t 3n(t 3)
式中,t 5表示考虑热时滞下,热网供给热负荷建筑功率改变的时刻。
依据上文,可得出园区综合能源系统热备用功率模型R H(t)为式。
Figure PCTCN2020107349-appb-000050
式中,t 3、t 4分别为热惯性备用供应的起始和截止时刻。
本发明的实施例中,取传输管道总长度、热水流速分别为l n=2000m,v n(t)=0.8268m/s。
可求出热时滞为:
Figure PCTCN2020107349-appb-000051
取得C AM A=1GJ/℃,
Figure PCTCN2020107349-appb-000052
T m,c=25℃,T m,l=15℃,T out=-5℃。
设t 3=1h时,系统发生功率缺额,热源供能瞬时下降,如图5中的(a)所示。
假设综合能源园区内共500栋热负荷建筑,则根据前文公式求得:
Figure PCTCN2020107349-appb-000053
Figure PCTCN2020107349-appb-000054
依据以上分析与计算,热网供应负荷热功率H m(t)、热负荷建筑内温度T m(t)、热备用功率
Figure PCTCN2020107349-appb-000055
示意图如图5中的(b)至(d)所示。
(3)协同考虑气热惯性备用、发电侧备用、需求侧备用,进行园区综合能源备用配置。
气热惯性备用数学模型为:
Figure PCTCN2020107349-appb-000056
式中,a t、b t分别为随时间t变化的气惯性、热惯性备用容量价格,
Figure PCTCN2020107349-appb-000057
为随时间t变化的气惯性、热惯性投入的备用容量。
发电侧备用数学模型为:
Figure PCTCN2020107349-appb-000058
式中,c t、d t为备用市场出清后随时间t变化的备用容量价格和电量价格,R S
Figure PCTCN2020107349-appb-000059
分别为随时间t变化的发电侧备用成交容量、实际所投入的备用容量。
需求侧备用数学模型为:
Figure PCTCN2020107349-appb-000060
式中,
Figure PCTCN2020107349-appb-000061
分别为随时间t变化的需求侧用户i的备用容量价格、电量补偿价格,R D,i
Figure PCTCN2020107349-appb-000062
分别为随时间t变化的需求侧用户i需求响应成交容量、实际所投入的备用容量,k为需求侧用户数目。
综合考虑气热惯性备用、发电侧备用、需求侧备用,构建园区综合能源备用模型,在保证系统可靠性水平的前提下,以所研究时段内备用购买总费用最低为目标函数:
Figure PCTCN2020107349-appb-000063
本发明方案所公开的技术手段不仅限于上述实施方式所公开的技术手段,还包括由以上技术特征任意组合所组成的技术方案。应当指出,对于本技术领域的普通技术人员来说,在不脱离本发明原理的前提下,还可以做出若干改进和润饰,这些改进和润饰也视为本发明的保护范围。

Claims (4)

  1. 一种气热惯性备用参与园区综合能源系统备用配置方法,其特征在于,包括如下步骤:
    (1)基于天然气管道暂态模型,建立气惯性备用应对系统功率缺额出力模型,具体包括:
    1)基于动态天然气流的连续性方程和动量方程,建立天然气管道暂态模型;
    2)基于有限元近似的思想,求解天然气管道末端压强响应模型;
    3)考虑天然气系统运行约束,构建气惯性备用应对系统功率缺额出力模型;
    (2)考虑热力系统热时滞、热损耗、热惯性特性,建立热惯性备用应对系统功率缺额出力模型,具体包括:
    a)综合考虑热力系统热时滞、热损耗、热惯性特性,建立热力系统模型;
    b)基于时频域变换,求解热负荷建筑室温响应模型;
    c)考虑热力系统运行约束,构建热惯性备用应对系统功率缺额出力模型;
    (3)综合考虑气热惯性备用、发电侧备用、需求侧备用,以最小化园区综合能源系统备用购买总成本为目标,构建园区综合能源备用模型,进行园区综合能源备用配置。
  2. 如权利要求1所述的一种气热惯性备用参与园区综合能源系统备用配置方法,其特征在于,步骤(1)具体为:
    1)天然气管道暂态模型为:
    Figure PCTCN2020107349-appb-100001
    式中,ρ、v、P分别为天然气的密度、流速、压强,λ、D、θ分别为管道的摩擦系数、内径、管道与水平面的倾角,g为重力加速度,x、t分别为时间变量和空间变量;
    2)利用拉普拉斯变换求解天然气管道末端压强响应模型:
    Figure PCTCN2020107349-appb-100002
    式中,A、L、T分别为天然气管道的横截面积、长度和温度,R M为天然气气体常数,P out(t)、
    Figure PCTCN2020107349-appb-100003
    分别为随时间t变化的天然气管道末端压强及其一阶、二阶导数,f out(t)、
    Figure PCTCN2020107349-appb-100004
    分别为随时间t变化的天然气管道末端流量及其一阶导数;
    3)气惯性备用应对系统功率缺额出力模型为:
    Figure PCTCN2020107349-appb-100005
    约束条件为:
    Figure PCTCN2020107349-appb-100006
    其中,
    Figure PCTCN2020107349-appb-100007
    Figure PCTCN2020107349-appb-100008
    分别为P out(t)的上下限,t 1和t 2分别为气惯性备用供应的起始和截止时刻,G M为天然气热力值,f 1、f 2分别为管道在t 1时刻、t 2时刻的末端流量。
  3. 如权利要求1所述的一种气热惯性备用参与园区综合能源系统备用配置方法,其特征在于,步骤(2)具体为:
    a)热力系统模型为:
    Figure PCTCN2020107349-appb-100009
    Figure PCTCN2020107349-appb-100010
    Figure PCTCN2020107349-appb-100011
    Figure PCTCN2020107349-appb-100012
    式中,τ n(t)为热负荷建筑m对应的传输管道n随时间t变化的热时滞,l n为传输管道n的长度,v n(t)为传输管道n随时间t变化的热水流速,
    Figure PCTCN2020107349-appb-100013
    为热传输过程中传输管道n的热损耗功率,
    Figure PCTCN2020107349-appb-100014
    为传输管道n的管道热损率,T m(t)和
    Figure PCTCN2020107349-appb-100015
    分别为热负荷建筑m随时间t变化的室内温度和其一阶导数,H m(t)为随时间t变化的热网络对热负荷建筑m的供热功率,L m(t)为随时间t变化的热负荷建筑m的热损耗功率,C A为热负荷建筑的室内空气比热容,M A为热负荷建筑的室内空气质量,
    Figure PCTCN2020107349-appb-100016
    为热负荷建筑的散热系数,T out(t)表示随时间t变化的热负荷建筑的室外温度,m=1,2,...,z,z为园区综合能源系统总热负荷建筑数目;
    2)利用拉普拉斯变换求解热负荷建筑室温响应模型:
    Figure PCTCN2020107349-appb-100017
    3)构建热惯性备用应对系统功率缺额的出力模型为:
    Figure PCTCN2020107349-appb-100018
    式中,T m,c为正常舒适温度,T m,l为最低舒适温度,
    Figure PCTCN2020107349-appb-100019
    为随时间t变化的热负荷建筑m 的热惯性备用,t 3、t 4分别为热惯性备用供应的起始和截止时刻。
  4. 如权利要求1所述的一种气热惯性备用参与园区综合能源系统备用配置方法,其特征在于,园区综合能源备用模型为:
    Figure PCTCN2020107349-appb-100020
    其中,气热惯性备用数学模型为
    Figure PCTCN2020107349-appb-100021
    a t、b t分别为随时间t变化的气惯性、热惯性备用容量价格,
    Figure PCTCN2020107349-appb-100022
    为随时间t变化的气惯性、热惯性投入的备用容量;发电侧备用数学模型为
    Figure PCTCN2020107349-appb-100023
    c t、d t为备用市场出清后随时间t变化的备用容量价格和电量价格,R S
    Figure PCTCN2020107349-appb-100024
    分别为随时间t变化的发电侧备用成交容量、实际所投入的备用容量;需求侧备用数学模型为
    Figure PCTCN2020107349-appb-100025
    分别为随时间t变化的需求侧用户i的备用容量价格、电量补偿价格,R D,i
    Figure PCTCN2020107349-appb-100026
    分别为随时间t变化的需求侧用户i需求响应成交容量、实际所投入的备用容量,k为需求侧用户数目。
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Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114048928A (zh) * 2022-01-12 2022-02-15 汉谷云智(武汉)科技有限公司 一种具备高度可迁移能力的建筑短期负荷预测方法
CN114362124A (zh) * 2022-01-14 2022-04-15 国网(苏州)城市能源研究院有限责任公司 一种电热协同控制方法及光储直柔系统
CN114723221A (zh) * 2022-03-11 2022-07-08 上海电力大学 面向整体性集中供热和需求响应的热电联合优化调度方法
CN114741988A (zh) * 2022-04-26 2022-07-12 东南大学 一种计及综合能源系统气热惯性的调频方法
CN114881416A (zh) * 2022-04-08 2022-08-09 东南大学溧阳研究院 一种计及热电联产机组灵活性的综合能源惯性支撑方法
CN114925501A (zh) * 2022-04-26 2022-08-19 东南大学 一种考虑气热惯性的综合能源系统可靠性评估方法
CN115081247A (zh) * 2022-07-19 2022-09-20 河北农业大学 一种基于贝叶斯网络的热力系统可靠性评估方法
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Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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CN114218765A (zh) * 2021-11-26 2022-03-22 国网江苏省电力有限公司 一种应对电网功率缺额的综合能源惯性支撑方法

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110016342A1 (en) * 2009-07-20 2011-01-20 Viridity Software, Inc. Techniques for power analysis
CN108808663A (zh) * 2018-06-12 2018-11-13 浙江大学 一种基于多能互补的工业用户热需求响应方法
CN109474025A (zh) * 2018-10-08 2019-03-15 国网能源研究院有限公司 一种园区级综合能源系统优化调度模型
CN109978625A (zh) * 2019-03-28 2019-07-05 河海大学 一种计及电热气网络的综合能源系统多目标运行优化方法
CN110503271A (zh) * 2019-08-30 2019-11-26 南京工业大学 一种综合能源系统的多类型储能配置方法
CN110544017A (zh) * 2019-08-12 2019-12-06 上海交通大学 考虑热惯性和能源网络约束的能源系统可靠性评估方法

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9244444B2 (en) * 2011-03-07 2016-01-26 Callida Energy Llc Systems and methods for optimizing energy and resource management for building systems
CN109376912B (zh) * 2018-09-29 2021-07-02 东南大学 基于民用建筑物热惯性的冷热电联供系统运行优化方法
CN109472050B (zh) * 2018-09-30 2023-10-24 东南大学 基于热惯性的热电联产系统混合时间尺度调度方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110016342A1 (en) * 2009-07-20 2011-01-20 Viridity Software, Inc. Techniques for power analysis
CN108808663A (zh) * 2018-06-12 2018-11-13 浙江大学 一种基于多能互补的工业用户热需求响应方法
CN109474025A (zh) * 2018-10-08 2019-03-15 国网能源研究院有限公司 一种园区级综合能源系统优化调度模型
CN109978625A (zh) * 2019-03-28 2019-07-05 河海大学 一种计及电热气网络的综合能源系统多目标运行优化方法
CN110544017A (zh) * 2019-08-12 2019-12-06 上海交通大学 考虑热惯性和能源网络约束的能源系统可靠性评估方法
CN110503271A (zh) * 2019-08-30 2019-11-26 南京工业大学 一种综合能源系统的多类型储能配置方法

Cited By (15)

* Cited by examiner, † Cited by third party
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CN114723221A (zh) * 2022-03-11 2022-07-08 上海电力大学 面向整体性集中供热和需求响应的热电联合优化调度方法
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CN114881416B (zh) * 2022-04-08 2023-05-30 东南大学溧阳研究院 一种计及热电联产机组灵活性的综合能源惯性支撑方法
CN114741988A (zh) * 2022-04-26 2022-07-12 东南大学 一种计及综合能源系统气热惯性的调频方法
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CN115081247A (zh) * 2022-07-19 2022-09-20 河北农业大学 一种基于贝叶斯网络的热力系统可靠性评估方法
CN116681545A (zh) * 2023-01-30 2023-09-01 兰州理工大学 一种计及生物质-p2g耦合的设施农业园区近零碳实现方法
CN116362478A (zh) * 2023-02-15 2023-06-30 浙江大学 考虑综合能源枢纽灵活性的电-气耦合系统风险调度方法
CN116362478B (zh) * 2023-02-15 2024-03-22 浙江大学 考虑综合能源枢纽灵活性的电-气耦合系统风险调度方法
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CN117669982B (zh) * 2023-12-18 2024-05-17 山东建筑大学 一种考虑用户多舒适性的园区综合能源系统容量配置方法
CN117993896A (zh) * 2024-04-07 2024-05-07 浙江大学 极端冰雪灾害下考虑热惯性的综合能源系统韧性提升方法

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