WO2020093296A1 - Procédé de calcul de flux de puissance basé sur l'intervalle pour un système d'énergie intégré puissance-chaleur - Google Patents
Procédé de calcul de flux de puissance basé sur l'intervalle pour un système d'énergie intégré puissance-chaleur Download PDFInfo
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- WO2020093296A1 WO2020093296A1 PCT/CN2018/114473 CN2018114473W WO2020093296A1 WO 2020093296 A1 WO2020093296 A1 WO 2020093296A1 CN 2018114473 W CN2018114473 W CN 2018114473W WO 2020093296 A1 WO2020093296 A1 WO 2020093296A1
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- 238000004364 calculation method Methods 0.000 title claims abstract description 19
- 238000000034 method Methods 0.000 claims abstract description 29
- 238000005457 optimization Methods 0.000 claims abstract description 12
- 238000012887 quadratic function Methods 0.000 claims abstract description 11
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 16
- 238000010438 heat treatment Methods 0.000 claims description 8
- 239000011159 matrix material Substances 0.000 claims description 6
- 230000001133 acceleration Effects 0.000 claims description 3
- 230000005494 condensation Effects 0.000 claims description 3
- 238000009833 condensation Methods 0.000 claims description 3
- 239000000446 fuel Substances 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims description 3
- 238000005485 electric heating Methods 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 238000012502 risk assessment Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
- 238000013076 uncertainty analysis Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- 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]
Definitions
- the invention relates to the field of operation scheduling and control of an integrated energy system, and in particular to an interval power flow calculation method of an electric-thermal interconnected integrated energy system.
- Energy Internet can cover energy systems such as power supply, gas supply, heating, cooling, hydrogen supply and electrified transportation.
- power supply gas supply
- heating cooling
- hydrogen supply electrified transportation
- the uncertainties of power systems and thermal systems increase.
- the distribution of power flow may fundamentally change, such as the reverse flow of reactive power in the grid
- the node voltage exceeds the limit and the flow of the heat network pipeline is reversed. Therefore, it is necessary to use the uncertainty analysis method to describe the coupling characteristics and power flow distribution of the electric heating interconnection system, and then analyze the mutual influence and risk assessment of the electric heating system.
- Uncertainty power flow calculation methods are mainly divided into three categories: stochastic power flow, fuzzy power flow and interval power flow according to the modeling method of uncertainty. Among them, the information of the uncertainty required by the interval flow is the least, and only the upper and lower bounds of the uncertainty need to be known. Random power flow and fuzzy power flow need to obtain the probability density function and membership density function of uncertain quantities, and these functions are often difficult to determine in practice, and they are often chosen by humans. At present, the most representative method of interval power flow calculation in power systems is the interval algorithm, but the interval iterative algorithm will encounter the problem of expansion of the interval solution set during the interval operation, resulting in poor numerical stability and computational complexity of the local optimal solution. Too large and other issues.
- the present invention provides a linear optimization-based In the electric-thermal interconnected interval power flow method, the power flow and thermal power flow equations are linearized by multivariate Taylor expansion, and the upper and lower limits of each state variable are iteratively solved using an optimization method. At the same time, considering that it is difficult for the electric heating load to reach the maximum or minimum at the same time, the concept of uncertain load budget is introduced to overcome the conservativeness of the interval solution.
- the method for calculating the interval power flow of the integrated energy system with electricity and heat according to the present invention includes:
- the model of the integrated energy system of electricity-heat interconnection established in step (1) is as follows:
- P i and Q i are the injected active and reactive power of node i respectively
- ⁇ ij ⁇ i - ⁇ j
- U i and ⁇ i are the voltage and phase angle of node i
- U j and ⁇ j are respectively Is the voltage and phase angle of node j
- G ij and B ij are the conductance and susceptance of the ⁇ -type equivalent circuit
- n represents the number of branches connected to node i
- A is the network node-branch pipe correlation matrix
- m is the heat network pipeline flow
- m q is the node inflow load flow
- B is the loop correlation matrix
- h f is the pipeline pressure drop caused by friction loss
- K is the pipeline resistance coefficient
- L is the pipeline length
- D is the pipeline diameter
- ⁇ is the water density
- g is the acceleration of gravity
- f is the friction coefficient
- ⁇ is the pipe roughness
- Re is the Reynolds number
- ⁇ is the
- the unary quadratic function of the flow m in step (2) is specifically:
- step (3) specifically includes:
- m q, i is the inflow load flow of the node of the ith pipe of the heat network
- step (4) specifically includes:
- Represents the vth element of the state variable at the kth iteration, with Respectively The upper and lower bounds of the interval, M represents the number of elements of the state variable, the load variable Z L [P L ; Q L ; ⁇ L ] T , P L is the active power of the electric load, Q L is the reactive power of the electric load, ⁇ L is the heat load power, Z Lr represents the rth load value, Represents the expected value of the rth load, ⁇ r represents the standard deviation of the rth load, ⁇ is the set of uncertain loads, n r is the number of uncertain loads, Uncertain budget for load, uncertain budget for load Value is greater than expected
- the present invention Compared with the prior art, the present invention has obvious advantages: the present invention introduces a linear optimization method into the heat network, linearizes the power flow and thermal power flow equations through multivariate Taylor expansion, and successively iteratively solves each state variable by using the optimization method Upper and lower limits. At the same time, considering that it is difficult for the electric heating load to reach the maximum or minimum at the same time, the concept of uncertain load budget is introduced to overcome the conservativeness of the interval solution.
- Figure 1 is a diagram of Beauty's electric-thermal interconnection integrated energy system.
- This embodiment provides a method for calculating the interval power flow of an integrated electric-thermal interconnected energy system, including the following steps:
- P i and Q i are the injected active and reactive power of node i respectively
- ⁇ ij ⁇ i - ⁇ j
- U i and ⁇ i are the voltage and phase angle of node i
- U j and ⁇ j are respectively Is the voltage and phase angle of node j
- G ij and B ij are the conductance and susceptance of the ⁇ -type equivalent circuit
- n represents the number of branches connected to node i
- A is the network node-branch pipe correlation matrix
- m is the heat network pipeline flow
- m q is the node inflow load flow
- B is the loop correlation matrix
- h f is the pipeline pressure drop caused by friction loss
- K is the pipeline resistance coefficient
- L is the pipeline length
- D is the pipeline diameter
- ⁇ is the water density
- g is the acceleration of gravity
- f is the friction coefficient
- ⁇ is the pipe roughness
- Re is the Reynolds number
- ⁇ is the
- Equations (1)-(2) are grid steady-state models
- equations (3)-(8) are heat network hydraulic models
- equation (3) is the node flow balance equation
- equation (4) is the loop pressure equation
- equation (5) Is the head loss equation
- the simultaneous equations (6)-(8) can obtain the pipeline resistance coefficient K.
- Equations (9)-(11) are the thermal network thermal model
- equation (9) is the heat load power equation
- equation (10) is the pipeline temperature drop equation
- equation (11) is the node power conservation equation.
- the fixed hot spot ratio in the coupling element is described by equation (12)
- the variable thermoelectric ratio is described by equation (13).
- the electrical load probability model is described by equation (14), and the thermal load probability model is described by equation (15).
- the resistance coefficient K of the pipeline can be determined by equations (6)-(8), and the pressure drop of the pipeline can be obtained by bringing K into equation (5), so K is an important physical quantity.
- equation (8) is the logarithmic equation in the transcendental equation, so the specific value of K cannot be given when the pipeline flow rate is unknown in advance.
- K the initial value of the flow m (0) , the initial value of the resistance coefficient K (0) , and then iteratively calculated K (1) K (2) ... K (i) , but the calculation is too large and more complicated. Therefore, the present invention proposes a conversion method of the drag coefficient K.
- equation (16) is transformed into:
- the present invention adopts an iterative method to ensure the linearization accuracy, and selects the initial iteration value by the following method.
- a linear optimization method is used to iteratively solve the upper and lower limits of the state variable. It includes the following steps:
- Represents the vth element of the state variable at the kth iteration, with Respectively The upper and lower bounds of the interval, M represents the number of elements of the state variable, the load variable Z L [P L ; Q L ; ⁇ L ] T , P L is the active power of the electric load, Q L is the reactive power of the electric load, ⁇ L is the heat load power, Z Lr represents the rth load value, Represents the expected value of the rth load, ⁇ r represents the standard deviation of the rth load, ⁇ is the set of uncertain loads, n r is the number of uncertain loads, Uncertain budget for load;
- ⁇ is the preset threshold.
- NLP nonlinear programming
- LP linear programming
- the following embodiment performs simulation verification on this embodiment.
- Method 1 represents the solution of the deterministic power flow
- Method 2 represents the interval solution obtained by (30) and (31)
- Method 3 represents the random sampling of 10000 groups within the expected value of each load ⁇ 10% Uniformly distributed, and the interval solution of the state quantity calculated by the Newton method of load flow; from Table 1 we can see that the deterministic power flow values are within the range of the range power flow, and the upper / lower limits of Method 3 are basically similar to the upper / lower limits of Method 1. Thus, the correctness and rationality of the proposed linear optimization method are verified.
- Method 4 means adding the uncertainty budget and the interval solution obtained by the basic invention method. It can be seen that the interval range is greatly reduced after the uncertainty budget is added.
- Table 2 gives the total width of each state variable interval range. As can be seen from Table 2, after considering the uncertain budget, the interval length of the power flow is greatly reduced, so the uncertain budget can effectively overcome the conservativeness of the interval
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Abstract
La présente invention concerne un procédé de calcul de flux de puissance basé sur l'intervalle pour un système d'énergie intégré puissance-chaleur, comprenant les étapes consistant à : (1) obtenir des informations de système d'énergie intégré puissance-chaleur et établir un modèle de système d'énergie intégré puissance-chaleur en fonction des informations ; (2) convertir une équation de chute de pression de tuyau dans le modèle de système en une fonction quadratique à une variable d'un débit m ; (3) obtenir la valeur initiale itérative d'une variable d'état par calcul selon le modèle de système d'énergie intégré puissance-chaleur ; (4) résoudre de manière itérative les limites supérieure et inférieure de la variable d'état au moyen d'un procédé d'optimisation linéaire en fonction de la valeur initiale itérative de la variable d'état et de la fonction quadratique à une variable du débit m ; et (5) donner aux limites supérieure et inférieure de la variable d'état la forme d'un intervalle et sortir l'intervalle en tant que solution de flux de puissance. La présente invention présente une faible complexité de calcul et surmonte le conservatisme de la solution d'intervalle.
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CN201811310786.1A CN109242365B (zh) | 2018-11-06 | 2018-11-06 | 一种电-热互联综合能源系统的区间潮流计算方法 |
CN201811310786.1 | 2018-11-06 |
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