CN110955954B - Method for reducing optimal load of layered decoupling electric heat comprehensive energy system - Google Patents
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Abstract
The invention relates to a method for reducing optimal load of a layered decoupling electric and thermal integrated energy system, which is technically characterized by comprising the following steps: step 1: inputting comprehensive energy system data, and setting and initializing relevant parameters of a model; step 2: solving a scheduling optimization result of the energy hub in the outer layer of the layered decoupling optimization model, and further correcting the load of each energy subsystem in the inner layer of the model; step 3: respectively calculating the optimal load reduction amount of the electric heating subsystem, and correcting the input upper limit of the energy concentrator in the outer layer model based on the optimal load reduction amount; step 4: and (3) iterating the steps 2 and 3 circularly until the result converges or the maximum iteration number is reached. According to the invention, the existing mature optimal power flow solving method is utilized to independently solve each energy subsystem, and then the energy coupling equation is solved based on the energy concentrator, so that the optimal load reduction problem of the comprehensive energy system is converted into the optimal power flow problem of a single system, the complexity of the original problem is greatly reduced, and the calculation efficiency, stability and practicability are remarkably improved.
Description
Technical Field
The invention relates to an optimal load reduction amount calculation method for a comprehensive energy system. In particular to a method for reducing the optimal load of a layered decoupling electric and thermal integrated energy system.
Background
With the increasing serious problems of environmental pollution, climate change and the like, the global energy field is being raised a history and the deepest and the most extensive revolution, the traditional power system is difficult to adapt to the new energy supply and demand pattern and development trend, and the comprehensive energy system (Integrated Energy System, IES) taking the power system as the core becomes the main bearing form of the energy of the future human society. The comprehensive energy system is coupled with a plurality of energy subsystems, and the processes of generating, transmitting, converting, distributing and the like of a plurality of energy sources are planned and scheduled uniformly, so that diversified demands on a demand side are met, the energy utilization efficiency is improved, and the flexibility of energy supply is enhanced. However, compared with the traditional power system, the comprehensive energy system planning and design and optimizing operation process face more uncertainty factors, such as new equipment of an air source heat pump, a gas turbine, an energy storage type electric heater and the like, and the uncertainty factors greatly increase the coupling degree of a power grid, a heat supply network and a gas network, so that the system planning and operation work are more complicated and difficult, and great challenges are brought to the safe and stable operation of the system.
The objective function of the comprehensive energy system optimal load reduction algorithm is that the load reduction amount of the system is the lowest, the equation constraint condition and the inequality constraint condition are combined, the minimum loss load of the system under the conditions of element faults, maintenance and the like is obtained by utilizing an optimization method, and the algorithm can be used for analyzing the influence of various uncertain factors such as the element faults of the comprehensive energy system, distributed energy output changes, load fluctuation and the like on energy supply adequacy and safety and providing corresponding lifting measures. Therefore, the method for calculating the optimal load reduction amount of the electric and thermal comprehensive energy system has extremely important significance for the processes of system planning, running, scheduling and the like.
The optimal load reduction algorithm can be used for quantitatively calculating the optimal load reduction condition under the fault state of the comprehensive energy system, the current research mostly adopts a unified solution, and the optimal load reduction model is built by integrating the trend process and the energy conversion process of each subsystem, but the equation of the model is always non-convex, the jacobian matrix is singular, the algorithm is difficult to converge, and the calculation result is difficult to ensure global optimal. Therefore, how to develop a method for calculating the optimal load reduction amount of an electric heat comprehensive energy system with high solving efficiency and easy convergence is a technical problem to be solved by the researchers in the field.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide the hierarchical decoupling optimal load reduction algorithm for the electric heat comprehensive energy system, which can efficiently and accurately solve the optimal load reduction amount of the electric heat comprehensive energy system in various fault states.
The invention solves the practical problems by adopting the following technical scheme:
an optimal load reduction method of a layered decoupling electric heat integrated energy system comprises an electric power system, a solar heat system, a thermodynamic system and an energy concentrator; establishing a layered decoupling model, and carrying out optimization solution on the optimal load reduction of the comprehensive energy system, wherein the method comprises the following steps of:
step 1: inputting reference data of each system in the comprehensive energy system into a hierarchical decoupling optimization model;
step 2: setting a convergence threshold delta and a maximum iteration number N of a hierarchical decoupling optimization model HDOF The method comprises the steps of carrying out a first treatment on the surface of the Let the initialization iteration number calculator n=1;
step 3: solving an energy concentrator at the outer layer of the layered decoupling model by adopting linear programming to achieve a scheduling optimization result, and taking the lowest load reduction as an objective function:
wherein: n (N) EH The number of energy hubs for the coupling nodes; i is the energy hub label; e. g and h are respectively three energy sources of electricity\gas\heat; ΔL e,i 、ΔL g,i And DeltaL h,i The electric load reduction amount, the gas load reduction amount and the heat load reduction amount of the i-th energy hub are respectively.
Step 4: correcting the load of each energy subsystem in the inner layer in the layered decoupling optimization model according to the dispatching optimization result of the energy hub system in the step 3;
step 5: calculating an optimal power flow for reducing the load of the power system to obtain an optimal load reduction amount of the power system;
step 6: calculating the optimal power flow of the load reduction of the natural gas system to obtain the optimal load reduction amount of the natural gas system;
step 7: calculating an optimal power flow of load reduction of the thermodynamic system to obtain an optimal load reduction amount of the thermodynamic system;
step 8: correcting the upper limit value P of the input of the energy concentrator in the outer layer model according to the optimal load reduction amounts of the power system, the natural gas system and the thermodynamic system which are respectively obtained max ；
Step 9: calculating a difference vector delta of the layer decoupling optimization model according to the optimal load reduction amounts of the electric heating subsystems in the steps 5, 6 and 7 max ；
Step 10: if delta max <Delta, turning to step 12, otherwise, turning to the next step;
step 11: iteration counter n=n+1, if n<N HDOF Turning to step 3, otherwise, the model is not converged, and exiting;
step 12: and outputting the optimal load reduction amount of the comprehensive energy system.
According to the structure type and the equipment parameters of the energy concentrator input in the step 1, an energy concentrator model is established, and the conversion and distribution of various equipment in the comprehensive energy system to energy sources such as electricity, heat and gas are accurately described by using a coupling matrix:
wherein: l, C and P vectors represent the input, coupling matrix and output of the energy hub, respectively; cij represents the efficiency of energy conversion from the ith input energy source to the jth output energy source.
The constraint conditions of the energy hub optimization objective function in the step 3 are as follows:
wherein: l, C and P are respectively substitutedThe output end, the input end and the coupling matrix of the meter energy hub; p (P) min And P max A lower limit value and an upper limit value of P; Δl is the reduction in electrical/gas/thermal output load of the energy hub; l (L) 0 The electric/gas/heat output load of the energy concentrator is realized.
In the step 4, the load of each energy subsystem in the inner layer in the layered decoupling optimization model is corrected:
wherein: l (L) e,i 、L g,j And L h,k Load reduction amounts for the power system node i, the natural gas system node j and the thermodynamic system node k respectively; p (P) e,i 、P g,j And P h,k Respectively calculating the tidal flows of the power system node i, the natural gas system node j and the thermodynamic system node k in the step 3); i epsilon EH, j epsilon EH and k epsilon EH respectively represent a power system node i, a natural gas system node j and a thermodynamic system node k, and are connected with an energy hub EH;and->The power system node i, the natural gas system node j and the thermodynamic system node k are respectively represented to be not connected with the energy hub EH; i epsilon N e Representing node i as a power system node; j E N g The expression node j is a natural gas system node; k is E N h Node k is denoted as the thermodynamic system node.
The optimal power flow model for power system load reduction in the step 5 is as follows:
the optimal load reduction model of the power system is based on the optimal power flow, and the lowest load reduction amount is taken as an objective function:
wherein: n (N) e The number of nodes of the power system; ΔL e,i The load of the power system node i is reduced. Constraint conditions of the corresponding model are as follows:
wherein: ΔL e Reducing the load of the power system node; l (L) e The node load is the power system node load; p (P) e The power flow is the power system node; p, Q, V, θ are respectively the active power flow, reactive power flow, voltage and phase angle of the power system, and the corresponding last four formulas respectively represent the upper and lower limits of the values; equation f e The node power equation of the relation between the injection power and the node voltage of the grid node is shown as the power balance equation in the polar coordinate form:
wherein: p (P) i And Q i Active power and reactive power respectively injected for node i, U i And U j Voltages at nodes i and j, G ij And B ij The conductance and susceptance, θ, of the node admittance matrix, respectively ij For the phase angle difference of voltage of nodes i and j, theta ij ＝θ i –θ j . The optimal power flow model for reducing the load of the natural gas system in the step 6 is as follows:
wherein: n (N) g The number of nodes of the natural gas system; ΔL g,j The load on the natural gas system node j is reduced. Constraint conditions of the corresponding model are as follows:
wherein: ΔL g Reducing the load of the natural gas system node; l (L) g The natural gas system node load is as follows; p (P) g The natural gas system node tide is provided; f (F) mn 、H c Pi is the branch flow of the natural gas network, the power of the compressor and the pressure of the node are respectively represented by the upper limit and the lower limit of the value of the corresponding three formulas; equation f g The tidal current equation of the natural gas system is as follows:
AF mn +S-L-GF c ＝0 (10)
wherein: a is a topological matrix of the system, and represents the association relation between nodes and branches, wherein the branches comprise compressors and pipelines; s is the output of the air source node; l is the load node demand; g is the association matrix of the compressor and the nodes; if the compressor is driven by a gas turbine, i.e. the compressor consumes a certain amount of natural gas, F c Gas consumption for the compressor:
wherein: a, a c 、b c And c c Fitting coefficients; h c Is the compressor power.
The optimal power flow model for reducing the load of the thermal system in the step 7 is as follows:
wherein: n (N) h The number of nodes of the natural gas system; ΔL h,k Reducing the load of a node k of the thermodynamic system; constraint conditions of the corresponding model are as follows:
wherein: ΔL h Reducing the node load of the thermodynamic system; l (L) h The node load of the thermodynamic system is set; p (P) h The node tide is the thermodynamic system; m, T s 、T r The pipeline flow, the node supply temperature and the node return temperature are respectively represented by the upper limit and the lower limit of the value of the corresponding three formulas; equation f e The flow equation of the thermodynamic system is as follows:
wherein: Φ is the thermal power consumed or supplied by the node.
The step 12 includes: calculating the optimal load reduction amount delta L of the comprehensive energy system Σ ：
ΔL Σ ＝ΔL e +ΔL g +ΔL h
Wherein:and->The loads of the power system node, the natural gas system node j and the thermodynamic system node k which are initially input in the step 1 and the output load of each energy concentrator are respectively; p (P) e,i 、P g,j And P h,k Respectively obtaining optimal power flow calculation results of the power system node i, the natural gas system node j and the thermodynamic system node k in the step 5 in the iteration of the round; ΔL e 、ΔL g And DeltaL h The sum of the load reduction amounts of the electric power system, the natural gas system and the thermodynamic system is respectively.
The invention has the advantages and beneficial effects that:
according to the method for calculating the optimal load reduction of the layered decoupling electric heat comprehensive energy system, the existing mature power flow solving method is utilized to independently solve each energy subsystem, and then the energy coupling equation is solved based on the energy concentrator, so that the solution is flexible and easy to converge. The whole algorithm model is divided into an outer layer and an inner layer, the inner layer is used for respectively carrying out Optimal Power Flow (OPF) calculation aiming at the minimum load reduction amount on an electric heat energy subsystem, the outer layer is used for carrying out overall optimization scheduling on three electric heat energy sources in a comprehensive energy system by utilizing an energy hub, so that the complementary conversion relation of the three energy sources is embodied, and the final convergence solution is obtained through continuous iterative solution of the inner layer model and the outer layer model. The model can convert the optimal load reduction problem of the comprehensive energy system into a single OPF problem, greatly reduces the complexity of the original problem, and remarkably improves the calculation efficiency, stability and practicability.
Drawings
FIG. 1 is a flow chart of a method for calculating optimal load shedding amount of a layered decoupled electric heat integrated energy system;
FIG. 2 is a hierarchical decoupling optimization model diagram of the electrical and thermal integrated energy system;
FIG. 3 is a schematic diagram of an energy hub;
FIG. 4 is a specific block diagram of an energy hub;
FIG. 5 is a diagram of an integrated energy system test example;
Detailed Description
The method for calculating the optimal load reduction amount of the layered decoupling electric heat integrated energy system according to the present invention is further described in detail below with reference to the examples and the accompanying drawings:
the method for calculating the optimal load reduction amount of the electric heat integrated energy system with layered decoupling is shown in fig. 1, and an integrated energy system layered decoupling optimization model (Hierarchical Decoupling Optimization Framework of IES, HDOF) established by an algorithm is shown in fig. 2 and comprises the following steps:
step 1: and inputting comprehensive energy system data, including an electric/gas/heat system, an energy concentrator and the like. The specific input is as follows: parameters of a power transmission line, a natural gas pipeline, a heating pipeline, a transformer and a compressor of the electric/gas/heat system, load data, structural types of a topological structure and an energy concentrator, equipment parameters of a transformer, an air conditioner, a cogeneration unit, a gas pipeline and a heat exchanger and the like;
wherein: the comprehensive energy system is used for coupling various energy sources through an energy hub, so that complementary conversion of the various energy sources is realized, the energy hub is shown in fig. 3, and the whole model is divided into an input end L, a coupling matrix C and an output end P, wherein the coupling matrix accurately describes the energy conversion and distribution processes of electricity, heat, gas and the like. The specific structure of the energy hub in this embodiment is shown in fig. 4, and the energy hub model accurately describes the conversion and distribution of various devices in the integrated energy system to energy such as electricity, heat, gas, and the like by using a coupling matrix. The structure of the energy concentrator is shown in fig. 3, and it can be seen that the input and output of the energy concentrator are electric, gas and heat, and the direction of the current in the electric heat system can be obviously seen. The energy hub comprises five devices: transformer (T), air Conditioner (AC), natural Gas Pipeline (GP), cogeneration unit (CHP) and Heat Exchanger (HE), AC and CHP are coupling devices, the coupling matrix of the energy hub is:
wherein: l (L) e 、L g 、L h 、P e 、P g And P h The electric heat three outputs and the electric heat three inputs of the energy hub are respectively; η is the efficiency of the energy conversion of the plant; η (eta) T Is the conversion efficiency of the transformer; η (eta) CHP-e The electricity generating efficiency of the cogeneration unit is; η (eta) CHP-h The heat generating efficiency of the cogeneration unit is; η (eta) AC Is the air conditioning efficiency; v is a scheduling factor related to electrical thermal energy source allocation; v e,T A duty cycle allocated to the transformer for the electrical input; v e,AC Duty cycle allocated to air conditioner for electrical input, v e,T +v e,AC ＝1；v g,CHP The duty cycle for the gas input to the cogeneration unit is allocated.
Step 2: setting a convergence threshold delta and a maximum iteration number N of a hierarchical decoupling optimization model of the comprehensive energy system HDOF . Initializing an iteration number calculator n=1;
step 3: and solving an energy hub dispatching optimization result of the outer layer of the layered decoupling model by adopting linear programming, wherein the lowest load reduction is taken as an objective function:
wherein: n (N) EH The number of energy hubs for the coupling nodes; i is the energy hub label; e. g and h are respectively three energy sources of electricity\gas\heat; ΔL e,i 、ΔL g,i And DeltaL h,i The electric load reduction amount, the gas load reduction amount and the heat load reduction amount of the i-th energy hub are respectively. The constraint conditions are as follows:
wherein: l, C and P represent the input, output and coupling matrix of the energy hub, respectively; p (P) min And P max A lower limit value and an upper limit value of P; Δl is the reduction in electrical/gas/thermal output load of the energy hub; l (L) 0 The electric/gas/heat output load of the energy concentrator is realized.
Step 4: according to the energy hub dispatching optimization result in the step 3, the load of each energy subsystem in the inner layer in the layered decoupling optimization model is corrected:
wherein: l (L) e,i 、L g,j And L h,k Load reduction amounts for the power system node i, the natural gas system node j and the thermodynamic system node k respectively; p (P) e,i 、P g,j And P h,k Respectively calculating the tidal flows of the power system node i, the natural gas system node j and the thermodynamic system node k in the step 3); i epsilon EH, j epsilon EH and k epsilon EH respectively represent a power system node i, a natural gas system node j and a thermodynamic system node k, and are connected with an energy hub EH;and->The power system node i, the natural gas system node j and the thermodynamic system node k are respectively represented to be not connected with the energy hub EH; i epsilon N e Representing node i as a power system node; j E N g The expression node j is a natural gas system node; k is E N h Node k is denoted as the thermodynamic system node.
In the steps 5-7: and respectively solving the optimal power flow problem of power system load reduction, the optimal power flow problem of natural gas system load reduction and the optimal power flow problem of thermodynamic system load reduction to obtain the optimal load reduction amount of the electric/gas/heat energy subsystem.
The specific method in the step 5 is as follows:
step 5 includes the optimal power flow problem of load shedding of the electric power system, the natural gas system and the thermodynamic system, and a specific model thereof is as follows:
(1) The optimal load reduction model of the power system is based on the optimal power flow, and the lowest load reduction amount is taken as an objective function:
wherein: n (N) e The number of nodes of the power system; ΔL e,i The load of the power system node i is reduced. Constraint conditions of the corresponding model are as follows:
wherein: ΔL e Reducing the load of the power system node; l (L) e The node load is the power system node load; p (P) e The power flow is the power system node; p, Q, V, θ are respectively the active power flow, reactive power flow, voltage and phase angle of the power system, and the corresponding last four formulas respectively represent the upper and lower limits of the values; equation f e The node power equation of the relation between the injection power and the node voltage of the grid node is shown as the power balance equation in the polar coordinate form:
wherein: p (P) i And Q i Active power and reactive power respectively injected for node i, U i And U j Voltages at nodes i and j, G ij And B ij The conductance and susceptance, θ, of the node admittance matrix, respectively ij For the phase angle difference of voltage of nodes i and j, theta ij ＝θ i –θ j 。
In step 6, the natural gas system comprises a gas source, a gas pipeline, a compressor, a load node and the like. The natural gas is supplied by the gas source node and is transmitted to the load node through the gas transmission pipeline, the gas turbine can convert the natural gas into electric energy and heat energy for users to use, and the compressor can improve the gas pressure in the natural gas transmission process so as to compensate the pressure loss in the transmission process. The optimal load shedding model of the natural gas system is as follows:
wherein: n (N) g The number of nodes of the natural gas system; ΔL g,j The load on the natural gas system node j is reduced. Constraint conditions of the corresponding model are as follows:
wherein: ΔL g Reducing the load of the natural gas system node; l (L) g The natural gas system node load is as follows; p (P) g The natural gas system node tide is provided; f (F) mn 、H c Pi is the branch flow of the natural gas network, the power of the compressor and the pressure of the node are respectively represented by the upper limit and the lower limit of the value of the corresponding three formulas; equation f g The tidal current equation of the natural gas system is as follows:
AF mn +S-L-GF c ＝0 (10)
wherein: a is a topological matrix of the system, and represents the association relation between nodes and branches, wherein the branches comprise compressors and pipelines; s is the output of the air source node; l is the load node demand; g is the association matrix of the compressor and the nodes; if the compressor is driven by a gas turbine, i.e. the compressor consumes a certain amount of natural gas, F c Gas consumption for the compressor:
wherein: a, a c 、b c And c c Fitting coefficients; h c Is the compressor power.
In step 7: the optimal load shedding model of the thermodynamic system is as follows:
wherein: n (N) h The number of nodes of the natural gas system; ΔL h,k The load on the thermodynamic system node k is reduced. Constraint conditions of the corresponding model are as follows:
wherein: ΔL h Reducing the node load of the thermodynamic system; l (L) h The node load of the thermodynamic system is set; p (P) h The node tide is the thermodynamic system; m, T s 、T r The pipeline flow, the node supply temperature and the node return temperature are respectively represented by the upper limit and the lower limit of the value of the corresponding three formulas; equation f e The flow equation of the thermodynamic system is as follows:
wherein: Φ is the thermal power consumed or supplied by the node.
Step 8: according to steps 5-7The calculated upper limit value P of the input P of the energy concentrator in the optimal load reduction correction outer layer model of each energy subsystem max ：
Wherein: p (P) emax,i 、P gmax,j And P hmax,k Respectively representing the upper limit value of the electric heat input of the energy concentrator connected with the power system node i, the natural gas system node j and the thermodynamic system node k; p (P) e,i 、P g,j And P h,k Respectively representing the electric/gas/heat energy input of the energy concentrator at the corresponding node; i epsilon N e The node i is a power system node, and the i epsilon EH is that the power system node i is connected with an energy hub; j E N g The node j is a natural gas system node, and j epsilon EH indicates that the natural gas system node j is connected with an energy hub; k is E N h The node k is a thermodynamic system node, and k epsilon EH indicates that the thermodynamic system node k is connected with an energy hub.
Step 9: calculating delta for judging whether the model is converged according to the optimal load reduction amount of the electric heating subsystem obtained in the step 5-7 max ：
δ max ＝max(δ i ,...,δ j ,...,δ k ,...)
Wherein: ΔL e,i Reducing the load of the power system node i; ΔL g,j Reducing the load of the natural gas system node j; ΔL h,k The load on the thermodynamic system node k is reduced.
Step 10: if delta max <Delta, turning to step 10, otherwise, turning to step 9;
step 11: iteration counter n=n+1, if n<N HDOF Turning to step 3, otherwise, the model is not converged, and exiting;
step 12: computing healdOptimal load reduction amount delta L of combined energy system Σ ：
ΔL Σ ＝ΔL e +ΔL g +ΔL h
Wherein:and->The loads of the power system node, the natural gas system node j and the thermodynamic system node k which are initially input in the step 1 and the output load of each energy concentrator are respectively; p (P) e,i 、P g,j And P h,k Respectively obtaining power flow calculation results of the power system node i, the natural gas system node j and the thermodynamic system node k in the step 5 in the iteration of the round; ΔL e 、ΔL g And DeltaL h The sum of the load reduction amounts of the electric power system, the natural gas system and the thermodynamic system is respectively.
The method for calculating the optimal load reduction of the layered decoupling electric heat comprehensive energy system realizes the optimal load reduction calculation of the electric heat comprehensive energy system under the fault condition, and can be used for reliability evaluation of the electric heat comprehensive energy system.
For the embodiment of the present invention, the calculation example is composed of an IEEE 33 node power system, a 32 node thermodynamic system and a 14 node natural gas system, as shown in fig. 5. The power generation capacity of the IEEE 33 node system is 9MW, the peak load is 3.175MW, the power generation capacity of the 32 node thermodynamic system is 4.5MW, and the peak load is 2.164MW. The 14-node natural gas system output capacity was 1.9MW with a peak load of 0.285MW. The compressor is driven by the gas turbine, and the tap position is the gas injection pipeline end. The parameter input includes: the type of nodes in the IEEE 33 node system, active load, reactive load, reference voltage and upper and lower voltage limits; the position of the generator, the upper limit and the lower limit of active output and the upper limit and the lower limit of reactive output; the node topology, resistance, reactance, power flow limit, etc. of the power line are shown in tables 1-3. The type of the node in the 14-node natural gas system, the load power, the upper and lower limits of the gas source supply power and the upper and lower limits of the node gas pressure; node topological relation and pipeline coefficient of natural gas pipeline; the node topology, characteristic constant, maximum compression ratio and minimum compression ratio of the compressor are shown in tables 4 to 6. Node load, upper limit of heat source output and upper and lower limit of node water supply and return temperature in the 32-node thermodynamic system; node topology, length, diameter, pipe heat transfer coefficient, roughness, forward flow limit and reverse flow limit of the thermodynamic pipe are shown in tables 7 and 8. The topological relation and the structure of the four energy hubs are shown in fig. 4, the maximum limit of electric/gas/heat input of the energy hubs is equal to 1.5 times of the corresponding load of the access node, the electric heat load of the output side is equal to the corresponding load of the access node, and the transmission efficiency and conversion efficiency parameters of the equipment such as a transformer, an air conditioner, a cogeneration unit, a natural gas pipeline, a heat exchanger and the like are shown in table 9.
The computer hardware configuration of the embodiment of the invention comprises a Core i5-6500 CPU (3.20 GHz) and an 8GB memory; the operating system is Windows 10 operating system, and the simulation software is MATLAB2018a.
In the embodiment of the invention, the method for calculating the optimal load reduction amount of the layered decoupling electric heat integrated energy system is applied to reliability evaluation, the reliability level of the system under the state of solving and analyzing line faults is calculated, the reliability evaluation method is a state enumeration method, the index is EENS, the state enumeration order is 2, the unavailability rate of an electric line, a natural gas pipeline and a thermodynamic pipeline is 0.1%, and the convergence threshold delta=0.001 and the maximum iteration number N of the layered decoupling optimization model of the integrated energy system HDOF ＝100。
The embodiment of the invention is provided with 4 energy hubs, the embodiment is taken as a basic embodiment A1, the internal structure of the energy hubs is changed, the elements with coupling effect in the energy hubs are an Air Conditioner (AC) and a cogeneration unit (CHP), the air conditioner has electric heating coupling effect, the cogeneration unit has electric heating coupling effect, and the change of the internal structure of the energy hubs is completed by adding and deleting the three elements to form the embodiment. The calculation example A2 deletes the cogeneration unit based on the calculation example A1, and only retains the air conditioner of the electric heating coupling element; the example A3 deletes the air conditioner based on the example A1, and only retains the electric heat coupling element cogeneration unit; example A4 the energy hub only maintains the components transformer, natural gas pipeline and heat exchanger, and the electrical/gas/thermal subsystem is completely decoupled. The reliability analysis was performed on examples A1-4, and the results are shown in Table 10.
Table 10 shows that the coupling element has a significant impact on system reliability. The energy-saving hub of the coupling ring has different structural settings, the coupling relations of all subsystems of the comprehensive energy system are different, the transfer and conversion processes between different corresponding energy sources are different, and the influence on the reliability is different. Table 11 shows the energy subsystem coupling relationships corresponding to the energy hubs in the various examples of Table 10, where the arrows indicate the energy flow direction. The impact of different energy hub structures on electrical/thermal reliability was obtained and ranked according to tables 10 and 11, see table 12.
Table 12 orders the energy hub structure with reliability impact capability, with the positive sign "(+)" in brackets indicating positive, i.e., increasing reliability, the negative sign "(-)" in brackets indicating negative, i.e., decreasing reliability, and the 0 "(0) in brackets indicating zero, i.e., unchanged reliability. It can be seen that the CHP and AC can convert electricity and gas into heat, and thus, after being introduced into the energy hub structure, the CHP and AC couple the power system, the natural gas system and the thermodynamic system, so that the thermal reliability is greatly improved. But at the same time may also lead to a certain reduction in the gas reliability or electrical reliability.
It should be emphasized that the embodiments described herein are illustrative rather than limiting, and that this invention encompasses other embodiments which may be made by those skilled in the art based on the teachings herein and which fall within the scope of this invention.
TABLE 1 IEEE 33 node System node parameters
Wherein node type 1 represents a PQ node, 2 represents a PV node, and 3 represents a balance node.
Table 2 IEEE 33 node system generator parameters
Table 3 IEEE 33 node system power line parameters
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Table 4 node parameters of 14 node natural gas system
Wherein node type 1 represents a load node and 2 represents an air source node.
Table 5 node natural gas system natural gas pipeline parameters
Table 6 14 node natural gas system compressor parameters
Table 7 nodes of the 32 node thermodynamic system and heat source parameters
/>
Wherein node type 1 represents a load node and 2 represents a heat source node.
Table 8 parameters of thermodynamic pipeline of 32 nodes thermodynamic system
Table 9 energy hub device parameters
Table 10 results of reliability evaluation of different coupling links
Table 11 energy subsystem coupling relationship
Table 12 influence capability of coupling links on reliability
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Claims (4)
1. An optimal load reduction method of a layered decoupling electric heat integrated energy system comprises an electric power system, a solar heat system, a thermodynamic system and an energy concentrator; the method is characterized by establishing a layered decoupling model and carrying out optimization solution on the optimal load reduction of the comprehensive energy system, and comprises the following steps:
step 1: inputting reference data of each system in the comprehensive energy system into a hierarchical decoupling optimization model;
step 2: setting a convergence threshold delta and a maximum iteration number N of a hierarchical decoupling optimization model HDOF The method comprises the steps of carrying out a first treatment on the surface of the Let the initialization iteration number calculator n=1;
step 3: solving an energy concentrator at the outer layer of the layered decoupling model by adopting linear programming to achieve a scheduling optimization result, and taking the lowest load reduction as an objective function:
wherein: n (N) EH The number of energy hubs for the coupling nodes; i is the energy hub label; e. g and h are respectively three energy sources of electricity\gas\heat; ΔL e,i 、ΔL g,i And DeltaL h,i An electric load reduction amount, a gas load reduction amount and a heat load reduction amount of the i-th energy hub respectively;
step 4: correcting the load of each energy subsystem in the inner layer in the layered decoupling optimization model according to the dispatching optimization result of the energy hub system in the step 3;
step 5: calculating an optimal power flow for reducing the load of the power system to obtain an optimal load reduction amount of the power system; wherein:
the optimal load reduction model of the power system is based on the optimal power flow, and the lowest load reduction amount is taken as an objective function:
wherein: n (N) e The number of nodes of the power system; ΔL e,i Reducing the load of the power system node i; constraint conditions of the corresponding model are as follows:
wherein: ΔL e Reducing the load of the power system node; l (L) e The node load is the power system node load; p (P) e The power flow is the power system node; p, Q, V, θ are respectively the active power flow, reactive power flow, voltage and phase angle of the power system, and the corresponding last four formulas respectively represent the upper and lower limits of the values; equation f e The node power equation of the relation between the injection power and the node voltage of the grid node is shown as the power balance equation in the polar coordinate form:
wherein: p (P) i And Q i Active power and reactive power respectively injected for node i, U i And U j Voltages at nodes i and j, G ij And B ij The conductance and susceptance, θ, of the node admittance matrix, respectively ij For the phase angle difference of voltage of nodes i and j, theta ij ＝θ i –θ j ；
Step 6: calculating the optimal power flow of the load reduction of the natural gas system to obtain the optimal load reduction amount of the natural gas system;
the optimal power flow model for load reduction of the natural gas system is as follows:
wherein: n (N) g The number of nodes of the natural gas system; ΔL g,j Reducing the load of the natural gas system node j; constraint conditions of the corresponding model are as follows:
wherein: ΔL g Reducing the load of the natural gas system node; l (L) g The natural gas system node load is as follows; p (P) g The natural gas system node tide is provided; f (F) mn 、H c Pi is the branch flow of the natural gas network, the power of the compressor and the pressure of the node are respectively represented by the upper limit and the lower limit of the value of the corresponding three formulas; equation f g The tidal current equation of the natural gas system is as follows:
AF mn +S-L-GF c ＝0 (10)
wherein: a is a topological matrix of the system, and represents the association relation between nodes and branches, wherein the branches comprise compressors and pipelines; s is the output of the air source node; l is the load node demand; g is the association matrix of the compressor and the nodes; if the compressor is driven by a gas turbine, i.e. the compressor consumes a certain amount of natural gas, F c Gas consumption for the compressor:
wherein: a, a c 、b c And c c Fitting coefficients; h c Is compressor power;
step 7: calculating an optimal power flow of load reduction of the thermodynamic system to obtain an optimal load reduction amount of the thermodynamic system; the optimal power flow model for load reduction of the thermodynamic system is as follows:
wherein: n (N) h The number of nodes of the natural gas system; ΔL h,k Reducing the load of a node k of the thermodynamic system; constraint conditions of the corresponding model are as follows:
wherein: ΔL h Reducing the node load of the thermodynamic system; l (L) h The node load of the thermodynamic system is set; p (P) h The node tide is the thermodynamic system; m, T s 、T r The pipeline flow, the node supply temperature and the node return temperature are respectively represented by the upper limit and the lower limit of the value of the corresponding three formulas; equation f e The flow equation of the thermodynamic system is as follows:
wherein: phi is the thermal power consumed or supplied by the node
Step 8: correcting the upper limit value P of the input of the energy concentrator in the outer layer model according to the optimal load reduction amounts of the power system, the natural gas system and the thermodynamic system which are respectively obtained max ；
Step 9: calculating a difference vector delta of the layered decoupling optimization model according to the optimal load reduction amounts of the electric heating subsystems in the steps 5, 6 and 7 max ；
Step 10: if delta max <Delta, turning to step 12, otherwise, turning to the next step;
step 11: iteration counter n=n+1, if n<N HDOF Turning to step 3, otherwise, the model is not converged, and exiting;
step 12: outputting the optimal load reduction amount of the comprehensive energy system; wherein, include:
calculating the optimal load reduction amount delta L of the comprehensive energy system Σ ：
ΔL Σ ＝ΔL e +ΔL g +ΔL h
Wherein:and->The loads of the power system node, the natural gas system node j and the thermodynamic system node k which are initially input in the step 1 and the output load of each energy concentrator are respectively; p (P) e,i 、P g,j And P h,k Respectively obtaining optimal power flow calculation results of the power system node i, the natural gas system node j and the thermodynamic system node k in the steps 5-7 in the iteration of the round; ΔL e 、ΔL g And DeltaL h The sum of the load reduction amounts of the electric power system, the natural gas system and the thermodynamic system is respectively.
2. The method for reducing optimal load of a layered decoupling electric heat integrated energy system according to claim 1, wherein the energy hub model is built according to the structure type and the equipment parameters of the energy hub input in the step 1,
wherein: l, C and P vectors represent the input, coupling matrix and output of the energy hub, respectively; c ij Representing the efficiency of energy conversion from the ith input energy source to the jth output energy source.
3. The method for reducing optimal load of a layered decoupling electric heat integrated energy system according to claim 1, wherein the constraint condition of the energy hub optimization objective function in the step 3 is:
wherein: l, C and P represent the output, input and coupling matrix of the energy hub, respectively; p (P) min And P max A lower limit value and an upper limit value of P; Δl is the reduction in electrical/gas/thermal output load of the energy hub; l (L) 0 The electric/gas/heat output load of the energy concentrator is realized.
4. The method for reducing the optimal load of the layered decoupling electric heat integrated energy system according to claim 1, wherein the load of each energy subsystem in the inner layer in the layered decoupling optimization model is corrected in the step 4:
wherein: l (L) e,i 、L g,j And L h,k Load reduction amounts for the power system node i, the natural gas system node j and the thermodynamic system node k respectively; p (P) e,i 、P g,j And P h,k Respectively calculating the tidal flows of the power system node i, the natural gas system node j and the thermodynamic system node k in the step 3); i epsilon EH, j epsilon EH and k epsilon EH respectively represent a power system node i, a natural gas system node j and a thermodynamic system node k, and are connected with an energy hub EH;and->The power system node i, the natural gas system node j and the thermodynamic system node k are respectively represented to be not connected with the energy hub EH; i epsilon N e Representing node i as a power system node; j E N g The expression node j is a natural gas system node; k is E N h Node k is denoted as the thermodynamic system node.
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