CN115619006B - Electric-gas-hydrogen series-parallel comprehensive energy system optimization scheduling method considering auxiliary service - Google Patents
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Abstract
The application discloses an optimization scheduling method of an electric-gas-hydrogen series-parallel integrated energy system considering auxiliary service, and provides an optimization scheduling model of the electric-gas series-parallel integrated energy system considering green hydrogen injection, and the optimization scheduling model of the electric-gas series-parallel integrated energy system considering power grid auxiliary service to support high-proportion new energy consumption. Firstly, a natural gas system operation model for taking green hydrogen injection and pipeline pipe storage into account is established, wherein the natural gas system operation model comprises an electric hydrogen production model and a natural gas system operation model for taking pipeline hydrogen loading into account; and then, the electric-gas-hydrogen series-parallel comprehensive energy system optimization scheduling model considering auxiliary service is constructed by taking the electric hydrogen production and the multi-energy cooperation to provide peak regulation and flexible standby power grid auxiliary service into consideration. The application not only can support new energy consumption through electric hydrogen production and multi-energy cooperation, but also can improve the system operation flexibility, and is expected to provide technical reference for economic operation and auxiliary service of the comprehensive energy system under high-proportion new energy and green hydrogen permeation.
Description
Technical Field
The application relates to the technical field of comprehensive energy system optimization scheduling, in particular to an electric-gas-hydrogen series-parallel comprehensive energy system optimization scheduling method considering auxiliary service.
Background
The high-proportion grid connection of new energy mainly comprising wind power and photovoltaic is an important measure for supporting the strategy of carbon peak and carbon neutralization and the construction of a novel power system in China. However, the traditional power grid has relatively limited flexible regulation resources, and intermittent new energy output brings challenges to safe and economical operation of the power system. The gradual maturation of the electro-hydrogen production technology and the natural gas pipeline hydrogen-adding technology provides a new idea for solving the problem. Specifically, the electric hydrogen production technology can convert surplus new energy into hydrogen (green hydrogen) to be injected into a natural gas pipeline, and the long-distance transmission and efficient utilization of the hydrogen energy are realized by utilizing the natural gas pipeline, so that support is provided for high-proportion new energy consumption and low-carbonization transformation in the electric power and natural gas industries. The electric conversion gas is used as an important coupling unit for connecting the power system and the natural gas system, has the characteristics of quick response and flexible regulation, and plays an important role in improving the new energy consumption capacity of the system, reducing the carbon emission of the system, supporting the peak shaving of the power grid and the like. Compared with the electric conversion gas efficiency of 60-65%, the electric hydrogen production efficiency (generally up to 70-80%) is higher, so that the electric hydrogen production economic feasibility is better. It is worth noting that hydrogen energy is a flexible energy carrier which is zero-carbon, clean and capable of being converted with electricity in two directions, and is expected to play a role in regulation in each link of an electric power system. The development of hydrogen energy can effectively optimize the energy structure, reduce the dependence of the energy industry on traditional fossil energy and promote the low-carbonization transformation of the energy structure. However, current hydrogen pipeline networks are still immature, and there are relatively few auxiliary service studies to schedule integrated energy systems that account for electro-hydrogen production, while at the same time account for peak shaving and flexible standby.
Based on the method, the following two aspects need to be fully considered in the optimal scheduling of the electric-gas-hydrogen series-parallel integrated energy system: firstly, analyzing the influence of the electric hydrogen on the peak regulation and standby of the system on the basis of the optimization scheduling of an electric-gas series-parallel integrated energy system for electric hydrogen production; secondly, considering the influence of green hydrogen injection on the dispatching of the gas transmission network, and further analyzing the influence of new energy permeability and the limitation of the hydrogen mixing ratio of the pipeline on the dispatching of the comprehensive energy system.
Disclosure of Invention
Technical problems: the application aims to solve the technical problem of overcoming the defects of the prior art and providing an optimization scheduling method of an electric-gas-hydrogen series-parallel integrated energy system taking auxiliary service into account. The application can realize the timely and sufficient consumption of new energy and the effective improvement of the mutual coordination capacity of the multi-energy flow cross coupling and the economic and stable operation of the system, and is expected to provide technical reference for the economic operation and auxiliary service of the comprehensive energy system under the high-proportion new energy and green hydrogen permeation.
The technical scheme is as follows: the application provides an optimization scheduling method of an electric-gas-hydrogen series-parallel integrated energy system considering auxiliary service, which comprises the following steps:
step 1, acquiring operation parameters of a comprehensive energy system, wherein the operation parameters comprise parameter information of a generator set, an electric hydrogen production line, a gas source, a pipeline and a compressor;
step 2, acquiring scene information of electric load, gas load and wind-light output;
step 3, based on the acquired scene information of electric load, gas load and wind-light output, building a natural gas system model meeting the electric hydrogen production operation constraint and the natural gas network operation constraint considering green hydrogen injection according to the operation mechanism of the electric hydrogen production and the natural gas pipeline containing green hydrogen injection;
step 4, establishing a power system model meeting a plurality of power constraints, and providing a technical scheme meeting system peak shaving and standby requirements by considering flexible adjustment capability required by a power system;
step 5, according to the natural gas system model, the electric power system model and the proposed technical scheme, an electric-gas-hydrogen series-parallel integrated energy system optimization scheduling model taking auxiliary service into account is established;
and 6, based on the electric-gas-hydrogen series-parallel integrated energy system optimization scheduling model considering auxiliary service, taking the minimum sum of the running cost of the natural gas system, the running cost of the electric power system and the peak shaving cost as an objective function, solving the model by using a nonlinear optimization solver, and performing optimization scheduling on the natural gas system and the electric power system to obtain an electric-gas-hydrogen series-parallel integrated energy system optimization scheduling scheme considering auxiliary service.
Further, in step 3, the natural gas system model includes electro-hydrogen production operation constraints and natural gas network operation constraints that account for green hydrogen injection;
1) Electric hydrogen production operation constraint
Wherein:represents the electric power P consumed by the hydrogen production h at the time t P2H ;/>Represents the hydrogen energy E prepared by the electrohydrogen h at the time t P2H ;/>Represents the flow F of hydrogen generated by electrohydrogen h at time t P2H ;/>The maximum hydrogen energy which can be generated for the electric hydrogen production h at the time t; />Is the high heating value of hydrogen; η (eta) P2H The energy conversion efficiency of the hydrogen production by electricity is improved;
2) Natural gas network operation constraints accounting for green hydrogen injection
0≤α≤α max (B-14)
Wherein: subscript w represents a source of natural gas; subscripts m and n represent natural gas nodes; g w (m) is a collection of gas source points connected to node m;energy E for supplying natural gas to a gas source w at time t S The method comprises the steps of carrying out a first treatment on the surface of the Subscript h represents electro-hydrogen production; g h (m) is an electrical hydrogen collection connected to node m; subscript e represents the gas load; g e (m) is a set of gas loads connected to node m; />For the actual consumption power (energy) E of the gas load E at time t D The method comprises the steps of carrying out a first treatment on the surface of the Subscript v represents a genset; g g (m) is a gas turbine set connected to node m; />Gas energy E consumed by gas turbine set v at time t G The method comprises the steps of carrying out a first treatment on the surface of the Subscript k denotes the natural gas compressor; g k (m) is a set of compressors connected to node m; g (m) is a natural gas pipeline set connected with the node m; e (E) mn,t The energy of the gas at the head end of the pipeline m-n at the moment t; />Energy E of gas flowing through compressor k at time t C ;/>The percentage of gas energy consumed for compressor k to delivered energy; />An average gas flow through the pipe m-n at time t; pi m,t The pressure of the node m at the moment t; pi n,t The pressure of the node n at the moment t; w (W) mn Weymouth constant, F, for pipe m-n mn,t The gas flow of the head end of the pipeline m-n at the moment t; f (F) nm,t The gas flow at the m-n end of the pipeline at the moment t; l (L) mn,t The pipe stock of the pipeline m-n at the moment t; k (K) mn The tube stock constant for the tube m-n; h m,t The heat value of the node m at the time t; h n,t The heat value of the node n at the time t; />For the heat value H of the gas at the head end of the pipeline m-n at the moment t L ;/>For the gas heat value H at the m-n end of the pipeline at the moment t L ;/>Natural gas supply flow F for gas source w at time t S ;H gas The natural gas has high heat value, and the value is 38.29MJ/m3; />For the flow rate F of gas flowing through the compressor k at time t C ;The energy E required for the gas load E at time t L ;/>And->The energy is supplied to the natural gas with the minimum and the maximum of the gas source w respectively; />The upper limit of climbing for the air source w; />The transmission energy for compressor k; />And->The upper and lower pressure limits of the node m are respectively; />The inlet pressure value of the compressor k at the moment t; />The outlet pressure value of the compressor k at the moment t; />And->The upper limit and the lower limit of the compression ratio of the compressor k are respectively; alpha is the hydrogen mixing ratio; alpha max Gpi is a natural gas pipeline set with the maximum hydrogen mixing ratio; l (L) min Minimum value for natural gas system pipe, L mn,T Representing the inventory of pipes m-n during the last period T.
Further, in step 4, the power system model includes power system operation constraints:
wherein: subscripts i and j represent power buses; the subscript r represents a new energy unit; subscript d represents an electrical load; subscript REF represents a reference busbar; u (U) v (i) A generator set connected with a bus i; u (U) r (i) The new energy unit set is connected with the bus i; u (U) d (i) Is in combination with a motherAn electrical load set connected by line i; u (U) h (i) A set of electrical hydrogen generating units connected with the bus i; u (i) is a line set connected with the bus i;active output P of unit v at time t G ;/>Internet surfing power P of new energy unit r at time t W 。/>Demand power P for electrical load d at time t L ;/>Actual absorbed power P for electrical load d at time t D ;θ i,t The voltage phase angle of the bus i at the moment t; θ j,t The voltage phase angle of the bus j at the moment t; x is x ij And->The line ij susceptance and the maximum transmission capacity are respectively; />And->The upper limit and the lower limit of the power generation power of the unit v are respectively set; />Maximum value of the adjustment for the set v> Predicted power P for new energy unit r at time t cal ;/>And->The minimum and the maximum conversion power of the hydrogen production by electricity are respectively; θ REF,t Reference is made to the voltage phase angle of the bus REF for time t.
Further, in step 4, the proposed technical scheme for meeting the system peak shaving and standby requirements is as follows:
1) Technical scheme for meeting peak shaving requirements
The peak shaving requirement is changed into peak shaving cost by introducing an economic conversion coefficient epsilon, the minimum comprehensive cost target is formed together with the system operation cost, and the economy of the system operation is considered during peak shaving.
minF=F E +F G +F P (B-26)
Wherein F is E F for the running cost of the power system G F is the running cost of the natural gas system P Peak shaving cost;
wherein: omega shape c The method is a coal-fired unit set; omega shape g Is a gas turbine set; t represents the number of time sections;generating cost coefficients for the coal-fired machine unit; />Maintaining a cost coefficient for operation of the gas turbine unit; />The cost coefficient is the cut-off load; />Cost coefficient of air supply for air source w;/>Is the cost coefficient of the cut gas load; epsilon is the economic conversion coefficient, P t NL And->Respectively represent the net load P of the system at time t NL And average payload +.>The calculation formula is as follows:
2) Technical scheme for meeting standby requirement
The standby requirement of the system is provided by a conventional generator set and electric hydrogen so as to stabilize the power balance problem caused by load, wind power and photovoltaic power prediction deviation.
Wherein:upper flexible standby R representing system demand at time t U ;/>Lower flexible standby R representing system needs at time t D ;/>And->Respectively representing the predicted power P before the day of wind power k and photovoltaic s at the moment t cal ;α k 、α s And alpha is d FR coefficients of wind power k, photovoltaic s and load d, respectively, < >>Representing the upper flexible reserve capacity P provided by the conventional unit v at time t G,U ;/>Representing the lower flexible reserve capacity P provided by the conventional unit v at time t G,D ;/>Representing the upper flexible reserve capacity P provided by the electrohydrogen h at time t P2H,U ;/>Representing the lower flexible reserve capacity P provided by the electrohydrogen h at time t P2H,D ;/>Representing the ascending slope rate and the maximum of the conventional unit vRatio of capacity-> Representing the ratio of the downslope rate of a conventional unit v to its maximum capacity Represents the ratio of the ascending ramp rate of electrical hydrogen h to its maximum capacity +.> Represents the ratio of the downhill climbing rate of electro-hydrogen h to its maximum capacity +.>
Drawings
FIG. 1 is a flow chart of the method of the present application;
FIG. 2 is an exemplary diagram of an integrated energy system;
FIG. 3 is an electrogenerated hydrogen and electrogram diagram;
the standby structure is flexibly shown in the figure 4.
Detailed Description
The present application is further illustrated in the accompanying drawings and detailed description which are to be understood as being merely illustrative of the application and not limiting of its scope, since various modifications of the application, which are equivalent to those skilled in the art, will fall within the scope of the application as defined in the appended claims after reading the application.
The application provides an optimization scheduling method of an electric-gas-hydrogen series-parallel integrated energy system considering auxiliary service, which comprises the following steps:
step 1, acquiring operation parameters of a comprehensive energy system, wherein the operation parameters comprise parameter information of a generator set, an electric hydrogen production line, a gas source, a pipeline and a compressor;
step 2, acquiring scene information of electric load, gas load and wind-light output;
step 3, based on the acquired scene information of electric load, gas load and wind-light output, building a natural gas system model meeting the electric hydrogen production operation constraint and the natural gas network operation constraint considering green hydrogen injection according to the operation mechanism of the electric hydrogen production and the natural gas pipeline containing green hydrogen injection;
step 4, establishing a power system model meeting a plurality of power constraints, and providing a technical scheme meeting system peak shaving and standby requirements by considering flexible adjustment capability required by a power system;
step 5, according to the natural gas system model, the electric power system model and the proposed technical scheme, an electric-gas-hydrogen series-parallel integrated energy system optimization scheduling model taking auxiliary service into account is established;
and 6, based on the electric-gas-hydrogen series-parallel integrated energy system optimization scheduling model considering auxiliary service, taking the minimum sum of the running cost of the natural gas system, the running cost of the electric power system and the peak shaving cost as an objective function, solving the model by using a nonlinear optimization solver, and performing optimization scheduling on the natural gas system and the electric power system to obtain an electric-gas-hydrogen series-parallel integrated energy system optimization scheduling scheme considering auxiliary service.
In the step 3, the natural gas system model comprises electric hydrogen production operation constraint and natural gas network operation constraint considering green hydrogen injection;
1) Electric hydrogen production operation constraint
Wherein:represents the electric power P consumed by the hydrogen production h at the time t P2H ;/>Represents the hydrogen energy E prepared by the electrohydrogen h at the time t P2H ;/>Represents the flow F of hydrogen generated by electrohydrogen h at time t P2H ;/>The maximum hydrogen energy which can be generated for the electric hydrogen production h at the time t; />Is the high heating value of hydrogen; η (eta) P2H The energy conversion efficiency of the hydrogen production by electricity is improved;
2) Natural gas network operation constraints accounting for green hydrogen injection
0≤α≤α max (B-14)
Wherein: subscript w represents a source of natural gas; subscripts m and n represent natural gas nodes; g w (m) is a collection of gas source points connected to node m;energy E for supplying natural gas to a gas source w at time t S The method comprises the steps of carrying out a first treatment on the surface of the Subscript h represents electro-hydrogen production; g h (m) is an electrical hydrogen collection connected to node m; subscript e represents the gas load; g e (m) is a set of gas loads connected to node m; />For the actual consumption power (energy) E of the gas load E at time t D The method comprises the steps of carrying out a first treatment on the surface of the Subscript v represents a genset; g g (m) is a gas turbine set connected to node m; />Gas energy E consumed by gas turbine set v at time t G The method comprises the steps of carrying out a first treatment on the surface of the Subscript k denotes the natural gas compressor; g k (m) is a set of compressors connected to node m; g (m) is a natural gas pipeline set connected with the node m; e (E) mn,t The energy of the gas at the head end of the pipeline m-n at the moment t; />Energy E of gas flowing through compressor k at time t C ;/>The percentage of gas energy consumed for compressor k to delivered energy; />An average gas flow through the pipe m-n at time t; pi m,t The pressure of the node m at the moment t; pi n,t The pressure of the node n at the moment t; w (W) mn Weymouth constant, F, for pipe m-n mn,t The gas flow of the head end of the pipeline m-n at the moment t; f (F) nm,t The gas flow at the m-n end of the pipeline at the moment t; l (L) mn,t The pipe stock of the pipeline m-n at the moment t; k (K) mn The tube stock constant for the tube m-n; h m,t The heat value of the node m at the time t; h n,t The heat value of the node n at the time t; />For the heat value H of the gas at the head end of the pipeline m-n at the moment t L ;/>For the gas heat value H at the m-n end of the pipeline at the moment t L ;/>Natural gas supply flow F for gas source w at time t S ;H gas The natural gas has high heat value, and the value is 38.29MJ/m3; />For the flow rate F of gas flowing through the compressor k at time t C ;The energy E required for the gas load E at time t L ;/>And->The energy is supplied to the natural gas with the minimum and the maximum of the gas source w respectively; />The upper limit of climbing for the air source w; />The transmission energy for compressor k; />And->The upper and lower pressure limits of the node m are respectively; />The inlet pressure value of the compressor k at the moment t; />The outlet pressure value of the compressor k at the moment t; />And->The upper limit and the lower limit of the compression ratio of the compressor k are respectively; alpha is the hydrogen mixing ratio; alpha max Gpi is a natural gas pipeline set with the maximum hydrogen mixing ratio; l (L) min Minimum value for natural gas system pipe, L mn,T Representing the inventory of pipes m-n during the last period T.
In step 4, the power system model includes power system operation constraints:
wherein: subscripts i and j represent power buses; the subscript r represents a new energy unit; subscript d represents an electrical load; subscript REF represents a reference busbar; u (U) v (i) A generator set connected with a bus i; u (U) r (i) The new energy unit set is connected with the bus i; u (U) d (i) Is an electric load set connected with the bus i; u (U) h (i) A set of electrical hydrogen generating units connected with the bus i; u (i) is a line set connected with the bus i;active output P of unit v at time t G ;/>Internet surfing power P of new energy unit r at time t W 。/>Demand power P for electrical load d at time t L ;/>Actual absorbed power P for electrical load d at time t D ;θ i,t The voltage phase angle of the bus i at the moment t; θ j,t The voltage phase angle of the bus j at the moment t; x is x ij And->The line ij susceptance and the maximum transmission capacity are respectively; />And->The upper limit and the lower limit of the power generation power of the unit v are respectively set; />Maximum value of the adjustment for the set v> Predicted power P for new energy unit r at time t cal ;/>And->The minimum and the maximum conversion power of the hydrogen production by electricity are respectively; θ REF,t Reference is made to the voltage phase angle of the bus REF for time t.
In step 4, the proposed technical scheme for meeting the system peak shaving and standby requirements is as follows:
1) Technical scheme for meeting peak shaving requirements
The peak shaving requirement is changed into peak shaving cost by introducing an economic conversion coefficient epsilon, the minimum comprehensive cost target is formed together with the system operation cost, and the economy of the system operation is considered during peak shaving.
minF=F E +F G +F P (B-26)
Wherein F is E F for the running cost of the power system G F is the running cost of the natural gas system P Peak shaving cost;
wherein: omega shape c The method is a coal-fired unit set; omega shape g Is a gas turbine set; t represents the number of time sections;generating cost coefficients for the coal-fired machine unit; />Maintaining a cost coefficient for operation of the gas turbine unit; />The cost coefficient is the cut-off load; />The cost coefficient of the air supply for the air source w; />Is the cost coefficient of the cut gas load; epsilon is the economic conversion coefficient, P t NL And->Respectively represent the net load P of the system at time t NL And average payload +.>The calculation formula is as follows:
2) Technical scheme for meeting standby requirement
The standby requirement of the system is provided by a conventional generator set and electric hydrogen so as to stabilize the power balance problem caused by load, wind power and photovoltaic power prediction deviation.
Wherein:upper flexible standby R representing system demand at time t U ;/>Lower flexible standby R representing system needs at time t D ;/>And->Respectively representing the predicted power P before the day of wind power k and photovoltaic s at the moment t cal ;α k 、α s And alpha is d FR coefficients of wind power k, photovoltaic s and load d, respectively, < >>Representing the upper flexible reserve capacity P provided by the conventional unit v at time t G,U ;/>Representing the lower flexible reserve capacity P provided by the conventional unit v at time t G,D ;/>Representing the upper flexible reserve capacity P provided by the electrohydrogen h at time t P2H,U ;/>Representing the lower flexible reserve capacity P provided by the electrohydrogen h at time t P2H,D ;/>Representing the ratio of the climbing rate of the conventional unit v to its maximum capacity +.> Representing the ratio of the downslope rate of a conventional unit v to its maximum capacity Represents the ratio of the ascending ramp rate of electrical hydrogen h to its maximum capacity +.> Represents the ratio of the downhill climbing rate of electro-hydrogen h to its maximum capacity +.>
Calculation case analysis
The application adopts the modified belgium 24-node power system and the 20-node natural gas system shown in fig. 2; wherein the gas turbine trains of the power nodes 2,6,8, 13, 15 and 22 are connected to natural gas nodes 4,4,4,6, 11 and 13, respectively. The total capacity of the electric power system is 19.95GW, wherein the new energy and the gas turbine assembly capacity account for 30 percent and 17 percent of the total capacity respectively. In addition, the input ends of the electric hydrogen production equipment are respectively connected with the power grid nodes 2,3,5,6,7,8 and 9, and the output ends are respectively connected with the natural gas network nodes 2,3,4 and 11,4,7. The method is realized through a GAMS optimization platform, and an IPOPT solver is adopted to solve the nonlinear programming problem.
Based on this example, the method of the application is adopted to simulate the value of electric hydrogen production and multi-energy synergy for supporting new energy consumption and improving the system operation flexibility (the result is shown in fig. 3 and 4) and the influence of green hydrogen injection on the economic dispatching result of the system (the result is shown in table 1) by comparing the electric hydrogen production and the gas turbine unit output (fig. 3) of the scene 1 (without considering the auxiliary service model, the objective function is only the system operation cost target) and the scene 3 (considering the auxiliary service model, and the objective function comprehensively considers the system operation cost target and the peak shaving target), and considering the flexible reserve amount (fig. 4) provided by each unit under the scene 3. The electric hydrogen production and gas turbine set can provide important support for auxiliary service of the power grid, and particularly the gas turbine set mainly bears flexible regulation task by virtue of the quick regulation capability. Increasing the maximum hydrogen loading ratio of the natural gas pipeline is beneficial to reducing the system operation cost (table 1).
TABLE 1 System costs at different Hydrogen loading ratios
The application not only can improve the capacity of the system for absorbing new energy through the synergistic effect of the electric hydrogen production and the gas turbine unit, but also can effectively utilize the operation flexibility of the electric hydrogen production and the multi-energy synergy, improve the stable and flexible operation of the system, reduce the operation cost of the system and improve the low carbon property and the economy of the system.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present application should be included in the scope of the present application.
Claims (1)
1. An electric-gas-hydrogen series-parallel integrated energy system optimization scheduling method considering auxiliary service is characterized by comprising the following steps:
step 1, acquiring operation parameters of a comprehensive energy system, wherein the operation parameters comprise parameter information of a generator set, an electric hydrogen production line, a gas source, a pipeline and a compressor;
step 2, acquiring scene information of electric load, gas load and wind-light output;
step 3, based on the acquired scene information of electric load, gas load and wind-light output, building a natural gas system model meeting the electric hydrogen production operation constraint and the natural gas network operation constraint considering green hydrogen injection according to the operation mechanism of the electric hydrogen production and the natural gas pipeline containing green hydrogen injection;
step 4, establishing a power system model meeting a plurality of power constraints, and providing a technical scheme meeting system peak shaving and standby requirements by considering flexible adjustment capability required by a power system;
step 5, according to the natural gas system model, the electric power system model and the proposed technical scheme, an electric-gas-hydrogen series-parallel integrated energy system optimization scheduling model taking auxiliary service into account is established;
step 6, based on the electric-gas-hydrogen series-parallel integrated energy system optimization scheduling model for the auxiliary service, taking the minimum sum of the running cost of the natural gas system, the running cost of the electric power system and the peak shaving cost as an objective function, solving the model by using a nonlinear optimization solver, and performing optimization scheduling on the natural gas system and the electric power system to obtain an electric-gas-hydrogen series-parallel integrated energy system optimization scheduling scheme for the auxiliary service;
in the step 3, the natural gas system model contains electric hydrogen production operation constraint and natural gas network operation constraint considering green hydrogen injection;
1) Electric hydrogen production operation constraint
Wherein:represents the electric power P consumed by the hydrogen production h at the time t P2H ;/>Represents the hydrogen energy E prepared by the electrohydrogen h at the time t P2H ;/>Represents the flow F of hydrogen generated by electrohydrogen h at time t P2H ;/>The maximum hydrogen energy which can be generated for the electric hydrogen production h at the time t; />Is the high heating value of hydrogen; η (eta) P2H The energy conversion efficiency of the hydrogen production by electricity is improved;
2) Natural gas network operation constraints accounting for green hydrogen injection
0≤α≤α max (A-14)
Wherein: subscript w represents a source of natural gas; subscripts m and n represent natural gas nodes; g w (m) is a collection of gas source points connected to node m;energy E for supplying natural gas to a gas source w at time t S The method comprises the steps of carrying out a first treatment on the surface of the Subscript h represents electro-hydrogen production; g h (m) is an electrical hydrogen collection connected to node m; subscript e represents the gas load; g e (m) is a set of gas loads connected to node m; />For the actual consumption power (energy) E of the gas load E at time t D The method comprises the steps of carrying out a first treatment on the surface of the Subscript v represents a genset; g g (m) is a gas turbine set connected to node m; />Gas energy E consumed by gas turbine set v at time t G The method comprises the steps of carrying out a first treatment on the surface of the G (m) is a natural gas pipeline set connected with the node m; e (E) mn,t The energy of the gas at the head end of the pipeline m-n at the moment t; subscript k denotes the natural gas compressor; g k (m) is a set of compressors connected to node m; />Energy E of gas flowing through compressor k at time t C ;θ k The percentage of gas energy consumed for compressor k to delivered energy; />An average gas flow through the pipe m-n at time t; pi m,t The pressure of the node m at the moment t; pi n,t The pressure of the node n at the moment t; w (W) mn Weymouth constant, F, for pipe m-n mn,t The gas flow of the head end of the pipeline m-n at the moment t; f (F) nm,t The gas flow at the m-n end of the pipeline at the moment t; l (L) mn,t The pipe stock of the pipeline m-n at the moment t; k (K) mn The tube stock constant for the tube m-n; h m,t The heat value of the node m at the time t; h n,t The heat value of the node n at the time t; />For the heat value H of the gas at the head end of the pipeline m-n at the moment t L ;/>For the gas heat value H at the m-n end of the pipeline at the moment t L ;/>Natural gas supply flow F for gas source w at time t S ;H gas Is natural gas with high heat value of 38.29MJ/m 3 ;/>For the flow rate F of gas flowing through the compressor k at time t C ;/>The energy E required for the gas load E at time t L ;/>And->The energy is supplied to the natural gas with the minimum and the maximum of the gas source w respectively;the upper limit of climbing for the air source w; />The transmission energy for compressor k; />And->The upper and lower pressure limits of the node m are respectively; />The inlet pressure value of the compressor k at the moment t; />The outlet pressure value of the compressor k at the moment t; />And->The upper limit and the lower limit of the compression ratio of the compressor k are respectively; alpha is the hydrogen mixing ratio; alpha max Gpi is a natural gas pipeline set with the maximum hydrogen mixing ratio; l (L) min Minimum value for natural gas system pipe, L mn,T Representing the inventory of the pipeline m-n during the last period T;
in step 4, the power system model includes power system operation constraints:
wherein: subscripts i and j represent power buses; the subscript r represents a new energy unit; subscript d represents an electrical load; subscript REF represents a reference busbar; u (U) v (i) A generator set connected with a bus i; u (U) r (i) The new energy unit set is connected with the bus i; u (U) d (i) Is an electric load set connected with the bus i; u (U) h (i) A set of electrical hydrogen generating units connected with the bus i; u (i) is a line set connected with the bus i;active output P of unit v at time t G ;/>Internet surfing power P of new energy unit r at time t W ;/>Actual absorbed power P for electrical load d at time t D ;/>Demand power P for electrical load d at time t L ;θ i,t The voltage phase angle of the bus i at the moment t; θ j,t The voltage phase angle of the bus j at the moment t; x is x ij And->The line ij susceptance and the maximum transmission capacity are respectively; />And->The upper limit and the lower limit of the power generation power of the unit v are respectively set; />Maximum value of the adjustment for the set v> Predicted power P for new energy unit r at time t cal ;/>And->The minimum and maximum conversion power of the hydrogen production by electricity h are respectivelyA rate; θ REF,t Reference the voltage phase angle of the bus REF for the time t;
in step 4, the proposed technical scheme for meeting the system peak shaving and standby requirements is as follows:
1) Technical scheme for meeting peak shaving requirements
The peak shaving requirement is changed into peak shaving cost by introducing an economic conversion coefficient epsilon, and the minimum comprehensive cost target is formed together with the system operation cost:
min F=F E +F G +F P (A-26)
wherein F is E F for the running cost of the power system G F is the running cost of the natural gas system P Peak shaving cost;
wherein: omega shape c The method is a coal-fired unit set; omega shape g Is a gas turbine set; t represents the number of time sections;generating cost coefficients for the coal-fired machine unit; />Maintaining a cost coefficient for operation of the gas turbine unit; />The cost coefficient is the cut-off load; />The cost coefficient of the air supply for the air source w; />Is the cost coefficient of the cut gas load; epsilon is the economic conversion coefficient, P t NL And->Respectively represent the net load P of the system at time t NL And average payload +.>The calculation formula is as follows:
2) Technical scheme for meeting standby requirement
The standby requirement of the system is provided by a conventional generator set and electric hydrogen so as to stabilize the power balance problem caused by load, wind power and photovoltaic power prediction deviation;
wherein:upper flexible standby R representing system demand at time t U ;/>Lower flexible standby R representing system needs at time t D ;And->Respectively representing the predicted power P before the day of wind power k and photovoltaic s at the moment t cal ;α k 、α s And alpha is d FR coefficients of wind power k, photovoltaic s and load d, respectively, < >>Representing the upper flexible reserve capacity P provided by the conventional unit v at time t G,U ;/>Representing the lower flexible reserve capacity P provided by the conventional unit v at time t G,D ;/>Representing the upper flexible reserve capacity P provided by the electrohydrogen h at time t P2H ,U ;/>Representing the lower flexible reserve capacity P provided by the electrohydrogen h at time t P2H,D ;/>Representing the ratio of the rate of ascent of a conventional unit v to its maximum capacityValue-> Representing the ratio of the downslope rate of the conventional unit v to its maximum capacity +.> Represents the ratio of the ascending ramp rate of electrical hydrogen h to its maximum capacity +.> Represents the ratio of the downhill climbing rate of electro-hydrogen h to its maximum capacity +.>
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Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2016198791A1 (en) * | 2015-06-08 | 2016-12-15 | Grdf | Device and method for injecting dihydrogen into a flow of natural gas originating from a first natural gas distribution network |
AU2019101043A4 (en) * | 2019-09-11 | 2019-10-24 | Southeast University | A two-stage robust scheduling method for a hydrogen conpressed natural gas integrated energy system |
WO2020237700A1 (en) * | 2019-05-28 | 2020-12-03 | 国电南瑞科技股份有限公司 | Operation scheduling method for multiple energy systems |
CN114358431A (en) * | 2022-01-07 | 2022-04-15 | 国网山东省电力公司青岛供电公司 | Multi-energy system optimal scheduling method and device considering supply and demand bidirectional demand response |
CN114676897A (en) * | 2022-03-16 | 2022-06-28 | 三峡大学 | Optimal scheduling method for comprehensive energy system of park containing CHP-P2G-hydrogen energy |
CN114841545A (en) * | 2022-04-25 | 2022-08-02 | 华南理工大学 | Electricity-mixed hydrogen natural gas urban comprehensive energy system |
CN114881328A (en) * | 2022-05-09 | 2022-08-09 | 四川大学 | Comprehensive energy system economic dispatching method considering gas network hydrogen mixing and low-carbon reward |
CN115017723A (en) * | 2022-06-27 | 2022-09-06 | 国网(苏州)城市能源研究院有限责任公司 | Power and natural gas system combined optimization load flow calculation method considering hydrogen energy injection |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20220283575A1 (en) * | 2021-03-05 | 2022-09-08 | Air Products And Chemicals, Inc. | Method and apparatus for monitoring operational characteristics of an industrial gas plant complex |
-
2022
- 2022-09-23 CN CN202211164916.1A patent/CN115619006B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2016198791A1 (en) * | 2015-06-08 | 2016-12-15 | Grdf | Device and method for injecting dihydrogen into a flow of natural gas originating from a first natural gas distribution network |
WO2020237700A1 (en) * | 2019-05-28 | 2020-12-03 | 国电南瑞科技股份有限公司 | Operation scheduling method for multiple energy systems |
AU2019101043A4 (en) * | 2019-09-11 | 2019-10-24 | Southeast University | A two-stage robust scheduling method for a hydrogen conpressed natural gas integrated energy system |
CN114358431A (en) * | 2022-01-07 | 2022-04-15 | 国网山东省电力公司青岛供电公司 | Multi-energy system optimal scheduling method and device considering supply and demand bidirectional demand response |
CN114676897A (en) * | 2022-03-16 | 2022-06-28 | 三峡大学 | Optimal scheduling method for comprehensive energy system of park containing CHP-P2G-hydrogen energy |
CN114841545A (en) * | 2022-04-25 | 2022-08-02 | 华南理工大学 | Electricity-mixed hydrogen natural gas urban comprehensive energy system |
CN114881328A (en) * | 2022-05-09 | 2022-08-09 | 四川大学 | Comprehensive energy system economic dispatching method considering gas network hydrogen mixing and low-carbon reward |
CN115017723A (en) * | 2022-06-27 | 2022-09-06 | 国网(苏州)城市能源研究院有限责任公司 | Power and natural gas system combined optimization load flow calculation method considering hydrogen energy injection |
Non-Patent Citations (3)
Title |
---|
"Market-based coordination of regional electric and natural gas systems: A peer-to-peer energy trading model";Guoqiang SUN etc.;《CSEE Journal of Power and Energy Systems》;全文 * |
考虑P2G备用服务的电―气联合网络风电消纳及低碳效益分析;许志恒;张勇军;陈泽兴;;电力科学与技术学报(第03期);全文 * |
许志恒 ; 张勇军 ; 陈泽兴 ; .考虑P2G备用服务的电―气联合网络风电消纳及低碳效益分析.电力科学与技术学报.2020,(第03期),全文. * |
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