CN116384536B - Comprehensive energy collaborative planning method for medium-large energy users - Google Patents
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Abstract
The invention discloses a comprehensive energy collaborative planning method and device for medium and large energy users, wherein the method comprises the following steps: s1, building a comprehensive energy system architecture; s2, establishing a comprehensive energy system station-network collaborative optimization planning model based on a comprehensive energy system architecture; s3, converting the comprehensive energy system station-network collaborative optimization planning model by using a large M method and second order cone relaxation; s4, acquiring comprehensive energy system parameters, and solving the converted planning model by adopting a solver to determine a planning scheme. The invention realizes the collaborative planning of the comprehensive energy system for medium and large energy users, and provides the planning scheme of energy network topology and capacity while planning the energy station equipment, thereby ensuring the economy, energy efficiency and overall rationality of the system planning scheme.
Description
Technical Field
The invention relates to the field of energy system planning, in particular to a comprehensive energy collaborative planning method and device for medium and large-sized energy users, which take energy efficiency and economy into account.
Background
With the rapid development of global economy, energy consumption continues to increase, and energy crisis is increasingly highlighted. Optimizing energy structures has become an important strategy for solving the problem of energy shortage in countries around the world, especially for large and medium-sized energy users (i.e. park-level energy users, large occupied area, high user load level and long energy network lines).
The comprehensive energy system covers a plurality of energy fields such as electricity, heat, cold, gas, traffic and the like, can eliminate barriers among energy subsystems, realizes comprehensive cascade utilization of various energy sources, improves the capability of absorbing clean energy sources, realizes advantage complementation among the energy sources, and meets various energy demands of users.
Although many experts and scholars have conducted a certain study on the capacity planning and the energy network planning of the energy station equipment, the independent planning and the actual situation of the energy network and the energy equipment are unhooked, and an information barrier exists between the two, so that the cooperative optimization of the energy network and the energy equipment cannot be realized, and the overall rationality of the system planning cannot be ensured.
Therefore, collaborative planning of energy stations and energy networks is of paramount importance.
Disclosure of Invention
Aiming at the problems, the invention provides a comprehensive energy collaborative planning method and device for medium and large-sized energy users, which plan energy station equipment and simultaneously provide a planning scheme for energy network topology and capacity, thereby ensuring the overall rationality of system planning.
In order to achieve the above purpose, the present invention provides the following technical solutions: a comprehensive energy collaborative planning method for medium and large-scale energy users comprises the following steps:
S1, building a comprehensive energy system architecture;
S2, establishing a comprehensive energy system station-network collaborative optimization planning model based on a comprehensive energy system architecture;
S3, converting the comprehensive energy system station-network collaborative optimization planning model by using a large M method and second order cone relaxation;
S4, acquiring comprehensive energy system parameters, and solving the converted planning model by adopting a solver to determine a planning scheme.
In step S1, the architecture of the integrated energy system includes an overall architecture of the integrated energy system of the medium-and large-sized energy users, an architecture of the energy station, and an architecture of the load side.
The overall architecture of the comprehensive energy system is as follows:
the comprehensive energy system comprises four energy networks of electricity, heat, cold and gas, four types of nodes of a power source node, an air source node, an energy station node and a load node,
The comprehensive energy system purchases electricity to an external power grid through a power supply node, and purchases natural gas to a gas company through a gas source node;
the power supply node and the air source node transmit electric energy and natural gas to the energy station and the user through the electric network and the air network, and the energy station provides three forms of energy of electricity, heat and cold for the user.
The energy station architecture is as follows:
The energy station adopts a bus structure and comprises an electric bus, a thermal bus, a cold bus and a gas bus, wherein the input energy comprises electric energy and natural gas, and the output energy comprises three energy forms of electricity, heat and cold;
The equipment inside the energy station comprises renewable energy power generation equipment, energy supply equipment and energy conversion equipment, and is also provided with energy storage equipment.
The load side architecture is:
the load side adopts a bus structure, and distributed energy equipment is also arranged besides the externally input electric, thermal, cold and gas energy.
In step S2, a comprehensive energy system station-network collaborative optimization planning model is built with the minimum total cost of the system as a target, as shown in formula (1):
F1＝CST,inv+CL,inv+Cnet,inv+CST,om+CL,om+Cgas+Cgrid (1)
Wherein F 1 is the total cost of the system, C ST,inv is the energy station equipment investment cost, C L,inv is the load side equipment investment cost, C net,inv is the energy network investment cost, C ST,om is the energy station equipment operation and maintenance cost, C L,om is the load side equipment operation and maintenance cost, C gas is the gas purchase cost, and C grid is the electricity purchase cost.
The investment cost of the energy station equipment is shown in the formulas (2) - (3):
Wherein N ST represents the number of nodes of the energy station, m represents the interest rate, y represents the service life of equipment, R represents the fund recovery coefficient, Representing the installed capacity of the energy station PV/WT/CHP,/>Representing the installed capacity of the energy station GB/EH/EC/AC,/>Representing the installed capacity of the energy station BT/HC/CD,/>Representing investment cost coefficients of energy stations PV/WT,/>Representing the investment cost coefficient of the energy station CHP/GB/EH/EC/AC,/>An investment cost coefficient representing the energy station BT/HC/CD;
PV represents photovoltaic power generation, WT represents a fan, CHP represents a cogeneration unit, GB represents a gas boiler, EH represents an electric heating boiler, EC represents an electric refrigerator, AC represents an absorption refrigerator, BT represents a storage battery, HC represents a heat storage tank, and CD represents a cold storage tank.
The investment cost of the load side equipment is shown as a formula (4):
wherein N L represents the number of load nodes, Representing the installed capacity of the load side EH/ECH,/>The investment cost coefficient of the load side EH/ECH is represented, EH represents an electric heating boiler, and ECH represents an electric air conditioner.
The investment cost of the energy network is shown in the formula (5):
Wherein N ES represents the number of power supply nodes, N GS represents the number of air source nodes, N ST represents the number of energy station nodes, N L represents the number of load nodes, Representing the capacity of a power/gas source to energy station network,/>Representing the capacity of the power/gas source to the load network,/>Representing the capacity of an energy station to a load electric/heat/cold network,/>Representing the length of the power supply to the energy station/the air supply to the energy station pipe network,/>Indicating the length of the power to load/gas to load piping network,Representing the length of the energy station to the load electric/heat/cold pipe network,/>The investment cost coefficient of representing the power supply/air source to the energy station pipe network is 1/2,/>Representing the investment cost factor 1/2 of the power/gas source to load side pipe network,The investment cost coefficient of the energy station to the load side power grid/heat supply network/cold network is 1/2;
ES represents a source node, GS represents a source node, ST represents an energy station node, and L represents a load node.
The operation and maintenance cost of the energy station equipment is shown in the formula (6):
wherein T represents the length of a scheduling period, deltat represents the scheduling time resolution, N ST represents the number of energy station nodes, Representing the output active power of the energy station PV/WT,/>Representing the output electrical active power of the energy station CHP,Representing the output power of the energy station GB/AC,/>Represents the energy storage/discharge power of the energy station BT/HC/CD,Representing the operation and maintenance cost coefficient of the energy station PV/WT,/>Representing the operation and maintenance cost coefficient of the energy station CHP/GB/EH/EC/AC,/>Representing the operation and maintenance cost coefficients of the energy station BT/HC/CD.
The operation and maintenance cost of the load side equipment is shown as a formula (7):
wherein N L represents the number of load nodes, Represents the output power of the load side EH,/>Representing the output heat/output cold power of the load side ECH,/>Representing the operation and maintenance cost coefficients of the load side EH/ECH.
The gas purchasing cost is shown as a formula (8):
Wherein N GS represents the number of air source nodes, Representing the output power of the air source node,/>Representing natural gas price/natural gas heating value.
The electricity purchasing cost is shown as a formula (9):
where N ES represents the number of power supply nodes, Representing the output active power of the power supply node,/>Indicating electricity prices.
The constraint conditions of the comprehensive energy system station-network collaborative optimization planning model comprise: grid constraints, heat and cold grid constraints, gas grid constraints, node power balance constraints, energy station power balance constraints, load side power balance constraints, energy station equipment installation capacity constraints, load side equipment installation capacity constraints, energy network installation capacity constraints, electricity purchasing and gas purchasing constraints, energy station equipment operating efficiency constraints, load side equipment operating efficiency constraints, energy station equipment operating output constraints, load side equipment operating output constraints, energy station equipment operating power factor constraints, load side equipment operating power factor constraints, energy network operating constraints, energy station energy storage equipment constraints.
The grid constraints include power flow constraints, upper and lower voltage-current limit constraints,
The tide constraint is shown as a formula (10):
In the method, in the process of the invention, Representing the per unit value of active/reactive power from the power supply to the head end/tail end of the energy station pipe network,/>Representing the per unit value of resistance/reactance of a power supply to an energy station grid,/>Voltage per unit value representing power/energy station/load node,/>Representing the current per unit value of the power supply to the energy station/power supply to the load/energy station to the load grid;
The upper and lower limit constraints of the voltage and the current are shown in formulas (11) - (12):
In the method, in the process of the invention, Represents the maximum value of the per unit value of the power/energy station/load side voltage,Representing the maximum value of the per unit value of the power supply to the energy station/power supply to the load/energy station to the load grid current;
the heat supply network and the cold network constraint comprise heat energy-flow constraint, heat loss constraint and flow upper and lower limit constraint,
The thermal energy-flow constraints of the hot and cold networks are as shown in formula (13):
In the method, in the process of the invention, Representing the head-end power of an energy station to a load side heat/cold network,/>The flow from the energy station to the load heat supply network/cold network is represented by T s/r,H/C, the water supply/return temperature of the heat supply network/cold network is represented by T s/r,H/C, and the specific heat capacity of water is represented by c;
the thermal constraints of the hot and cold networks are as shown in formula (14):
In the method, in the process of the invention, Representing the loss rate from the energy station to the load side heat network/cold network;
the upper and lower flow limit constraints of the heat supply network and the cold supply network are shown in a formula (15):
In the method, in the process of the invention, Representing the maximum flow from the energy station to the load heat/cold network;
the air network constraint comprises:
Flow-pressure constraint
The flow-pressure constraint of the air network is shown in formula (16):
In the method, in the process of the invention, Air pressure representing power/energy station/load node,/>Representing the flow of air source to energy station/load air network,/>Representing the transmission coefficient from the air source to the energy station/load side;
Flow-power constraint
The flow-pressure constraint of the air network is shown in formula (17):
In the method, in the process of the invention, Representing the power from the air source to the energy station/load side pipe network;
Flow pressure upper and lower limit constraints
The upper and lower limit constraints of the flow pressure of the air network are shown in formulas (18) - (19):
In the method, in the process of the invention, Air pressure minimum/maximum representing power/energy station/load node,/>Representing the maximum flow of the air source to the energy station/load air network;
the node power balancing constraint includes:
Power supply output
The output power balance constraints of the power supply nodes are shown in formulas (20) - (21):
In the method, in the process of the invention, Representing the output reactive power of the power supply node,/>Representing the active/reactive power of the power supply to the head end of the energy station pipe network;
Air source output
The output power balance constraint of the air source node is shown in formula (22):
energy station input
The input power balance constraint of the energy station node is shown in the formula (23):
In the method, in the process of the invention, Representing the end active/reactive power of the power supply to the network of energy stations,Representing input electric active/electric reactive/gas power of the energy station node;
energy station output
The output power balance constraint of the energy station node is as shown in formula (24):
In the method, in the process of the invention, Representing the head-end active/reactive power of the energy source station to the load side grid,Representing the output electric active/electric reactive/hot/cold power of the energy station node;
Load input
The input power balance constraint of the load node is shown in formula (25):
In the method, in the process of the invention, Representing the end active/reactive power of the power supply to the load side network,Representing the end active/reactive power of the energy station to the load side grid,/>Representing the head end/tail end power of an energy station to a load side heat/cold network,/>Representing the input electric active/electric reactive/hot/cold/gas power of the load node;
the energy station power balancing constraint includes:
The electric active power, electric reactive power, heat, cold and air power balance constraint of the energy station is shown as a formula (26):
In the method, in the process of the invention, Representing the output reactive power of the energy station PV/WT,/>Representing input/output electrical reactive/output thermal power of energy station CHP,/>Representing the input power of the energy station GB/AC,Representing input active/input reactive power of energy station EH/EC,/>Values representing the energy storage/release active power of the energy station BT/HC/CD interacting with the system,/>A value representing the interaction of the energy storage/release reactive power of the energy station BT with the system;
The load side power balancing constraint includes:
the load side electric active, electric reactive, hot, cold and air power balance constraint is shown as a formula (27):
In the method, in the process of the invention, Representing electric active/electric reactive/heat/cold/gas load power,/>Representing input active/input reactive power of load side EH,/>Input active/input reactive power representing load side ECH;
the energy station device installation capacity constraint includes:
The upper and lower limit constraints of the installation capacity of the energy station equipment are shown in a formula (28):
In the method, in the process of the invention, Indicating whether the energy station is installed with PV/WT/CHP,/>Indicating whether the energy station is installed with GB/EH/EC/AC,/>Indicating whether the energy station installs BT/HC/CD,/>Indicating whether the energy station is PV/WT installed,Indicating whether or not the energy station is equipped with CHP/GB/EH/EC/AC,/>Indicating whether the energy station installs BT/HC/CD,/>Representing minimum/maximum installation capacity of energy station PV/WT,/>Representing the minimum/maximum installation capacity of an energy station CHP,/>Representing minimum/maximum installation capacity of energy station GB/EH/EC/AC,/>Minimum/maximum installation capacity representing the energy station BT/HC/CD;
the load side equipment installation capacity constraint includes:
the load side equipment installation capacity upper and lower limit constraints are as shown in (29):
In the method, in the process of the invention, Indicating whether EH/ECH is installed on load side,/>Indicating whether EH/ECH is installed on load side,/>Representing the minimum/maximum installation capacity of the load side EH/ECH;
the energy network installation capacity constraints include:
the line installation capacity upper and lower limit constraints are as shown in (30):
In the method, in the process of the invention, Indicating whether or not a power/gas source is installed in the network of energy stations,/>Indicating whether or not the power/gas source is installed in the load network,/>Indicating whether or not an energy station is installed to a load electric/heat/cold pipe network,/>Indicating whether or not a power/gas source is installed in the network of energy stations,/>Indicating whether or not the power/gas source is installed in the load network,/>Indicating whether or not an energy station is installed to a load electric/heat/cold pipe network,/>Representing minimum/maximum installation capacity of power/gas source to energy station grid,/>Representing the minimum/maximum installed capacity of the power/air supply to the load side network,Representing minimum/maximum installation capacity of the energy station to the load side power grid/heat supply network/cold network;
The electricity and gas purchase constraint comprises:
the power upper and lower limit constraints of the power supply node and the power supply node are as shown in formula (31):
In the method, in the process of the invention, Representing the minimum/maximum output active/reactive power of the power supply node,Representing the minimum/maximum output power of the air source node;
The energy station equipment operation efficiency constraint comprises:
The energy station equipment operating efficiency constraints are as shown in formula (32):
In the method, in the process of the invention, Representing the power generation efficiency of the energy station CHP,/>Representing the heat-to-power ratio of the energy station CHP,Representing the efficiency of the energy station GB/EH/EC/AC;
the load side equipment operating efficiency constraint includes:
The load side plant operating efficiency constraint is as shown in equation (33):
In the method, in the process of the invention, Indicating the heating/cooling state of the load side ECH,/>Indicating the efficiency of the load side EH,Indicating heating/cooling efficiency of the load side ECH;
the energy station device operation output constraint comprises:
The upper and lower limit constraints of the energy station equipment operation output are shown in a formula (34):
In the method, in the process of the invention, Representing the ratio of the predicted output power of the energy station PV/WT to the installed capacity,/>Representing the ratio of the minimum/maximum output electric power of the energy station CHP to the installed capacity,/>Representing the ratio of the minimum/maximum output power of the energy station GB/EH/EC/AC to the installed capacity;
the load side plant operating force constraint includes:
the load side plant operating force upper and lower limit constraints are as shown in equation (35):
In the method, in the process of the invention, Representing the ratio of the minimum/maximum output power of the load side EH to the installed capacity,A ratio of minimum/maximum output hot/cold power to installed capacity representing the load side ECH;
the energy station device operation power factor constraint comprises:
the energy station device operating power factor constraints are as shown in equation (36):
In the method, in the process of the invention, Representing the power factor of the energy station PV/WT,/>Representing the power factor of an energy station CHP,/>Representing the power factor of an energy station EH/EC,/>Representing the energy storage/discharge power factor of the energy station BT;
the load side equipment operation power factor constraint comprises:
the load side plant operating power factor constraint is as shown in equation (37):
In the method, in the process of the invention, Representing the power factor of load side EH,/>The heating/cooling power factor of the load side ECH;
the energy network operation constraints include:
The power supply to energy station grid operation constraints are shown in equation (38), and the power supply to load and energy station to load grid operation constraints are the same; the operational constraints of the heat, cold and air networks are as shown in equation (39):
In the method, in the process of the invention, Representing the ratio of minimum/maximum transmission power to capacity of a power/air source to energy station network,/>Representing the ratio of minimum/maximum transmission power to capacity of the power/air supply to load side network,Representing the ratio of the minimum/maximum transmission power to the capacity of the energy station to the load side power grid/heat supply network/cold network;
The energy station energy storage device constraints include:
Charge-discharge efficiency constraints
The charge and discharge efficiency constraint of the energy station energy storage device is shown as a formula (40):
In the method, in the process of the invention, Representing energy storage/discharge efficiency of the energy station BT/HC/CD;
Upper and lower limit constraint of charge and discharge power
The upper and lower limit constraint of the charge and discharge power of the energy station energy storage device is shown as a formula (41):
In the method, in the process of the invention, Representing the energy storage/release state of the energy station BT/HC/CD,/>Representing the ratio of the minimum/maximum energy storage/release power of the energy station BT/HC/CD to the installed capacity;
Energy constraint
The energy constraints of the energy station energy storage device are shown in formulas (42) - (43):
In the method, in the process of the invention, Representing the ratio of minimum/maximum energy stored by the energy station BT/HC/CD to installed capacity,/>Representing the energy stored in the energy station BT/HC/CD,/>Indicating the self-loss rate of the energy station BT/HC/CD.
In the step S3 of the process,
The load side equipment operation efficiency constraint, the load side equipment operation power factor constraint and the energy station energy storage equipment constraint are respectively processed by adopting a large M method so as to be equivalently converted into linear constraint;
And the power grid constraint and the air grid constraint are respectively processed by adopting second-order cone relaxation, and finally the constraint in a second-order cone form is obtained.
In the step S4 of the process of the present invention,
Investment cost, operation cost, energy cost and operation limit value are obtained and are used as known quantity to be input into a converted planning model, and a Gurobi or CPLEX solver is adopted to solve the planning model.
A comprehensive energy collaborative planning device for medium and large-scale energy users, comprising:
The architecture module is used for establishing a comprehensive energy system architecture;
the model module is used for establishing a comprehensive energy system station-network collaborative optimization planning model based on the comprehensive energy system architecture;
The conversion module is used for converting the comprehensive energy system station-network collaborative optimization planning model by using a large M method and second order cone relaxation;
and the planning module is used for acquiring the comprehensive energy system parameters, and solving the converted planning model by adopting a solver so as to determine a planning scheme.
According to the invention, the system architecture of the comprehensive energy system, the energy station and the load side is established, the comprehensive energy system station-network collaborative optimization planning model is established, the model is converted into the mixed integer second order cone planning model, and the model is solved, so that collaborative planning of the energy station and the energy network is realized, rationality of a planning scheme is ensured, the advantage of multi-energy complementation of the comprehensive energy system is fully exerted, the energy cost of the system is reduced, and the energy utilization efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of the overall architecture of a comprehensive energy system;
FIG. 2 is a schematic diagram of an energy station architecture;
FIG. 3 is a load side architecture schematic;
FIG. 4 is a graph of the location of nodes in an embodiment;
FIG. 5 is a system topology diagram of a limitation in scenario 4 in an embodiment;
FIG. 6 is an electrical power balance diagram of an energy station in scenario 1 in an embodiment;
FIG. 7 is a thermal power balance diagram of an energy station in scenario 1 according to an embodiment;
FIG. 8 is a graph of the cold power balance of the energy station in scenario 1 according to an embodiment;
FIG. 9 is a graph of output power of a power node in scenario 1 according to an embodiment;
FIG. 10 is an electrical power balance diagram of an energy station in scenario 2 in an embodiment;
FIG. 11 is a thermal power balance diagram of an energy station in scenario 2 in an embodiment;
FIG. 12 is a graph of the cold power balance of an energy station in scenario 2 according to an embodiment;
FIG. 13 is a graph of output power of a power node in scenario 2 according to an embodiment;
FIG. 14 is an electrical power balance diagram of an energy station in scenario 3 in an embodiment;
FIG. 15 is a thermal power balance diagram of an energy station in scenario 3 according to an embodiment;
FIG. 16 is a graph of the cold power balance of an energy station in scenario 3 according to an embodiment;
FIG. 17 is a graph of output power of a power node in scenario 3 according to an embodiment;
FIG. 18 is an electrical power balance diagram of an energy station in scenario 4 in an embodiment;
FIG. 19 is a thermal power balance diagram of an energy station in scenario 4 according to an embodiment;
FIG. 20 is a graph of the cold power balance of the energy stations in scenario 4 according to an embodiment;
FIG. 21 is a graph of output power of a power node in scenario 4 according to an embodiment;
fig. 22 is a flow chart of the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 22, a comprehensive energy collaborative planning method for medium-and large-scale energy users includes the following steps:
s1, building a comprehensive energy system architecture, wherein the comprehensive energy system architecture comprises an overall architecture of a comprehensive energy system, an architecture of an energy station and an architecture of a load side;
S2, based on a comprehensive energy system architecture, combining operation models of all equipment and energy networks of the system, taking relevant constraint conditions into consideration, and establishing a comprehensive energy system station-network collaborative optimization planning model with the minimum total cost of the comprehensive energy system as a target;
S3, processing the comprehensive energy system station-network collaborative optimization planning model established in the step S2, and converting the original mixed integer nonlinear planning model into a mixed integer second order cone planning model by using a large M method and a second order cone relaxation technology so as to directly solve by using a commercial solver;
S4, aiming at the comprehensive energy system station-network collaborative planning model in the mixed integer second order cone form established in the step S3, acquiring system parameters such as investment cost, energy cost, operation limit value and the like, and solving the planning model by adopting commercial solvers such as Gurobi, CPLEX and the like to determine a system planning scheme.
Based on the refined modeling of the energy network and the equipment, the collaborative planning of the energy station and the power, heat supply, refrigeration and gas energy network is researched to break the barrier of independent planning, so as to coordinate the planning of the energy equipment and the energy network and realize the integral optimization of the system.
As shown in fig. 1, in step S1,
The overall architecture of the comprehensive energy system is as follows:
The comprehensive energy system includes four kinds of energy network including power source node, air source node, energy station node and load node, and the nodes are shown in ES, GS, ST, L.
The comprehensive energy system purchases electricity to an external power grid through the power supply node, and purchases natural gas to a gas company through the gas source node. The power supply node and the air supply node can transmit electric energy and natural gas to the energy station and the user through the electric network and the air network, and the energy station can provide three forms of energy of electricity, heat and cold for the user.
As shown in fig. 2, the energy station architecture is:
The energy station adopts a bus structure and comprises an electric bus, a thermal bus, a cold bus and a gas bus, wherein the input energy comprises electric energy and natural gas, and the output energy comprises three energy forms of electricity, heat and cold. The devices inside the energy station comprise renewable energy power generation devices such as PV, WT and the like, energy supply devices such as CHP, GB, EH, EC, AC and energy conversion devices, and energy storage devices such as BT, HC, CD and the like. PV represents photovoltaic power generation, WT represents a fan, CHP represents a cogeneration unit, GB represents a gas boiler, EH represents an electric heating boiler, EC represents an electric refrigerator, AC represents an absorption refrigerator, BT represents a storage battery, HC represents a heat storage tank, and CD represents a cold storage tank.
As shown in fig. 3, the load side architecture is:
The load side adopts a bus type structure, and besides the externally input electric, thermal, cold and gas energy sources, the load side is also provided with distributed energy source equipment such as EH, ECH and the like, so that the energy supply modes are more diversified. EH represents an electric heating boiler, ECH represents an electric air conditioner, EL represents an electric load, HL represents a heat load, CL represents a cooling load, and GL represents a gas load.
Preferably, in step S2, the method for establishing the comprehensive energy system station-network collaborative optimization planning model includes:
In step S2, a comprehensive energy system station-network collaborative optimization planning model is built with the minimum total cost of the system as a target, as shown in formula (1):
F1＝CST,inv+CL,inv+Cnet,inv+CST,om+CL,om+Cgas+Cgrid (1)
Wherein F 1 is the total cost of the system, C ST,inv is the energy station equipment investment cost, C L,inv is the load side equipment investment cost, C net,inv is the energy network investment cost, C ST,om is the energy station equipment operation and maintenance cost, C L,om is the load side equipment operation and maintenance cost, C gas is the gas purchase cost, and C grid is the electricity purchase cost.
The investment cost of the energy station equipment is shown in the formulas (2) - (3):
Wherein N ST represents the number of nodes of the energy station, m represents the interest rate, y represents the service life of equipment, R represents the fund recovery coefficient, Representing the installed capacity of the energy station PV/WT/CHP,/>Representing the installed capacity of the energy station GB/EH/EC/AC,/>Representing the installed capacity of the energy station BT/HC/CD,/>Representing investment cost coefficients of energy stations PV/WT,/>Representing the investment cost coefficient of the energy station CHP/GB/EH/EC/AC,/>Representing the investment cost coefficient of the energy station BT/HC/CD.
The investment cost of the load side equipment is shown as a formula (4):
wherein N L represents the number of load nodes, Representing the installed capacity of the load side EH/ECH,/>Representing the investment cost factor of the load side EH/ECH.
The investment cost of the energy network is shown in the formula (5):
Wherein N ES represents the number of power supply nodes, N GS represents the number of air source nodes, N ST represents the number of energy station nodes, N L represents the number of load nodes, Representing the capacity of a power/gas source to energy station network,/>Representing the capacity of the power/gas source to the load network,/>Representing the capacity of an energy station to a load electric/heat/cold network,/>Representing the length of the power supply to the energy station/the air supply to the energy station pipe network,/>Indicating the length of the power to load/gas to load piping network,Representing the length of the energy station to the load electric/heat/cold pipe network,/>The investment cost coefficient of representing the power supply/air source to the energy station pipe network is 1/2,/>Representing the investment cost factor 1/2 of the power/gas source to load side pipe network,Representing the investment cost factor 1/2 of the energy station to the load side grid/heat/cold.
The operation and maintenance cost of the energy station equipment is shown in the formula (6):
wherein T represents the length of a scheduling period, deltat represents the scheduling time resolution, N ST represents the number of energy station nodes, Representing the output active power of the energy station PV/WT,/>Representing the output electrical active power of the energy station CHP,Representing the output power of the energy station GB/AC,/>Represents the energy storage/discharge power of the energy station BT/HC/CD,Representing the operation and maintenance cost coefficient of the energy station PV/WT,/>Representing the operation and maintenance cost coefficient of the energy station CHP/GB/EH/EC/AC,/>Representing the operation and maintenance cost coefficients of the energy station BT/HC/CD. The scheduling time resolution is 1 hour, i.e., Δt=1.
The operation and maintenance cost of the load side equipment is shown as a formula (7):
wherein N L represents the number of load nodes, Represents the output power of the load side EH,/>Representing the output heat/output cold power of the load side ECH,/>Representing the operation and maintenance cost coefficients of the load side EH/ECH.
The gas purchasing cost is shown as a formula (8):
Wherein N GS represents the number of air source nodes, Representing the output power of the air source node,/>Representing natural gas price/natural gas heating value.
The electricity purchasing cost is shown as a formula (9):
where N ES represents the number of power supply nodes, Representing the output active power of the power supply node,/>Indicating electricity prices.
The constraint conditions of the comprehensive energy system station-network collaborative optimization planning model comprise: grid constraints, heat and cold grid constraints, gas grid constraints, node power balance constraints, energy station power balance constraints, load side power balance constraints, energy station equipment installation capacity constraints, load side equipment installation capacity constraints, energy network installation capacity constraints, electricity purchasing and gas purchasing constraints, energy station equipment operating efficiency constraints, load side equipment operating efficiency constraints, energy station equipment operating output constraints, load side equipment operating output constraints, energy station equipment operating power factor constraints, load side equipment operating power factor constraints, energy network operating constraints, energy station energy storage equipment constraints.
The grid constraints include power flow constraints, upper and lower voltage-current limit constraints,
The tide constraint is shown as a formula (10):
In the method, in the process of the invention, Representing the per unit value of active/reactive power from the power supply to the head end/tail end of the energy station pipe network,/>Representing the per unit value of resistance/reactance of a power supply to an energy station grid,/>Voltage per unit value representing power/energy station/load node,/>Representing the per-unit value of current from the power source to the energy source station/from the power source to the load/energy source station to the load grid.
The upper and lower limit constraints of the voltage and the current are shown in formulas (11) - (12).
In the method, in the process of the invention,Represents the maximum value of the per unit value of the power/energy station/load side voltage,Representing the maximum of the per unit values of power to energy station/power to load/energy station to load grid current.
The heat supply network and the cold network constraint comprise heat energy-flow constraint, heat loss constraint and flow upper and lower limit constraint,
The thermal energy-flow constraints of the hot and cold networks are as shown in formula (13):
In the method, in the process of the invention, Representing the head-end power of an energy station to a load side heat/cold network,/>The flow of the energy station to the load heat supply network/cold network is represented by T s/r,H/C, the water supply/return temperature of the heat supply network/cold network is represented by C, and the specific heat capacity of water is represented by C.
The thermal constraints of the hot and cold networks are as shown in formula (14):
In the method, in the process of the invention, Representing the loss rate of the energy station to the load side hot/cold network.
The upper and lower flow limit constraints of the heat supply network and the cold supply network are shown in a formula (15):
In the method, in the process of the invention, Representing the maximum flow of energy stations to the load heat/cold network.
S223, air net constraint
Flow-pressure constraint
The flow-pressure constraint of the air network is shown in formula (16).
In the method, in the process of the invention,Air pressure representing power/energy station/load node,/>Representing the flow of air source to energy station/load air network,/>Representing the transmission coefficient of the gas source to the energy station/load side.
Flow-power constraint
The flow-pressure constraint of the air network is shown in formula (17).
In the method, in the process of the invention,Representing the power from the source to the source station/load side network.
Flow pressure upper and lower limit constraints
The upper and lower limits of the flow pressure of the air network are shown in formulas (18) - (19).
In the method, in the process of the invention,Air pressure minimum/maximum representing power/energy station/load node,/>Representing the maximum flow of gas source to the energy station/load grid.
S224, node power balance constraint
Power supply output
The output power balance constraints of the power supply nodes are shown in equations (20) - (21).
/>
In the method, in the process of the invention,Representing the output reactive power of the power supply node,/>Representing the active/reactive power of the power supply to the head end of the energy station pipe network.
Air source output
The output power balance constraint of the air source node is shown in equation (22).
Energy station input
The input power balance constraint of the energy station node is shown in formula (23).
In the method, in the process of the invention,Representing the end active/reactive power of the power supply to the network of energy stations,Representing the input electrical active/reactive/gas power of the energy station node.
Energy station output
The output power balance constraint of the energy station node is shown in equation (24).
In the method, in the process of the invention,Representing the head-end active/reactive power of the energy source station to the load side grid,Representing the output electric active/electric reactive/hot/cold power of the energy station node.
Load input
The input power balance constraint of the load node is shown in equation (25).
In the method, in the process of the invention,Representing the end active/reactive power of the power supply to the load side network,Representing the end active/reactive power of the energy station to the load side grid,/>Representing the head end/tail end power of an energy station to a load side heat/cold network,/>Representing the input electrical active/electrical reactive/hot/cold/gas power of the load node.
S225, energy station power balance constraint
The electric active power, electric reactive power, heat, cold and air power balance constraint of the energy station is shown as a formula (26).
In the method, in the process of the invention,Representing the output reactive power of the energy station PV/WT,/>Representing input/output electrical reactive/output thermal power of energy station CHP,/>Representing the input power of the energy station GB/AC,Representing input active/input reactive power of energy station EH/EC,/>Values representing the energy storage/release active power of the energy station BT/HC/CD interacting with the system,/>A value representing the energy storage/release reactive power of the energy station BT interacting with the system.
S226, load side power balance constraint
The load side electric active, electric reactive, hot, cold, and air power balance constraint is shown in formula (27).
In the method, in the process of the invention,Representing electric active/electric reactive/heat/cold/gas load power,/>Representing input active/input reactive power of load side EH,/>Representing the input active/input reactive power of the load side ECH.
S227, energy station equipment installation capacity constraint
The upper and lower limit constraints of the installation capacity of the energy station equipment are shown in the formula (28).
In the method, in the process of the invention,Indicating whether the energy station is installed with PV/WT/CHP (0-1 variable),/>Indicating whether the energy station is installed with GB/EH/EC/AC (0-1 variable)/>Indicating whether the energy station installs BT/HC/CD (0-1 variable),Indicating whether the energy station is PV/WT (constant) installed,/>Indicating whether the energy station is installed with CHP/GB/EH/EC/AC (constant),/>Indicating whether the energy station installs BT/HC/CD (constant)/>Representing minimum/maximum installation capacity of energy station PV/WT,/>Representing the minimum/maximum installation capacity of the energy station CHP,Representing minimum/maximum installation capacity of energy station GB/EH/EC/AC,/>Representing the minimum/maximum installed capacity of the energy station BT/HC/CD.
S228, load side equipment installation capacity constraint
The load side equipment installation capacity upper and lower limit constraint is as shown in formula (29).
In the method, in the process of the invention,Indicating whether EH/ECH (0-1 variable) is installed on the load side,/>Indicating whether the load side is mounted with EH/ECH (constant),/>The minimum/maximum installation capacity of the load side EH/ECH is indicated.
S229, energy network installation capacity constraint
The line installation capacity upper and lower limit constraints are shown in equation (30).
In the method, in the process of the invention,Indicating whether or not a power/gas source is installed (0-1 variable) to the network of energy stations,/>Indicating whether the power/gas source is installed (0-1 variable) to the load network,/>Indicating whether an energy station is installed (0-1 variable) to a load electricity/heat/cold network,/>Indicating whether or not the power/gas source is installed (constant) to the network of energy stations,/>Indicating whether the power/gas source is installed (constant) to the load network,/>Indicating whether the energy station is installed (constant) to the load electrical/thermal/cold network,Representing minimum/maximum installation capacity of power/gas source to energy station grid,/>Representing minimum/maximum installation capacity of power/gas source to load side network of pipes,/>Representing the minimum/maximum installed capacity of the energy station to the load side grid/heat/cold network.
S2210 electricity and gas purchase constraint
The power upper and lower limit constraints of the power supply node and the power supply node are shown in formula (31).
In the method, in the process of the invention,Representing the minimum/maximum output active/reactive power of the power supply node,Representing the minimum/maximum output power of the air source node.
S2211, energy station equipment operation efficiency constraint
The energy station apparatus operating efficiency constraints are shown in equation (32).
In the method, in the process of the invention,Representing the power generation efficiency of the energy station CHP,/>Representing the heat-to-power ratio of the energy station CHP,Representing the efficiency of the energy station GB/EH/EC/AC.
S2212, load side equipment operation efficiency constraint
The load side plant operating efficiency constraint is shown in equation (33).
In the method, in the process of the invention,Indicating the heating/cooling state of the load side ECH,/>Indicating the efficiency of the load side EH,The heating/cooling efficiency of the load side ECH is shown.
S2213, energy station equipment operation output constraint
The upper and lower limit constraints of the power plant operating output are shown in equation (34).
In the method, in the process of the invention,Representing the ratio of the predicted output power of the energy station PV/WT to the installed capacity,/>Representing the ratio of the minimum/maximum output electric power of the energy station CHP to the installed capacity,/>Representing the ratio of the minimum/maximum output power of the energy station GB/EH/EC/AC to the installed capacity.
S2214, load side equipment operation output constraint
The load side plant operating force upper and lower limit constraints are shown in equation (35).
In the method, in the process of the invention,Representing the ratio of the minimum/maximum output power of the load side EH to the installed capacity,The ratio of the minimum/maximum output hot/cold power to the installed capacity of the load side ECH is shown.
S2215, energy station equipment operation power factor constraint
The energy station device operating power factor constraints are shown in equation (36).
In the method, in the process of the invention,Representing the power factor of the energy station PV/WT,/>Representing the power factor of an energy station CHP,/>Representing the power factor of an energy station EH/EC,/>Representing the energy storage/discharge power factor of the energy station BT.
S2216, load side equipment operation power factor constraint
The load side plant operating power factor constraint is shown in equation (37).
In the method, in the process of the invention,Representing the power factor of load side EH,/>The heating/cooling power factor of the load side ECH is shown.
S2217, energy network operation constraint
The grid operation constraints for the power to energy station are shown in equation (38), and the grid operation constraints for the power to load and the energy station to load are the same. The operational constraints of the hot, cold and air networks are shown in equation (39).
/>
In the method, in the process of the invention,Representing the ratio of minimum/maximum transmission power to capacity of a power/air source to energy station network,/>Representing the ratio of minimum/maximum transmission power to capacity of the power/air supply to load side network,Representing the ratio of minimum/maximum transmission power to capacity of the energy station to the load side grid/hot/cold.
S2218, energy station energy storage equipment constraint
Charge-discharge efficiency constraints
The charge and discharge efficiency constraints of the energy storage device of the energy station are shown in formula (40).
In the method, in the process of the invention,Indicating the energy storage/discharge efficiency of the energy station BT/HC/CD.
Upper and lower limit constraint of charge and discharge power
The upper and lower limit constraint of the charge and discharge power of the energy station energy storage equipment is shown in a formula (41).
In the method, in the process of the invention,Representing the energy storage/release state of the energy station BT/HC/CD,/>Representing the ratio of minimum/maximum stored/discharged power to installed capacity of the energy station BT/HC/CD.
Energy constraint
The energy constraints of the energy station energy storage device are shown in equations (42) - (43).
In the method, in the process of the invention,Representing the ratio of minimum/maximum energy stored by the energy station BT/HC/CD to installed capacity,/>Representing the energy stored in the energy station BT/HC/CD,/>Indicating the self-loss rate of the energy station BT/HC/CD.
Preferably, in step S3, the conversion method of the comprehensive energy system station-network collaborative optimization planning model is as follows:
s31, large M method
S311, load side equipment operation efficiency constraint
The term in equation (33) where the 0-1 variable and the continuous variable are multiplied is a nonlinear term, and is processed by a large M method to be equivalently converted into a linear constraint, thereby eliminating the nonlinear term. Taking formula (44) as an example:
this can be equivalently converted into 4 formulas shown in formula (45):
by using the quantitative relation in the text, the linear constraint shown in the formula (46) can be obtained by eliminating the nonlinear term:
Similarly, there are
S312, load side equipment operation power factor constraint
The term in equation (37) where the 0-1 variable and the continuous variable are multiplied is a nonlinear term, and is processed by the large M method to be equivalently converted into a linear constraint, thereby eliminating the nonlinear term. Taking formula (48) as an example:
Order the Substitution into the above formula can be obtained:
this can be equivalently converted into 4 formulas shown in formula (50):
By using the quantitative relation in the text, the nonlinear term is eliminated, and the linear constraint shown in the formula (51) can be obtained:
Similarly, there are
S313, energy station energy storage equipment constraint
The term in which the 0-1 variable and the continuous variable are multiplied in the expression (41) is a nonlinear term, and is processed by a large M method to be equivalently converted into a linear constraint, so that the nonlinear term is eliminated. The constraint after processing is shown in formula (53):
s32, second order Cone relaxation
S321, grid constraint
Since the fourth equation in constraint (10) is nonlinear, U 2 and I 2 are regarded as a whole, and second order cone relaxation is adopted for processing, so that the constraint in the form of a second order cone is finally obtained. Converting the original formula into a whole formula:
the left side of the equation is equivalently transformed, and two sides are multiplied by 4:
Shift and relax:
Conversion to a second order cone form:
Similarly, there are
/>
S322, air net constraint
And (3) processing by adopting second-order cone relaxation due to nonlinearity of the formula (16), and finally obtaining the constraint of the second-order cone form. Square the original equal sign two sides:
Shift and relax:
Conversion to a second order cone form:
Similarly, there are:
Preferably, in step S4, the solution method of the station-network collaborative planning model of the converted hybrid integer second order cone is as follows:
and acquiring system parameters such as investment cost, operation cost, energy cost, operation limit value and the like, inputting the system parameters as known quantities into a planning model, solving the planning model by adopting commercial solvers such as Gurobi, CPLEX and the like to obtain values of decision variables so as to determine a planning scheme of a system energy network and energy equipment, and realizing comprehensive energy system station-network collaborative planning for medium and large energy users.
Wherein the decision variables include both continuous type and 0-1 type, the continuous type decision variables such asEtc., type 0-1 decision variables such as/>Etc.
A comprehensive energy collaborative planning device for medium and large-scale energy users, comprising:
The architecture module is used for establishing a comprehensive energy system architecture;
the model module is used for establishing a comprehensive energy system station-network collaborative optimization planning model based on the comprehensive energy system architecture;
The conversion module is used for converting the comprehensive energy system station-network collaborative optimization planning model by using a large M method and second order cone relaxation;
and the planning module is used for acquiring the comprehensive energy system parameters, and solving the converted planning model by adopting a solver so as to determine a planning scheme.
Examples:
Table 1 is a description of each scene. The system comprises 3 power supply nodes, 1 air source node, 2 energy station nodes and 4 load nodes. The location of each node is shown in fig. 4. The energy networks of scenario 1-3 employ an unrestricted topology, i.e., the network topology is completely determined by the algorithm, without being limited by external factors, while the energy network in scenario 4 employs a restricted topology as shown in fig. 5. The time-of-use electricity prices are used when purchasing electricity from the upper distribution grid, as shown in table 2.
Table 1 scene description
TABLE 2 time-of-use electricity price
Scene 1
The capacity configurations of the energy stations and the load side energy devices are shown in tables 3 and 4, in which all devices except GB, EH, and HC in the energy stations are configured with a certain capacity. Furthermore, the load 1 is not equipped with a distributed energy source device.
TABLE 3 Capacity of energy station apparatus (Unit: kW) in scenario 1
TABLE 4 Capacity of load side Equipment (Unit: kW) in scenario 1
Figures 6-8 show the electrical, thermal, and cold power balance of the energy station. It can be seen that the supply of electrical energy is relatively diverse. More specifically, in addition to renewable energy generation, CHP units play a critical role in the supply of electrical energy, while charging and discharging of BT is important in peak shaving and valley filling. A small amount of power is purchased from an external grid to meet the overall power demand. In terms of thermal energy, it is entirely provided by CHP units, while cold energy is produced primarily by EC and AC.
The output power of the power supply node is shown in fig. 9. Most of the electrical energy is delivered directly to the consumer load, while a small portion is delivered to the energy station. Furthermore, it can be seen that during peak electricity prices, the system purchases only a small amount of electricity at a relatively high price. In such a scenario, the energy utilization efficiency of the entire system is 113.58% (this value is higher than 100% because the efficiency of the energy devices such as EH, ECH, AC is higher than 100%).
Table 5 shows the cost of each part of the system, where the cost of purchasing gas and electricity is the largest proportion. Therefore, reducing the energy consumption and improving the energy utilization efficiency are key to reducing the total cost of the system.
TABLE 5 costs of parts of the system (Unit: yuan) in scenario 1
Scene 2
Tables 6-7 show the capacity configurations of the energy stations and the load side energy devices. Because of the high construction cost of the gas transmission pipeline, the energy station is no longer driven by natural gas. Thus, AC is not deployed either, as the supply of thermal power is reduced. Instead, more distributed energy devices are employed on the user load side, as it is cheaper to generate heating and cooling power locally.
TABLE 6 Capacity of energy station apparatus (Unit: kW) in scenario 2
TABLE 7 Capacity of load side Equipment (Unit: kW) in scenario 2
The power balance of electricity, heat and cold of the energy station is shown in fig. 10 to 12. Compared with scenario 1, the CHP unit is not used in the system, and the energy station purchases more power from the external grid. Without CHP, EH becomes the primary device in the energy station that generates thermal energy. The results also indicate that less power and less heat is provided to the consumer load.
Fig. 13 shows the output power of the power supply node. Unlike scenario 1, the energy station purchases a large amount of power from the power supply node and uses the power as the primary input energy source. In addition, the energy source station provides less power, resulting in an increase in the power purchased by the user load from the power source node.
The cost of the various parts of the system is shown in table 8. Obviously, the gas purchase cost is reduced, and the electricity purchase cost is obviously increased. In addition, the investment cost of the energy network is increased. Thus, the total cost of the system is 26.41% higher than scenario 1.
TABLE 8 costs of parts of the system in scenario 2 (Unit: yuan)
Scene 3
For scenario 3, the energy station and user loaded energy device corresponding capacity configurations are shown in tables 9 and 10. The capacity of the energy devices within the energy station is increased compared to scenario 1. Furthermore, the load side is rarely equipped with distributed energy devices because they are all electric power devices, and the electric power line construction costs are extremely high.
Table 9 Capacity of energy station apparatus (Unit: kW) in scenario 3
Table 10 Capacity of load side Equipment (Unit: kW) in scenario 3
Figures 14-16 show the electrical, thermal, and cold power balance of the energy station. The energy station is driven by natural gas only. In addition, due to the increase in the construction cost of the transmission line, the output power of the energy station decreases, and the amount of heating and cooling power output increases. It can also be seen that the primary source of heating and cooling power in the consumer load is natural gas.
According to the output power of the power supply node shown in fig. 17, almost all the power is directly supplied to the load of the user due to the high construction cost of the power line.
Table 11 shows the cost of the various parts of the system. Compared to scenario 1, the energy network investment cost increases significantly, resulting in a total cost increase of 38.56%.
TABLE 11 cost of parts of the system in scene 3 (Unit: yuan)
Scene 4
Tables 12 and 13 describe the capacity configurations of the energy stations and the user load side energy devices. Compared to scenario 1, the energy station uses more energy devices, and the configuration capacity of the energy devices in the user load is reduced.
Table 12 Capacity of energy station apparatus (Unit: kW) in scenario 4
Table 13 Capacity of load side Equipment (Unit: kW) in scenario 4
/>
The power balance of the energy station is shown in fig. 18-20, where the energy station purchases more power from the external grid than in scenario 1, and the EH provides some of the thermal energy. The power transferred from the energy station to the consumer load increases.
As can be seen from fig. 21, not only the user load, but also the energy station purchases power from the power source node, unlike scenario 1. In addition, the amount of power purchased by the user load from the power supply node increases slightly. The energy utilization efficiency is 92.91%, which is much lower than 113.58% of scheme 1. It can be seen that the loss in the energy transfer process is more due to the limitation of the energy network topology.
Table 14 summarizes the cost of the various parts of the system. The cost of purchasing electricity increases dramatically due to the large energy loss, which results in a 42.32% increase in the overall cost of the system.
Table 14 costs of the parts of the System (Unit: yuan) in scene 4
The results of the examples show that the topology of the energy network plays a decisive role in the overall cost of the system. The maximum cost difference caused by various energy network topologies is 42.32%, and the energy loss can be reduced by the proper topology, so that the energy efficiency is improved from 92.91% to 113.58%. Furthermore, the choice of topology is directly related to the investment costs of the energy network, affecting the way in which energy is supplied to the energy stations. If the energy supply means of the energy station only comprises electricity or natural gas, the total cost will increase by 26.41% and 38.56%, respectively. In summary, the collaborative planning of energy stations and multi-energy networks has profound significance due to their advantages in terms of improving energy utilization efficiency and reducing overall system cost.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
Claims (8)
1. The comprehensive energy collaborative planning method for the medium-and-large-scale energy users is characterized by comprising the following steps of:
S1, building a comprehensive energy system architecture;
S2, establishing a comprehensive energy system station-network collaborative optimization planning model based on a comprehensive energy system architecture;
S3, converting the comprehensive energy system station-network collaborative optimization planning model by using a large M method and second order cone relaxation;
S4, acquiring comprehensive energy system parameters, and solving the converted planning model by adopting a solver to determine a planning scheme;
In step S1, the architecture of the integrated energy system includes an overall architecture of the integrated energy system of the medium-and large-sized energy users, an architecture of the energy station and an architecture of the load side;
The overall architecture of the comprehensive energy system is as follows:
the comprehensive energy system comprises four energy networks of electricity, heat, cold and gas, four types of nodes of a power source node, an air source node, an energy station node and a load node,
The comprehensive energy system purchases electricity to an external power grid through a power supply node, and purchases natural gas to a gas company through a gas source node;
The power supply node and the air source node transmit electric energy and natural gas to the energy station and the user through the power grid and the air network, and the energy station provides three forms of energy of electricity, heat and cold for the user;
The energy station architecture is as follows:
The energy station adopts a bus structure and comprises an electric bus, a thermal bus, a cold bus and a gas bus, wherein the input energy comprises electric energy and natural gas, and the output energy comprises three energy forms of electricity, heat and cold;
the equipment inside the energy station comprises renewable energy power generation equipment, energy supply equipment and energy conversion equipment, and is also provided with energy storage equipment;
the load side architecture is:
The load side adopts a bus structure, and is provided with distributed energy equipment besides the externally input electric, thermal, cold and gas energy sources;
In step S2, a comprehensive energy system station-network collaborative optimization planning model is built with the minimum total cost of the system as a target, as shown in formula (1):
F1＝CST,inv+CL,inv+Cnet,inv+CST,om+CL,om+Cgas+Cgrid (1)
Wherein F 1 is the total cost of the system, C ST,inv is the equipment investment cost of the energy station, C L,inv is the equipment investment cost of the load side, C net,inv is the energy network investment cost, C ST,om is the operation and maintenance cost of the energy station equipment, C L,om is the operation and maintenance cost of the load side equipment, C gas is the gas purchase cost, and C grid is the electricity purchase cost;
The constraint conditions of the comprehensive energy system station-network collaborative optimization planning model comprise: grid constraints, heat and cold network constraints, gas network constraints, node power balance constraints, energy station power balance constraints, load side power balance constraints, energy station equipment installation capacity constraints, load side equipment installation capacity constraints, energy network installation capacity constraints, electricity purchasing and gas purchasing constraints, energy station equipment operation efficiency constraints, load side equipment operation efficiency constraints, energy station equipment operation output constraints, load side equipment operation output constraints, energy station equipment operation power factor constraints, load side equipment operation power factor constraints, energy network operation constraints and energy station energy storage equipment constraints;
The grid constraints include power flow constraints, upper and lower voltage-current limit constraints,
The tide constraint is shown as a formula (10):
In the method, in the process of the invention, Representing the active/reactive power per unit value from the power source to the head/end of the power station network,Representing the per unit value of resistance/reactance of a power supply to an energy station grid,/>Voltage per unit value representing power/energy station/load node,/>Representing the current per unit value of the power supply to the energy station/power supply to the load/energy station to the load grid;
The upper and lower limit constraints of the voltage and the current are shown in formulas (11) - (12):
In the method, in the process of the invention, Represents the maximum value of the per unit value of the power/energy station/load side voltage,Representing the maximum value of the per unit value of the power supply to the energy station/power supply to the load/energy station to the load grid current;
the heat supply network and the cold network constraint comprise heat energy-flow constraint, heat loss constraint and flow upper and lower limit constraint,
The thermal energy-flow constraints of the hot and cold networks are as shown in formula (13):
In the method, in the process of the invention, Representing the head-end power of an energy station to a load side heat/cold network,/>The flow from the energy station to the load heat supply network/cold network is represented by T s/r,H/C, the water supply/return temperature of the heat supply network/cold network is represented by T s/r,H/C, and the specific heat capacity of water is represented by c;
the thermal constraints of the hot and cold networks are as shown in formula (14):
In the method, in the process of the invention, Representing the loss rate from the energy station to the load side heat network/cold network;
the upper and lower flow limit constraints of the heat supply network and the cold supply network are shown in a formula (15):
In the method, in the process of the invention, Representing the maximum flow from the energy station to the load heat/cold network;
the air network constraint comprises:
Flow-pressure constraint
The flow-pressure constraint of the air network is shown in formula (16):
In the method, in the process of the invention, Air pressure representing power/energy station/load node,/>Representing the flow of air source to energy station/load air network,/>Representing the transmission coefficient from the air source to the energy station/load side;
Flow-power constraint
The flow-pressure constraint of the air network is shown in formula (17):
In the method, in the process of the invention, Representing the power from the air source to the energy station/load side pipe network;
Flow pressure upper and lower limit constraints
The upper and lower limit constraints of the flow pressure of the air network are shown in formulas (18) - (19):
In the method, in the process of the invention, Air pressure minimum/maximum representing power/energy station/load node,/>Representing the maximum flow of the air source to the energy station/load air network;
the node power balancing constraint includes:
Power supply output
The output power balance constraints of the power supply nodes are shown in formulas (20) - (21):
In the method, in the process of the invention, Representing the output reactive power of the power supply node,/>Representing the active/reactive power of the power supply to the head end of the energy station pipe network;
Air source output
The output power balance constraint of the air source node is shown in formula (22):
energy station input
The input power balance constraint of the energy station node is shown in the formula (23):
In the method, in the process of the invention, Representing the end active/reactive power of the power supply to the network of energy stations,Representing input electric active/electric reactive/gas power of the energy station node;
energy station output
The output power balance constraint of the energy station node is as shown in formula (24):
In the method, in the process of the invention, Representing the head-end active/reactive power of the energy source station to the load side grid,Representing the output electric active/electric reactive/hot/cold power of the energy station node;
Load input
The input power balance constraint of the load node is shown in formula (25):
In the method, in the process of the invention, Representing the end active/reactive power of the power supply to the load side pipe network,/>Representing the end active/reactive power of the energy station to the load side grid,/>Representing the head end/tail end power of an energy station to a load side heat/cold network,/>Representing the input electric active/electric reactive/hot/cold/gas power of the load node;
the energy station power balancing constraint includes:
The electric active power, electric reactive power, heat, cold and air power balance constraint of the energy station is shown as a formula (26):
In the method, in the process of the invention, Representing the output reactive power of the energy station PV/WT,/>Representing input/output electrical reactive/output thermal power of energy station CHP,/>Representing the input power of the energy station GB/AC,Representing input active/input reactive power of energy station EH/EC,/>Values representing the energy storage/release active power of the energy station BT/HC/CD interacting with the system,/>A value representing the interaction of the energy storage/release reactive power of the energy station BT with the system;
The load side power balancing constraint includes:
the load side electric active, electric reactive, hot, cold and air power balance constraint is shown as a formula (27):
In the method, in the process of the invention, Representing electric active/electric reactive/heat/cold/gas load power,/>Representing input active/input reactive power of load side EH,/>Input active/input reactive power representing load side ECH;
the energy station device installation capacity constraint includes:
The upper and lower limit constraints of the installation capacity of the energy station equipment are shown in a formula (28):
In the method, in the process of the invention, Indicating whether the energy station is installed with PV/WT/CHP,/>Indicating whether the energy station is installed with GB/EH/EC/AC,/>Indicating whether the energy station installs BT/HC/CD,/>Indicating whether the energy station is PV/WT installed,Indicating whether or not the energy station is equipped with CHP/GB/EH/EC/AC,/>Indicating whether the energy station installs BT/HC/CD,/>Representing minimum/maximum installation capacity of energy station PV/WT,/>Representing the minimum/maximum installation capacity of an energy station CHP,/>Representing minimum/maximum installation capacity of energy station GB/EH/EC/AC,/>Minimum/maximum installation capacity representing the energy station BT/HC/CD;
the load side equipment installation capacity constraint includes:
the load side equipment installation capacity upper and lower limit constraints are as shown in (29):
In the method, in the process of the invention, Indicating whether EH/ECH is installed on load side,/>Indicating whether EH/ECH is installed on the load side,Representing the minimum/maximum installation capacity of the load side EH/ECH;
the energy network installation capacity constraints include:
the line installation capacity upper and lower limit constraints are as shown in (30):
In the method, in the process of the invention, Indicating whether or not a power/gas source is installed in the network of energy stations,/>Indicating whether or not the power/gas source is installed in the load network,/>Indicating whether or not an energy station is installed to a load electric/heat/cold pipe network,/>Indicating whether or not a power/gas source is installed in the network of energy stations,/>Indicating whether or not the power/gas source is installed in the load network,/>Indicating whether or not an energy station is installed to a load electric/heat/cold pipe network,/>Representing minimum/maximum installation capacity of power/gas source to energy station grid,/>Representing the minimum/maximum installed capacity of the power/air supply to the load side network,Representing minimum/maximum installation capacity of the energy station to the load side power grid/heat supply network/cold network;
The electricity and gas purchase constraint comprises:
the power upper and lower limit constraints of the power supply node and the power supply node are as shown in formula (31):
In the method, in the process of the invention, Representing the minimum/maximum output active/reactive power of the power supply node,Representing the minimum/maximum output power of the air source node;
The energy station equipment operation efficiency constraint comprises:
The energy station equipment operating efficiency constraints are as shown in formula (32):
In the method, in the process of the invention, Representing the power generation efficiency of the energy station CHP,/>Representing the thermoelectric ratio of the energy station CHP,/>Representing the efficiency of the energy station GB/EH/EC/AC;
the load side equipment operating efficiency constraint includes:
The load side plant operating efficiency constraint is as shown in equation (33):
In the method, in the process of the invention, Indicating the heating/cooling state of the load side ECH,/>Indicating the efficiency of the load side EH,Indicating heating/cooling efficiency of the load side ECH;
the energy station device operation output constraint comprises:
The upper and lower limit constraints of the energy station equipment operation output are shown in a formula (34):
In the method, in the process of the invention, Representing the ratio of the predicted output power of the energy station PV/WT to the installed capacity,/>Representing the ratio of the minimum/maximum output electric power of the energy station CHP to the installed capacity,/>Representing the ratio of the minimum/maximum output power of the energy station GB/EH/EC/AC to the installed capacity;
the load side plant operating force constraint includes:
the load side plant operating force upper and lower limit constraints are as shown in equation (35):
In the method, in the process of the invention, Representing the ratio of the minimum/maximum output power of the load side EH to the installed capacity,A ratio of minimum/maximum output hot/cold power to installed capacity representing the load side ECH;
the energy station device operation power factor constraint comprises:
the energy station device operating power factor constraints are as shown in equation (36):
In the method, in the process of the invention, Representing the power factor of the energy station PV/WT,/>Representing the power factor of an energy station CHP,/>Representing the power factor of an energy station EH/EC,/>Representing the energy storage/discharge power factor of the energy station BT;
the load side equipment operation power factor constraint comprises:
the load side plant operating power factor constraint is as shown in equation (37):
In the method, in the process of the invention, Representing the power factor of load side EH,/>The heating/cooling power factor of the load side ECH;
the energy network operation constraints include:
The power supply to energy station grid operation constraints are shown in equation (38), and the heat, cold and air grid operation constraints are shown in equation (39):
In the method, in the process of the invention, Representing the ratio of minimum/maximum transmission power to capacity of the power/air supply to energy station network,Representing the ratio of minimum/maximum transmission power to capacity of the power/air supply to load side network,Representing the ratio of the minimum/maximum transmission power to the capacity of the energy station to the load side power grid/heat supply network/cold network;
The energy station energy storage device constraints include:
Charge-discharge efficiency constraints
The charge and discharge efficiency constraint of the energy station energy storage device is shown as a formula (40):
In the method, in the process of the invention, Representing energy storage/discharge efficiency of the energy station BT/HC/CD;
Upper and lower limit constraint of charge and discharge power
The upper and lower limit constraint of the charge and discharge power of the energy station energy storage device is shown as a formula (41):
In the method, in the process of the invention, Representing the energy storage/release state of the energy station BT/HC/CD,/>Representing the ratio of the minimum/maximum energy storage/release power of the energy station BT/HC/CD to the installed capacity;
Energy constraint
The energy constraints of the energy station energy storage device are shown in formulas (42) - (43):
In the method, in the process of the invention, Representing the ratio of minimum/maximum energy stored by the energy station BT/HC/CD to installed capacity,Representing the energy stored in the energy station BT/HC/CD,/>The self-loss rate of the energy station BT/HC/CD is represented;
in the step S3 of the process,
The load side equipment operation efficiency constraint, the load side equipment operation power factor constraint and the energy station energy storage equipment constraint are respectively processed by adopting a large M method so as to be equivalently converted into linear constraint;
the power grid constraint and the air grid constraint are respectively processed by adopting second-order cone relaxation, and finally, the constraint in a second-order cone form is obtained;
in the step S4 of the process of the present invention,
Investment cost, operation cost, energy cost and operation limit value are obtained and are used as known quantity to be input into a converted planning model, and a Gurobi or CPLEX solver is adopted to solve the planning model.
2. The comprehensive energy collaborative planning method for medium and large-scale energy users according to claim 1 is characterized in that,
The investment cost of the energy station equipment is shown in the formulas (2) - (3):
Wherein N ST represents the number of nodes of the energy station, m represents the interest rate, y represents the service life of equipment, R represents the fund recovery coefficient, Representing the installed capacity of the energy station PV/WT/CHP,/>Representing the installed capacity of the energy station GB/EH/EC/AC,/>Representing the installed capacity of the energy station BT/HC/CD,/>Representing investment cost coefficients of energy stations PV/WT,/>Representing the investment cost coefficient of the energy station CHP/GB/EH/EC/AC,/>An investment cost coefficient representing the energy station BT/HC/CD;
PV represents photovoltaic power generation, WT represents a fan, CHP represents a cogeneration unit, GB represents a gas boiler, EH represents an electric heating boiler, EC represents an electric refrigerator, AC represents an absorption refrigerator, BT represents a storage battery, HC represents a heat storage tank, and CD represents a cold storage tank.
3. The comprehensive energy collaborative planning method for medium and large-scale energy users according to claim 1 is characterized in that,
The investment cost of the load side equipment is shown as a formula (4):
wherein N L represents the number of load nodes, Representing the installed capacity of the load side EH/ECH,/>The investment cost coefficient of the load side EH/ECH is represented, EH represents an electric heating boiler, and ECH represents an electric air conditioner.
4. The comprehensive energy collaborative planning method for medium and large-scale energy users according to claim 1 is characterized in that,
The investment cost of the energy network is shown in the formula (5):
Wherein N ES represents the number of power supply nodes, N GS represents the number of air source nodes, N ST represents the number of energy station nodes, N L represents the number of load nodes, Representing the capacity of a power/gas source to energy station network,/>Representing the capacity of the power/gas source to the load network,/>Representing the capacity of an energy station to a load electric/heat/cold network,/>Representing the length of the power supply to the energy station/the air supply to the energy station pipe network,/>Representing the length of the power supply to load/air supply to load pipe network,/>Representing the length of the energy station to the load electric/heat/cold pipe network,/>The investment cost coefficient of representing the power supply/air source to the energy station pipe network is 1/2,/>The investment cost coefficient of representing the power supply/air source to the load side pipe network is 1/2,/>The investment cost coefficient of the energy station to the load side power grid/heat supply network/cold network is 1/2;
ES represents a source node, GS represents a source node, ST represents an energy station node, and L represents a load node.
5. The comprehensive energy collaborative planning method for medium and large-scale energy users according to claim 1 is characterized in that,
The operation and maintenance cost of the energy station equipment is shown in the formula (6):
wherein T represents the length of a scheduling period, deltat represents the scheduling time resolution, N ST represents the number of energy station nodes, Representing the output active power of the energy station PV/WT,/>Representing the output electrical active power of the energy station CHP,Representing the output power of the energy station GB/AC,/>Represents the energy storage/discharge power of the energy station BT/HC/CD,Representing the operation and maintenance cost coefficient of the energy station PV/WT,/>Representing the operation and maintenance cost coefficient of the energy station CHP/GB/EH/EC/AC,/>Representing the operation and maintenance cost coefficients of the energy station BT/HC/CD.
6. The comprehensive energy collaborative planning method for medium and large-scale energy users according to claim 1 is characterized in that,
The operation and maintenance cost of the load side equipment is shown as a formula (7):
wherein N L represents the number of load nodes, Represents the output power of the load side EH,/>Representing the output heat/output cold power of the load side ECH,/>Representing the operation and maintenance cost coefficients of the load side EH/ECH.
7. The comprehensive energy collaborative planning method for medium and large-scale energy users according to claim 1 is characterized in that,
The gas purchasing cost is shown as a formula (8):
Wherein N GS represents the number of air source nodes, Representing the output power of the air source node,/>Representing natural gas price/natural gas heating value.
8. The comprehensive energy collaborative planning method for medium and large-scale energy users according to claim 1 is characterized in that,
The electricity purchasing cost is shown as a formula (9):
where N ES represents the number of power supply nodes, Representing the output active power of the power supply node,/>Indicating electricity prices. /(I)
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