A hierarchical optimization method for geothermal public building heating system with heat storage

Abstract

The present invention discloses a hierarchical optimization method for a geothermal public building heating system with heat storage, comprising the following steps: establishing a hierarchical architecture based on a geothermal public building heating system with heat storage, the hierarchical architecture comprising a system planning layer and an operation optimization layer; establishing an upper optimization model and a lower optimization model according to the system planning layer and the operation optimization layer; combining the upper optimization model and the lower optimization model to form a system double-layer optimization model, and using a particle swarm algorithm combined with a mixed integer linear programming method to solve the system double-layer optimization model, and obtaining the system's optimal equipment capacity configuration and corresponding operation strategy. The beneficial effects of the present invention are: fully considering the mutual influence between the system equipment capacity configuration and the operation strategy, taking into account the coordinated optimization of the system investment cost and the operation cost, and effectively improving the system's economy.

Description

Technical Field

[0001] The present invention relates to the technical field of geothermal heating system optimization, and in particular to a hierarchical optimization method for a geothermal public building heating system with heat storage. Background Art

[0002] As a clean, low-carbon, safe and efficient green energy, geothermal energy has broad application prospects. At present, my country's geothermal energy development is mainly based on direct utilization, among which the scale of hydrothermal geothermal heating is accelerating. By the end of 2019, the area of ​​hydrothermal geothermal heating in northern China reached 282 million m 2 , an increase of 176.5% compared to 2015.

[0003] my country's total energy consumption is huge and growing rapidly, of which public buildings account for a large proportion. As a heating target, public buildings do not need or have only a small amount of heating load during the night period. However, the deep well pump of the hydrothermal geothermal heating system is affected by the equipment process and cannot be frequently started and stopped within a heating season, which makes it difficult to match the continuity of the heating source with the intermittent heat load of public buildings, resulting in a large amount of energy loss. The geothermal heating system with heat storage can make full use of my country's time-of-use electricity price policy, reduce the rated operating cost of the system, alleviate the contradiction between heating demand and high costs, and effectively utilize geothermal resources at night to improve the utilization rate of geothermal energy. In addition, the geothermal heating system with heat storage can also achieve a certain degree of "peak shaving and valley filling" effect, reducing the operating pressure of the power grid.

[0004] In the existing literature, the optimization of geothermal heating systems with heat storage is mostly single-objective optimization for system equipment capacity configuration or operation strategy, without considering the impact of system equipment capacity configuration on operation strategy optimization. Similarly, operation strategy optimization will also affect system equipment capacity configuration to a certain extent. The optimization of the two is interdependent and inseparable. It is unreasonable to consider any one of them alone, and it is difficult to ensure the optimal economic efficiency of the system. Summary of the invention

[0005] In view of the above problems, the present invention proposes a hierarchical optimization method for a geothermal public building heating system with heat storage, aiming to solve the problem of coordinated optimization design of equipment capacity configuration and operation strategy of a geothermal heating system with heat storage.

[0006] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0007] A hierarchical optimization method for a geothermal public building heating system with heat storage comprises the following steps: establishing a hierarchical architecture based on a geothermal public building heating system with heat storage, the hierarchical architecture comprising a system planning layer and an operation optimization layer; establishing an upper optimization model and a lower optimization model according to the system planning layer and the operation optimization layer; combining the upper optimization model and the lower optimization model to form a system double-layer optimization model, and using a particle swarm algorithm combined with a mixed integer linear programming method to solve the system double-layer optimization model to obtain the system optimal equipment capacity configuration and the corresponding operation strategy.

[0008] In some preferred embodiments, the upper optimization model takes minimizing the total annual cost of the system as the objective function, and takes the rated installed capacity constraint of all equipment and the maximum storage / release power constraint of the heat storage device as constraints.

[0009] In some preferred embodiments, the lower-level optimization model takes minimizing the annual operating cost of the system as the objective function, and takes thermal power balance constraints, electrical power balance constraints, equipment operation constraints, and fluid network operation constraints as constraints.

[0010] The beneficial effects of the present invention are: fully considering the mutual influence between system equipment capacity configuration and operation strategy, taking into account the coordinated optimization of system investment cost and operation cost, and effectively improving the economy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A schematic flow chart of a hierarchical optimization method for a geothermal public building heating system with heat storage disclosed in an embodiment of the present invention;

[0012] Figure 2 A hierarchical architecture diagram of a geothermal public building heating system with heat storage disclosed in an embodiment of the present invention;

[0013] Figure 3 A simplified flow chart of a geothermal public building heating system with heat storage disclosed in an embodiment of the present invention;

[0014] Figure 4 A flowchart for solving the system double-layer optimization model disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the content of the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It is understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for the convenience of description, only the parts related to the present invention are shown in the accompanying drawings, rather than all the contents.

[0016] This embodiment proposes a hierarchical optimization method for geothermal public building heating systems with heat storage. The system planning layer takes the minimum annual total cost of the system as the optimization goal, combines the optimal operation strategy obtained by the operation optimization layer to solve the system equipment capacity configuration, and outputs the system equipment capacity configuration parameters to the operation optimization layer; the operation optimization layer model takes the minimum annual operation cost of the system as the optimization goal, and solves the system optimal operation strategy according to the system equipment capacity configuration parameters given by the system planning layer model. Through continuous iterative calculation and particle update, the mutual influence between the system equipment capacity configuration and the operation strategy is fully considered, and the coordinated optimization of the system investment cost and the operation cost is taken into account, which can effectively improve the economy of the system.

[0017] like Figure 1 As shown, it includes the following three steps:

[0018] Step 1: Establish a hierarchical architecture of geothermal public building heating system with heat storage, such as Figure 2 As shown, the layered architecture includes the system planning layer and the operation optimization layer.

[0019] In step 1, the system planning layer uses the rated installed capacity of all equipment in the heating system and the maximum storage / release power constraints of the hot water storage tank as constraints. In this embodiment, the rated installed capacity mainly includes the rated flow of the deep well pump, the rated area of ​​the plate heat exchanger, the rated output power of the heat pump and the rated volume of the hot water storage tank. The operation optimization layer is based on the system equipment capacity configuration parameters given by the system planning layer, and uses thermal power balance, electric power balance constraints, equipment operation constraints and fluid network operation constraints as constraints. In this embodiment, the equipment operation constraints mainly include deep well pumps, plate heat exchangers, heat pumps and hot water storage tank operation constraints.

[0020] Step 2: Establish an upper optimization model and a lower optimization model according to the system planning layer and the operation optimization layer;

[0021] In step 2, the establishment of the upper-level optimization model and the lower-level optimization model needs to be combined with the actual system, such as Figure 3 As shown in the figure, a relatively common geothermal public building heating system with heat storage is schematically illustrated. The geothermal water is used as a heat source fluid and then enters the heat pump as a low-temperature heat source after heat exchange through a plate heat exchanger. The secondary water on the heating side is heated up by the plate heat exchanger and the heat pump to heat the public building. When the sum of the output power of the plate heat exchanger and the heat pump is greater than the heat load demand of the public building, the excess heat is stored in the heat storage tank. When it is in a high electricity price period such as peak, peak or parity, the operating frequency of the deep well pump can be reduced, that is, the geothermal water flow rate can be reduced, and the heat storage tank can gradually release heat to supplement the heat load demand of the building, thereby achieving the purpose of making full use of valley electricity and saving operating costs.

[0022] In step 2, the above-mentioned upper-level optimization model takes the minimization of the total annual cost of the system as the objective function, and takes the rated installed capacity constraint of all equipment and the maximum storage / discharge power constraint of the hot water storage tank as constraints.

[0023] The objective function of the upper optimization model is expressed as follows:

[0024]

[0025] In the formula, They are the system's annual investment cost, the system's annual operating cost, and the system's annual maintenance cost.

[0026] It should be noted that for the same parameter in different formulas, its definition is only described when it appears for the first time.

[0027] The expression of the system annual investment cost is as follows:

[0028]

[0029] Where CRF is the investment recovery factor; c pp 、c HX 、c HP and c TES are the unit investment costs of deep well pump, plate heat exchanger, heat pump unit and hot water storage tank respectively; m pp,rated , A HX,rated , Q HP,rated and V TES,rated They are the rated flow of the deep well pump, the rated area of ​​the plate heat exchanger, the rated output power of the heat pump unit and the capacity of the hot water storage tank.

[0030] The expression of the system annual operating cost is as follows:

[0031]

[0032] Where n is the total number of scheduling times; is the electricity purchase price at time t; c geo The unit price of geothermal water resource fee; and They are respectively the electricity purchased from the grid and the geothermal water flow rate at time t.

[0033] The expression for the annual maintenance cost of the system is as follows:

[0034]

[0035] Where η M is the maintenance cost factor.

[0036] The rated installed capacity constraints of all equipment include the rated flow constraint of the deep well pump, the rated area constraint of the plate heat exchanger, the rated output power constraint of the heat pump, and the rated volume constraint of the hot water storage tank. The expressions are as follows:

[0037]

[0038] In the formula, m geo,min and m geo,max are the lower and upper limits of geothermal water flow, respectively, and A HX,min and A HX,max are the lower and upper limits of the plate heat exchanger area, Q HP,min and Q HP,max are the lower and upper limits of the rated power of the heat pump unit, V TES,min and V TES,max They are the lower and upper limits of the hot water storage tank capacity respectively.

[0039] The expression of the maximum storage / discharge power constraint of the hot water storage tank is as follows:

[0040]

[0041] In the formula, Q TES,cha,rated With Q TES,dis,rated are the rated heat storage / release power; Q TES,cha,min With Q TES,cha,max are the lower and upper limits of the heat storage power respectively; Q TES,dis,min With Q TES,dis,max are the lower and upper limits of heat release power respectively.

[0042] The lower-level optimization model takes the minimization of the system's annual operating cost as its objective function, and takes thermal power balance constraints, electrical power balance constraints, equipment operation constraints, and fluid network operation constraints as constraints.

[0043] The expression of the objective function of the lower optimization model is as follows:

[0044]

[0045] Where n is the total number of scheduling times; is the electricity purchase price at time t; c geo The unit price of geothermal water resource fee; and They are respectively the electricity purchased from the grid and the geothermal water flow rate at time t.

[0046] The expression of thermal power balance constraint is as follows:

[0047]

[0048] In the formula, is the output power of the plate heat exchanger at time t; is the heat pump output power at time t; is the heat load at time t; and are the storage / release power of the hot water tank at time t respectively.

[0049] The expression of the electric power balance constraint is as follows:

[0050]

[0051] In the formula, is the power consumption of the deep well pump at time t; is the power consumption of the heat pump at time t.

[0052] Equipment operation constraints include deep well pump operation constraints, plate heat exchanger operation constraints, heat pump operation constraints, and hot water storage tank operation constraints.

[0053] The expression of deep well pump operation constraint is as follows:

[0054]

[0055] In the formula, ff min With ff max They are the minimum and maximum effective operating frequencies of the deep well pump respectively;

[0056] The expressions of the plate heat exchanger operation constraints are as follows:

[0057]

[0058] Where U HX is the total heat transfer coefficient of the plate heat exchanger; is the logarithmic mean temperature difference of the heat exchanger at time t, which is approximated by the arithmetic mean; c p is the specific heat of water; and are the geothermal water temperatures at the inlet and outlet of the heat exchanger at time t respectively; is the secondary water flow rate of the heat exchanger at time t; and are the secondary water temperatures of the heating system at the inlet and outlet of the heat exchanger at time t; ΔT pinch is the pinch point temperature difference.

[0059] The expressions of heat pump operation constraints are as follows:

[0060]

[0061] In the formula, COP t is the heat pump performance coefficient at time t; a and b are the empirical coefficients of the heat pump COP fitting formula; is the heat pump input thermal power at time t; is the secondary water flow rate on the high temperature side of the heat pump at time t; and are the secondary water temperatures at the inlet and outlet of the high temperature side of the heat pump at time t respectively; LF is the geothermal water temperature at the outlet of the low temperature side of the heat pump at time t; min is the minimum load factor of the heat pump; δ HP Indicates the operating status of the heat pump, with a value of 0 or 1.

[0062] The expression of the hot water storage tank operation constraint is as follows:

[0063]

[0064] In the formula, and are the heat storage in the hot water storage tank at time t and t+1 respectively; ρ is the density of water; is the heat storage temperature at time t; Δt is the time step; η cha , η dis and η los are heat storage efficiency, heat release efficiency and heat loss rate respectively; T TES,min With T TES,max are the lower and upper limits of the heat storage temperature respectively; δ cha Indicates the heat storage state, with a value of 0 or 1, δ dis Indicates the heat release state, with a value of 0 or 1, indicating that the hot water storage tank can only store or release heat at the same time.

[0065] The fluid network operation constraint expression is as follows:

[0066]

[0067] In the formula, and They represent the fluid mass flow rates flowing into and out of node i at time t respectively; and Respectively represent the fluid temperature flowing into and out of node i at time t; m i,min With m i,max Respectively represent the lower and upper limits of the fluid mass flow rate at node i; T i,min With T i,max They represent the lower and upper limits of the fluid temperature at node i respectively.

[0068] In step 2, optionally, the bilinear term in the above model is and etc. used McCormick convex envelope method to approximate linearization. Without loss of generality, an auxiliary variable z is introduced, and z = xy, and the upper and lower limits of x and y are x min ≤x≤x max and min ≤y≤ymax , then:

[0069]

[0070] Step three, combine the upper optimization model and the lower optimization model to form a system double-layer optimization model, and use the particle swarm algorithm combined with the mixed integer linear programming method to solve the system double-layer optimization model to obtain the system's optimal equipment capacity configuration and corresponding operation strategy.

[0071] Specifically, the particle swarm algorithm described in step 3 is combined with the mixed integer linear programming method to solve the system two-level optimization model as follows:

[0072] In the upper optimization model, the particle swarm algorithm is used to iteratively optimize the rated installed capacity of the equipment in the geothermal public building heating system with heat storage. The mixed integer linear programming problem in the lower optimization model is optimized by calling the Gurobi solver through the Yalmip toolbox. Finally, the optimal equipment capacity configuration and corresponding operation strategy of the geothermal public building heating system with heat storage are obtained. The solution process is as follows: Figure 4 shown.

[0073] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable ordinary technicians in the field to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made based on the essence of the content of the present invention should be included in the protection scope of the present invention.

Claims

1. A hierarchical optimization method for a geothermal public building heating system with heat storage, characterized in that: The following steps are involved: Establishing a hierarchical architecture of a geothermal public building heating system with heat storage, the hierarchical architecture comprising a system planning layer and an operation optimization layer; An upper optimization model and a lower optimization model are established according to the system planning layer and the operation optimization layer; the lower optimization model takes the minimum annual operation cost of the system as the objective function, and takes thermal power balance constraints, electrical power balance constraints, equipment operation constraints, and fluid network operation constraints as constraints; the fluid network operation constraint expression is as follows: In the formula, and They represent the fluid mass flow rates flowing into and out of node i at time t respectively; and Respectively represent the fluid temperature flowing into and out of node i at time t; m i,min With m i,max They represent the lower and upper limits of the fluid mass flow rate at node i respectively; T i,min With T i,max They represent the lower and upper limits of the fluid temperature at node i respectively; The upper-layer optimization model and the lower-layer optimization model are combined to form a system double-layer optimization model, and the particle swarm algorithm combined with the mixed integer linear programming method is used to solve the system double-layer optimization model to obtain the system optimal equipment capacity configuration and corresponding operation strategy.

2. The hierarchical optimization method for geothermal public building heating system with heat storage according to claim 1, characterized in that: The upper optimization model takes the minimization of the system annual total cost as the objective function, and takes the rated installed capacity constraint of all equipment and the maximum storage / release power constraint of the heat storage device as the constraint conditions.

3. The hierarchical optimization method for geothermal public building heating system with heat storage according to claim 2, characterized in that: The objective function of the upper optimization model is expressed as follows: In the formula, They are the annual investment cost of the system, the annual operation cost of the system, and the annual maintenance cost of the system; The expression of the annual investment cost of the system is as follows: Where CRF is the investment recovery factor; c pp 、c HX 、c HP and c TES are the unit investment costs of deep well pump, plate heat exchanger, heat pump unit and hot water storage tank respectively; m pp,rated , A HX,rated , Q HP,rated and V TES,rated They are the rated flow of the deep well pump, the rated area of ​​the plate heat exchanger, the rated output power of the heat pump unit and the volume of the hot water storage tank; The expression of the annual operating cost of the system is as follows: Where n is the total number of scheduling times; is the electricity purchase price at time t; c geo The unit price of geothermal water resource fee; and They are respectively the power purchased from the grid and the flow rate of geothermal water by the system at time t; The expression of the annual maintenance cost of the system is as follows: Where η M is the maintenance cost factor.

4. The hierarchical optimization method for geothermal public building heating system with heat storage according to claim 3, characterized in that: The rated installed capacity constraints of all the equipment include the rated flow constraint of the deep well pump, the rated area constraint of the plate heat exchanger, the rated output power constraint of the heat pump, and the rated volume constraint of the hot water storage tank, and the expression is as follows: In the formula, m geo,min and m geo,max They are the lower and upper limits of geothermal water flow rate, respectively; A HX,min and A HX,max They are the lower and upper limits of the plate heat exchanger area respectively; Q HP,min and Q HP,max are the lower and upper limits of the rated power of the heat pump unit; V TES,min and V TES,max They are the lower and upper limits of the hot water storage tank volume respectively; The expression of the maximum storage / discharge power constraint of the hot water storage tank is as follows: In the formula, Q TES,cha,rated With Q TES,dis,rated are the rated heat storage / release power; Q TES,cha,min With Q TES,cha,max are the lower and upper limits of the heat storage power respectively; Q TES,dis,min With Q TES,dis,max are the lower and upper limits of heat release power respectively.

5. The hierarchical optimization method for geothermal public building heating system with heat storage according to claim 1, characterized in that: The expression of the objective function of the lower optimization model is as follows: Where n is the total number of scheduling times; is the electricity purchase price at time t; c geo The unit price of geothermal water resource fee; and They are respectively the electricity purchased from the grid and the geothermal water flow rate at time t.

6. The hierarchical optimization method for geothermal public building heating system with heat storage according to claim 5, characterized in that: The expression of the thermal power balance constraint is as follows: In the formula, is the output power of the plate heat exchanger at time t; is the heat pump output power at time t; is the heat load at time t; and are the storage / release power of the hot water tank at time t respectively.

7. The hierarchical optimization method for geothermal public building heating system with heat storage according to claim 6, characterized in that: The expression of the electric power balance constraint is as follows: In the formula, is the power consumption of the deep well pump at time t; is the power consumption of the heat pump at time t.

8. The hierarchical optimization method for geothermal public building heating system with heat storage according to claim 7, characterized in that: The equipment operation constraints include deep well pump operation constraints, plate heat exchanger operation constraints, heat pump operation constraints, and hot water storage tank operation constraints; The expression of the deep well pump operation constraint is as follows: In the formula, ff min With ff max They are the minimum and maximum effective operating frequencies of the deep well pump respectively; The expression of the plate heat exchanger operation constraint is as follows: Where U HX is the total heat transfer coefficient of the plate heat exchanger; is the logarithmic mean temperature difference of the heat exchanger at time t, which is approximated by the arithmetic mean; c p is the specific heat of water; and are the geothermal water temperatures at the inlet and outlet of the heat exchanger at time t respectively; is the secondary water flow rate of the heat exchanger at time t; and are the secondary water temperatures of the heating system at the inlet and outlet of the heat exchanger at time t; ΔT pinch is the pinch point temperature difference; The expression of the heat pump operation constraint is as follows: In the formula, COP t is the heat pump performance coefficient at time t; a and b are the empirical coefficients of the heat pump COP fitting formula; is the heat pump input thermal power at time t; is the secondary water flow rate on the high temperature side of the heat pump at time t; and are the secondary water temperatures at the inlet and outlet of the high temperature side of the heat pump at time t respectively; LF is the geothermal water temperature at the outlet of the low temperature side of the heat pump at time t; min is the minimum load factor of the heat pump; δ HP Indicates the operating status of the heat pump, with a value of 0 or 1; The expression of the hot water storage tank operation constraint is as follows: In the formula, and are the heat storage capacity of the hot water storage tank at time t and t+1 respectively; ρ is the density of water; is the heat storage temperature at time t; Δt is the time step; η cha , η dis and η los are heat storage efficiency, heat release efficiency and heat loss rate respectively; T TES,min With T TES,max are the lower and upper limits of the heat storage temperature respectively; δ cha Indicates the heat storage state, with a value of 0 or 1, δ dis Indicates the heat release state, with a value of 0 or 1, indicating that the hot water storage tank can only store or release heat at the same time.

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