WO2018153138A1 - Dispatch method and apparatus for combined heat and power system - Google Patents

Dispatch method and apparatus for combined heat and power system Download PDF

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WO2018153138A1
WO2018153138A1 PCT/CN2017/114317 CN2017114317W WO2018153138A1 WO 2018153138 A1 WO2018153138 A1 WO 2018153138A1 CN 2017114317 W CN2017114317 W CN 2017114317W WO 2018153138 A1 WO2018153138 A1 WO 2018153138A1
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chp
chs
period
eps
during
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Wenchuan Wu
Boming Zhang
Hongbin Sun
Chenhui Lin
Qinglai Guo
Bin Wang
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Tsinghua University
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    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24DDOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
    • F24D19/00Details
    • F24D19/10Arrangement or mounting of control or safety devices
    • F24D19/1006Arrangement or mounting of control or safety devices for water heating systems
    • F24D19/1009Arrangement or mounting of control or safety devices for water heating systems for central heating
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06Energy or water supply
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for AC mains or AC distribution networks
    • H02J3/38Arrangements for feeding a single network from two or more generators or sources in parallel; Arrangements for feeding already energised networks from additional generators or sources in parallel
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for AC mains or AC distribution networks
    • H02J3/38Arrangements for feeding a single network from two or more generators or sources in parallel; Arrangements for feeding already energised networks from additional generators or sources in parallel
    • H02J3/381Dispersed generators
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for AC mains or AC distribution networks
    • H02J3/38Arrangements for feeding a single network from two or more generators or sources in parallel; Arrangements for feeding already energised networks from additional generators or sources in parallel
    • H02J3/46Controlling the sharing of generated power between the generators, sources or networks
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2101/00Supply or distribution of decentralised, dispersed or local electric power generation
    • H02J2101/20Dispersed power generation using renewable energy sources
    • H02J2101/28Wind energy
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2103/00Details of circuit arrangements for mains or AC distribution networks
    • H02J2103/30Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/70Wind energy
    • Y02E10/76Power conversion electric or electronic aspects
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70Smart grids as climate change mitigation technology in the energy generation sector
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00Climate change mitigation technologies for sector-wide applications
    • Y02P80/10Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
    • Y02P80/15On-site combined power, heat or cool generation or distribution, e.g. combined heat and power [CHP] supply
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Definitions

  • the present disclosure relates to the power system operation technology field, and more particularly, to a dispatch method and a dispatch apparatus for a combined heat and power system.
  • a combined heat and power (CHP for short) system may include electric power systems (EPSs for short) and central heating systems (CHSs for short) .
  • the CHP system may include CHP units, non-CHP thermal units, wind farms and heating boilers.
  • the CHP units are configured to generate electricity for the EPSs and useful heat for the CHSs at the same time.
  • utilization of wind power in the CHP system has encountered a critical problem in winter. For example, the wind resources are abundant but the electricity load is insufficient. More seriously, a significant conflict exists between the CHSs and wind power utilization.
  • CHSs are supplied by the CHP units, and the generation output of a CHP unit is determined solely by the heat load demand.
  • a typical daily residential heat load curve peak occurs at nighttime, which is exactly when the daily curve of wind power peaks. Due to heating supply priority, CHP units must generate a large amount of electricity overnight, and thus wind power generation must be restricted. This conflict between the central heating supply and wind power utilization exists in urban areas with CHSs all over the world.
  • Embodiments of the present disclosure provide a dispatch method for controlling a combined heat and power (CHP for short) system.
  • the CHP system includes CHP units, non-CHP thermal units, wind farms and heating boilers; the CHP units, the non-CHP thermal units and the wind farms form an electric power system (EPS for short) of the CHP system; the CHP units and the heating boilers form a central heating system (CHS for short) of the CHP system; and the EPS and the CHS are isolable.
  • EPS electric power system
  • CHS central heating system
  • the method includes: establishing a combined heat and power dispatch (CHPD for short) model of the CHP system, in which an objective function of the CHPD model is a minimizing function of a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers and constraints of the CHPD model are established based on generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers; solving the CHPD model based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS; and controlling the EPS and the CHS according to the corresponding dispatch parameters respectively.
  • CHPD combined heat and power dispatch
  • Embodiments of the present disclosure provide a dispatch device for controlling a CHP system.
  • the CHP system includes CHP units, non-CHP thermal units, wind farms and heating boilers; the CHP units, the non-CHP thermal units and the wind farms form an EPS of the CHP system; the CHP units and the heating boilers form a CHS of the CHP system; and the EPS and the CHS are isolable.
  • the device includes a processor; and a memory for storing instructions executable by the processor, in which the processor is configured to perform the above dispatch method for controlling a CHP system.
  • Embodiments of the present disclosure provide a non-transitory computer-readable storage medium having stored therein instructions that, when executed by a processor of a computer, causes the computer to perform the above dispatch method for controlling a CHP system.
  • Fig. 1 is a schematic diagram of a combined heat and power (CHP) system according to an exemplary embodiment.
  • CHP combined heat and power
  • Fig. 2 is a flow chart of a dispatch method for a CHP system according to an exemplary embodiment.
  • Fig. 3 is a flow chart of a method for solving a CHPD model according to another exemplary embodiment.
  • Fig. 1 is a schematic diagram of a combined heat and power (CHP for short) system according to an exemplary embodiment.
  • the CHP system includes a non-CHP thermal unit1, a non-CHP thermal unit 2, a wind farm 3, a CHP unit 4, and a heating boiler 5.
  • the non-CHP thermal unit1, the non-CHP thermal unit 2, the wind farm 3 and the CHP unit 4 form an electric power system (EPS for short) of the CHP system.
  • the CHP unit 4 and the heating boiler 5 form a central heating system (CHS for short) of the CHP system.
  • the EPS and the CHS are isolable.
  • Fig. 1 also illustrates loads and first nodes in the EPS, and second nodes and heat exchange stations in the CHS.
  • Fig. 2 is a flow chart of a dispatch method for a CHP system according to an exemplary embodiment. As illustrated in Fig. 2, the method includes followings.
  • a combined heat and power dispatch (CHPD for short) model of the CHP system is established.
  • An objective function of the CHPD model is a minimizing function of a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers and constraints of the CHPD model are established based on generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers.
  • the CHPD model is solved based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS.
  • the EPS and the CHS are controlled respectively according to the corresponding dispatch parameters.
  • the CHPD model of the CHP system is established.
  • the CHPD model includes the objective function and the constraints.
  • the CHPD model is described in detail as follows.
  • the objective function of the CHPD model aims to minimize a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers.
  • the total generation cost is established by a formula of
  • t represents a dispatch time period
  • T represents an index set of dispatch time periods
  • I CHP represents an index set of the CHP units
  • I TU represents an index set of the non-CHP thermal units
  • I WD represents an index set of the wind farms
  • I HB represents an index set of the heating boilers
  • a generation cost function of wind farm i during the period t represents a generation cost function of heating boiler i during the period t.
  • the generation cost function of the CHP unit i during the period t is established by a formula of
  • generation cost coefficients of the CHP unit i represents a power output of the CHP unit i during the period t, and represents a heat output of the CHP unit i during the period t.
  • the generation cost coefficients are characteristic parameters of the CHP unit.
  • the generation cost function of the non-CHP thermal unit i during the period t is established by a formula of
  • generation cost coefficients are characteristic parameters of the non-CHP thermal unit.
  • the generation cost function of the wind farm i during the period t is established by a formula of
  • a penalty coefficient represents an available power output of the wind farm i during the period t and represents a power output of the wind farm i during the period t.
  • a value of the penalty coefficient is determined according to consumption demands of wind power, which is adjusted by a power system dispatching center according to a dispatch feedback result.
  • the generation cost function of the heating boiler i during the period t is established by a formula of
  • the constraints of the CHPD model include constraints of the EPS and constraints of the CHS.
  • the constraints of the EPS include operation constraints of the CHP units, ramping up and down constraints of the CHP units, operation constraints of the non-CHP thermal units, ramping up and down constraints of the non-CHP thermal units, spinning reserve constraints of the non-CHP thermal units, operation constraints of the wind farms, a power balance constraint of the EPS, a line flow limit constraint of the EPS, and a spinning reserve constraint of the EPS.
  • the constraints of the CHS include: constraints between supply/return water temperature differences of nodes and heat outputs, heat output constraints of the heating boilers, supply water temperature constraints at nodes with heat sources connected, constraints between supply/return water temperature differences of nodes and heat exchanges of heat exchange stations, return water temperature constraints of heat exchange stations, and operation constraints of heating networks of the CHS.
  • NE i represents an index set of extreme points of the CHP unit i, represent respectively a power output at extreme point ⁇ of the CHP unit i and a heat output at the extreme point ⁇ of the CHP unit i, and represents a convex combination coefficient of the extreme point ⁇ of the CHP unit i during the period t.
  • the extreme points refer to points formed by heat output limits and power output limits of the CHP units.
  • the power balance constraint of the EPS is denoted by a formula of
  • I LD represents an index set of loads in the EPS and D m
  • t represents a power demand of load m in the EPS during the period t.
  • the line flow limit constraint of the EPS is denoted by a formula of
  • I EPS represents an index set of buses in the EPS
  • SF j-l represents a shift factor for bus l on line j of the EPS
  • L j represents a flow limit of the line j of the EPS
  • I LN represents an index set of lines in the EPS.
  • the spinning reserve constraint of the EPS is denoted by a formula of
  • SRU t represents an upward spinning reserve demand of the EPS during the period t and SRD t represents a downward spinning reserve demand of the EPS during the period t.
  • C represents a specific heat capacity of water
  • C represents a total mass flow rate of water at the node k of the CHS
  • C represents a specific heat capacity of water
  • C represents a total mass flow rate of water at the node k of the CHS
  • represents a mass flow rate of water transferred from node k2 to node k1 in supply pipelines of the CHS represents a mass flow rate of return water transferred from the node k2 to the node k1 in return pipelines of the CHS
  • represents an index set of child nodes of the node k1 in supply pipelines of the CHS represents an index set of child nodes of the node k1 in return pipelines of the CHS
  • the CHPD model is summarized as a following quadratic programming (QP) problem in the matrix form by a formula of:
  • x E represents variables of the EPS
  • the variables of the EPS comprises and and
  • x H represents variables of the CHS
  • the variables of the CHS comprises and
  • C E represents the objective function of the EPS and C H represents the objective function of the CHS.
  • C E refers to and C H refers to
  • a E x E ⁇ b E refers to the constraints of the EPS, which includes all constraints described in (1-2-1) .
  • Each row in A E and b E has one-to-one correspondence with each constraint in the EPS.
  • Each column in A E and b E has one-to-one correspondence with each variable in the EPS.
  • Each element in A E is a coefficient of a variable corresponding to a column where the element is located in a constraint corresponding to a row where the element is located.
  • Elements in each row in b E are inequality constant terms in the constraint corresponding to the elements.
  • a H x H ⁇ b H refers to the constraints of the CHS except the constraints between the supply/return water temperature differences of the nodes and the heat outputs, which includes the constraints described in (1-2-2) except the constraints between the supply/return water temperature differences of the nodes and the heat outputs.
  • Each row in A H and b H has one-to-one correspondence with each constraint in the CHS.
  • Each column in A H and b H has one-to-one correspondence with each variable in the CHS.
  • Each element in A H is a coefficient of a variable corresponding to a column where the element is located in a constraint corresponding to a row where the element is located.
  • Elements in each row in b H are inequality constant terms in the constraint corresponding to the elements.
  • Dx E +Ex H ⁇ f refers to the constraints between the supply/return water temperature differences of the nodes and the heat outputs described in (1-2-2) , i.e. coupling constraints on the EPS and the CHS.
  • Each row in D, E and f has one-to-one correspondence with each constraint in the coupling constraints on the EPS and the CHS.
  • Each row in D has one-to-one correspondence with each variable in the EPS.
  • Each row in E has one-to-one correspondence with each variable in the CHS.
  • Each element in D and E is a coefficient of a variable corresponding to a column where the element is located in a constraint corresponding to a row where the element is located.
  • Elements in each row in f are inequality constant terms in the constraint corresponding to the elements.
  • Fig. 3 is a flow chart of a method for solving a CHPD model according to another exemplary embodiment. As illustrated in Fig. 3, the method includes followings.
  • represents a Lagrange multiplier of a constraint in (3-2) , and represents an objective value of the CHS problem in (3-2) .
  • (3-2-2-3) denoting a Lagrange multiplier of a constraint A H x H ⁇ b H in the relaxed feasibility problem of the CHS problem (3-2-2-2) as and a Lagrange multiplier of a constraint in the relaxed feasibility problem (3-2-2-2) as and calculating and according to a formula of:
  • Embodiments of the present disclosure further provide a dispatch apparatus for controlling a CHP system.
  • the device includes: a processor; and a memory for storing instructions executable by the processor.
  • the processor is configured to perform the above method.
  • Embodiments of the present disclosure further provide a non-transitory computer readable storage medium.
  • the non-transitory computer readable storage medium may include instructions that, when executed by a processor of an apparatus, causes the apparatus to execute the above method.
  • the CHPD model can be established by combining the dispatch model of the EPS and the dispatch model of the CHS.
  • An algorithm for solving the proposed CHPD model is provided based on Benders decomposition.
  • the operator of the EPS and the operator of the CHS can optimize corresponding internal systems independently, and the global optimal solution of the CHPD model can be obtained based on the interactive iteration between the boundary conditions of the EPS and CHS.
  • the provided algorithm for solving the proposed CHPD model may have a good convergence rate and significantly improve an operation flexibility of the CHS.
  • Any process or method described in the flowing diagram or other means may be understood as a module, segment or portion including one or more executable instruction codes of the procedures configured to achieve a certain logic function or process, and the preferred embodiments of the present disclosure include other performances, in which the performance may be achieved in other orders instead of the order shown or discussed, such as in an almost simultaneous way or in an opposite order, which should be appreciated by those having ordinary skills in the art to which embodiments of the present disclosure belong.
  • the logic and/or procedures indicated in the flowing diagram or described in other means herein, such as a constant sequence table of the executable code for performing a logical function, may be implemented in any computer readable storage medium so as to be adopted by the code execution system, the device or the equipment (such a system based on the computer, a system including a processor or other systems fetching codes from the code execution system, the device and the equipment , and executing the codes) or to be combined with the code execution system, the device or the equipment to be used.
  • the computer readable storage medium may include any device including, storing, communicating, propagating or transmitting program so as to be used by the code execution system, the device and the equipment or to be combined with the code execution system, the device or the equipment to be used.
  • the computer readable medium includes specific examples (a non-exhaustive list) : the connecting portion (electronic device) having one or more arrangements of wire, the portable computer disc cartridge (a magnetic device) , the random access memory (RAM) , the read only memory (ROM) , the electrically programmable read only memory (EPROMM or the flash memory) , the optical fiber device and the compact disk read only memory (CDROM) .
  • the computer readable storage medium even may be papers or other proper medium printed with program, as the papers or the proper medium may be optically scanned, then edited, interpreted or treated in other ways if necessary to obtain the program electronically which may be stored in the computer memory.
  • each part of the present disclosure may be implemented by the hardware, software, firmware or the combination thereof.
  • the plurality of procedures or methods may be implemented by the software or hardware stored in the computer memory and executed by the proper code execution system.
  • any one of the following known technologies or the combination thereof may be used, such as discrete logic circuits having logic gates for implementing various logic functions upon an application of one or more data signals, application specific integrated circuits having appropriate logic gates, programmable gate arrays (PGA) , field programmable gate arrays (FPGA) .
  • each functional unit in the present disclosure may be integrated in one progressing module, or each functional unit exists as an independent unit, or two or more functional units may be integrated in one module.
  • the integrated module can be embodied in hardware, or software. If the integrated module is embodied in software and sold or used as an independent product, it can be stored in the computer readable storage medium.
  • the non-transitory computer-readable storage medium may be, but is not limited to, read-only memories, magnetic disks, or optical disks.

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Abstract

A dispatch method and apparatus for controlling a combined heat and power CHP system is disclosed. The CHP system includes CHP units, non-CHP thermal units, wind farms and heating boilers; the CHP units, the non-CHP thermal units and the wind farms form an electric power system EPS of the CHP system; the CHP units and the heating boilers form a central heating system CHS of the CHP system; and the EPS and the CHS are isolable. The method includes: establishing a combined heat and power dispatch CHPD model, an objective function being a minimizing function of a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers; solving the CHPD model based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS; and controlling the EPS and the CHS according to the corresponding dispatch parameters respectively.

Description

DISPATCH METHOD AND APPARATUS FOR COMBINED HEAT AND POWER SYSTEM
CROSS-REFERENCE TO RELATED APPLICATION
This application claims priority to and benefits of Chinese Patent Application No. 201710097510.9, filed with the State Intellectual Property Office of P. R. China on February 22, 2017, the entire contents of which are incorporated herein by reference.
FIELD
The present disclosure relates to the power system operation technology field, and more particularly, to a dispatch method and a dispatch apparatus for a combined heat and power system.
BACKGROUND
A combined heat and power (CHP for short) system may include electric power systems (EPSs for short) and central heating systems (CHSs for short) . For example, the CHP system may include CHP units, non-CHP thermal units, wind farms and heating boilers. The CHP units are configured to generate electricity for the EPSs and useful heat for the CHSs at the same time. However, utilization of wind power in the CHP system has encountered a critical problem in winter. For example, the wind resources are abundant but the electricity load is insufficient. More seriously, a significant conflict exists between the CHSs and wind power utilization. CHSs are supplied by the CHP units, and the generation output of a CHP unit is determined solely by the heat load demand. A typical daily residential heat load curve peak occurs at nighttime, which is exactly when the daily curve of wind power peaks. Due to heating supply priority, CHP units must generate a large amount of electricity overnight, and thus wind power generation must be restricted. This conflict between the central heating supply and wind power utilization exists in urban areas with CHSs all over the world.
SUMMARY
Embodiments of the present disclosure provide a dispatch method for controlling a combined heat and power (CHP for short) system. The CHP system includes CHP units, non-CHP thermal units, wind farms and heating boilers; the CHP units, the non-CHP thermal units and the wind  farms form an electric power system (EPS for short) of the CHP system; the CHP units and the heating boilers form a central heating system (CHS for short) of the CHP system; and the EPS and the CHS are isolable. The method includes: establishing a combined heat and power dispatch (CHPD for short) model of the CHP system, in which an objective function of the CHPD model is a minimizing function of a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers and constraints of the CHPD model are established based on generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers; solving the CHPD model based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS; and controlling the EPS and the CHS according to the corresponding dispatch parameters respectively.
Embodiments of the present disclosure provide a dispatch device for controlling a CHP system. The CHP system includes CHP units, non-CHP thermal units, wind farms and heating boilers; the CHP units, the non-CHP thermal units and the wind farms form an EPS of the CHP system; the CHP units and the heating boilers form a CHS of the CHP system; and the EPS and the CHS are isolable. The device includes a processor; and a memory for storing instructions executable by the processor, in which the processor is configured to perform the above dispatch method for controlling a CHP system.
Embodiments of the present disclosure provide a non-transitory computer-readable storage medium having stored therein instructions that, when executed by a processor of a computer, causes the computer to perform the above dispatch method for controlling a CHP system.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
In order to explicitly illustrate embodiments of the present disclosure, a brief introduction for the accompanying drawings corresponding to the embodiments will be listed as follows. Apparently, the drawings described below are only corresponding to some embodiments of the present disclosure, and those skilled in the art may obtain other drawings according to these drawings without creative labor.
Fig. 1 is a schematic diagram of a combined heat and power (CHP) system according to an exemplary embodiment.
Fig. 2 is a flow chart of a dispatch method for a CHP system according to an exemplary embodiment.
Fig. 3 is a flow chart of a method for solving a CHPD model according to another exemplary embodiment.
DETAILED DESCRIPTION
In order to make objectives, technical solutions and advantages of the present disclosure clearer, in the following the present disclosure will be described in detail with reference to drawings. Apparently, the described embodiments are only some embodiments of the present disclosure and do not represent all the embodiments. Based on the embodiment described herein, all the other embodiments obtained by those skilled in the art without creative labor belong to the protection scope of the present disclosure.
Fig. 1 is a schematic diagram of a combined heat and power (CHP for short) system according to an exemplary embodiment. As illustrated in Fig. 1, the CHP system includes a non-CHP thermal unit1, a non-CHP thermal unit 2, a wind farm 3, a CHP unit 4, and a heating boiler 5. The non-CHP thermal unit1, the non-CHP thermal unit 2, the wind farm 3 and the CHP unit 4 form an electric power system (EPS for short) of the CHP system. The CHP unit 4 and the heating boiler 5 form a central heating system (CHS for short) of the CHP system. The EPS and the CHS are isolable. In addition, Fig. 1 also illustrates loads and first nodes in the EPS, and second nodes and heat exchange stations in the CHS.
Fig. 2 is a flow chart of a dispatch method for a CHP system according to an exemplary embodiment. As illustrated in Fig. 2, the method includes followings.
At block 10, a combined heat and power dispatch (CHPD for short) model of the CHP system is established. An objective function of the CHPD model is a minimizing function of a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers and constraints of the CHPD model are established based on generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers.
At block 20, the CHPD model is solved based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS.
At block 30, the EPS and the CHS are controlled respectively according to the corresponding dispatch parameters.
In the following, the dispatch method will be described in detail.
(1) The CHPD model of the CHP system is established. The CHPD model includes the objective function and the constraints. The CHPD model is described in detail as follows.
(1-1) The objective function of the CHPD model
The objective function of the CHPD model aims to minimize a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers. The total generation cost is established by a formula of
Figure PCTCN2017114317-appb-000001
where, t represents a dispatch time period, T represents an index set of dispatch time periods, ICHP represents an index set of the CHP units, ITU represents an index set of the non-CHP thermal units, IWD represents an index set of the wind farms, IHB represents an index set of the heating boilers, 
Figure PCTCN2017114317-appb-000002
represents a generation cost function of CHP unit i during period t, 
Figure PCTCN2017114317-appb-000003
represents a generation cost function of non-CHP thermal unit i during the period t, 
Figure PCTCN2017114317-appb-000004
represents a generation cost function of wind farm i during the period t, and
Figure PCTCN2017114317-appb-000005
represents a generation cost function of heating boiler i during the period t.
The generation cost function of the CHP unit i during the period t is established by a formula of
Figure PCTCN2017114317-appb-000006
where, 
Figure PCTCN2017114317-appb-000007
and
Figure PCTCN2017114317-appb-000008
represent generation cost coefficients of the CHP unit i, 
Figure PCTCN2017114317-appb-000009
represents a power output of the CHP unit i during the period t, and
Figure PCTCN2017114317-appb-000010
represents a heat output of the CHP unit i during the period t. The generation cost coefficients are characteristic parameters of the CHP unit.
The generation cost function of the non-CHP thermal unit i during the period t is established by a formula of
Figure PCTCN2017114317-appb-000011
where, 
Figure PCTCN2017114317-appb-000012
and
Figure PCTCN2017114317-appb-000013
represent generation cost coefficients of the non-CHP thermal unit i, and
Figure PCTCN2017114317-appb-000014
represents a power output of the non-CHP thermal unit i during the period t. Similarly, the generation cost coefficients are characteristic parameters of the non-CHP thermal unit.
The generation cost function of the wind farm i during the period t is established by a formula of
Figure PCTCN2017114317-appb-000015
where, 
Figure PCTCN2017114317-appb-000016
represents a penalty coefficient, 
Figure PCTCN2017114317-appb-000017
represents an available power output of the wind farm i during the period t and
Figure PCTCN2017114317-appb-000018
represents a power output of the wind farm i during the period t. A value of the penalty coefficient is determined according to consumption demands of wind power, which is adjusted by a power system dispatching center according to a dispatch feedback result.
The generation cost function of the heating boiler i during the period t is established by a formula of
Figure PCTCN2017114317-appb-000019
where, 
Figure PCTCN2017114317-appb-000020
represents a generation cost coefficient of the heating boiler i, which is a characteristic parameter of the heating boiler i, and
Figure PCTCN2017114317-appb-000021
represents a heat output of the wind farm i during the period t.
(1-2) The constraints of the CHPD model
The constraints of the CHPD model include constraints of the EPS and constraints of the CHS.
The constraints of the EPS include operation constraints of the CHP units, ramping up and down constraints of the CHP units, operation constraints of the non-CHP thermal units, ramping up and down constraints of the non-CHP thermal units, spinning reserve constraints of the non-CHP thermal units, operation constraints of the wind farms, a power balance constraint of the EPS, a line flow limit constraint of the EPS, and a spinning reserve constraint of the EPS.
The constraints of the CHS include: constraints between supply/return water temperature differences of nodes and heat outputs, heat output constraints of the heating boilers, supply water temperature constraints at nodes with heat sources connected, constraints between supply/return water temperature differences of nodes and heat exchanges of heat exchange stations, return water temperature constraints of heat exchange stations, and operation constraints of heating networks of the CHS.
(1-2-1) The constraints of the EPS.
The operation constraints of the CHP units are denoted by a formula of
Figure PCTCN2017114317-appb-000022
Figure PCTCN2017114317-appb-000023
where, NEi represents an index set of extreme points of the CHP unit i, 
Figure PCTCN2017114317-appb-000024
represent respectively a power output at extreme point γ of the CHP unit i and a heat output at the extreme point γ of the CHP unit i, and
Figure PCTCN2017114317-appb-000025
represents a convex combination coefficient of the extreme point γ of the CHP unit i during the period t. The extreme points refer to points formed by heat output limits and power output limits of the CHP units.
The ramping up and down constraints of the CHP units are denoted by a formula of
Figure PCTCN2017114317-appb-000026
where, 
Figure PCTCN2017114317-appb-000027
represents an upward ramp rate of the CHP unit i, 
Figure PCTCN2017114317-appb-000028
represents a downward ramp rate of the CHP unit i, 
Figure PCTCN2017114317-appb-000029
represents a power output of the CHP unit i during period t+1, and ΔT represents a dispatch interval.
The operation constraints of the non-CHP thermal units are denoted by a formula of
Figure PCTCN2017114317-appb-000030
where, 
Figure PCTCN2017114317-appb-000031
represents an upper output bound of the non-CHP thermal unit i, and
Figure PCTCN2017114317-appb-000032
represents a lower output bound of the non-CHP thermal unit i.
The ramping up and down constraints of the non-CHP thermal units are denoted by a formula of
Figure PCTCN2017114317-appb-000033
where, 
Figure PCTCN2017114317-appb-000034
represents an upward ramp rate of the non-CHP thermal unit i, 
Figure PCTCN2017114317-appb-000035
represents a downward ramp rate of the non-CHP thermal unit i, and
Figure PCTCN2017114317-appb-000036
represents a power output of the non-CHP thermal unit i during period t+1.
The spinning reserve constraints of the non-CHP thermal units are denoted by a formula of
Figure PCTCN2017114317-appb-000037
Figure PCTCN2017114317-appb-000038
where, 
Figure PCTCN2017114317-appb-000039
represents an upward spinning reserve contribution of the non-CHP thermal unit i during the period t, and
Figure PCTCN2017114317-appb-000040
represents a downward spinning reserve contribution of the non-CHP thermal unit i during the period t.
The operation constraints of the wind farms are denoted by a formula of
Figure PCTCN2017114317-appb-000041
where, 
Figure PCTCN2017114317-appb-000042
represents a power output of the wind farm i during the period t, and
Figure PCTCN2017114317-appb-000043
represents an available power output of the wind farm i during the period t.
The power balance constraint of the EPS is denoted by a formula of
Figure PCTCN2017114317-appb-000044
where, ILD represents an index set of loads in the EPS and Dm, t represents a power demand of load m in the EPS during the period t.
The line flow limit constraint of the EPS is denoted by a formula of
Figure PCTCN2017114317-appb-000045
where, IEPS represents an index set of buses in the EPS, SFj-l represents a shift factor for bus l on line j of the EPS, 
Figure PCTCN2017114317-appb-000046
represents an index set of CHP units connected to the bus l of the EPS, 
Figure PCTCN2017114317-appb-000047
represents an index set of non-CHP thermal units connected to the bus l of the EPS, 
Figure PCTCN2017114317-appb-000048
represents an index set of wind farms connected to the bus l of the EPS, 
Figure PCTCN2017114317-appb-000049
represents an index set of loads connected to the bus l of the EPS, Lj represents a flow limit of the line j of the EPS, and ILN represents an index set of lines in the EPS.
The spinning reserve constraint of the EPS is denoted by a formula of
Figure PCTCN2017114317-appb-000050
where, SRUt represents an upward spinning reserve demand of the EPS during the period t and SRDt represents a downward spinning reserve demand of the EPS during the period t.
(1-2-2) The constraints of the CHS
(1-2-2-1) Heating constraints of heat sources of the CHP units and the heating boilers
The constraints between the supply/return water temperature differences of the nodes and the heat outputs are denoted by a formula of
Figure PCTCN2017114317-appb-000051
where, 
Figure PCTCN2017114317-appb-000052
represents an index set of CHP units connected to node k of the CHS, 
Figure PCTCN2017114317-appb-000053
represents an index set of heating boilers connected to the node k of the CHS, C represents a specific heat capacity of water, 
Figure PCTCN2017114317-appb-000054
represents a total mass flow rate of water at the node k of the CHS, 
Figure PCTCN2017114317-appb-000055
represents a water temperature of the node k in supply pipelines of the CHS during the period t, 
Figure PCTCN2017114317-appb-000056
represents a water temperature of the node k in return pipelines of the CHS during the period t, and
Figure PCTCN2017114317-appb-000057
represents an index set of nodes with heat sources connected  in the CHS.
The heat output constraints of the heating boilers are denoted by a formula of
Figure PCTCN2017114317-appb-000058
where, 
Figure PCTCN2017114317-appb-000059
represents an upper heat output bound of the heating boiler i.
The supply water temperature constraints at the nodes with heat sources connected are denoted by a formula of
Figure PCTCN2017114317-appb-000060
where, 
Figure PCTCN2017114317-appb-000061
represents an upper bound of the water temperature at the node k in the supply pipelines of the CHS and
Figure PCTCN2017114317-appb-000062
represents a lower bound of the water temperature at the node k in the supply pipelines of the CHS.
(1-2-2-2) Operation constraints of the heat exchange stations
The constraints between the supply/return water temperature differences of the nodes and the heat exchanges of the heat exchange stations in the CHS are denoted by a formula of
Figure PCTCN2017114317-appb-000063
where, 
Figure PCTCN2017114317-appb-000064
represents an index set of heat exchange stations connected to node k of the CHS, 
Figure PCTCN2017114317-appb-000065
represents a heat exchange of heat exchange station n during the period t, C represents a specific heat capacity of water, 
Figure PCTCN2017114317-appb-000066
represents a total mass flow rate of water at the node k of the CHS, and
Figure PCTCN2017114317-appb-000067
represents an index set of nodes with heat exchange stations connected in the CHS.
The return water temperature constraints of the heat exchange stations are denoted by a formula of
Figure PCTCN2017114317-appb-000068
where, 
Figure PCTCN2017114317-appb-000069
represents an upper bound of the water temperature at the node k in the return pipelines of the CHS and
Figure PCTCN2017114317-appb-000070
represents a lower bound of the water temperature at the node k in the return pipelines of the CHS.
(1-2-2-3) Operation constraints of heating networks
The operation constraints of the heating networks of the CHS are denoted by a formula of
Figure PCTCN2017114317-appb-000071
Figure PCTCN2017114317-appb-000072
where, 
Figure PCTCN2017114317-appb-000073
represents a mass flow rate of water transferred from node k2 to node k1 in supply pipelines of the CHS, 
Figure PCTCN2017114317-appb-000074
represents a mass flow rate of return water transferred from the node k2 to the node k1 in return pipelines of the CHS, 
Figure PCTCN2017114317-appb-000075
represents an index set of child nodes of the node k1 in supply pipelines of the CHS, 
Figure PCTCN2017114317-appb-000076
represents an index set of child nodes of the node k1 in return pipelines of the CHS, 
Figure PCTCN2017114317-appb-000077
represents an ambient temperature during the period t, 
Figure PCTCN2017114317-appb-000078
represents a heat transfer factor of water transferred from the node k2 to the node k1 in supply pipelines of the CHS, 
Figure PCTCN2017114317-appb-000079
represents a heat transfer factor of water transferred from the node k2 to the node k1 in return pipelines of the CHS.
Figure PCTCN2017114317-appb-000080
and
Figure PCTCN2017114317-appb-000081
are calculated by a formula of
Figure PCTCN2017114317-appb-000082
Figure PCTCN2017114317-appb-000083
where, 
Figure PCTCN2017114317-appb-000084
represents a heat transfer coefficient per unit length of pipeline from the node k2 to the node k1 in the supply pipelines of the CHS, 
Figure PCTCN2017114317-appb-000085
represents a heat transfer coefficient per unit length of pipeline from the node k2 to the node k1 in the return pipelines of the CHS, 
Figure PCTCN2017114317-appb-000086
represents a length of the supply pipeline from the node k2 to the node k1, 
Figure PCTCN2017114317-appb-000087
represents a length of the return pipeline from the node k2 to the node k1.
Figure PCTCN2017114317-appb-000088
and
Figure PCTCN2017114317-appb-000089
are intermediate variables representing temperature of the node k1 and only considering a transfer delay of water from its child node k2, wherein
Figure PCTCN2017114317-appb-000090
and 
Figure PCTCN2017114317-appb-000091
are denoted by a formula of
Figure PCTCN2017114317-appb-000092
Figure PCTCN2017114317-appb-000093
where, 
Figure PCTCN2017114317-appb-000094
represents transfer time periods of water from the node k2 to the node k1 in supply pipelines of the CHS, 
Figure PCTCN2017114317-appb-000095
represents transfer time periods of water from the node k2 to the node k1 in return pipelines of the CHS, and
Figure PCTCN2017114317-appb-000096
represents a rounding down operator.
(2) The CHPD model established in (1) is transformed into a model in a matrix form.
In detail, the CHPD model is summarized as a following quadratic programming (QP) problem in the matrix form by a formula of:
Figure PCTCN2017114317-appb-000097
where, xE represents variables of the EPS, and the variables of the EPS comprises
Figure PCTCN2017114317-appb-000098
Figure PCTCN2017114317-appb-000099
and
Figure PCTCN2017114317-appb-000100
and xH represents variables of the CHS, and the variables of the CHS comprises
Figure PCTCN2017114317-appb-000101
and
Figure PCTCN2017114317-appb-000102
CE represents the objective function of the EPS and CH represents the objective function of the CHS. CE refers to
Figure PCTCN2017114317-appb-000103
and CH refers to
Figure PCTCN2017114317-appb-000104
AExE≤bE refers to the constraints of the EPS, which includes all constraints described in (1-2-1) . Each row in AE and bE has one-to-one correspondence with each constraint in the EPS. Each column in AE and bE has one-to-one correspondence with each variable in the EPS. Each element in AE is a coefficient of a variable corresponding to a column where the element is located in a constraint corresponding to a row where the element is located. Elements in each row in bE are inequality constant terms in the constraint corresponding to the elements.
AHxH≤bH refers to the constraints of the CHS except the constraints between the supply/return water temperature differences of the nodes and the heat outputs, which includes the constraints described in (1-2-2) except the constraints between the supply/return water temperature differences of the nodes and the heat outputs. Each row in AH and bH has one-to-one correspondence with each constraint in the CHS. Each column in AH and bH has one-to-one correspondence with each variable in the CHS. Each element in AH is a coefficient of a variable corresponding to a column where the element is located in a constraint corresponding to a row where the element is located. Elements in each row in bH are inequality constant terms in the constraint corresponding to the elements.
DxE+ExH≤f refers to the constraints between the supply/return water temperature differences of the nodes and the heat outputs described in (1-2-2) , i.e. coupling constraints on the EPS and the CHS. Each row in D, E and f has one-to-one correspondence with each constraint in the coupling constraints on the EPS and the CHS. Each row in D has one-to-one correspondence with each variable in the EPS. Each row in E has one-to-one correspondence with each variable in the CHS. Each element in D and E is a coefficient of a variable corresponding to a column where the element is located in a constraint corresponding to a row  where the element is located. Elements in each row in f are inequality constant terms in the constraint corresponding to the elements.
(3) The CHPD model in the matrix form described in (2) is solved by the Benders decomposition.
Fig. 3 is a flow chart of a method for solving a CHPD model according to another exemplary embodiment. As illustrated in Fig. 3, the method includes followings.
(3-1) Initializing: an iteration number m is initialized as 0, the number of optimal cuts p is initialized as 0 and the number of feasible cuts q is initialized as 0. Then an EPS problem is solved to obtain a solution as
Figure PCTCN2017114317-appb-000105
by a formula of
Figure PCTCN2017114317-appb-000106
(3-2) A CHS problem is solved according to the solution
Figure PCTCN2017114317-appb-000107
by a formula of
Figure PCTCN2017114317-appb-000108
(3-2-1) If the CHS problem in (3-2) is feasible, p is increased by 1 and an optimal cut is generated as follows,
Figure PCTCN2017114317-appb-000109
where, 
Figure PCTCN2017114317-appb-000110
and λ represents a Lagrange multiplier of a constraint
Figure PCTCN2017114317-appb-000111
in (3-2) , and
Figure PCTCN2017114317-appb-000112
represents an objective value of the CHS problem in (3-2) .
(3-2-2) If the CHS problem in (3-2) is infeasible, q is increased by 1 and an feasible cut is generated as follows,
Figure PCTCN2017114317-appb-000113
Figure PCTCN2017114317-appb-000114
and
Figure PCTCN2017114317-appb-000115
are calculated according to following acts:
(3-2-2-1) denoting a feasibility problem of the CHS problem as a formula of:
Figure PCTCN2017114317-appb-000116
(3-2-2-2) introducing a relaxation term ε to relax the feasibility problem of the CHS problem in (3-2-2-1) as a formula of:
Figure PCTCN2017114317-appb-000117
(3-2-2-3) denoting a Lagrange multiplier of a constraint AHxH≤bH in the relaxed feasibility problem of the CHS problem (3-2-2-2) as
Figure PCTCN2017114317-appb-000118
and a Lagrange multiplier of a constraint 
Figure PCTCN2017114317-appb-000119
in the relaxed feasibility problem (3-2-2-2) as
Figure PCTCN2017114317-appb-000120
and calculating
Figure PCTCN2017114317-appb-000121
and
Figure PCTCN2017114317-appb-000122
according to a formula of:
Figure PCTCN2017114317-appb-000123
(3-3) The EPS problem is solved by a formula of
Figure PCTCN2017114317-appb-000124
the iteration number m is increased by 1 and a solution is denoted as
Figure PCTCN2017114317-appb-000125
(3-4) A convergence is checked. 
Figure PCTCN2017114317-appb-000126
the iteration is terminated to obtain the dispatch parameters for the EPS and the CHS according to the solution, in which Δ is a convergence threshold, for example, a value of Δ is 0.001, and then (3-5) is executed; and 
Figure PCTCN2017114317-appb-000127
(3-2) is returned.
(3-5) The obtained solution is used as the dispatch parameters for the EPS and the CHS.
Embodiments of the present disclosure further provide a dispatch apparatus for controlling a CHP system. The device includes: a processor; and a memory for storing instructions executable by the processor. The processor is configured to perform the above method.
Embodiments of the present disclosure further provide a non-transitory computer readable storage medium. The non-transitory computer readable storage medium according to embodiments of the present disclosure may include instructions that, when executed by a processor of an apparatus, causes the apparatus to execute the above method.
The technical solutions provided by embodiments of the present disclosure have following advantageous effects.
In the technical solutions of the present disclosure, the CHPD model can be established by combining the dispatch model of the EPS and the dispatch model of the CHS. An algorithm for  solving the proposed CHPD model is provided based on Benders decomposition. In the provided algorithm for solving the proposed CHPD model, the operator of the EPS and the operator of the CHS can optimize corresponding internal systems independently, and the global optimal solution of the CHPD model can be obtained based on the interactive iteration between the boundary conditions of the EPS and CHS. The provided algorithm for solving the proposed CHPD model may have a good convergence rate and significantly improve an operation flexibility of the CHS.
Any process or method described in the flowing diagram or other means may be understood as a module, segment or portion including one or more executable instruction codes of the procedures configured to achieve a certain logic function or process, and the preferred embodiments of the present disclosure include other performances, in which the performance may be achieved in other orders instead of the order shown or discussed, such as in an almost simultaneous way or in an opposite order, which should be appreciated by those having ordinary skills in the art to which embodiments of the present disclosure belong.
The logic and/or procedures indicated in the flowing diagram or described in other means herein, such as a constant sequence table of the executable code for performing a logical function, may be implemented in any computer readable storage medium so as to be adopted by the code execution system, the device or the equipment (such a system based on the computer, a system including a processor or other systems fetching codes from the code execution system, the device and the equipment , and executing the codes) or to be combined with the code execution system, the device or the equipment to be used. With respect to the description of the present invention, “the computer readable storage medium” may include any device including, storing, communicating, propagating or transmitting program so as to be used by the code execution system, the device and the equipment or to be combined with the code execution system, the device or the equipment to be used. The computer readable medium includes specific examples (a non-exhaustive list) : the connecting portion (electronic device) having one or more arrangements of wire, the portable computer disc cartridge (a magnetic device) , the random access memory (RAM) , the read only memory (ROM) , the electrically programmable read only memory (EPROMM or the flash memory) , the optical fiber device and the compact disk read only memory (CDROM) . In addition, the computer readable storage medium even may be papers or other proper medium printed with program, as the papers or the proper medium may be optically scanned, then edited, interpreted or treated in other ways if necessary to obtain the program electronically which  may be stored in the computer memory.
It should be understood that, each part of the present disclosure may be implemented by the hardware, software, firmware or the combination thereof. In the above embodiments of the present invention, the plurality of procedures or methods may be implemented by the software or hardware stored in the computer memory and executed by the proper code execution system. For example, if the plurality of procedures or methods is to be implemented by the hardware, like in another embodiment of the present invention, any one of the following known technologies or the combination thereof may be used, such as discrete logic circuits having logic gates for implementing various logic functions upon an application of one or more data signals, application specific integrated circuits having appropriate logic gates, programmable gate arrays (PGA) , field programmable gate arrays (FPGA) .
It can be understood by those having the ordinary skills in the related art that all or part of the steps in the method of the above embodiments can be implemented by instructing related hardware via programs, the program may be stored in a computer readable storage medium, and the program includes one step or combinations of the steps of the method when the program is executed.
In addition, each functional unit in the present disclosure may be integrated in one progressing module, or each functional unit exists as an independent unit, or two or more functional units may be integrated in one module. The integrated module can be embodied in hardware, or software. If the integrated module is embodied in software and sold or used as an independent product, it can be stored in the computer readable storage medium.
The non-transitory computer-readable storage medium may be, but is not limited to, read-only memories, magnetic disks, or optical disks.
Reference throughout this specification to “an embodiment, ” “some embodiments, ” “one embodiment” , “another example, ” “an example, ” “a specific example, ” or “some examples, ” means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. Thus, the appearances of the phrases such as “in some embodiments, ” “in one embodiment” , “in an embodiment” , “in another example, ” “in an example, ” “in a specific example, ” or “in some examples, ” in various places throughout this specification are not necessarily referring to the same embodiment or example of the present disclosure. Furthermore, the particular features, structures, materials, or characteristics may be combined in any suitable  manner in one or more embodiments or examples.
Although explanatory embodiments have been shown and described, it would be appreciated by those skilled in the art that the above embodiments cannot be construed to limit the present disclosure, and changes, alternatives, and modifications can be made in the embodiments without departing from spirit, principles and scope of the present disclosure.

Claims (19)

  1. A dispatch method for a combined heat and power CHP system, wherein, the CHP system comprises CHP units, non-CHP thermal units, wind farms and heating boilers; the CHP units, the non-CHP thermal units and the wind farms form an electric power system EPS of the CHP system; the CHP units and the heating boilers form a central heating system CHS of the CHP system; the EPS and the CHS are isolable; and the method comprises:
    establishing a combined heat and power dispatch CHPD model of the CHP system, wherein an objective function of the CHPD model is a minimizing function of a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers and constraints of the CHPD model are established based on generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers;
    solving the CHPD model based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS; and
    controlling the EPS and the CHS according to the corresponding dispatch parameters respectively.
  2. The method according to claim 1, wherein the total generation cost is established by a formula of
    Figure PCTCN2017114317-appb-100001
    where, t represents a dispatch time period, T represents an index set of dispatch time periods, ICHP represents an index set of the CHP units, ITU represents an index set of the non-CHP thermal units, IWD represents an index set of the wind farms, IHB represents an index set of the heating boilers, 
    Figure PCTCN2017114317-appb-100002
    represents a generation cost function of CHP unit i during period t, 
    Figure PCTCN2017114317-appb-100003
    represents a generation cost function of non-CHP thermal unit i during the period t, 
    Figure PCTCN2017114317-appb-100004
    represents a generation cost function of wind farm i during the period t, and 
    Figure PCTCN2017114317-appb-100005
    represents a generation cost function of heating boiler i during the period t.
  3. The method according to claim 2, wherein the generation cost function of the CHP unit i during the period t is established by a formula of
    Figure PCTCN2017114317-appb-100006
    where, 
    Figure PCTCN2017114317-appb-100007
    and
    Figure PCTCN2017114317-appb-100008
    represent generation cost coefficients of the CHP unit i, 
    Figure PCTCN2017114317-appb-100009
    represents a power output of the CHP unit i during the period t, and
    Figure PCTCN2017114317-appb-100010
    represents a heat output of the CHP unit i during the period t.
  4. The method according to claim 2, wherein the generation cost function of the non-CHP thermal unit i during the period t is established by a formula of
    Figure PCTCN2017114317-appb-100011
    where, 
    Figure PCTCN2017114317-appb-100012
    and
    Figure PCTCN2017114317-appb-100013
    represent generation cost coefficients of the non-CHP thermal unit i, and
    Figure PCTCN2017114317-appb-100014
    represents a power output of the non-CHP thermal unit i during the period t.
  5. The method according to claim 2, wherein the generation cost function of the wind farm i during the period t is established by a formula of
    Figure PCTCN2017114317-appb-100015
    where, 
    Figure PCTCN2017114317-appb-100016
    represents a penalty coefficient, 
    Figure PCTCN2017114317-appb-100017
    represents an available power output of the wind farm i during the period t and
    Figure PCTCN2017114317-appb-100018
    represents a power output of the wind farm i during the period t.
  6. The method according to claim 2, wherein the generation cost function of the heating boiler i during the period t is established by a formula of
    Figure PCTCN2017114317-appb-100019
    where, 
    Figure PCTCN2017114317-appb-100020
    represents a generation cost coefficient of the heating boiler i, and
    Figure PCTCN2017114317-appb-100021
    represents a heat output of the wind farm i during the period t.
  7. The method according to claim 2, wherein, the constraints comprise constraints of the EPS and constraints of the CHS;
    the constraints of the EPS comprise: operation constraints of the CHP units, ramping up and down constraints of the CHP units, operation constraints of the non-CHP thermal units, ramping up and down constraints of the non-CHP thermal units, spinning reserve constraints of the non-CHP thermal units, operation constraints of the wind farms, a power balance constraint of the  EPS, a line flow limit constraint of the EPS, and a spinning reserve constraint of the EPS; and
    the constraints of the CHS comprise: constraints between supply/return water temperature differences of nodes and heat outputs, heat output constraints of the heating boilers, supply water temperature constraints at nodes with heat sources connected, constraints between supply/return water temperature differences of nodes and heat exchanges of heat exchange stations, return water temperature constraints of heat exchange stations, and operation constraints of heating networks of the CHS.
  8. The method according to claim 7, wherein the operation constraints of the CHP units are denoted by a formula of
    Figure PCTCN2017114317-appb-100022
    Figure PCTCN2017114317-appb-100023
    where, 
    Figure PCTCN2017114317-appb-100024
    represents a power output of the CHP unit i during the period t, 
    Figure PCTCN2017114317-appb-100025
    represents a heat output of the CHP unit i during the period t, NEi represents an index set of extreme points of the CHP unit i, 
    Figure PCTCN2017114317-appb-100026
    represent respectively a power output at extreme point γ of the CHP unit i and a heat output at the extreme point γ of the CHP unit i, and
    Figure PCTCN2017114317-appb-100027
    represents a convex combination coefficient of the extreme point γ of the CHP unit i during the period t; and
    the ramping up and down constraints of the CHP units are denoted by a formula of
    Figure PCTCN2017114317-appb-100028
    where, 
    Figure PCTCN2017114317-appb-100029
    represents an upward ramp rate of the CHP unit i, 
    Figure PCTCN2017114317-appb-100030
    represents a downward ramp rate of the CHP unit i, 
    Figure PCTCN2017114317-appb-100031
    represents a power output of the CHP unit i during period t+1, and ΔT represents a dispatch interval.
  9. The method according to claim 7, wherein the operation constraints of the non-CHP thermal units are denoted by a formula of
    Figure PCTCN2017114317-appb-100032
    where, 
    Figure PCTCN2017114317-appb-100033
    represents an upper output bound of the non-CHP thermal unit i, Pi TU represents a lower output bound of the non-CHP thermal unit i and
    Figure PCTCN2017114317-appb-100034
    represents a power output of the non-CHP thermal unit i during the period t;
    the ramping up and down constraints of the non-CHP thermal units are denoted by a formula of
    Figure PCTCN2017114317-appb-100035
    where, 
    Figure PCTCN2017114317-appb-100036
    represents an upward ramp rate of the non-CHP thermal unit i, 
    Figure PCTCN2017114317-appb-100037
    represents a downward ramp rate of the non-CHP thermal unit, 
    Figure PCTCN2017114317-appb-100038
    represents a power output of the non-CHP thermal unit i during period t+1, and ΔT represents a dispatch interval; and
    the spinning reserve constraints of the non-CHP thermal units are denoted by a formula of
    Figure PCTCN2017114317-appb-100039
    Figure PCTCN2017114317-appb-100040
    where, 
    Figure PCTCN2017114317-appb-100041
    represents an upward spinning reserve contribution of the non-CHP thermal unit i during the period t, and
    Figure PCTCN2017114317-appb-100042
    represents a downward spinning reserve contribution of the non-CHP thermal unit i during the period t.
  10. The method according to claim 7, wherein the operation constraints of the wind farms are denoted by a formula of
    Figure PCTCN2017114317-appb-100043
    where, 
    Figure PCTCN2017114317-appb-100044
    represents a power output of the wind farm i during the period t, and
    Figure PCTCN2017114317-appb-100045
    represents an available power output of the wind farm i during the period t.
  11. The method according to claim 7, wherein the power balance constraint of the EPS is denoted by a formula of
    Figure PCTCN2017114317-appb-100046
    where, 
    Figure PCTCN2017114317-appb-100047
    represents a power output of the CHP unit i during the period t, 
    Figure PCTCN2017114317-appb-100048
    represents a power output of the non-CHP thermal unit i during the period t, 
    Figure PCTCN2017114317-appb-100049
    represents a power output of the wind farm i during the period t, ILD represents an index set of loads in the EPS and Dm, t represents a power demand of load m in the EPS during the period t;
    the line flow limit constraint of the EPS is denoted by a formula of
    Figure PCTCN2017114317-appb-100050
    where, IEPS represents an index set of buses in the EPS, SFj-l represents a shift factor for bus l on line j of the EPS, 
    Figure PCTCN2017114317-appb-100051
    represents an index set of CHP units connected to the bus l of  the EPS, 
    Figure PCTCN2017114317-appb-100052
    represents an index set of non-CHP thermal units connected to the bus l of the EPS, 
    Figure PCTCN2017114317-appb-100053
    represents an index set of wind farms connected to the bus l of the EPS, 
    Figure PCTCN2017114317-appb-100054
    represents an index set of loads connected to the bus l of the EPS, Lj represents a flow limit of the line j of the EPS, and ILN represents an index set of lines in the EPS; and
    the spinning reserve constraint of the EPS is denoted by a formula of
    Figure PCTCN2017114317-appb-100055
    where, 
    Figure PCTCN2017114317-appb-100056
    represents an upward spinning reserve contribution of the non-CHP thermal unit i during the period t, 
    Figure PCTCN2017114317-appb-100057
    represents a downward spinning reserve contribution of the non-CHP thermal unit i during the period t, SRUt represents an upward spinning reserve demand of the EPS during the period t and SRDt represents a downward spinning reserve demand of the EPS during the period t.
  12. The method according to claim 7, wherein the constraints between the supply/return water temperature differences of the nodes and the heat outputs are denoted by a formula of
    Figure PCTCN2017114317-appb-100058
    where, 
    Figure PCTCN2017114317-appb-100059
    represents an index set of CHP units connected to node k of the CHS, 
    Figure PCTCN2017114317-appb-100060
    represents an index set of heating boilers connected to the node k of the CHS, 
    Figure PCTCN2017114317-appb-100061
    represents a heat output of the CHP unit i during the period t, 
    Figure PCTCN2017114317-appb-100062
    represents a heat output of the heating boiler i during the period t, C represents a specific heat capacity of water, 
    Figure PCTCN2017114317-appb-100063
    represents a total mass flow rate of water at the node k of the CHS, 
    Figure PCTCN2017114317-appb-100064
    represents a water temperature of the node k in supply pipelines of the CHS during the period t, 
    Figure PCTCN2017114317-appb-100065
    represents a water temperature of the node k in return pipelines of the CHS during the period t, and
    Figure PCTCN2017114317-appb-100066
    represents an index set of nodes with heat sources connected in the CHS;
    the heat output constraints of the heating boilers are denoted by a formula of
    Figure PCTCN2017114317-appb-100067
    where, 
    Figure PCTCN2017114317-appb-100068
    represents an upper heat output bound of the heating boiler i; and
    the supply water temperature constraints at the nodes with heat sources connected are denoted by a formula of
    Figure PCTCN2017114317-appb-100069
    where, 
    Figure PCTCN2017114317-appb-100070
    represents an upper bound of the water temperature at the node k in the supply  pipelines of the CHS and
    Figure PCTCN2017114317-appb-100071
    represents a lower bound of the water temperature at the node k in the supply pipelines of the CHS.
  13. The method according to claim 7, wherein the constraints between the supply/return water temperature differences of the nodes and the heat exchanges of the heat exchange stations in the CHS are denoted by a formula of
    Figure PCTCN2017114317-appb-100072
    where, 
    Figure PCTCN2017114317-appb-100073
    represents an index set of heat exchange stations connected to node k of the CHS, 
    Figure PCTCN2017114317-appb-100074
    represents a heat exchange of heat exchange station n during the period t, C represents a specific heat capacity of water, 
    Figure PCTCN2017114317-appb-100075
    represents a total mass flow rate of water at the node k of the CHS, 
    Figure PCTCN2017114317-appb-100076
    represents a water temperature of the node k in supply pipelines of the CHS during the period t, 
    Figure PCTCN2017114317-appb-100077
    represents a water temperature of the node k in return pipelines of the CHS during the period t, and
    Figure PCTCN2017114317-appb-100078
    represents an index set of nodes with heat exchange stations connected in the CHS; and
    the return water temperature constraints of the heat exchange stations are denoted by a formula of
    Figure PCTCN2017114317-appb-100079
    where, 
    Figure PCTCN2017114317-appb-100080
    represents an upper bound of the water temperature at the node k in the return pipelines of the CHS and
    Figure PCTCN2017114317-appb-100081
    represents a lower bound of the water temperature at the node k in the return pipelines of the CHS.
  14. The method according to claim 7, wherein the operation constraints of the heating networks of the CHS are denoted by a formula of
    Figure PCTCN2017114317-appb-100082
    Figure PCTCN2017114317-appb-100083
    where, 
    Figure PCTCN2017114317-appb-100084
    represents a mass flow rate of water transferred from node k2 to node k1 in supply pipelines of the CHS, 
    Figure PCTCN2017114317-appb-100085
    represents a mass flow rate of return water transferred from the node k2 to the node k1 in return pipelines of the CHS, 
    Figure PCTCN2017114317-appb-100086
    represents an index set of child nodes of the node k1 in supply pipelines of the CHS, 
    Figure PCTCN2017114317-appb-100087
    represents an index set of  child nodes of the node k1 in return pipelines of the CHS, 
    Figure PCTCN2017114317-appb-100088
    represents an ambient temperature during the period t, 
    Figure PCTCN2017114317-appb-100089
    represents a heat transfer factor of water transferred from the node k2 to the node k1 in supply pipelines of the CHS, 
    Figure PCTCN2017114317-appb-100090
    represents a heat transfer factor of water transferred from the node k2 to the node k1 in return pipelines of the CHS, wherein
    Figure PCTCN2017114317-appb-100091
    and
    Figure PCTCN2017114317-appb-100092
    are calculated by a formula of
    Figure PCTCN2017114317-appb-100093
    where, 
    Figure PCTCN2017114317-appb-100095
    represents a heat transfer coefficient per unit length of pipeline from the node k2 to the node k1 in the supply pipelines of the CHS, 
    Figure PCTCN2017114317-appb-100096
    represents a heat transfer coefficient per unit length of pipeline from the node k2 to the node k1 in the return pipelines of the CHS, 
    Figure PCTCN2017114317-appb-100097
    represents a length of the supply pipeline from the node k2 to the node k1, 
    Figure PCTCN2017114317-appb-100098
    represents a length of the return pipeline from the node k2 to the node k1;
    Figure PCTCN2017114317-appb-100099
    and
    Figure PCTCN2017114317-appb-100100
    are intermediate variables representing temperature of the node k1 and only considering a transfer delay of water from its child node k2, wherein
    Figure PCTCN2017114317-appb-100101
    and
    Figure PCTCN2017114317-appb-100102
    are denoted by a formula of
    Figure PCTCN2017114317-appb-100103
    where, 
    Figure PCTCN2017114317-appb-100104
    represents transfer time periods of water from the node k2 to the node k1 in supply pipelines of the CHS, 
    Figure PCTCN2017114317-appb-100105
    represents transfer time periods of water from the node k2 to the node k1 in return pipelines of the CHS, and
    Figure PCTCN2017114317-appb-100106
    represents a rounding down operator.
  15. The method according to claim 7, wherein the CHPD model is summarized as a following quadratic programming QP problem by a formula of:
    Figure PCTCN2017114317-appb-100107
    where, xE represents variables of the EPS, and the variables of the EPS comprises
    Figure PCTCN2017114317-appb-100108
    Figure PCTCN2017114317-appb-100109
    and
    Figure PCTCN2017114317-appb-100110
    in which
    Figure PCTCN2017114317-appb-100111
    represents a power output of the non-CHP thermal unit i during the period t, 
    Figure PCTCN2017114317-appb-100112
    represents an upward spinning reserve contribution of the non-CHP thermal unit i during the period t, 
    Figure PCTCN2017114317-appb-100113
    represents a downward spinning reserve contribution of the non-CHP thermal unit i during the period t, 
    Figure PCTCN2017114317-appb-100114
    represents a power output of the wind farm i during the period t, 
    Figure PCTCN2017114317-appb-100115
    represents a power output of the CHP unit i during the period t, 
    Figure PCTCN2017114317-appb-100116
    represents a heat output of the CHP unit i during the period t and 
    Figure PCTCN2017114317-appb-100117
    represents a coefficient of extreme point γ of the CHP unit i during the period t; xH represents variables of the CHS, and the variables of the CHS comprises
    Figure PCTCN2017114317-appb-100118
    and
    Figure PCTCN2017114317-appb-100119
    in which
    Figure PCTCN2017114317-appb-100120
    represents a heat output of the heating boiler i during the period t, 
    Figure PCTCN2017114317-appb-100121
    represents a water temperature of the node k in supply pipelines of the CHS during the period t, and
    Figure PCTCN2017114317-appb-100122
    represents a water temperature of the node k in return pipelines of the CHS during the period t; AExE≤bE refers to the constraints of the EPS; AHxH≤bH refers to the constraints of the CHS except the constraints between the supply/return water temperature differences of the nodes and the heat outputs; and DxE+ExH≤f refers to the constraints between the supply/return water temperature differences of the nodes and the heat outputs.
  16. The method according to claim 15, wherein solving the CHPD model based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS comprises:
    splitting the QP problem into an EPS problem and a CHS problem;
    initializing an iteration number m as 0, the number of optimal cuts p as 0, and the number of feasible cuts q as 0;
    solving the EPS problem to obtain a solution as
    Figure PCTCN2017114317-appb-100123
    by a formula of
    Figure PCTCN2017114317-appb-100124
    solving the CHS problem according to the solution
    Figure PCTCN2017114317-appb-100125
    by a formula of
    Figure PCTCN2017114317-appb-100126
    if the CHS problem is feasible, increasing p by 1 and generating an optimal cut of
    Figure PCTCN2017114317-appb-100127
    if the CHS problem is infeasible, increasing q by 1 and generating an feasible cut of
    Figure PCTCN2017114317-appb-100128
    solving the EPS problem by a formula of
    Figure PCTCN2017114317-appb-100129
    increasing the iteration number m by 1 and denoting a solution as
    Figure PCTCN2017114317-appb-100130
    if
    Figure PCTCN2017114317-appb-100131
    terminating the iteration to obtain the dispatch parameters for the EPS and the CHS according to the solution; and
    if
    Figure PCTCN2017114317-appb-100132
    returning to act of solving the CHS problem according to the solution 
    Figure PCTCN2017114317-appb-100133
  17. The method according to claim 16, wherein
    Figure PCTCN2017114317-appb-100134
    and λ represents a Lagrange multiplier of a constraint
    Figure PCTCN2017114317-appb-100135
    and
    Figure PCTCN2017114317-appb-100136
    represents an objective value of the CHS problem;
    Figure PCTCN2017114317-appb-100137
    and
    Figure PCTCN2017114317-appb-100138
    are calculated according to following acts:
    denoting a feasibility problem of the CHS problem as a formula of:
    Figure PCTCN2017114317-appb-100139
    introducing a relaxation term ε to relax the feasibility problem of the CHS problem as a formula of:
    Figure PCTCN2017114317-appb-100140
    denoting a Lagrange multiplier of a constraint AHxH≤bH in the relaxed feasibility problem of the CHS problem as
    Figure PCTCN2017114317-appb-100141
    and a Lagrange multiplier of a constraint
    Figure PCTCN2017114317-appb-100142
    in the relaxed feasibility problem of the CHS problem as
    Figure PCTCN2017114317-appb-100143
    and calculating
    Figure PCTCN2017114317-appb-100144
    and
    Figure PCTCN2017114317-appb-100145
    according to a formula of:
    Figure PCTCN2017114317-appb-100146
  18. A dispatch apparatus for controlling a combined heat and power CHP system, wherein, the CHP system comprises CHP units, non-CHP thermal units, wind farms and heating boilers; the CHP units, the non-CHP thermal units and the wind farms form an electric power system EPS of the CHP system; the CHP units and the heating boilers form a central heating system CHS of the CHP system; the EPS and the CHS are isolable; and the device comprises:
    a processor; and
    a memory for storing instructions executable by the processor,
    wherein the processor is configured to:
    establish a combined heat and power dispatch CHPD model of the CHP system, wherein an objective function of the CHPD model is a minimizing function of a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers and constraints of the CHPD model are established based on generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers;
    solve the CHPD model based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS; and
    control the EPS and the CHS according to the corresponding dispatch parameters respectively.
  19. A non-transitory computer-readable storage medium having stored therein instructions that, when executed by a processor of a computer, causes the computer to perform a dispatch method for a combined heat and power CHP system, wherein the CHP system comprises CHP units, non-CHP thermal units, wind farms and heating boilers; the CHP units, the non-CHP thermal units and the wind farms form an electric power system EPS of the CHP system; the CHP units and the heating boilers form a central heating system CHS of the CHP system; the EPS and the CHS are isolable; and the method comprises:
    establishing a combined heat and power dispatch CHPD model of the CHP system, wherein an objective function of the CHPD model is a minimizing function of a total generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers and constraints of the CHPD model are established based on generation cost of the CHP units, the non-CHP thermal units, the wind farms and the heating boilers;
    solving the CHPD model based on Benders decomposition to obtain dispatch parameters for the EPS and the CHS; and
    controlling the EPS and the CHS according to the corresponding dispatch parameters respectively.
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