CN112966869A - Optimal scheduling method and system for park comprehensive energy system - Google Patents

Optimal scheduling method and system for park comprehensive energy system Download PDF

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CN112966869A
CN112966869A CN202110273830.1A CN202110273830A CN112966869A CN 112966869 A CN112966869 A CN 112966869A CN 202110273830 A CN202110273830 A CN 202110273830A CN 112966869 A CN112966869 A CN 112966869A
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energy
park
period
chp
energy system
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张新鹤
李克成
王松岑
何桂雄
李德智
钟鸣
黄伟
刘向向
卢婕
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State Grid Jiangxi Electric Power Co ltd
State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
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State Grid Jiangxi Electric Power Co ltd
State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION 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
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    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION 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
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
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    • Y—GENERAL 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
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Abstract

The invention relates to a method and a system for optimizing and scheduling a park comprehensive energy system, which comprise the following steps: acquiring the predicted electric load, thermal load, load rate and photovoltaic power generation unit output of the park at each time interval of the optimization cycle; substituting the electric load, the heat load, the output of the photovoltaic power generation unit and the load rate of the park at each time interval of the optimization cycle into a pre-established optimization scheduling model for solving to obtain the optimal solution of the electricity purchasing power and the gas purchasing power of the park comprehensive energy system at each time interval of the optimization cycle, the energy using power and the energy generating power of the energy generating equipment in the park comprehensive energy system and the charge-discharge energy power of the energy storing equipment in the park comprehensive energy system; and scheduling the park comprehensive energy system according to the optimal solution. According to the technical scheme provided by the invention, the influence of the load rate on the energy concentrator model is considered, the construction rationality of the optimized scheduling model is improved, and the optimized scheduling of the park comprehensive energy system is more reasonable and reliable.

Description

Optimal scheduling method and system for park comprehensive energy system
Technical Field
The invention relates to the field of optimal scheduling of a park integrated energy system, in particular to an optimal scheduling method and system of the park integrated energy system.
Background
With the acceleration of social development and the increase of energy demand, the contradiction between large energy demand and energy shortage is increasingly prominent, and in order to solve the problem, the development trend of global energy technology is formed by improving the energy utilization efficiency and enhancing the comprehensive utilization of energy.
The comprehensive energy system integrates energy subsystems such as electricity, heat, gas and the like, covers energy technologies of various energy links such as energy production, transmission, conversion, energy storage and the like, fully explores the potential of each energy subsystem, and is an important direction for the revolution and development of the current energy technology.
According to the factors such as geographic environment and energy characteristics, the comprehensive energy system can be divided into: the system comprises a global energy Internet, a trans-regional comprehensive energy system, an area-level comprehensive energy system and a user-level comprehensive energy system. The park comprehensive energy system is a typical user-level comprehensive energy system, the integrated operation of various energy systems of electricity, heat and gas and the combined supply of multiple energy sources are realized through technologies such as renewable energy power generation and combined heat and power generation (CHP), the comprehensive utilization rate of energy sources can be effectively improved, the energy consumption cost is reduced, the user income is improved, and the multi-energy complementation and the integrated optimization among different energy forms of electricity, heat, gas and the like are realized. The operation economy and the energy utilization rate of the park integrated energy system are closely related to the optimal scheduling method, so that the research on the optimal scheduling method of the park integrated energy system has important economic benefits and social significance.
The physical-mathematical model is a basic tool for researching the generation and operation mechanism of the park comprehensive energy system. As a general modeling method of the comprehensive energy system, the energy hub model abstracts the internal equipment elements of the park comprehensive energy system and the coupling relationship between the internal equipment elements into a coupling matrix so as to reflect the input-output relationship of the park comprehensive energy system. The energy concentrator is not limited by the size and the topological structure of the system to be modeled, and therefore becomes a classical model for optimal planning and operation of the park comprehensive energy system.
When the energy hub model is established for the to-be-analyzed park integrated energy system, the traditional optimization scheduling method usually assumes that the energy conversion efficiency and the distribution coefficient of main energy equipment in the to-be-analyzed park integrated energy system are constant, however, the situation that the equipment energy conversion efficiency and the distribution coefficient change along with the load rate exists in the actual working condition operating environment, so the park integrated energy system model assuming constant energy conversion efficiency and distribution coefficient of the energy equipment is not accurate enough, and the optimization scheduling scheme of the park integrated energy system is unreasonable.
In view of the above, a new technology is needed to solve the above problems.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a method and a system for optimizing and scheduling a park integrated energy system, which consider the influence of the load rate on the energy conversion efficiency and the distribution coefficient, improve the construction rationality of an optimization scheduling model and further enable the optimization scheduling of the park integrated energy system to be more reasonable and reliable.
The purpose of the invention is realized by adopting the following technical scheme:
the invention provides an optimal scheduling method for a park comprehensive energy system, which comprises the following steps:
acquiring the predicted electric load, thermal load, load rate and photovoltaic power generation unit output of the park at each time interval of the optimization cycle;
substituting the electric load, the heat load, the output of the photovoltaic power generation unit and the load rate of the park at each time interval of the optimization cycle into a pre-established optimization scheduling model for solving to obtain the optimal solution of the electricity purchasing power and the gas purchasing power of the park comprehensive energy system at each time interval of the optimization cycle, the energy using power and the energy generating power of the energy generating equipment in the park comprehensive energy system and the charge-discharge energy power of the energy storing equipment in the park comprehensive energy system;
scheduling the park comprehensive energy system according to the optimal solution;
wherein the optimized scheduling model is established based on load rate modified energy hub model constraints.
The invention relates to a garden comprehensive energy system optimization scheduling system, which comprises:
the acquisition module is used for acquiring the predicted electric load, thermal load, load rate and photovoltaic power generation unit output of the park at each time interval of the optimization cycle;
the solving module is used for substituting the electric load, the heat load, the output power and the load rate of the photovoltaic power generation unit of the park in each time period of the optimization cycle into a pre-established optimization scheduling model for solving to obtain the optimal solution of the electricity purchasing power and the gas purchasing power of the park comprehensive energy system in each time period of the optimization cycle, the energy using power and the capacity generating power of the capacity generating equipment in the park comprehensive energy system and the charge-discharge energy power of the energy storage equipment in the park comprehensive energy system;
the scheduling module is used for scheduling the park comprehensive energy system according to the optimal solution;
wherein the optimized scheduling model is established based on load rate modified energy hub model constraints.
Compared with the closest prior art, the invention has the following beneficial effects:
according to the technical scheme provided by the invention, the electric load, the thermal load, the load rate and the output of the photovoltaic power generation unit of the forecast park in each time period of the optimization cycle are obtained; substituting the electric load, the heat load, the output of the photovoltaic power generation unit and the load rate of the park at each time interval of the optimization cycle into a pre-established optimization scheduling model for solving to obtain the optimal solution of the electricity purchasing power and the gas purchasing power of the park comprehensive energy system at each time interval of the optimization cycle, the energy using power and the energy generating power of the energy generating equipment in the park comprehensive energy system and the charge-discharge energy power of the energy storing equipment in the park comprehensive energy system; and scheduling the park comprehensive energy system according to the optimal solution. According to the scheme, the influence of the load rate on the energy concentrator model is considered, the establishment rationality of the optimized dispatching model is improved, and further the optimized dispatching of the park comprehensive energy system is more reasonable and reliable.
Drawings
FIG. 1 is a flow chart of a method for optimal scheduling of a campus integrated energy system;
fig. 2 is a structural diagram of a campus integrated energy system optimization scheduling system.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1:
the invention provides an optimal scheduling method for a park integrated energy system, which comprises the following steps of:
step 101, acquiring the predicted electric load, thermal load, load rate and output of a photovoltaic power generation unit of the park at each time interval of an optimization cycle;
step 102, substituting the electric load, the heat load, the output power and the load rate of the photovoltaic power generation unit of the park at each time interval of the optimization cycle into a pre-established optimization scheduling model for solving, and obtaining the optimal solution of the electricity purchasing power and the gas purchasing power of the park comprehensive energy system at each time interval of the optimization cycle, the energy using power and the energy generating power of the energy generating equipment in the park comprehensive energy system and the charge-discharge energy power of the energy storage equipment in the park comprehensive energy system;
103, scheduling the comprehensive energy system of the park according to the optimal solution;
wherein the optimized scheduling model is established based on load rate modified energy hub model constraints.
Specifically, the construction of the optimized scheduling model includes:
constructing an objective function with the goals of lowest operation cost and maximum energy utilization rate;
and constructing an energy balance constraint, an energy hub model constraint of load rate correction, an energy conversion equipment operation inequality constraint and an energy storage equipment operation constraint for the objective function.
Specifically, the load rate corrected energy hub model constraint is obtained by correcting the energy conversion efficiency and the distribution coefficient in the energy hub model by using the load rate.
Further, the load rate corrected energy hub model constraint is calculated as follows:
Figure BDA0002975673780000031
in the formula, Pe,tFor the t th in the optimization period of the park integrated energy systemElectric power purchase of time period, Pg,tRespectively the gas purchasing power L of the integrated energy system of the park in the t-th period in the optimization cyclee,tOutput electric power L of the comprehensive energy system of the park in the t period of the optimization cycleh,tFor the output thermal power of the park comprehensive energy system in the t period of the optimization cycle, Me,tFor the electric power storage, M, of the comprehensive energy system of the park in the t-th period of the optimization cycleg,tThe heat storage power v of the comprehensive energy system in the optimization periodHP(ξt) As the load factor is xitDistribution coefficient v of the heat pump in the t-th period of the optimization cycleCHP(ξt) As the load factor is xitDistribution coefficient, eta of the time-CHP unit in the t-th period of the optimization cycleHP(ξt) As the load factor is xitEnergy conversion efficiency of heat pump, etaCHP(ξt) As the load factor is xitEnergy conversion efficiency, eta, of hour-CHP unitsGB(ξt) As the load factor is xitEnergy conversion efficiency of time gas boiler unit, alphaCHP(ξt) As the load factor is xitThermoelectric ratio, ξ, of hour CHP unittTo optimize the duty cycle for the t-th period of the cycle.
Further, the load factor is ξtEnergy conversion efficiency eta of time-CHP unitCHP(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the energy conversion efficiency of the CHP unit based on a relation curve between the actual energy conversion efficiency and the load rate acquired under the actual working condition of the CHP unit;
the load ratio is xitThermoelectric ratio alpha of time-CHP unitCHP(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the thermoelectric ratio of the CHP unit based on a relation curve between the actual thermoelectric ratio and the load rate acquired under the actual working condition of the CHP unit;
the load ratio is xitEnergy conversion efficiency eta of time gas boilerGB(ξt) The calculation formula of (2) is based on a relation curve between the actual energy conversion efficiency and the load rate obtained under the actual working condition of the gas-fired boiler,carrying out polynomial fitting on the load rate and the energy conversion efficiency of the gas boiler to obtain the load rate and the energy conversion efficiency of the gas boiler;
the load ratio is xitEnergy conversion efficiency eta of time-lapse heat pumpHP(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the energy conversion efficiency of the heat pump based on a relation curve between the actual energy conversion efficiency and the load rate acquired under the actual working condition of the heat pump.
Still further, the load factor is ξtEnergy conversion efficiency eta of time-CHP unitCHP(ξt) Is calculated as follows:
ηCHP(ξt)＝k1ξt 4+k2ξt 3+k3ξt 2+k4ξt+k0
in the formula, k0Is etaCHP(ξt) Coefficient of constant term, k, in the formula4Is etaCHP(ξt) Coefficient of first order term, k, in the formula3Is etaCHP(ξt) Coefficient of quadratic term, k, in the formula2Is etaCHP(ξt) Coefficient of cubic term, k, in the formula1Is etaCHP(ξt) Coefficient of quartic term in the calculation formula (1);
the load ratio is xitThermoelectric ratio alpha of time-CHP unitCHP(ξt) Is calculated as follows:
αCHP(ξt)＝k2'ξt 2+k1'ξt+k0'
in the formula, k0' is alphaCHP(ξt) Coefficient of constant term, k, in the formula1' is alphaCHP(ξt) Coefficient of first order term, k, in the formula2' is alphaCHP(ξt) Coefficient of quadratic term in the calculation formula (1);
the load ratio is xitEnergy conversion efficiency eta of time gas boilerGB(ξt) Is calculated as follows:
Figure BDA0002975673780000051
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000052
is etaGB(ξt) The coefficient of the constant term in the calculation formula (2),
Figure BDA0002975673780000053
is etaGB(ξt) Coefficient of a first order term in the calculation formula (1);
the load ratio is xitEnergy conversion efficiency eta of time-lapse heat pumpHP(ξt) Is calculated as follows:
Figure BDA0002975673780000054
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000055
is etaHP(ξt) The coefficient of the constant term in the calculation formula (2),
Figure BDA0002975673780000056
is etaHP(ξt) The coefficient of the first order term in the calculation formula (2),
Figure BDA0002975673780000057
is etaHP(ξt) Coefficient of quadratic term in the calculation formula (2).
Further, the load factor corrected energy hub model constraint calculation formula further includes:
Figure BDA0002975673780000058
Figure BDA0002975673780000059
Figure BDA00029756737800000510
Figure BDA00029756737800000511
Figure BDA00029756737800000512
Figure BDA00029756737800000513
in the formula (I), the compound is shown in the specification,
Figure BDA00029756737800000514
for the output electric power of the CHP unit in the t-th period of the optimization cycle,
Figure BDA00029756737800000515
for the input natural gas power of the CHP unit in the t-th period of the optimization cycle,
Figure BDA00029756737800000516
for the output thermal power of the CHP unit in the t-th period of the optimization cycle,
Figure BDA00029756737800000517
for the output thermal power of the gas boiler in the t period of the optimization cycle,
Figure BDA00029756737800000518
for the input natural gas power of the gas boiler in the t period in the optimization cycle,
Figure BDA0002975673780000061
to optimize the output thermal power of the heat pump during the tth period of the cycle,
Figure BDA0002975673780000062
the input electric power of the heat pump in the t period in the optimization cycle is obtained.
Further, the objective function is calculated as follows:
F＝minf1+maxf2
wherein F is the value of the objective function, F1To optimize the operating cost of the park's integrated energy system in the period, f2The energy utilization rate average value of the garden comprehensive energy system in the period is optimized.
Wherein the operation cost f of the park comprehensive energy system in the optimization period1Is calculated as follows:
Figure BDA0002975673780000063
in the formula, σ1For optimizing the weight corresponding to the operating cost of the district's integrated energy system in the period, Ce,tTo optimize the electricity price in the t-th period of the cycle, Cg,tTo optimize natural gas prices, C, for the t-th period of the cycleM,kFor the unit power operation maintenance cost, P, of the kth equipment in the park integrated energy systeme,tThe electricity purchasing power P of the t period of the optimization cycle of the park comprehensive energy systemg,tRespectively the gas purchasing power P of the integrated energy system of the park in the t-th period of the optimization cycleout,k,tThe output power of the kth equipment in the optimization period in the comprehensive energy system of the park is T from (1 to T), T is the total time period contained in the optimization period, i from (1 to S)k)，SkThe total number of equipment contained in the park comprehensive energy system;
the average value f of the energy utilization rate of the garden comprehensive energy system in the optimization period2Is calculated as follows:
Figure BDA0002975673780000064
in the formula, σ2For optimizing the weight corresponding to the average value of the energy utilization rate of the park comprehensive energy system in the period, Le,tOutput electric power L of the comprehensive energy system of the park in the t period of the optimization cycleh,tAnd outputting thermal power for the comprehensive energy system of the park in the tth period of the optimization cycle.
Further, the calculation formula of the inequality constraint of the operation of the energy conversion device is as follows:
Figure BDA0002975673780000071
in the formula, Pe maxThe upper limit value P of the electricity purchasing power of the park comprehensive energy systeme minFor the lower limit value, P, of the purchasing power of the park's integrated energy systemg maxIs the upper limit value, P, of the gas purchasing power of the park comprehensive energy systemg minFor the lower limit value, P, of the purchasing power of the park's integrated energy systemt PVThe output power P of the photovoltaic power generation unit in the t-th period in the optimization cycle in the park comprehensive energy systemPV maxIs the maximum output power, P, of the photovoltaic power generation unitCHP maxFor the maximum load capacity, P, of the CHP units in the park complex energy systemGB maxFor the maximum loading capacity, P, of the gas-fired boiler in the park complex energy systemHP maxThe maximum loading capacity of the heat pump in the park integrated energy system.
Specifically, the capacity generating device includes: the system comprises a photovoltaic power generation unit, a CHP unit, a gas boiler and a heat pump;
the energy storage device includes: an electricity storage device and a heat storage device.
Example 2:
the invention provides an optimized dispatching system of a park comprehensive energy system, which comprises the following components as shown in figure 2:
the acquisition module is used for acquiring the predicted electric load, thermal load, load rate and photovoltaic power generation unit output of the park at each time interval of the optimization cycle;
the solving module is used for substituting the electric load, the heat load, the output power and the load rate of the photovoltaic power generation unit of the park in each time period of the optimization cycle into a pre-established optimization scheduling model for solving to obtain the optimal solution of the electricity purchasing power and the gas purchasing power of the park comprehensive energy system in each time period of the optimization cycle, the energy using power and the capacity generating power of the capacity generating equipment in the park comprehensive energy system and the charge-discharge energy power of the energy storage equipment in the park comprehensive energy system;
the scheduling module is used for scheduling the park comprehensive energy system according to the optimal solution;
wherein the optimized scheduling model is established based on load rate modified energy hub model constraints.
Specifically, the system further includes a building module for building an optimized scheduling model in advance, where the building module includes:
an objective function construction unit for constructing an objective function with an objective of lowest running cost and maximum energy utilization rate;
and the constraint condition construction unit is used for constructing energy balance constraint, load rate corrected energy hub model constraint, energy conversion equipment operation inequality constraint and energy storage equipment operation constraint for the objective function.
Specifically, the load rate corrected energy hub model constraint is obtained by correcting the energy conversion efficiency and the distribution coefficient in the energy hub model by using the load rate.
Specifically, the load factor corrected energy hub model constraint calculation formula is as follows:
Figure BDA0002975673780000081
in the formula, Pe,tThe electricity purchasing power P of the t period of the optimization cycle of the park comprehensive energy systemg,tRespectively the gas purchasing power L of the integrated energy system of the park in the t-th period in the optimization cyclee,tOutput electric power L of the comprehensive energy system of the park in the t period of the optimization cycleh,tIs a gardenOutput thermal power M of district integrated energy system in t-th time period of optimization cyclee,tFor the electric power storage, M, of the comprehensive energy system of the park in the t-th period of the optimization cycleg,tThe heat storage power v of the comprehensive energy system in the optimization periodHP(ξt) As the load factor is xitDistribution coefficient v of the heat pump in the t-th period of the optimization cycleCHP(ξt) As the load factor is xitDistribution coefficient, eta of the time-CHP unit in the t-th period of the optimization cycleHP(ξt) As the load factor is xitEnergy conversion efficiency of heat pump, etaCHP(ξt) As the load factor is xitEnergy conversion efficiency, eta, of hour-CHP unitsGB(ξt) As the load factor is xitEnergy conversion efficiency of time gas boiler unit, alphaCHP(ξt) As the load factor is xitThermoelectric ratio, ξ, of hour CHP unittTo optimize the duty cycle for the t-th period of the cycle.
Further, the load factor is ξtEnergy conversion efficiency eta of time-CHP unitCHP(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the energy conversion efficiency of the CHP unit based on a relation curve between the actual energy conversion efficiency and the load rate acquired under the actual working condition of the CHP unit;
the load ratio is xitThermoelectric ratio alpha of time-CHP unitCHP(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the thermoelectric ratio of the CHP unit based on a relation curve between the actual thermoelectric ratio and the load rate acquired under the actual working condition of the CHP unit;
the load ratio is xitEnergy conversion efficiency eta of time gas boilerGB(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the energy conversion efficiency of the gas-fired boiler based on a relation curve between the actual energy conversion efficiency and the load rate acquired under the actual working condition of the gas-fired boiler;
the load ratio is xitEnergy conversion efficiency eta of time-lapse heat pumpHP(ξt) Is based on heatObtaining a relation curve between the actual energy conversion efficiency and the load rate under the actual working condition of the pump, and carrying out polynomial fitting on the load rate and the energy conversion efficiency of the heat pump to obtain the relation curve.
Still further, the load factor is ξtEnergy conversion efficiency eta of time-CHP unitCHP(ξt) Is calculated as follows:
ηCHP(ξt)＝k1ξt 4+k2ξt 3+k3ξt 2+k4ξt+k0
in the formula, k0Is etaCHP(ξt) Coefficient of constant term, k, in the formula4Is etaCHP(ξt) Coefficient of first order term, k, in the formula3Is etaCHP(ξt) Coefficient of quadratic term, k, in the formula2Is etaCHP(ξt) Coefficient of cubic term, k, in the formula1Is etaCHP(ξt) Coefficient of quartic term in the calculation formula (1);
the load ratio is xitThermoelectric ratio alpha of time-CHP unitCHP(ξt) Is calculated as follows:
αCHP(ξt)＝k2'ξt 2+k1'ξt+k0'
in the formula, k0' is alphaCHP(ξt) Coefficient of constant term, k, in the formula1' is alphaCHP(ξt) Coefficient of first order term, k, in the formula2' is alphaCHP(ξt) Coefficient of quadratic term in the calculation formula (1);
the load ratio is xitEnergy conversion efficiency eta of time gas boilerGB(ξt) Is calculated as follows:
Figure BDA0002975673780000091
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000092
is etaGB(ξt) The coefficient of the constant term in the calculation formula (2),
Figure BDA0002975673780000093
is etaGB(ξt) Coefficient of a first order term in the calculation formula (1);
the load ratio is xitEnergy conversion efficiency eta of time-lapse heat pumpHP(ξt) Is calculated as follows:
Figure BDA0002975673780000094
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000095
is etaHP(ξt) The coefficient of the constant term in the calculation formula (2),
Figure BDA0002975673780000096
is etaHP(ξt) The coefficient of the first order term in the calculation formula (2),
Figure BDA0002975673780000097
is etaHP(ξt) Coefficient of quadratic term in the calculation formula (2).
Further, the load factor corrected energy hub model constraint calculation formula further includes:
Figure BDA0002975673780000098
Figure BDA0002975673780000099
Figure BDA00029756737800000910
Figure BDA00029756737800000911
Figure BDA00029756737800000912
Figure BDA0002975673780000101
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000102
for the output electric power of the CHP unit in the t-th period of the optimization cycle,
Figure BDA0002975673780000103
for the input natural gas power of the CHP unit in the t-th period of the optimization cycle,
Figure BDA0002975673780000104
for the output thermal power of the CHP unit in the t-th period of the optimization cycle,
Figure BDA0002975673780000105
for the output thermal power of the gas boiler in the t period of the optimization cycle,
Figure BDA0002975673780000106
for the input natural gas power of the gas boiler in the t period in the optimization cycle,
Figure BDA0002975673780000107
to optimize the output thermal power of the heat pump during the tth period of the cycle,
Figure BDA0002975673780000108
the input electric power of the heat pump in the t period in the optimization cycle is obtained.
Specifically, the objective function is calculated as follows:
F＝minf1+maxf2
wherein F is the value of the objective function, F1To optimize the operating cost of the park's integrated energy system in the period, f2The energy utilization rate average value of the garden comprehensive energy system in the period is optimized.
Wherein the operation cost f of the park comprehensive energy system in the optimization period1Is calculated as follows:
Figure BDA0002975673780000109
in the formula, σ1For optimizing the weight corresponding to the operating cost of the district's integrated energy system in the period, Ce,tTo optimize the electricity price in the t-th period of the cycle, Cg,tTo optimize natural gas prices, C, for the t-th period of the cycleM,kFor the unit power operation maintenance cost, P, of the kth equipment in the park integrated energy systeme,tThe electricity purchasing power P of the t period of the optimization cycle of the park comprehensive energy systemg,tRespectively the gas purchasing power P of the integrated energy system of the park in the t-th period of the optimization cycleout,k,tThe output power of the kth equipment in the optimization period in the comprehensive energy system of the park is T from (1 to T), T is the total time period contained in the optimization period, i from (1 to S)k)，SkThe total number of equipment contained in the park comprehensive energy system;
the average value f of the energy utilization rate of the garden comprehensive energy system in the optimization period2Is calculated as follows:
Figure BDA00029756737800001010
in the formula, σ2For optimizing the weight corresponding to the average value of the energy utilization rate of the park comprehensive energy system in the period, Le,tOutput electric power L of the comprehensive energy system of the park in the t period of the optimization cycleh,tFor the park comprehensive energy system in the optimization weekThe output thermal power of the t-th period.
Specifically, the calculation formula of the inequality constraint of the operation of the energy conversion equipment is as follows:
Figure BDA0002975673780000111
in the formula, Pe maxThe upper limit value P of the electricity purchasing power of the park comprehensive energy systeme minFor the lower limit value, P, of the purchasing power of the park's integrated energy systemg maxIs the upper limit value, P, of the gas purchasing power of the park comprehensive energy systemg minFor the lower limit value, P, of the purchasing power of the park's integrated energy systemt PVThe output power P of the photovoltaic power generation unit in the t-th period in the optimization cycle in the park comprehensive energy systemPV maxIs the maximum output power, P, of the photovoltaic power generation unitCHP maxFor the maximum load capacity, P, of the CHP units in the park complex energy systemGB maxFor the maximum loading capacity, P, of the gas-fired boiler in the park complex energy systemHP maxThe maximum loading capacity of the heat pump in the park integrated energy system.
Specifically, the capacity generating device includes: the system comprises a photovoltaic power generation unit, a CHP unit, a gas boiler and a heat pump;
the energy storage device includes: an electricity storage device and a heat storage device.
Example 3:
in the traditional optimization scheduling method, when an energy concentrator model is established for a to-be-analyzed park integrated energy system, the energy conversion efficiency and the distribution coefficient of main energy equipment in the to-be-analyzed park integrated energy system are generally assumed to be constant, however, the situation that the equipment energy conversion efficiency and the distribution coefficient change along with the load rate exists in the operating environment under the actual working condition, so the park integrated energy system model assuming constant energy conversion efficiency and distribution coefficient is not accurate enough, and the optimization scheduling scheme of the park integrated energy system is unreasonable, and in view of the above problems, in order to ensure the reliability of the optimization scheduling scheme of the park integrated energy system, the optimization scheduling method of the park integrated energy system is provided, the energy concentrator model of the park integrated energy system reflecting the actual operating condition is established by the method, so that the optimization scheduling scheme of the park integrated energy system is more reasonable and reliable, the method has reference significance for the optimization scheduling work of the comprehensive energy system.
The optimal scheduling method for the park integrated energy system provided by the invention is adopted to perform optimal scheduling on the park integrated energy system, and comprises the following steps:
step A: constructing a universal model of an 'electricity-heat-gas' energy concentrator corresponding to the park comprehensive energy system:
1): analyzing the energy equipment type, the energy coupling relation and the energy structure in the park comprehensive energy system, and collecting equipment parameters;
energy equipment of the park integrated energy system includes: photovoltaic power generation unit (PV), CHP unit, Gas Boiler (GB), Heat Pump (HP) and energy storage equipment, energy storage equipment includes: an electricity storage device and a heat storage device;
2): establishing a universal model of the 'electricity-heat-gas' energy concentrator corresponding to the park comprehensive energy system by using a typical energy concentrator modeling method;
the model can be represented by the following formula:
Figure BDA0002975673780000121
in the formula, LeAnd LhRespectively outputs electric power and thermal power, P, for the park comprehensive energy systemeAnd PgRespectively the electricity purchasing power and the gas purchasing power, M, of the park comprehensive energy systemeAnd MhRespectively the electricity storage capacity and the heat storage capacity of the park comprehensive energy system, vHPThe distribution coefficient corresponding to the heat pump is the ratio of the electric quantity used for heat production of the heat pump to the total electric quantity, vCHPThe distribution coefficient corresponding to the CHP unit is the ratio of the natural gas amount used for the electricity generation of the CHP unit to the total natural gas amount, etaHP、ηCHPAnd ηGBRespectively the energy conversion efficiency of the heat pump, the CHP unit and the gas boiler, alphaCHPIs the heat-to-power ratio of the CHP unit.
3): considering the influence of the load rate on the energy conversion efficiency and the distribution coefficient in the universal model of the 'electricity-heat-gas' energy concentrator corresponding to the park comprehensive energy system, and correcting the universal model of the 'electricity-heat-gas' energy concentrator;
the energy conversion efficiency changes due to the load rate changes, and the energy conversion efficiency changes are fed back to the dispatching center to redistribute the energy in the system, so that the energy distribution coefficient changes. In order to obtain an accurate universal model of the 'electro-thermal-pneumatic' energy concentrator corresponding to the park integrated energy system, the model is corrected, and after correction, the model can be represented by the following formula:
Figure BDA0002975673780000122
in the formula, Le,tAnd Lh,tRespectively outputting electric power and thermal power, P, of the park comprehensive energy system in the t period of the optimization cyclee,tAnd Pg,tRespectively the electricity purchasing power and the gas purchasing power, M, of the t-th period in the optimization cycle of the park comprehensive energy systeme,tAnd Mg,tRespectively the electricity storage power and the heat storage power of the comprehensive energy system in the optimization period at the tth time interval of the parkHP(ξt) As the load factor is xitThe distribution coefficient of the corresponding heat pump in the t-th period in the optimization cycle has the value of xi as the load factortThe ratio of the electric power used by the heat pump for generating heat to the purchasing power during the t-th period in the optimization period, vCHP(ξt) As the load factor is xitThe distribution coefficient of the corresponding CHP unit in the t-th period of the optimization cycle is the load factor xitThe ratio of the natural gas power used for power generation in the t-th period of the optimization cycle of the time-CHP unit to the gas purchasing power, etaHP(ξt)、ηCHP(ξt) And ηGB(ξt) Respectively, the load factor is xitHeat pump, CHP unit, gas boilerEfficiency of energy conversion, alphaCHP(ξt) As the load factor is xitThermoelectric ratio xi of CHP unit corresponding to timetThe load rate of the t-th period in the optimized period is equal to the ratio of the average value of the optimized period load rates to the maximum value of the optimized period load rates.
4): giving out the operation parameters of each device of the park comprehensive energy system reflected by the general model of the 'electricity-heat-gas' energy concentrator corresponding to the corrected park comprehensive energy system;
(1) CHP unit
Relationship between CHP unit output electric power and input natural gas power:
Figure BDA0002975673780000131
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000132
for the output electric power of the CHP unit in the t-th period of the optimization cycle,
Figure BDA0002975673780000133
the input natural gas power of the CHP unit in the t-th period of the optimization cycle;
relationship between CHP unit output thermal power and output electric power:
Figure BDA0002975673780000134
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000135
outputting thermal power for the Tth period of the CHP unit in the optimization cycle;
thus, the available load factor is ξtDistribution coefficient v corresponding to CHP unitCHP(ξt) Is calculated as follows:
Figure BDA0002975673780000136
wherein eta isCHP(ξt) The calculation formula is obtained by fitting a relation curve between the actual energy conversion efficiency and the load factor acquired under the actual working condition of the CHP unit, wherein eta isCHP(ξt) The calculation formula (2) is specifically as follows:
ηCHP(ξt)＝k1ξt 4+k2ξt 3+k3ξt 2+k4ξt+k0
in the formula, k 0-k 4 are fitting factors of the polynomial.
αCHP(ξt) The calculation formula is obtained by fitting a relation curve between the actual electric heating ratio and the load rate acquired under the actual working condition of the CHP unit, and alpha isCHP(ξt) The calculation formula (2) is specifically as follows:
αCHP(ξt)＝k2'ξt 2+k1'ξt+k0'
in the formula, k0'～k2' is a fitting factor of a polynomial.
(2) Gas Boiler (GB)
The relationship between the output thermal power and the input natural gas power of the gas boiler is as follows:
Figure BDA0002975673780000141
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000142
for the output thermal power of the gas boiler in the t period of the optimization cycle,
Figure BDA0002975673780000143
the input natural gas power of the gas boiler in the t period in the optimization cycle is obtained.
Wherein eta isGB(ξt) Meter (2)The equation is obtained by fitting a relation curve between the actual energy conversion efficiency and the load factor obtained under the actual working condition of the gas boiler, wherein eta isGB(ξt) The calculation formula (2) is specifically as follows:
Figure BDA0002975673780000144
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000145
fitting factors for the polynomial.
(3) Heat Pump (HP)
Relationship between heat pump output thermal power and input electrical power:
Figure BDA0002975673780000146
in the formula (I), the compound is shown in the specification,
Figure BDA0002975673780000147
to optimize the output thermal power of the heat pump during the tth period of the cycle,
Figure BDA0002975673780000148
input electric power for the heat pump during a tth period of the optimization cycle;
Figure BDA0002975673780000149
distribution coefficient of electric energy for heat pump:
Figure BDA00029756737800001410
wherein eta isHP(ξt) The calculation formula is obtained by fitting a relation curve between the actual energy conversion efficiency and the load factor obtained under the actual working condition of the heat pump, wherein eta isHP(ξt) The calculation formula (2) is specifically as follows:
Figure BDA00029756737800001411
in the formula (I), the compound is shown in the specification,
Figure BDA00029756737800001412
fitting factors for the polynomial.
And B: comprehensively considering the park operation economic cost and the energy utilization rate, and combining the corrected general model of the 'electricity-heat-gas' energy concentrator corresponding to the park comprehensive energy system and the operation parameters of all the equipment of the park comprehensive energy system, constructing an optimized dispatching model in advance:
1) the optimization scheduling model is constructed by using the goals of lowest operation cost and maximum energy utilization rate;
the objective function is calculated as follows:
F＝minf1+maxf2
wherein F is the value of the objective function, F1To optimize the operating cost of the park's integrated energy system in the period, f2The average value of the energy utilization rate of the comprehensive energy system of the garden area in the optimization period is obtained;
wherein, the operation cost of the park comprehensive energy system mainly comprises park electricity and gas purchasing cost and maintenance cost of various devices, f1Is calculated as follows:
Figure BDA0002975673780000151
in the formula, σ1For optimizing the weight corresponding to the operating cost of the district's integrated energy system in the period, Ce,tTo optimize the electricity price in the t-th period of the cycle, Cg,tTo optimize natural gas prices, C, for the t-th period of the cycleM,kFor the unit power operation maintenance cost, P, of the kth equipment in the park integrated energy systemout,k,tThe output power of the kth equipment in the optimization period of the kth equipment in the park comprehensive energy system is T from (1-T), and T is the optimization periodTotal number of time periods covered, i ∈ (1 to S)k)，SkThe total number of equipment contained in the park comprehensive energy system;
wherein the energy utilization rate is defined as the ratio of the total energy output to the total energy input of the system, f2Is calculated as follows:
Figure BDA0002975673780000152
in the formula, σ2The weight corresponding to the average value of the energy utilization rate of the garden comprehensive energy system in the period is optimized.
Here, Pe,t，Pg,t，Le,tAnd Lh,tThe method is determined by utilizing a universal model of an 'electricity-heat-gas' energy concentrator corresponding to the park integrated energy system and the operation parameters of the park integrated energy system equipment reflected by the universal model.
2) According to the system energy coupling characteristic and the energy equipment operation characteristic, constructing an energy balance constraint, an energy conversion equipment and an energy storage equipment operation constraint for an objective function of a pre-constructed optimization scheduling model:
the energy balance constraint is calculated as follows:
the electric energy network model is established by node complex power balance, and a complex power balance equation is established for any node i in the power grid:
Figure BDA0002975673780000153
in the formula, SiFor complex power injected into grid node i, SijFor complex power flowing from grid node i to grid node j connected thereto,
Figure BDA0002975673780000161
in the form of a vector of the voltage of the grid node i,
Figure BDA0002975673780000162
in the form of a vector of the voltage of the grid node j, yijFor the transadmittance of line ij, yioIs the self-admittance of the grid node i;
the natural gas pipeline network model is established by node flow balance, and for any node theta in the natural gas pipeline, a flow balance equation is established:
∑mθ,θ(t)+∑mo,θ(t)＝0
in the formula, sigma mθ,θ(t) mass flow, kg/s, ∑ m, flowing into node θ for the t-th period of the optimization cycleo,θAnd (t) is the mass flow rate of the outflow node theta in the t-th period in the optimization cycle, kg/s.
And the energy conversion equipment is subjected to operation constraint:
and B, taking an equation related in the corrected general model of the electric-heat-gas energy hub in the step A as an equality constraint of the operation of the energy conversion equipment, and establishing an inequality constraint of the operation of the energy conversion equipment as follows:
Figure BDA0002975673780000163
in the formula, Pe maxAnd Pe minRespectively the upper and lower limit values, P, of the purchasing power of the park comprehensive energy systemg maxAnd Pg minRespectively the upper and lower limit values, P, of the gas purchasing power of the park comprehensive energy systemt PVThe output power P of the photovoltaic power generation unit in the t-th period in the optimization cycle in the park comprehensive energy systemPV maxRespectively, the maximum output power, P, of the photovoltaic power generation unitCHP max、PGB maxAnd PHP maxThe maximum loading capacities of the CHP unit, the gas boiler and the heat pump in the park comprehensive energy system are respectively.
The calculation formula of the energy storage device operation constraint is as follows:
Figure BDA0002975673780000164
in the formula, Pin maxAnd Pout maxRespectively providing the maximum energy charging power and the maximum energy discharging power for the energy storage equipment in the park comprehensive energy system, wherein M (t) is the energy storage quantity of the energy storage equipment in the park comprehensive energy system in the t period of the optimization cycle, MminAnd MmaxRespectively the maximum energy storage amount and the minimum energy storage amount of the energy storage equipment in the park comprehensive energy system.
And C: acquiring the electric load, the heat load and the load rate of the park in each period of an optimization cycle;
step D: substituting the electric load, the heat load and the load rate of the garden at each time interval of an optimization cycle into a pre-established optimization scheduling model, and solving the model by using a particle swarm algorithm to obtain the optimal solution of an optimization variable;
the optimization variables include: and the electricity purchasing power and gas purchasing power of the park comprehensive energy system in each time period of the optimization cycle, and the energy utilization power and the energy production power of each device in the park comprehensive energy system.
The particle swarm algorithm solving method specifically comprises the following steps:
initializing a particle swarm scale m, searching a space n, setting the maximum iteration number, giving a learning factor value and an initial value of inertia weight, and randomly initializing the space position and the speed of particles;
calculating a fitness function value of each particle in the particle swarm;
comparing the adaptive value of the current position Xk of each particle with the adaptive value corresponding to the historical optimal position Pk of each particle, if the adaptive value of the current position is higher, updating the historical optimal position of each particle by using the current position, otherwise, not updating;
comparing the adaptive value of the current position Xk of each particle with the adaptive value corresponding to the optimal position Gk of the population, if the adaptive value of the current position is higher, updating the optimal position of the population by using the current position, otherwise, not updating;
updating the speed and the position of each particle according to an iterative formula of the speed and the position of the particle, wherein the iterative formula is shown as the following formula:
Figure BDA0002975673780000171
wherein r1 and r2 are in the interval [0,1 ]]Random numbers which are uniformly distributed, c1 and c2 are learning factors which are both normal numbers, omega is inertia weight, Z is maximum iteration number, Z is current iteration number, omega is the current iteration numbermaxIs the maximum allowable value of inertia weight, omegaminIs the minimum allowable value of the inertia weight,
Figure BDA0002975673780000172
for z +1 th iteration
Figure BDA0002975673780000178
The position of the particles is determined by the position of the particles,
Figure BDA0002975673780000173
for the z-th iteration
Figure BDA00029756737800001711
The position of the particles is determined by the position of the particles,
Figure BDA0002975673780000174
for the z-th iteration
Figure BDA0002975673780000179
The velocity of the individual particles is determined,
Figure BDA0002975673780000175
for z +1 th iteration
Figure BDA00029756737800001710
The velocity of the individual particles is determined,
Figure BDA0002975673780000176
for the individual best position for the z-th iteration,
Figure BDA0002975673780000177
the best position of the group for the z-th iteration;
sixthly, judging whether the algorithm is finished or not, if the finishing condition is not met, returning to the step two, if the finishing condition is met, finishing the algorithm, and obtaining the optimal position of the population, namely the optimal solution of the target function.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (12)

1. A campus integrated energy system optimization scheduling method is characterized by comprising the following steps:
acquiring the predicted electric load, thermal load, load rate and photovoltaic power generation unit output of the park at each time interval of the optimization cycle;
substituting the electric load, the heat load, the output of the photovoltaic power generation unit and the load rate of the park at each time interval of the optimization cycle into a pre-established optimization scheduling model for solving to obtain the optimal solution of the electricity purchasing power and the gas purchasing power of the park comprehensive energy system at each time interval of the optimization cycle, the energy using power and the energy generating power of the energy generating equipment in the park comprehensive energy system and the charge-discharge energy power of the energy storing equipment in the park comprehensive energy system;
scheduling the park comprehensive energy system according to the optimal solution;
wherein the optimized scheduling model is established based on load rate modified energy hub model constraints.
2. The method of claim 1, wherein the construction of the optimized scheduling model comprises:
constructing an objective function with the goals of lowest operation cost and maximum energy utilization rate;
and constructing an energy balance constraint, an energy hub model constraint of load rate correction, an energy conversion equipment operation inequality constraint and an energy storage equipment operation constraint for the objective function.
3. The method according to claim 1 or 2, wherein the load rate modified energy hub model constraints are obtained by modifying energy conversion efficiency and distribution coefficients in the energy hub model using the load rate.
4. The method of claim 1 or 2, wherein the load rate corrected energy hub model constraint is calculated as follows:
Figure FDA0002975673770000011
in the formula, Pe,tThe electricity purchasing power P of the t period of the optimization cycle of the park comprehensive energy systemg,tRespectively the gas purchasing power L of the integrated energy system of the park in the t-th period in the optimization cyclee,tOutput electric power L of the comprehensive energy system of the park in the t period of the optimization cycleh,tFor the output thermal power of the park comprehensive energy system in the t period of the optimization cycle, Me,tFor the electric power storage, M, of the comprehensive energy system of the park in the t-th period of the optimization cycleg,tThe heat storage power v of the comprehensive energy system in the optimization periodHP(ξt) As the load factor is xitDistribution coefficient v of the heat pump in the t-th period of the optimization cycleCHP(ξt) As the load factor is xitDistribution coefficient, eta of the time-CHP unit in the t-th period of the optimization cycleHP(ξt) As the load factor is xitEnergy conversion efficiency of heat pump, etaCHP(ξt) As the load factor is xitEnergy conversion efficiency, eta, of hour-CHP unitsGB(ξt) As the load factor is xitEnergy conversion efficiency of time gas boiler unit, alphaCHP(ξt) As the load factor is xitThermoelectric ratio, ξ, of hour CHP unittTo optimize the duty cycle for the t-th period of the cycle.
5. A method as claimed in claim 3, wherein the load factor is ξtEnergy conversion efficiency eta of time-CHP unitCHP(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the energy conversion efficiency of the CHP unit based on a relation curve between the actual energy conversion efficiency and the load rate acquired under the actual working condition of the CHP unit;
the load ratio is xitThermoelectric ratio alpha of time-CHP unitCHP(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the thermoelectric ratio of the CHP unit based on a relation curve between the actual thermoelectric ratio and the load rate acquired under the actual working condition of the CHP unit;
the load ratio is xitEnergy conversion efficiency eta of time gas boilerGB(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the energy conversion efficiency of the gas-fired boiler based on a relation curve between the actual energy conversion efficiency and the load rate acquired under the actual working condition of the gas-fired boiler;
the load ratio is xitEnergy conversion efficiency eta of time-lapse heat pumpHP(ξt) The calculation formula is obtained by performing polynomial fitting on the load rate and the energy conversion efficiency of the heat pump based on a relation curve between the actual energy conversion efficiency and the load rate acquired under the actual working condition of the heat pump.
6. The method of claim 4, wherein the duty ratio is ξtEnergy conversion efficiency eta of time-CHP unitCHP(ξt) Is calculated as follows:
ηCHP(ξt)＝k1ξt 4+k2ξt 3+k3ξt 2+k4ξt+k0
in the formula, k0Is etaCHP(ξt) Coefficient of constant term, k, in the formula4Is etaCHP(ξt) Coefficient of first order term, k, in the formula3Is etaCHP(ξt) Coefficient of quadratic term, k, in the formula2Is etaCHP(ξt) Coefficient of cubic term, k, in the formula1Is etaCHP(ξt) Coefficient of quartic term in the calculation formula (1);
the load ratio is xitThermoelectric ratio alpha of time-CHP unitCHP(ξt) Is calculated as follows:
αCHP(ξt)＝k2'ξt 2+k1'ξt+k0'
in the formula, k0' is alphaCHP(ξt) Coefficient of constant term, k, in the formula1' is alphaCHP(ξt) Coefficient of first order term, k, in the formula2' is alphaCHP(ξt) Coefficient of quadratic term in the calculation formula (1);
the load ratio is xitEnergy conversion efficiency eta of time gas boilerGB(ξt) Is calculated as follows:
Figure FDA0002975673770000021
in the formula (I), the compound is shown in the specification,
Figure FDA0002975673770000022
is etaGB(ξt) The coefficient of the constant term in the calculation formula (2),
Figure FDA0002975673770000023
is etaGB(ξt) Coefficient of a first order term in the calculation formula (1);
the load ratio is xitEnergy conversion efficiency eta of time-lapse heat pumpHP(ξt) Is calculated as follows:
Figure FDA0002975673770000031
in the formula (I), the compound is shown in the specification,
Figure FDA0002975673770000032
is etaHP(ξt) The coefficient of the constant term in the calculation formula (2),
Figure FDA0002975673770000033
is etaHP(ξt) The coefficient of the first order term in the calculation formula (2),
Figure FDA0002975673770000034
is etaHP(ξt) Coefficient of quadratic term in the calculation formula (2).
7. The method of claim 4, wherein the load rate corrected energy hub model constraint calculation further comprises:
Figure FDA0002975673770000035
Figure FDA0002975673770000036
Figure FDA0002975673770000037
Figure FDA0002975673770000038
Figure FDA0002975673770000039
Figure FDA00029756737700000310
in the formula (I), the compound is shown in the specification,
Figure FDA00029756737700000311
for the output electric power of the CHP unit in the t-th period of the optimization cycle,
Figure FDA00029756737700000312
for the input natural gas power of the CHP unit in the t-th period of the optimization cycle,
Figure FDA00029756737700000313
for the output thermal power of the CHP unit in the t-th period of the optimization cycle,
Figure FDA00029756737700000314
for the output thermal power of the gas boiler in the t period of the optimization cycle,
Figure FDA00029756737700000315
for the input natural gas power of the gas boiler in the t period in the optimization cycle,
Figure FDA00029756737700000316
to optimize the output thermal power of the heat pump during the tth period of the cycle,
Figure FDA00029756737700000317
the input electric power of the heat pump in the t period in the optimization cycle is obtained.
8. The method of claim 2, wherein the objective function is calculated as follows:
F＝minf1+maxf2
wherein F is the value of the objective function, F1To optimize the operating cost of the park's integrated energy system in the period, f2The energy utilization rate average value of the garden comprehensive energy system in the period is optimized.
9. The method of claim 8, wherein the optimization cycle is based on an operating cost f of the campus energy complex system1Is calculated as follows:
Figure FDA0002975673770000041
in the formula, σ1For optimizing the weight corresponding to the operating cost of the district's integrated energy system in the period, Ce,tTo optimize the electricity price in the t-th period of the cycle, Cg,tTo optimize natural gas prices, C, for the t-th period of the cycleM,kFor the unit power operation maintenance cost, P, of the kth equipment in the park integrated energy systeme,tThe electricity purchasing power P of the t period of the optimization cycle of the park comprehensive energy systemg,tRespectively the gas purchasing power P of the integrated energy system of the park in the t-th period of the optimization cycleout,k,tThe output power of the kth equipment in the optimization period in the comprehensive energy system of the park is T from (1 to T), T is the total time period contained in the optimization period, i from (1 to S)k)，SkThe total number of equipment contained in the park comprehensive energy system;
the average value f of the energy utilization rate of the garden comprehensive energy system in the optimization period2Is calculated as follows:
Figure FDA0002975673770000042
in the formula, σ2For optimizing the weight corresponding to the average value of the energy utilization rate of the park comprehensive energy system in the period, Le,tOutput electric power L of the comprehensive energy system of the park in the t period of the optimization cycleh,tAnd outputting thermal power for the comprehensive energy system of the park in the tth period of the optimization cycle.
10. The method of claim 2, wherein the energy conversion device operates under the inequality constraint calculated as follows:
Figure FDA0002975673770000043
in the formula, Pe maxThe upper limit value P of the electricity purchasing power of the park comprehensive energy systeme minFor the lower limit value, P, of the purchasing power of the park's integrated energy systemg maxIs the upper limit value, P, of the gas purchasing power of the park comprehensive energy systemg minFor the lower limit value, P, of the purchasing power of the park's integrated energy systemt PVThe output power P of the photovoltaic power generation unit in the t-th period in the optimization cycle in the park comprehensive energy systemPV maxIs the maximum output power, P, of the photovoltaic power generation unitCHP maxFor the maximum load capacity, P, of the CHP units in the park complex energy systemGB maxFor the maximum loading capacity, P, of the gas-fired boiler in the park complex energy systemHP maxThe maximum loading capacity of the heat pump in the park integrated energy system.
11. The method of claim 1, wherein the energy-producing device comprises: the system comprises a photovoltaic power generation unit, a CHP unit, a gas boiler and a heat pump;
the energy storage device includes: an electricity storage device and a heat storage device.
12. An optimal scheduling system for a park integrated energy system, the system comprising:
the acquisition module is used for acquiring the predicted electric load, thermal load, load rate and photovoltaic power generation unit output of the park at each time interval of the optimization cycle;
the solving module is used for substituting the electric load, the heat load, the output power and the load rate of the photovoltaic power generation unit of the park in each time period of the optimization cycle into a pre-established optimization scheduling model for solving to obtain the optimal solution of the electricity purchasing power and the gas purchasing power of the park comprehensive energy system in each time period of the optimization cycle, the energy using power and the capacity generating power of the capacity generating equipment in the park comprehensive energy system and the charge-discharge energy power of the energy storage equipment in the park comprehensive energy system;
the scheduling module is used for scheduling the park comprehensive energy system according to the optimal solution;
wherein the optimized scheduling model is established based on load rate modified energy hub model constraints.
CN202110273830.1A 2021-03-15 2021-03-15 Optimal scheduling method and system for park comprehensive energy system Pending CN112966869A (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112308321A (en) * 2020-11-03 2021-02-02 国网四川省电力公司经济技术研究院 Optimized dispatching system for park comprehensive energy system
CN113806952A (en) * 2021-09-24 2021-12-17 沈阳工程学院 Source-load-storage-considered cooling, heating and power comprehensive energy system and optimized operation method thereof
CN116596279A (en) * 2023-07-14 2023-08-15 中通服建设有限公司 Intelligent park energy consumption scheduling system
CN116596279B (en) * 2023-07-14 2024-04-26 中通服建设有限公司 Intelligent park energy consumption scheduling system

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112308321A (en) * 2020-11-03 2021-02-02 国网四川省电力公司经济技术研究院 Optimized dispatching system for park comprehensive energy system
CN113806952A (en) * 2021-09-24 2021-12-17 沈阳工程学院 Source-load-storage-considered cooling, heating and power comprehensive energy system and optimized operation method thereof
CN113806952B (en) * 2021-09-24 2024-02-27 沈阳工程学院 Cold-hot electricity comprehensive energy system considering source-charge-storage and optimal operation method thereof
CN116596279A (en) * 2023-07-14 2023-08-15 中通服建设有限公司 Intelligent park energy consumption scheduling system
CN116596279B (en) * 2023-07-14 2024-04-26 中通服建设有限公司 Intelligent park energy consumption scheduling system

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