CN115600759A - CSP and P2G-containing comprehensive energy system optimal scheduling method considering controllable load - Google Patents

CSP and P2G-containing comprehensive energy system optimal scheduling method considering controllable load Download PDF

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CN115600759A
CN115600759A CN202211377214.1A CN202211377214A CN115600759A CN 115600759 A CN115600759 A CN 115600759A CN 202211377214 A CN202211377214 A CN 202211377214A CN 115600759 A CN115600759 A CN 115600759A
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任永峰
孟庆天
云平平
李兴国
米玥
任博
刘佳树
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Inner Mongolia University of Technology
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Abstract

The invention relates to an optimized scheduling method of an integrated energy system with CSP and P2G considering controllable loads. The integrated energy system includes: the system comprises a photovoltaic power generation unit, a wind power generation unit, a thermal power generation unit, a photo-thermal power generation unit, a thermal power waste heat collection unit, a photo-thermal waste heat collection unit, a gas boiler unit, a double-layer electricity-to-gas unit, a thermal energy storage unit, an electric load unit and a thermal load unit; the optimization scheduling comprises the following processes: establishing an objective function; inputting simulation data; building a model by using a YALMIP toolbox; setting different installation permeabilities in different scenes; calling a CPLEX solver to carry out simulation solving; and obtaining an optimized scheduling result. The photo-thermal power station improves the scheduling flexibility of the renewable energy at the source side; the storage side double-layer electricity-to-gas system effectively improves the consumption and utilization of new energy.

Description

CSP and P2G-containing comprehensive energy system optimal scheduling method considering controllable load
The technical field is as follows:
the invention relates to a distributed energy system, in particular to a CSP and P2G integrated energy system optimal scheduling method considering controllable load.
Background art:
on the background of the modern environmental and energy crisis problems becoming more serious, renewable energy power generation is taking an increasingly important position. In order to cope with the impact of high-proportion new energy access on a power system, how to fully and reasonably schedule flexible resources on three sides of 'source-storage-load' of the power system becomes the central importance, and energy flow cooperation technologies such as electric energy flow, hydrogen energy flow and heat energy flow provide a new research direction for the consumption of renewable energy sources with obvious peak counter-regulation characteristics such as wind power and photovoltaic.
Currently, many researchers have conducted research on the problem of scheduling optimization of IES, but the attention is focused on one side of the IES, namely "source-store-load". A source side solar thermal power station (CSP) has the capability and function of providing system backup and absorbing new energy as a flexible power source. Coupling the electric boiler into the CSP power station and converting redundant electric energy into heat energy, utilizing the CSP power station heat-retaining system to realize energy storage, reducing the scheduling pressure of the cogeneration unit and promoting the wind power consumption of the system. The photo-thermal power station has good dispatching characteristics due to the unique working principle. The electric heater and the CSP power station containing heat storage are operated jointly, and the electric heater and the CSP power station are considered to provide rotary standby for the system together, so that the system scheduling flexibility can be effectively improved, and the dependence of the system on a thermal power generating unit is reduced. By introducing the IES into the CSP power station, the consumption level of new energy is improved, the utilization rate of the CSP unit is improved, and the carbon emission of the system is reduced.
The CSP power station has the energy time shifting characteristic compared with other renewable energy power stations. Because the CSP power station is provided with the molten salt heat storage equipment, the electrically coupled CSP power station can store heat energy converted by mirror field heat collection, wind abandoning and light abandoning power into the heat storage system in the load demand valley period. While releasing the stored heat during peak load demand periods. In a comprehensive energy system with high installed permeability of new and new energy in the future, photo-thermal power generation becomes an important peak regulation means.
The storage side has an energy storage function and realizes the multi-directional flow of energy at the same time by a double-layer power-to-gas (P2G) system. The P2G technology can not only solve the problems of surplus and waste of energy, but also further deepen the coupling between the power grid and the natural gas grid. However, the P2G energy conversion rate in the whole process is low, which is not beneficial to the efficient utilization of energy. In the electricity-gas comprehensive energy system, a graded P2G system is provided, the whole process of converting electricity into natural gas is divided into two steps of converting electricity into hydrogen and converting electricity into natural gas, and a double-energy closed loop moving coil is formed by the whole process of converting electricity into natural gas and the whole process of converting electricity into hydrogen and the whole process of converting electricity into natural gas respectively with a hydrogen fuel cell and a micro gas engine, so that the multidirectional flow and the cascade utilization of energy are realized.
And excavating the controllable load on the load side to realize the operation flexibility. Thermal compliance loads are considered to reduce energy waste while not disrupting the user experience.
With the increase of the permeability of new energy installation, the scheduling flexibility of the comprehensive energy system is continuously reduced, and how to coordinate the source storage and the load storage is the key for coping with the difficulty in stable operation of the comprehensive energy system due to the continuous increase of the permeability of the new energy installation.
The invention content is as follows:
the invention provides an IES optimization scheduling model considering controllable load, including an electric coupling optical thermal power station and double-layer electric gas transfer, and considering how to improve the economy and low carbon of the IES from three aspects of source, storage and load. The specific technical scheme is as follows:
the CSP and P2G-containing integrated energy system optimization scheduling method considering controllable load comprises the following steps: the system comprises a photovoltaic power generation unit, a wind power generation unit, a thermal power generation unit, a photo-thermal power generation unit, a thermal power waste heat collection unit, a photo-thermal waste heat collection unit, a gas boiler unit, a double-layer electricity-to-gas unit, a hydrogen energy storage unit, a hydrogen fuel cell, a thermal energy storage unit, an electric load unit and a thermal load unit; the method comprises the following steps:
the comprehensive energy system takes the lowest operation cost as a target to optimize the output of each device in the system; meanwhile, as the response of the demand side is user-oriented, the lowest comprehensive electricity utilization cost of the user is taken as a target; the objective function is established as follows:
minF＝α·(C 1 +C 2 +C 3 +C 4 )+β·C 5 ，
where F represents the total cost of system operation, α, β are proportional parameters, α + β =1, α =0.6, β =0.4 when considering the electrical load demand response, α =1, β =0, c when not considering the electrical load demand response 1 Representing the equipment operation and maintenance cost, C 2 Represents the cost of carbon treatment, C 3 Representing the cost of energy purchase, C 4 Representing the cost of wind and light abandonment;
equipment operation and maintenance cost:
Figure BDA0003927206030000021
wherein T represents total operation time, N represents the number of operation and maintenance equipment, and C W-i Representing i operating maintenance costs of the plant, p i Representing the output of the i device;
carbon treatment cost:
Figure BDA0003927206030000022
in the formula:
Figure BDA0003927206030000031
represents the carbon dioxide processing cost, λ b Representing the amount of carbon dioxide produced per unit of natural gas burned,
Figure BDA0003927206030000032
representing the heat value of natural gas, eta b Representing the efficiency of the gas boiler, H b Representing the total output, λ, of the gas-fired boiler tp Representing the amount of carbon dioxide, P, produced per unit of electricity in a thermal power plant tp Representing the total output of thermal power, λ g The carbon yield index is obtained on behalf of the unit power methane reactor,
Figure BDA0003927206030000033
represents the total power of the methane reactor;
energy purchase cost:
Figure BDA0003927206030000034
in the formula: g c Represents the coal purchase price, mu tp Representing the coal consumption per unit of electricity of the thermal power plant,
Figure BDA0003927206030000035
represents the time-of-use natural gas value;
abandon wind and abandon light cost:
C 4 ＝λ a ·(P w-a +P pv-a )，
in the formula, λ a Represents wind and light abandon penalty, P w-a Representing the waste air volume, p pv-a Representing the light rejection amount;
the constraints are as follows:
and power balance constraint:
Figure BDA0003927206030000036
in the formula, p csp Representing the output of the photothermal power station, p w Representing wind power output, p pv Representing the photovoltaic contribution, p fc Representing fuel cell output, p ec Representing the cell power, p h Representing electric heater power, p L Representing the electrical load, h tp Representing thermal power output, h csp RepresentsThe thermal output of the photo-thermal power station;
and (3) equipment start and stop restraint:
Figure BDA0003927206030000037
in the formula, D represents a start-stop state indicating variable, onoff i Representing the start-stop state of the i equipment by binary variables, range representing a starting Range variable, T on Represents a minimum continuous start-up time;
and (4) energy storage system constraint:
Figure BDA0003927206030000041
in the formula, Q cspmin 、Q cspmax Respectively representing the upper and lower limit capacities, Q, of the heat energy storage system csp Representing the energy stored in the thermal storage system at time t. Eta heat Represents the thermal insulation coefficient, q m The mirror field of the representative photo-thermal power station collects heat values, and the hydrogen energy storage system is similar to the heat storage system and is not described in detail.
And (3) restraining the upper and lower limits of the output of the equipment:
onoff i ·(t)P imin ≤p i (t)≤onoff i (t)·P imax ，
in the formula, P imin 、P imax Representing the upper and lower output limits of the i equipment;
unit climbing restraint:
P iCn ≤p i (t+1)-p i (t)≤P iCp ，
in the formula, P iCn 、P iCp Representing the maximum upward and downward climbing power of the device;
restraint of renewable energy sources:
Figure BDA0003927206030000042
in the formula, P wmax Representing the maximum available wind power output, P pvmax Represents the maximum available output of the photovoltaic;
device contradiction constraints: the constraint is to prevent the energy storage system from charging and discharging energy at the same time,
Figure BDA0003927206030000043
the solving method comprises the following steps:
step 1: inputting simulation data;
step 2: building a model by using a YALMIP toolbox;
and step 3: setting different installation permeabilities in different scenes;
and 4, step 4: calling a CPLEX solver to carry out simulation solving;
and 5: and obtaining an optimized scheduling result.
Aiming at the problems of green, low carbon and strategy optimization in the comprehensive energy system, the patent establishes a day-ahead optimization scheduling model of the comprehensive energy system considering controllable load, a photo-thermal power station and electricity-to-gas from three aspects of source-storage-load. Through simulation modeling and example analysis, the method has the following beneficial effects:
the photo-thermal power station effectively improves the scheduling flexibility of the renewable energy at the source side by means of the energy time shifting characteristic. The storage side double-layer electricity-to-gas system can effectively improve the consumption and utilization of new energy through hierarchical management.
The load side respectively considers the operation scenes of electric load demand response and thermal flexible load, the load transfer is realized by utilizing the influence mechanism of controllable load, the consumption level and the economic benefit of renewable energy sources are effectively improved, and simultaneously the carbon emission is reduced.
Description of the drawings:
fig. 1 is an integrated energy system framework diagram.
FIG. 2 is a schematic diagram of an electrically coupled photothermal power station.
Fig. 3 is a schematic diagram of the double-layer electric-to-gas conversion.
FIG. 4 is a flow chart of an optimized schedule analysis in an embodiment.
FIG. 5 is a predicted value of renewable energy output in an embodiment; in the figure, the abscissa represents the time and the ordinate represents the power value.
FIG. 6 shows predicted values of electrical, thermal load and temperature for an embodiment; in the figure, the abscissa represents time, the left ordinate represents power value, and the right ordinate represents temperature.
The specific implementation mode is as follows:
the embodiment is as follows:
a model is constructed by taking an industrial park as a reference, and the real-time price of park energy is shown in a table 1.
TABLE 1 time-sharing energy prices in the park
Figure BDA0003927206030000051
The relevant parameter data of the system unit are shown in a table 2.
TABLE 2 IES Unit parameters
Figure BDA0003927206030000061
The predicted output of renewable energy sources before the day of a typical winter day of the park is shown in fig. 5, and the predicted curves of electricity, heat load and outdoor temperature are shown in fig. 6. The electric load demand response and the thermal flexible load are introduced into the comprehensive energy system, and the influence of the electric load demand response and the thermal flexible load on the day-ahead optimal scheduling of the comprehensive energy system is researched. The following four scenarios are set:
scene one: and in a basic scene, the day-ahead optimization scheduling of the comprehensive energy system without considering the electric load demand response and the thermal flexible load.
Scene two: and only considering the day-ahead optimal scheduling of the comprehensive energy system of the thermal flexible load on the basis of a basic scene.
Scene three: and only considering the day-ahead optimized scheduling of the comprehensive energy system of the electric load demand response on the basis scene.
Scene four: and meanwhile, the day-ahead optimized scheduling of the comprehensive energy system considering the electric load demand response and the thermal flexible load is carried out.
And (4) analyzing a scene four scheduling result: the output condition and the load scheduling condition of each device of the comprehensive energy system are analyzed and known as follows: the energy that the source side light and heat power station utilized its electrothermal energy time shift characteristic to store daytime is released at night according to the dispatch demand, has improved the operation flexibility of system. The storage side double-layer electric gas conversion system absorbs the abandoned wind and abandoned light power in stages, and the fuel cell supplies energy to the system at the load peak period, so that the coupling of each energy system is deepened, and the grading high-efficiency absorption and utilization of the abandoned wind and abandoned light power are realized while the energy storage is realized. The charge side electric energy part realizes the transfer of price type load along with the time-of-use electricity price by using the demand response characteristic, and the peak clipping function of the charge side electric energy part in a period of 16-23: period 00-07 and period 10-00. The peak value dispatching pressure of the user side of the power system is reduced, the electricity utilization cost of the user is reduced, and meanwhile, the excitation type load is not started, so that the system can be used as an emergency standby of the system, and the stable operation of the system is ensured under the condition that the new energy output is suddenly reduced. The heat energy part reduces the output of the gas boiler in two high natural gas price periods of 9. The heat load is transferred along with the time-sharing natural gas price, so that the system energy purchasing cost is reduced. Meanwhile, by utilizing a thermal flexible load operation mechanism, under the condition of ensuring that the heat supply effect of a user is not changed, the refined utilization of energy is realized. The heat energy supply is changed from the traditional high-emission and extensive energy supply mode to a low-carbon, user-friendly and intelligent future energy supply mode.
The scene comparison results analysis is shown in table 3.
TABLE 3 System operation results under different scenarios
Figure BDA0003927206030000071
The total system operation cost and the total carbon emission of the scenes I, II, III and IV are summarized in a table 3, and analysis shows that the comprehensive energy system operation cost and the carbon emission can be reduced by respectively considering the electric load demand response and the thermal flexible load. The electric load demand response is excellent in the consumption of new energy and the reduction of carbon emission, and the effect of reducing the operation cost by the thermal flexible load is remarkable. Under the condition of comprehensively considering the electric load demand response and the thermal flexible load, the system operation cost is reduced by 9.97 ten thousand yuan, and the comparable reduction is 6.68%. The carbon emission is reduced by 214.6 tons, and the carbon emission is reduced by 13.3 percent on the same scale. The wind and light abandoning rate is reduced by about 6 percentage points, and the light and electricity abandoning amount is 96.6 MW.
And (3) new energy installed permeability analysis: and taking a comprehensive energy system with the new energy installed permeability of 60% as a reference. Keeping the total loading quantity unchanged, proportionally amplifying the new energy loading quantity in the system, and proportionally reducing the thermal power loading quantity until the new energy loading quantity reaches 100%. As a result, when the new energy loading capacity is increased from 60% to 80%, the system cost and the carbon emission are uniformly reduced, and the maintenance cost, the carbon treatment cost and the coal purchase cost of the thermal power equipment are reduced due to the increase of the new energy loading capacity and the reduction of the thermal power output and the loading capacity. When the new energy installation rate reaches 90%, the scene one and the scene two cannot operate, the scene three and the scene four not only operate normally, and the operation cost and the carbon emission level are also obviously reduced. The operation of a scene one and a scene two cannot be performed due to the fluctuation of new energy, randomness and insufficient thermal power scheduling resources, and the operation of a comprehensive energy system is maintained due to the fact that the scene three and the scene four consider the electric load demand response. When the permeability of the new energy installation machine is increased from 90% to 100%, the reduction trend of cost and carbon emission is slowed down, because the comprehensive energy system can completely depend on the new energy for energy supply when 90% of the new energy is installed, and the operation cost and the carbon emission basically have no reduced space.
And (3) analyzing the installation scene of 100% new energy: when the new energy installation reaches 100%, the scheduling flexibility of the system is greatly reduced. The working time and the working power of the energy storage system are greatly increased compared with the basic situation, and the purpose is to replace scheduling resources reduced due to the lack of thermal power. Wherein the power portion 06. The heat energy is partly due to the reduction of thermal power, more energy supply pressure is dropped on the gas boiler, and the gas boiler is close to full power operation in the period of 01.

Claims (1)

1. The optimized scheduling method of the comprehensive energy system with CSP and P2G considering controllable load comprises the following steps: the system comprises a photovoltaic power generation unit, a wind power generation unit, a thermal power generation unit, a photo-thermal power generation unit, a thermal power waste heat collection unit, a photo-thermal waste heat collection unit, a gas boiler unit, a double-layer electricity-to-gas unit, a hydrogen energy storage unit, a hydrogen fuel cell, a thermal energy storage unit, an electric load unit and a thermal load unit; the method is characterized by comprising the following steps:
the comprehensive energy system takes the lowest operation cost as a target to optimize the output of each device in the system; meanwhile, as the response of the demand side is user-oriented, the lowest comprehensive electricity utilization cost of the user is taken as a target; the objective function is established as follows:
min F＝α·(C 1 +C 2 +C 3 +C 4 )+β·C 5 ，
where F represents the total cost of system operation, α, β are proportional parameters, α + β =1, α =0.6, β =0.4 when considering the electrical load demand response, α =1, β =0, c when not considering the electrical load demand response 1 Representing the equipment operation and maintenance cost, C 2 Represents the cost of carbon treatment, C 3 Representing the cost of energy purchase, C 4 Representing the cost of wind and light abandonment;
equipment operation and maintenance cost:
Figure FDA0003927206020000011
wherein T represents total operation time, N represents the number of operation and maintenance equipment, and C W-i Representing i operating maintenance costs of the plant, p i Representing the output of the i device;
carbon treatment cost:
Figure FDA0003927206020000012
in the formula:
Figure FDA0003927206020000013
represents the carbon dioxide treatment cost, lambda b Representing the amount of carbon dioxide produced per unit of natural gas burned,
Figure FDA0003927206020000014
representing the heat value of natural gas, eta b Representing the efficiency of the gas boiler, H b Representing the total output, λ, of the gas-fired boiler tp Representing the amount of carbon dioxide, P, produced per unit of electricity in a thermal power plant tp Representing the total output of thermal power, λ g The carbon yield index is obtained on behalf of the unit power methane reactor,
Figure FDA0003927206020000015
represents the total power of the methane reactor;
energy purchase cost:
Figure FDA0003927206020000016
in the formula: g c Represents the coal purchase price, mu tp Representing the coal consumption per unit of electricity of the thermal power plant,
Figure FDA0003927206020000017
represents the time-of-use natural gas price;
abandon wind and abandon light cost:
C 4 ＝λ a ·(P w-a +P pv-a )，
in the formula, λ a Represents wind and light abandon penalty, P w-a Representing the waste air volume, p pv-a Representing the amount of abandoned light;
the constraints are as follows:
and power balance constraint:
Figure FDA0003927206020000021
in the formula, p csp Representing the output of the photothermal power station, p w Representative of wind power output, p pv Representing the photovoltaic contribution, p fc Representing fuel cell output, p ec Representing the cell power, p h Representing electric heater power, p L Representing the electrical load, h tp Representing thermal power output, h csp Representing the thermal output of the photo-thermal power station;
and (3) equipment start and stop restraint:
Figure FDA0003927206020000022
in the formula, D represents a start-stop state indicating variable, onoff i Representing the start-stop state of the i equipment by binary variables, range representing a starting Range variable, T on Represents a minimum continuous start-up time;
and (4) energy storage system constraint:
Figure FDA0003927206020000023
in the formula, Q cspmin 、Q cspmax Respectively representing the upper and lower limit capacities, Q, of the heat energy storage system csp Representing the energy stored in the heat storage system at time t, eta heat Represents the thermal insulation coefficient, q m The method is characterized in that the method represents that the mirror field of the photo-thermal power station collects heat values, and a hydrogen energy storage system is similar to a heat storage system;
and (3) restraining the upper and lower limits of the output of the equipment:
onoff i ·(t)P imin ≤p i (t)≤onoff i (t)·P imax ，
in the formula, P imin 、P imax Representing the upper and lower output limits of the i equipment;
unit climbing restraint:
P iCn ≤p i (t+1)-p i (t)≤P iCp ，
in the formula, P iCn 、P iCp Representing the maximum upward and downward climbing power of the device;
restraint of renewable energy sources:
Figure FDA0003927206020000031
in the formula, P wmax Representing the maximum available wind power output, P pvmax Represents the maximum available output of the photovoltaic;
device contradiction constraints: the constraint is to prevent the energy storage system from charging and discharging energy at the same time,
Figure FDA0003927206020000032
the solving method comprises the following steps:
step 1: inputting simulation data;
step 2: building a model by using a YALMIP toolbox;
and step 3: setting different installation permeabilities in different scenes;
and 4, step 4: calling a CPLEX solver to carry out simulation solving;
and 5: and obtaining an optimized scheduling result.
CN202211377214.1A 2022-11-04 2022-11-04 CSP and P2G-containing comprehensive energy system optimal scheduling method considering controllable load Pending CN115600759A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116169682A (en) * 2023-03-15 2023-05-26 国网湖北省电力有限公司十堰供电公司 Comprehensive energy system optimization scheduling strategy considering carbon emission flow and wind-solar energy consumption
CN116718059A (en) * 2023-08-07 2023-09-08 山西中能天胜科技有限公司 Power station peak shaving system and method based on high-capacity high-temperature molten salt energy storage

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116169682A (en) * 2023-03-15 2023-05-26 国网湖北省电力有限公司十堰供电公司 Comprehensive energy system optimization scheduling strategy considering carbon emission flow and wind-solar energy consumption
CN116169682B (en) * 2023-03-15 2023-10-24 国网湖北省电力有限公司十堰供电公司 Comprehensive energy system optimization scheduling strategy considering carbon emission flow and wind-solar energy consumption
CN116718059A (en) * 2023-08-07 2023-09-08 山西中能天胜科技有限公司 Power station peak shaving system and method based on high-capacity high-temperature molten salt energy storage
CN116718059B (en) * 2023-08-07 2023-10-27 山西中能天胜科技有限公司 Power station peak shaving system and method based on high-capacity high-temperature molten salt energy storage

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