CN114565245A - Comprehensive energy system optimization scheduling method and device considering electricity, cold and heat - Google Patents
Comprehensive energy system optimization scheduling method and device considering electricity, cold and heat Download PDFInfo
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Abstract
The invention provides an optimized scheduling method, an optimized scheduling device, electronic equipment and a medium for an integrated energy system, wherein the method comprises the following steps: establishing an objective function of the optimized scheduling of the comprehensive energy system, and determining constraint conditions of the optimized scheduling; solving the objective function by adopting an improved elite lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system; and scheduling the comprehensive energy system according to the optimal scheduling scheme. The method can generate the comprehensive energy system optimization scheduling scheme which meets practical production requirements and has good robustness of real-time optimization scheduling.
Description
Technical Field
The invention relates to the technical field of comprehensive energy complementary optimization scheduling, in particular to a comprehensive energy system optimization scheduling method, a comprehensive energy system optimization scheduling device, electronic equipment and a comprehensive energy system optimization scheduling medium.
Background
The comprehensive energy system is considered to be one of important forms of future energy utilization by virtue of the characteristics of cleanness and high efficiency, mainly focuses on 'ubiquitous interconnection' between a power system and a natural gas system and between a thermodynamic system and fusion between information and a physical system, considers the problems of information communication, internet of things and the like on the basis of the research of energy internet, and emphasizes the complex interaction between subsystem information flow and energy flow. The natural gas power generation is an effective way for relieving regional energy shortage, reducing the coal-fired power generation proportion and reducing the environmental pollution, and can provide considerable heat for a regional heat supply network. From the environmental benefit, sulfur dioxide discharged by the natural gas combusted by the same power generation amount is less than one thousandth of that of coal combusted, nitrogen oxide discharged is less than fifty percent of that of coal combusted, and the combustion product of the natural gas does not contain solids such as ash slag, so that the water consumption is reduced by two thirds compared with that of coal combusted, and the occupied area is reduced by about fifty percent.
The comprehensive energy system fully competes for guiding energy sources to be converted between different forms in the most efficient mode through cross-energy source and multi-space-time cooperation in multiple links of development, conversion, storage, transportation, scheduling, consumption and the like, so that multi-step effective utilization of the energy sources is realized, and intermittent renewable energy sources are fully consumed. The reasonable optimization scheduling of the comprehensive energy system has important significance for comprehensive utilization of energy and environmental protection.
Disclosure of Invention
The invention aims to provide an optimized scheduling method, electronic equipment and medium for an integrated energy system, and the optimized scheduling method, the electronic equipment and the medium for the integrated energy system can generate an optimized scheduling scheme of the integrated energy system, which meets practical production requirements and has better robustness for real-time optimized scheduling, by applying a lion group algorithm to the optimized scheduling of the integrated energy system.
Specifically, the invention is realized by the following technical scheme:
in a first aspect, the present invention provides an optimized scheduling method for an integrated energy system, where the method includes:
establishing an objective function of the optimized scheduling of the comprehensive energy system, and determining constraint conditions of the optimized scheduling;
solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system;
and scheduling the comprehensive energy system according to the optimal scheduling scheme.
Further, the establishing of the objective function of the optimal scheduling of the integrated energy system includes:
constructing an integrated energy system model, establishing an objective function of the integrated energy system optimization scheduling according to the integrated energy system model,
the comprehensive energy system model comprises at least one of a cogeneration unit model, a solar photovoltaic power generation system model, an electric refrigeration unit model and a compressed air preparation system model.
Further, the objective function is expressed as a total cost equal to the sum of total daily electricity purchase costs, costs for fuel purchase, solar photovoltaic generation costs, and municipal steam purchase costs of a typical integrated energy system.
Further, the constraints include device contribution constraints and electrical balance constraints, wherein the device contribution constraints are expressed as:
Pgen，min≤Pgen≤Pgen，max
in the formula Pgen，min，Pgen，maxLower and upper output power limits for the generator power;
the electrical balance constraint is expressed as:
PPV+Pbuy+PCHP＝Pin，voec+Pin，HP
in the formula PPVIs photovoltaic power generation workThe ratio; pbuyIs the electricity purchase amount of the scheduling period; pCHPThe external output electric power of the cogeneration unit is represented; pin，voecIs the power consumed by the electric refrigerating unit; pin，HPIs the input electrical power of the heat pump.
Furthermore, the input quantity of the lion group algorithm comprises an initial position, a population size, a lion ratio and iteration times, and the output quantity of the lion group algorithm is a lion king position, namely an optimal scheduling scheme.
Further, the lion group algorithm comprises the following steps:
initializing all parameters of the lion group, wherein the parameters comprise the positions of a lion king, a parent lion and a young lion in the lion group, the size of the species group and the number of iterations;
calculating a fitness value, and updating a global optimal position and a historical optimal position;
and judging whether the maximum iteration times is reached, outputting an optimal solution if the maximum iteration times is reached, and otherwise, updating the positions of various lions in the lion group.
Further, the total cost in the objective function ignores the solar photovoltaic power generation cost, i.e., the solar photovoltaic power generation cost is set to 0.
In a second aspect, the present invention provides an integrated energy system optimization scheduling apparatus, including:
the function and constraint construction unit is used for establishing an objective function of the optimized scheduling of the comprehensive energy system and determining constraint conditions of the optimized scheduling;
the optimal scheduling scheme calculation unit is used for solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system;
and the optimized scheduling unit schedules the comprehensive energy system according to the optimal scheduling scheme.
In a third aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the steps of the method for optimizing and scheduling an integrated energy system according to the first aspect.
In a fourth aspect, the present invention provides a non-transitory computer readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for optimized scheduling of an integrated energy system according to the first aspect.
According to the method, the device and the medium for optimizing and scheduling the comprehensive energy system, the comprehensive energy system can be optimized and scheduled and practical production requirements can be met by establishing an objective function of the optimizing and scheduling of the comprehensive energy system, determining a constraint condition of the optimizing and scheduling, solving the objective function by adopting a lion group algorithm according to the constraint condition, obtaining an optimal scheduling scheme of the comprehensive energy system, and scheduling the comprehensive energy system according to the optimal scheduling scheme.
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In order to more clearly illustrate the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of an integrated energy system optimization scheduling method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of an integrated energy system optimal scheduling device according to an embodiment of the invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, 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.
The various terms or phrases used herein have the ordinary meaning as is known to those skilled in the art, and even then, it is intended that the present invention not be limited to the specific terms or phrases set forth herein. To the extent that the terms and phrases referred to herein have a meaning inconsistent with the known meaning, the meaning ascribed to the present invention controls; and have the meaning commonly understood by a person of ordinary skill in the art if not defined herein.
Fig. 1 is a flowchart of an integrated energy system optimization scheduling method according to an embodiment of the present invention. Referring to fig. 1, the method for optimizing and scheduling an integrated energy system may include the steps of:
step 101: establishing an objective function of the optimized scheduling of the comprehensive energy system, and determining constraint conditions of the optimized scheduling;
step 102: solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system;
step 103: and scheduling the comprehensive energy system according to the optimal scheduling scheme.
Specifically, in this embodiment, before step 101, an integrated energy system model needs to be constructed first, and then an objective function of the optimal scheduling of the integrated energy system is established according to the constructed integrated energy system model. The specific optimization scheduling model of the comprehensive energy system comprises the following steps: the system comprises at least one of a cogeneration unit model, a solar photovoltaic power generation system model, an electric refrigeration unit model and a compressed air preparation system model. Specific equipment parameters are shown in table 1.
TABLE 1 parameter Table of device
In the comprehensive energy system optimization scheduling model, a combined heat and power generation unit model is as follows:
ηb，iGfuel，iQLHV＝Gb，i(hbout，i-hbin，i)
PCHP＝Qbηe(1-ηpl)
in the formula etab，iIndicating the efficiency of the ith boiler; gfuel，iThe fuel flow of the ith boiler is expressed in kg/s; qLHVRepresenting the lower calorific value of the fuel, kJ/kg; gb，iThe flow rate of the working medium output by the ith boiler is expressed in kg/s; h isbout，iAnd hbin，iRespectively representing the enthalpy values of the working media entering and exiting the boiler, kJ/kg; qbIndicating the total output thermal power, KW, of the plurality of boilers; pCHPThe external output electric power KW of the cogeneration unit is represented; etaeRepresenting the electric efficiency of the cogeneration unit; etaplAnd the plant power rate of the cogeneration unit is represented.
The output power of a photovoltaic module can generally be calculated by:
in the formula fPVThe reduction coefficient of the photovoltaic module is used for calculating the energy loss caused by the aging of the module, wind, snow and dust covering, and is 0.9 in the invention; p isV，capIs the rated power of the photovoltaic module; i isSRepresenting the illumination intensity under the standard working condition, and the value is 1kW/m2；TcellRepresents the photovoltaic cell temperature at actual operation; t iscell，STCThe temperature of the photovoltaic cell under the standard condition is 25 ℃; i isTIs the intensity of light, alphapIs the power-temperature factor.
The invention selects an electric refrigerator, a heat pump and a gas-fired hot water boiler as a typical cold and heat supply quasi-steady-state model. The electric refrigerator supplies cold to the outside by consuming electric energy, and the corresponding relation between the power consumption and the cold supply in unit hour can be represented by the following formula:
Pout，cool＝CvoecPin，voec
in the formula, Pout，coolIs the output power of the electric refrigerator; cvoecRepresenting the energy efficiency ratio of the electric refrigerator; pin，voecElectric power is input to the electric refrigerator.
The relationship between the consumed electric power and the input electric power of the electric refrigerator is as follows:
Pout，cool＝(1+αvoec)Pin，voec
in the formula, alphavoecIs the power consumption coefficient of the electric refrigerator.
The heat pump consumes electric energy to supply cold or heat to the outside, and the refrigeration power and the heating power are as follows:
Qout，HP，heat＝uHPCHP，heatPin，HP
Qout，HP，cool＝(1-uHP)CHP，coolPin，HP
in the formula, Qout，HP，heat-the output thermal power of the heat pump; u. ofHPThe operation state of the heat pump is 0, which indicates that the heat pump operates in a cooling state, and 1, which indicates that the heat pump operates in a heating state; pin，HPIs the input electrical power of the heat pump; cHP，coolThe refrigeration energy efficiency ratio of the heat pump; qout，HP，coolThe output cold power of the heat pump; cHP，heatThe heating energy efficiency ratio of the heat pump.
Similar to the electric refrigerator, considering that the heat pump supporting equipment has large power consumption, the relationship between the heat pump consumed electric power and the input electric power can be expressed as follows:
PHP，cool，cons＝(1+αHP，cool)UHPPin，HP
PHP，heat，cons＝(1+αHP，heat)(1-UHP)Pin，HP
in the formula: alpha is alphaHP，cool-the power consumption coefficient of the heat pump in the cooling state; alpha is alphaHP，heat-the power consumption coefficient of the heat pump in the heating state.
The heat value of the natural gas consumed in the delta t time period of the gas-fired hot water boiler is as follows:
in the formula: fWGB-fuel calorific value, kWh; pWGB，heat-thermal power output by the gas-fired hot water boiler; etaWGB-gas hot water boiler efficiency.
In step 101, based on the integrated energy system model, an objective function of the integrated energy system optimal scheduling is established, and a constraint condition of the optimal scheduling is determined, where the objective function may be represented as:
f＝Cgrid+Cfuel+Csteam
in the formula: f is the total cost, CgridTotal daily electricity purchase cost, C, for a typical integrated energy systemfuelFor the cost of fuel purchase, CsteamThe purchase cost of the municipal steam is neglected, namely the solar photovoltaic power generation cost is set to 0.
The constraints may include device contribution constraints and electrical balance constraints, wherein the device contribution constraints are expressed as:
Pgen，min≤Pgen≤Pgen，max
in the formula Pgen，min，Pgen，maxLower and upper output power limits for the generator power;
the electrical balance constraint is expressed as:
PPV+Pbuy+PCHP＝Pin，voec+Pin，HP
in the formula PPVIs the photovoltaic power generation power; pbuyIs the electricity purchase amount of the scheduling period; pCHPThe external output electric power of the cogeneration unit is represented; pin，voecIs the power consumed by the electric refrigerating unit; pin，HPIs a heat pumpElectric power is input.
In step 102, according to the constraint conditions, a lion group algorithm is adopted to solve the objective function, so as to obtain an optimal scheduling scheme of the comprehensive energy system.
The lion group algorithm comprises the following steps:
s1: initializing the positions and the number N of the lion in the lion group, the maximum iteration number and the dimension space, wherein the adult lion accounts for the scale factor beta of the lion group;
s2: calculating the number of the lion king and the parent lion in the lion group according to the following formula, setting the historical optimal position of each lion as the current position of each lion, and setting the optimal position of the initial group as the position of the lion king:
nLeader＝N×β
wherein the nLeader is the number of adult lions, namely the total number of the lion king and the parent lion, and the number of the lion king is 1;
adding and recording the last historical best position best of the lion king before iterative optimization, and setting the lion king stable value as s; if the optimal position of the history of the lion king is not changed after the next optimization, adding 1 to s; if the history optimal position of the lion king is changed, setting s to be 0; updating the number of times of sending in the current cycle to be t equal to 0.2 Tt; when t is less than 1, the value is 1;
s3: updating the position of the lion king according to the following formula, and calculating the fitness value:
wherein γ is a random number generated according to a normal distribution N (0, 1);
historical optimal positions for the ith lion for the kth generation; gkRepresenting the optimal position of the kth generation population;
s4: update the position of the lion according to the following formula:
in the formula
Is the historical best position of another parent lion except the ith lion from the kth parent lion;
s5: updating the position of the young lion according to the following formula:
g′k＝low′-high′-gk
in the formula
The position where the ith young lion is driven in the hunting range and a place far away from the lion king adopt the typical elite reverse learning thought,
representing the historical optimal position of the ith lion individual after the kth updating iteration;
historical optimal positions at the k-th generation for the parent lion group; g'kA reverse position representing an optimal position of the population; low 'and high' are respectively the minimum mean value and the maximum mean value of each dimension in the lion movement space range, and are the k-th generation historical best positions of the young lion following the mother lion, and the probability factor q is a uniform random value generated according to uniform distribution U (0, 1). Alpha is alphacA perturbation factor for the young lion, t is the current iteration number, an
S6: calculating a fitness value, adopting an elite strategy, keeping a maximum fitness value, and updating a global optimal position and a historical optimal position, wherein the elite strategy is a strategy of directly copying the best individual appearing so far in the evolution process of a population into the next generation without genetic operation and replacing the best individual in the next generation with the best individual;
s7: and judging whether the maximum iteration number is reached, outputting the optimal solution if the maximum iteration number is reached, and otherwise, repeating the steps from S2 to S7.
In this embodiment, for example, the number N of lion group lions may be set to 40, the maximum iteration number T may be 200, and the scale factor β of adult lion to lion group may be set to 0.4; the method comprises the steps that the output electric quantity of a cogeneration unit, a photovoltaic power generation system and external electricity purchasing is distributed according to a proportion, for example, an initial proportion (namely an initial group position) can be set to be (0.7, 0.2 and 0.1), and the dimensionality of the initial proportion is 3; the electricity rate is calculated according to the average electricity rate of 0.6 yuan of a certain place. When a problem is solved by utilizing a lion group algorithm, 3 proportions (the sum of the normalized proportions is 1) of a cogeneration unit, photovoltaic power generation and external power purchase are used as codes of the positions of the lions. Each possible solution to the problem is encoded as an individual, several individuals making up the population (all possible solutions). The initial group position is (0.7, 0.2, 0.1), and the lion king position is set.
When calculating, the highest radiation intensity of the sun at 12h is taken, and the power of the photovoltaic power generation is about the product of the area and the radiation intensity, and is about 36 MW. According to economic benefits, the optimal individual codes are (0.75, 0.15 and 0.1) through optimization and iteration of a lion group algorithm by 100 axes, namely the weight proportion of 3 targets in the cogeneration unit, the photovoltaic power generation and the external power purchase is 0.75, 0.15 and 0.1 in sequence, at the moment, not only can the electric power balance constraint and other constraints be met, but also the fitness value function (external power purchase cost) is the lowest, so that the optimal scheduling schemes are (0.75, 0.15 and 0.1), namely the cogeneration unit of 0.75, the photovoltaic power generation of 0.15 and the external power purchase of 0.1 can be obtained.
In step 103, the integrated energy system may be scheduled according to the obtained optimal scheduling scheme. For example, the integrated energy system can be optimally scheduled according to the above calculation results (0.75, 0.15, 0.1), i.e., 0.75 cogeneration unit, 0.15 photovoltaic power generation, and 0.1 external power purchase.
In summary, in this embodiment, an objective function of the optimal scheduling of the integrated energy system is established and a constraint condition of the optimal scheduling is determined, the objective function is solved by using the lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the integrated energy system, and the integrated energy system is scheduled according to the optimal scheduling scheme, so that the optimal scheduling of the integrated energy system can be realized and practical production requirements can be met.
Fig. 2 is a schematic diagram of an integrated energy system optimization scheduling device according to an embodiment of the present invention. Referring to fig. 2, the apparatus includes: the function and constraint construction unit is used for establishing an objective function of the optimized scheduling of the comprehensive energy system and determining constraint conditions of the optimized scheduling; the optimal scheduling scheme calculation unit is used for solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system; and the optimized scheduling unit schedules the comprehensive energy system according to the optimal scheduling scheme. The comprehensive energy system optimal scheduling device can be used for solving the objective function by establishing an objective function of comprehensive energy system optimal scheduling and determining constraint conditions of the optimal scheduling according to the constraint conditions by adopting a lion group algorithm to obtain an optimal scheduling scheme of the comprehensive energy system, and scheduling the comprehensive energy system according to the optimal scheduling scheme, so that the comprehensive energy system optimal scheduling can be realized and practical production requirements can be met.
The integrated energy system optimal scheduling device provided by the embodiment of the invention can be used for executing the integrated energy system optimal scheduling method described in the embodiment, and the working principle is similar, so detailed description is omitted here, and specific contents can be referred to the description of the embodiment.
Based on the same inventive concept, another embodiment of the present invention provides an electronic device, referring to fig. 3, which specifically includes the following contents: a processor 301, a memory 302, a communication interface 303, and a communication bus 304; the processor 301, the memory 302 and the communication interface 303 complete communication with each other through the communication bus 304.
The processor 301 is configured to call a computer program in the memory 302, and the processor executes the computer program to implement all the steps of the above-mentioned method for optimizing and scheduling an integrated energy system, for example, when the processor executes the computer program, the processor implements the following processes: establishing an objective function of the optimized scheduling of the comprehensive energy system, and determining constraint conditions of the optimized scheduling; solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system; and scheduling the comprehensive energy system according to the optimal scheduling scheme.
It will be appreciated that the detailed functions and extended functions that the computer program may perform may be as described with reference to the above embodiments.
Based on the same inventive concept, another embodiment of the present invention provides a non-transitory computer-readable storage medium, having a computer program stored thereon, which when executed by a processor implements all the steps of the above-mentioned method for optimized scheduling of an integrated energy system, for example, the processor implements the following processes when executing the computer program: establishing an objective function of the optimized scheduling of the comprehensive energy system, and determining constraint conditions of the optimized scheduling; solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system; and scheduling the comprehensive energy system according to the optimal scheduling scheme.
It will be appreciated that the detailed functions and extended functions that the computer program may perform may be as described with reference to the above embodiments.
Based on the same inventive concept, another embodiment of the present invention provides a computer program product, which includes a computer program, when being executed by a processor, the computer program implements all the steps of the above-mentioned method for optimizing and scheduling an integrated energy system, for example, when the processor executes the computer program, the processor implements the following processes: establishing an objective function of the optimized scheduling of the comprehensive energy system, and determining constraint conditions of the optimized scheduling; solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system; and scheduling the comprehensive energy system according to the optimal scheduling scheme.
It will be appreciated that the detailed functions and extended functions that the computer program may perform may be as described with reference to the above embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on such understanding, the technical solutions mentioned above may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method for optimizing and scheduling an integrated energy system according to each embodiment or some portions of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. An optimal scheduling method for an integrated energy system is characterized by comprising the following steps:
establishing an objective function of the optimized scheduling of the comprehensive energy system, and determining constraint conditions of the optimized scheduling;
solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system;
and scheduling the comprehensive energy system according to the optimal scheduling scheme.
2. The method according to claim 1, wherein the establishing an objective function of the optimal scheduling of the integrated energy system comprises:
constructing an integrated energy system model, establishing an objective function of the integrated energy system optimization scheduling according to the integrated energy system model,
the comprehensive energy system model comprises at least one of a cogeneration unit model, a solar photovoltaic power generation system model, an electric refrigeration unit model and a compressed air preparation system model.
3. The method of claim 2, wherein the objective function is expressed as a total cost equal to a sum of total daily electricity purchase costs, costs for fuel purchase, solar photovoltaic generation costs, and municipal steam purchase costs of a typical integrated energy system.
4. The method of claim 3, wherein the constraints include device contribution constraints and electrical balance constraints,
wherein the device output constraint is expressed as:
Pgen，min≤Pgen≤Pgen，max
in the formula Pgen，min，Pgen，maxLower and upper output power limits for the generator power;
the electrical balance constraint is expressed as:
PPV+Pbuy+PCHP＝Pin，voec+Pin，HP
in the formula PPVIs the photovoltaic power generation power; pbuyIs the electricity purchase amount of the scheduling period; pCHPThe external output electric power of the cogeneration unit is represented; pin，voecIs the power consumed by the electric refrigerating unit; pin，HPIs the input electrical power of the heat pump.
5. The optimized scheduling method for the integrated energy system according to claim 1, wherein the input quantity of the lion-group algorithm comprises an initial position, a population size, a lion ratio and an iteration number, and the output quantity of the lion-group algorithm is a lion king position, namely an optimal scheduling scheme.
6. The method for optimized scheduling of an integrated energy system according to claim 5, wherein the lion group algorithm comprises the steps of:
initializing all parameters of the lion group, wherein the parameters comprise the positions of a lion king, a parent lion and a young lion in the lion group, the size of the species group and the number of iterations;
calculating a fitness value, and updating a global optimal position and a historical optimal position;
and judging whether the maximum iteration times is reached, outputting an optimal solution if the maximum iteration times is reached, and otherwise, updating the positions of various lions in the lion group.
7. The optimal scheduling method for integrated energy system according to claim 3, wherein the total cost in the objective function ignores the solar photovoltaic power generation cost, i.e. the solar photovoltaic power generation cost is set to 0.
8. An optimized scheduling device for an integrated energy system, comprising:
the function and constraint construction unit is used for establishing an objective function of the optimized scheduling of the comprehensive energy system and determining constraint conditions of the optimized scheduling;
the optimal scheduling scheme calculation unit is used for solving the objective function by adopting a lion group algorithm according to the constraint condition to obtain an optimal scheduling scheme of the comprehensive energy system;
and the optimized scheduling unit schedules the comprehensive energy system according to the optimal scheduling scheme.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method according to any one of claims 1 to 7.
10. A non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the steps of the method for optimized scheduling of an integrated energy system according to any of claims 1 to 7.
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