CN116681188B - Comprehensive energy system optimization method and device, electronic equipment and storage medium - Google Patents
Comprehensive energy system optimization method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention is suitable for the technical field of power supply systems, and provides a comprehensive energy system optimization method, a device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring optimal energy storage transaction information of a target area comprehensive energy system and an energy storage aggregator in a period to be optimized; the energy storage aggregate performs energy storage transaction with a plurality of regional comprehensive energy systems, and the target regional comprehensive energy system is one regional comprehensive energy system; according to the optimal energy storage transaction information, a first objective function is established by taking the minimum running cost of the target area comprehensive energy system in the period to be optimized as a target; establishing constraint conditions of a first objective function, and solving the first objective function to obtain an optimal unit output strategy of a target comprehensive energy system in a period to be optimized; and carrying out optimal scheduling on the target comprehensive energy system based on the optimal unit output strategy. The invention can improve the utilization rate of energy storage resources and reduce the operation cost of the comprehensive energy system.
Description
Technical Field
The invention belongs to the technical field of power supply systems, and particularly relates to a comprehensive energy system optimization method, a comprehensive energy system optimization device, electronic equipment and a storage medium.
Background
At present, most of researches on the comprehensive energy system and the operation optimization thereof take the problems of multi-energy coupling analysis, multi-type equipment modeling and renewable energy output uncertainty in the system as cores, and the researches on the operation optimization of the comprehensive energy system participating in external collaborative scheduling are still deficient. With the great development of shared economy and energy storage technology, the shared energy storage technology has been developed, and has remarkable advantages in terms of reducing investment and construction costs, providing auxiliary services and the like. How to utilize the shared energy storage technology, improve energy storage utilization efficiency and reduce the overall operation cost of the system is a problem to be solved.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a method, an apparatus, an electronic device, and a storage medium for optimizing an integrated energy system, so as to improve the utilization rate of energy storage resources and reduce the running cost of the system.
A first aspect of an embodiment of the present invention provides a method for optimizing an integrated energy system, including:
acquiring optimal energy storage transaction information of a target area comprehensive energy system and an energy storage aggregator in a period to be optimized; the energy storage aggregate performs energy storage transaction with a plurality of regional comprehensive energy systems, and the target regional comprehensive energy system is one regional comprehensive energy system;
According to the optimal energy storage transaction information, a first objective function is established by taking the minimum running cost of the target area comprehensive energy system in the period to be optimized as a target;
establishing constraint conditions of a first objective function, and solving the first objective function to obtain an optimal unit output strategy of a target comprehensive energy system in a period to be optimized;
and carrying out optimal scheduling on the target comprehensive energy system based on the optimal unit output strategy.
With reference to the first aspect, in one possible implementation manner of the first aspect, obtaining optimal energy storage transaction information of the target area comprehensive energy system and the energy storage aggregator in the period to be optimized includes:
and establishing a second objective function by taking the minimum running cost of the energy storage polymer in the period to be optimized as a target, and solving the second objective function to obtain the optimal energy storage transaction information of the energy storage polymer and the comprehensive energy system of each region.
With reference to the first aspect, in one possible implementation manner of the first aspect, the second objective function is:
；
in the method, in the process of the invention,cost of purchasing energy storage use right for energy storage aggregate to comprehensive energy system of each area, +.>The charge and discharge loss cost generated by the actual scheduling of the energy storage aggregator;The charge and discharge loss cost generated by the actual dispatching of the comprehensive energy system of each region; / >And renting the energy storage service to the energy storage aggregator for the comprehensive energy system of each region.
With reference to the first aspect, in a possible implementation manner of the first aspect, the optimal energy storage transaction information of the energy storage aggregator and the comprehensive energy source system of each area includes:
the energy storage aggregators purchase energy storage using rights from the comprehensive energy systems of all areas and lease the optimal transaction strategies of the energy storage service from the energy storage aggregators by the leasing energy systems of all areas.
With reference to the first aspect, in one possible implementation manner of the first aspect, the first objective function is:
；
in the method, in the process of the invention,the operation and maintenance cost of the renewable energy unit is realized;The fuel consumption cost and the climbing cost of the unit are;Calling cost for interruptible load;A fee paid to the energy storage aggregator for leasing the energy storage;The cost of purchasing electricity from the regional power grid;Punishment cost for wind and light abandonment;Is discharged into carbon
The cost is high;the daily chemical life cycle cost is set;And renting the fee for the energy storage use right.
With reference to the first aspect, in a possible implementation manner of the first aspect, the constraint condition of the first objective function includes:
balance constraints, including electrical system balance constraints, thermal system balance constraints, and cold system balance constraints;
The energy storage equipment frequency division constraint comprises high-frequency constraint of a super capacitor, secondary low-frequency constraint of a lithium battery, lowest-frequency constraint of a heat storage system and lowest-frequency constraint of a cold storage system;
the equipment network constraints include energy supply equipment operation constraints and grid energy supply constraints.
With reference to the first aspect, in a possible implementation manner of the first aspect, the algorithm for solving the first objective function is any one of the following optimization algorithms: genetic algorithm, tabu search algorithm, simulated annealing algorithm, sparrow search algorithm, marine predator algorithm.
A second aspect of an embodiment of the present invention provides an integrated energy system optimizing apparatus, including:
the first optimization module is used for acquiring optimal energy storage transaction information of the target area comprehensive energy system and the energy storage aggregator in the period to be optimized; the energy storage aggregate performs energy storage transaction with a plurality of regional comprehensive energy systems, and the target regional comprehensive energy system is one regional comprehensive energy system;
the second optimization module is used for establishing a first objective function with the minimum running cost of the target area comprehensive energy system in the period to be optimized as a target according to the optimal energy storage transaction information; establishing constraint conditions of a first objective function, and solving the first objective function to obtain an optimal unit output strategy of a target comprehensive energy system in a period to be optimized;
And the scheduling module is used for optimally scheduling the target comprehensive energy system based on the optimal unit output strategy.
A third aspect of the embodiments of the present invention provides an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method as described above in the first aspect or any implementation of the first aspect when the computer program is executed.
A fourth aspect of embodiments of the present invention provides a computer readable storage medium storing a computer program which when executed by a processor performs the steps of a method as in the first aspect or any implementation of the first aspect.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
according to the embodiment of the invention, the energy storage transaction is carried out through the energy storage aggregator and the comprehensive energy systems of all areas, so that shared energy storage is realized, the utilization rate of energy storage resources is improved, the in-situ consumption of new energy is promoted, and the running and construction cost of the system is reduced. Further, the optimal energy storage transaction information of the target area comprehensive energy system and the energy storage aggregate in the period to be optimized is obtained, and according to the optimal energy storage transaction information, the target area comprehensive energy system is optimally scheduled with the minimum running cost of the target area comprehensive energy system in the period to be optimized as a target, and meanwhile, the running economy of the energy storage aggregate and the target area comprehensive energy system is realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an integrated energy system according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of an integrated energy system optimization method according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an integrated energy system optimizing device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to illustrate the technical scheme of the invention, the following description is made by specific examples.
The embodiment firstly carries out model and characteristic analysis on typical equipment of the regional comprehensive energy system, and specifically comprises energy production equipment, energy conversion equipment and energy storage equipment.
1. Energy production equipment
(1) Wind power generation
Wind Turbines (WTs) are an energy supply device that converts mechanical energy into electrical energy. The amount of the electric energy output has a direct correlation with the wind speed. Due to the intermittence and randomness of wind speeds, the present embodiment selects the weibull distribution to account for wind speed uncertainty.
The probability density function of wind speed is as follows:
in the method, in the process of the invention,is a shape parameter in the weibull distribution;Is a scale parameter;For a given wind speed.
In the constructed probability density function, parametersIs->The determination can be carried out by a maximum likelihood estimation method, and the parameter estimation model is as follows:
based on the wind speed data, the relationship between the output of the fan and the wind speed can be modeled. During operation, the wind speed needs to be ensured to be within a rated range, otherwise, the fan stops generating electricity to ensure the safety of energy supply. The fan output piecewise function is as follows:
In the method, in the process of the invention,generating power for the fan;Is the real-time wind speed;Is the cut-in wind speed;To cut out wind speed;Is the rated wind speed;、Fitting parameters;Is rated power.
(2) Photovoltaic power generation
Photovoltaic is energy equipment for converting solar energy into electric energy, roof distributed photovoltaic can be developed, a large-scale photovoltaic power station can be built, and the application is wide. The photovoltaic output curve is affected by the solar radiation intensity with a strong uncertainty, so the solar radiation intensity is represented by a non-parametric kernel density estimation:
in the method, in the process of the invention,is the intensity of solar radiation;Is the number of samples;Is the bandwidth;Sample values were collected for the irradiation intensity. The calculation formula of the photovoltaic output power is obtained as follows:
in the method, in the process of the invention,the actual power supply of the photovoltaic;Rated power supply for photovoltaic;Is the actual solar irradiation intensity;Is generally set to 1000W/m for the solar irradiation intensity under standard test conditions 2 ；The temperature coefficient of the photovoltaic output device is generally set to be-0.35/°c;Is the temperature of the photovoltaic device;For the temperature of the photovoltaic cell assembly under standard test conditions, 25 ℃ is typically taken.
(3) Heat pump
The heat pump is energy supply equipment for converting heat energy from low grade to high grade, has higher energy conversion efficiency and low power consumption, and can be classified into an air source heat pump, a ground source heat pump, a water source heat pump and the like according to different heat dissipation sources and heat extraction sources. Has the dual functions of heating in winter and cooling in summer.
Building an output formula of the heat pump from the energy point of view:
in the method, in the process of the invention,、cooling and heating power of the heat pump;The power consumption is the power consumption when the heat pump operates;、COP curves for heat pump cooling and heating;For the operating mode of the heat pump, when->The heat pump is set to be in a cooling condition when +.>When the heat pump is set to a heating condition. In order to ensure the service life of the device, in general, the operating conditions of the heat pump in the same day are not adjusted.
2. Energy conversion equipment
(1) Cold-heat-electricity triple supply
As shown in fig. 2, the main equipment constituting the cold-heat-electricity triple supply system (Combined Cooling Heating and Power, CCHP) comprises a gas turbine, a waste heat boiler and an absorption refrigerator, and can simultaneously satisfy three loads of cold, heat and electricity, and the energy utilization efficiency can be improved through the cascade utilization of energy.
The output model of the CCHP system is as follows:
in the method, in the process of the invention,generating power for the gas turbine;The natural gas demand of the lower combustion engine in unit time;Taking 9.78kWh/m3 as the calorific value of natural gas;Is the power generation efficiency of the gas turbine.
The gas turbine can generate huge amount of waste heat during operation, and the absorption refrigerator and the waste heat boiler can utilize the waste heat to provide cold and heat for users.
In a gas turbine, the model of waste heat generation is as follows:
in the method, in the process of the invention,generating power of waste heat for the gas turbine;The waste heat utilization efficiency is achieved;Is the running loss factor. Gas turbine generatorThe waste heat can be used for generating heat energy by a waste heat boiler to meet the heat load of a user, and the heat energy can be converted into cold energy by an absorption refrigerator.
In the waste heat boiler, the heat energy generation power is as follows:
in the method, in the process of the invention,the heat supply power of the waste heat boiler is provided;Is the heat conversion coefficient of the waste heat boiler;-waste heat utilization efficiency.
Under the promotion of the waste heat of the gas turbine, the output power of the absorption refrigerator is as follows:
in the method, in the process of the invention,cooling power of the absorption refrigerator;Waste heat utilization efficiency of the absorption refrigerator is achieved;Is the operation efficiency of the absorption refrigerator.
(2) Electric refrigerator output model
The COP of the electric refrigerator (Electric Refrigerator, ER) can reach more than 3, and the equipment model is as follows:
in the method, in the process of the invention,the cooling power of the electric refrigerating unit is supplied;Is the cold conversion coefficient of the electric refrigerator;Is the power consumption of the electric refrigerator.
(3) Electric boiler output model
The Electric Boiler (EB) COP is typically below 1. But is often supplied rapidly as a thermal replacement device in the presence of thermal gaps due to its relatively high start-up speed.
The equipment model of the electric boiler is as follows:
in the method, in the process of the invention,generating heat power for an electric boiler;The electric energy input power of the electric boiler;Is the operation efficiency of the electric boiler.
(4) Gas boiler output model
The gas boiler operates faster and can be used as peak shaving equipment for heat supply. Hot water is often produced by a gas boiler to supply heat to users of the regional comprehensive energy system. The output model of the gas boiler is as follows:
in the method, in the process of the invention,the heat generating power of the gas boiler;Is natural gas consumption;Is natural gas calorific value, generally 9.78kWh/m 3 ；Is the heat conversion efficiency of the gas boiler.
3. Energy storage device
In the regional comprehensive energy system, the energy storage can play a role in peak clipping and valley filling, store energy in the period of low load and release energy in the period of high load, so that the running cost of the regional comprehensive energy system is reduced, and the energy has a transmission characteristic in time and space. In regional integrated energy systems, the energy storage device mainly includes electric energy storage, thermal energy storage, and cold energy storage.
(1) Power storage equipment (Electrical energy storage, EES)
Because of uncertainty of the wind turbine and the photovoltaic output, an energy storage system is generally configured in the regional comprehensive energy system so as to stabilize fluctuation of wind and light output. In addition, the electric energy storage can reduce the cost of the regional comprehensive energy system by using peak-valley price difference. The physical model is as follows:
In the method, in the process of the invention,、for electric power storage equipment>Time and->The residual electric quantity at the moment;The self-loss coefficient of the electricity storage equipment;、Charging and discharging power of the electricity storage equipment;、Is the charge and discharge efficiency of the electricity storage equipment.
(2) Heat storage equipment (Thermal energy storage TES)
The comprehensive energy system integrates cold, heat and electric loads, in the energy supply, not only can electric energy be stored, but also heat energy can be stored by utilizing the heat storage tank, and the heat energy is released when needed. Similar to electrical energy storage, there are also two conditions of heat storage and heat release for thermal energy storage devices. The heat storage and release output model of the heat energy storage system is as follows:
and (3) heat storage process:
exothermic process:
in the method, in the process of the invention,、is a heat storage deviceAt->Time and->The remaining heat at the moment;Is the self-loss coefficient of the heat storage equipment;The input power for the heat storage device;The output power of the heat storage equipment;The input efficiency of the heat storage equipment;Is the output efficiency of the heat storage device.
(3) Cold storage equipment (Cold energy storage, CES)
As with the hot energy storage, the cold energy storage system operates as follows:
and (3) a cold storage process:
and (3) a cooling process:
in the method, in the process of the invention,、for cold storage equipment>Time and->Residual cooling capacity at moment; / >Is the self-loss coefficient of the cold storage equipment;The input power of the cold storage equipment;The output power of the cold storage equipment;The input efficiency of the cold storage equipment is;Is the output efficiency of the cold storage device.
Based on the constructed equipment model, the embodiment respectively constructs the target of operation optimization aiming at the regional comprehensive energy system and the energy storage aggregator so as to minimize the operation cost of each main body.
Specifically, referring to fig. 2, the integrated energy system optimization method includes:
step S201, obtaining optimal energy storage transaction information of a target area comprehensive energy system and an energy storage aggregator in a period to be optimized; the energy storage aggregate performs energy storage transaction with a plurality of regional comprehensive energy systems, and the target regional comprehensive energy system is one regional comprehensive energy system.
The energy storage aggregator provides energy storage leasing services for all the regional comprehensive energy systems, and when the regional comprehensive energy system needs to schedule energy storage to realize self energy supply optimization, the energy storage aggregator should pay corresponding service fees. The energy storage aggregator can realize benefits by collecting service fees, optimizing scheduling strategies and collecting lease fees, so that the total life cycle cost of energy storage construction and management of the regional comprehensive energy system can be effectively reduced. The shared energy storage utilizes the load non-simultaneity and wind-light resource complementation between the comprehensive energy systems of different areas to meet the charge and discharge demands of the comprehensive energy systems of the areas by using the energy storage device with the least investment. Therefore, the resource utilization is maximized, the wind power and photovoltaic absorption rate is improved, and meanwhile, the economical efficiency of the regional comprehensive energy system is improved. On the side of the energy storage polymerizer, the minimum running cost of the energy storage polymerizer can be used as a target, so that the optimal energy storage transaction information of the comprehensive energy systems of all areas and the energy storage polymerizer is determined, and the cost optimization is carried out on the comprehensive energy systems of all areas by taking the optimal energy storage transaction information as an initial condition.
Specifically, a second objective function is established with the minimum running cost of the energy storage aggregator in the period to be optimized as a goal:
cost of purchasing energy storage usage rights for energy storage aggregators to various regional integrated energy systems:
charge and discharge loss costs generated for the actual scheduling of energy storage aggregators:
the charge and discharge loss cost generated for the actual scheduling of the comprehensive energy system in each region is as follows:
service fees paid for the integrated energy systems of each region to lease energy storage services to energy storage aggregators:
in the above-mentioned method, the step of,Nthe number of energy systems is synthesized for the areas participating in scheduling;Tis an operation period;tfor one of the operating cycles;S ESS,t comprehensive energy system for regioniThe energy storage capacity is configured;integrating the cost of energy storage unit capacity for an energy storage aggregator;P cha-i,,t 、P dis-i,,t comprehensive energy system for regioniAt->Charging and discharging electric quantity purchased from an energy storage aggregator in a period;Charging and discharging efficiency for charging and discharging energy storage;The percentage of the service charge is increased for the energy storage aggregator according to the lease charge, and the proportion can be different according to various factors, such as market demand, competition condition, technical cost and the like;k 3 the energy storage aggregate provides preferential or price-raising percentages according to the operation requirements of the regional comprehensive energy system.
By establishing constraint conditions of the second objective function and solving the constraint conditions, the optimal energy storage transaction information of the energy storage aggregators and the comprehensive energy systems of all areas can be obtained, namely, the energy storage aggregators purchase energy storage utilization rights from the comprehensive energy systems of all areas and the optimal transaction strategy that the energy storage service is leased by the leasing energy systems of all areas to the energy storage aggregators can be further explained as how many energy storage resources are purchased by the energy storage aggregators from the comprehensive energy systems of all areas and how many energy storage resources are leased by the leasing energy systems of all areas to the energy storage aggregators.
Step S202, according to the optimal energy storage transaction information, a first objective function is established with the aim of minimizing the running cost of the target area comprehensive energy system in the period to be optimized.
In this embodiment, the first objective function is:
in the method, in the process of the invention,the operation and maintenance cost of the renewable energy unit is realized;The fuel consumption cost and the climbing cost of the unit are;Calling cost for interruptible load;A fee paid to the energy storage aggregator for leasing the energy storage;The cost of purchasing electricity from the regional power grid;Punishment cost for wind and light abandonment;Is discharged into carbon
The cost is high;the daily chemical life cycle cost is set; / >And renting the fee for the energy storage use right.
Specific:
in the method, in the process of the invention,the number of fans and photovoltaics;For fans and photovoltaics in time period->Output power of (2);the operation and maintenance cost of the fan and the photovoltaic is high;For scheduling time intervals.
In the method, in the process of the invention,the power generation cost coefficient of the unit is;For the unit in time period->Output power of (2);For the up and down time period of the machine set>Is used for climbing power;The unit power cost for climbing up and down the unit is provided.
To schedule power for interruptible loads;To schedule the unit cost of interruptible load.
In the method, in the process of the invention,for regional comprehensive energy system>Charging and discharging electric quantity purchased from an energy storage aggregator in a period;charging and discharging efficiency for charging and discharging energy storage;Providing energy storage service charge for an energy storage aggregator;The price increasing proportion of the purchase service of the regional comprehensive energy system;The energy storage capacity is configured for the regional comprehensive energy system;The cost of energy storage unit capacity is integrated for the energy storage aggregator.
In the method, in the process of the invention,for period->Purchasing power to a large power grid;The unit cost of purchasing electricity for a large power grid.
In the method, in the process of the invention,punishment cost is given for the unit of wind and light discarding;The total amount of waste wind and waste light is used.
In the method, in the process of the invention,carbon emission coefficient for purchasing electricity to the grid; / >Carbon emission coefficient for natural gas combustion;The electricity purchasing quantity to the power grid;Natural gas consumption;Is the carbon dioxide emission unit cost.
The total life cycle cost of energy storage in the regional comprehensive energy system mainly comprises initial investment cost, equipment replacement cost, operation maintenance cost and scrapping treatment cost. The regional comprehensive energy system converts the total life cycle cost of the stored energy to each scheduling time, and uses the cost as a basis for determining the lease fees charged to the energy storage aggregators. The daily chemical life cycle cost calculation formula is as follows:
in the method, in the process of the invention,initial investment cost for energy storage;Replacement cost for the energy storage device;For storing energy->Annual operation maintenance cost;The scrapping treatment cost of energy storage;Is the discount rate;Is the life of the energy storage system;Is a daily cost impression coefficient.
And step S203, a constraint condition of the first objective function is established, and the first objective function is solved, so that an optimal unit output strategy of the target comprehensive energy system in the period to be optimized is obtained.
As one possible implementation, the constraint condition of the first objective function includes:
balance constraints, including electrical system balance constraints, thermal system balance constraints, and cold system balance constraints;
The energy storage equipment frequency division constraint comprises high-frequency constraint of a super capacitor, secondary low-frequency constraint of a lithium battery, lowest-frequency constraint of a heat storage system and lowest-frequency constraint of a cold storage system;
the equipment network constraints include energy supply equipment operation constraints and grid energy supply constraints.
The formulas for each constraint are described in detail below.
(one) Balancing constraints
The regional comprehensive energy system structure mainly comprises an electric system, a thermal system and a cold system, and in the running process of the regional comprehensive energy system, energy balance between energy supply and user load needs must be ensured. Thus mainly establishing electrical system balance constraints, thermal system balance constraints and cold system balance constraints.
(1) Electrical system balance constraints
The power supply side comprises a fan, photovoltaic output, cogeneration equipment power supply, energy storage equipment discharging and power grid electricity buying quantity, and the power utilization side comprises a user electricity load, electricity boiler power consumption and energy storage charging quantity.
In the method, in the process of the invention,purchasing power of electric quantity from a power grid for the regional comprehensive energy system;Output power for wind power generation;The power is output by distributed photovoltaic power generation;The electrical output power of the CCHP;、The power consumption of the electric boiler is used for users; / >、And the energy storage battery is charged and discharged with power.
(2) Thermal system balance constraints
The heat supply side comprises heat supply quantity of the cogeneration equipment, heat supply quantity of a heat pump, heat supply quantity of an electric boiler and heat release quantity of the heat storage equipment, and the user side comprises heat storage quantity of a heat storage tank and user heat load.
In the method, in the process of the invention,heat output power for CCHP;Heat output power of the heat pump;The heat output power of the electric boiler;Is the thermal load within the system;、And charges and discharges power for heat storage.
(3) Cold system balance constraint
The cooling side comprises cooling capacity of the cogeneration equipment, cooling capacity of the heat pump and cooling capacity of the cold storage equipment, and the user side comprises heat storage capacity of the ice storage tank and user cooling load.
In the method, in the process of the invention,cold output power for CCHP;Cold output power of the heat pump;Is the cooling load in the system;、And charging and discharging power for the ice storage tank.
(II) energy storage device frequency division constraint
In the process of frequency decomposition using a wavelet packet decomposition discrete fourier transform two-stage frequency decomposition model, it is necessary to ensure a safe operating state of energy storage. Thus, constraints of corresponding different types of energy storage devices are constructed in different frequency ranges.
(1) High frequency constraints: super capacitor
The charging and discharging power of the super capacitor should be in the rated power range, and the charge state of the super capacitor should be in a reasonable range so as to prevent the damage to the service life of the battery.
In the method, in the process of the invention,、the minimum value and the maximum value of the SOC of the super capacitor;、Maximum value of the charging and discharging power for the supercapacitor.
(2) The secondary low frequency constraint: lithium battery
The charge and discharge power and the state of charge of the lithium battery are required to be within a reasonable range.
In the method, in the process of the invention,、is a lithium batteryState of charge minimum and maximum;、Maximum charge and discharge power for a lithium battery.
(3) Minimum frequency constraint: heat storage
The charging and discharging power of the heat storage system should be strictly controlled within the upper limit and the lower limit.
In the method, in the process of the invention,、the heat storage proportion is the minimum value and the maximum value;Is the maximum value of heat storage power of heat storage.
(4) Minimum frequency constraint: cold storage
The cold power of the cold storage system should be strictly controlled within the upper and lower limits.
In the method, in the process of the invention,、the minimum value and the maximum value of the ice storage proportion of the ice storage tank are adopted;Is the maximum value of the ice storage power of the ice storage tank.
(III) device network constraints
(1) Device constraints
The energy supply device has a constraint in the operation process.
In the method, in the process of the invention,the lower limit of the output of different equipment in the regional comprehensive energy system is set;The upper limit of the output of different equipment in the regional comprehensive energy system is set;For the start-up or stop state of the device, when +.>When =0 means the device is off, when +. >When=1, it indicates that the device is on;For device time->Is a climbing rate of (a);For different device moments->A lower limit of the ramp rate of (a);For different device moments->An upper limit of the ramp rate of (a).
(2) Power grid energy supply constraint
Along with the continuous increase of regional load, the power supply pressure of the power grid is also increased, and the upgrading and transformation of the power grid in a short period of time can bring huge fund pressure to power grid companies and the like. Therefore, constraints of power grid supply must be fully considered when optimizing the operation of the regional integrated energy system.
In the method, in the process of the invention,the maximum power supply capacity of the power grid is achieved;Is->The power consumption of the station apparatus;Is->Generating power of the station apparatus;And (5) an electric load designed for the interior of the regional comprehensive energy system.
And step S204, optimizing and scheduling the target comprehensive energy system based on the optimal unit output strategy.
Considering that the regional comprehensive energy system taking the shared energy storage into account involves a plurality of variables in the operation optimization process, the operation condition of the equipment is relatively complex, the user load curve also has fluctuation characteristics, the operation optimization model constructed by the embodiment is a nonlinear mathematical model, is difficult to solve rapidly and accurately by using a traditional algorithm, consumes a long time, and is easy to fall into a local optimal state. Accordingly, any of the following may be employed, but is not limited to: and solving the model by intelligent optimization algorithms such as a genetic algorithm, a tabu search algorithm, a simulated annealing algorithm, a sparrow search algorithm, a marine predator algorithm and the like.
Illustratively, the present embodiment utilizes a marine predator algorithm to solve the operational optimization model.
The inspiration of the marine predator algorithm mainly comes from predation behaviors and foraging behavior strategies of marine organisms such as sharks, giant exendins and the like, and the optimization problem is solved by simulating the rules of the marine organism predators. The foraging strategies are summarized into two categories, namely Lewy flight and Brownian movement. During the specific algorithm, the probability of meeting between predators and prey is maximized by balancing the choice of the lewy flight and brownian motion at different stages. Brownian motion and Lewy flight are described below.
(1) Brownian motion
Standard brownian motion is a random process, and their step size is taken from a probability function defined by a normal (gaussian) distribution. The control probability density function of the motion at the x point is as follows:
(2) Lewy movement
L-lay motion describes a motion characterized by frequent small-step movements and occasional large-step movements. The rice motion is a random walk whose step size is determined by a probability function defined by the rice distribution:
wherein,is the flight length>Is a power law exponent.
The probability density function of the integrated form of the Lev stabilization process is defined as:
Wherein,defining a distribution index and controlling the scale properties of the process, while +.>The scale units are selected. When->When equal to 2, it means obeying the Gaussian distribution when +.>Equal to 1, compliance with the cauchy distribution is indicated. The expansion of the number of stages is generally only needed when the value of x is large, and the expansion method is as follows:
wherein,represents a Gamma function, wherein for the integer +.>Count (n)/(l)>Equal to->!。
The generation of random numbers based on the Lewye distribution is shown as follows:
wherein,and->Is two normal distribution variables with standard deviation +.>And->The following is shown:
in the above equation, the term "in" is used,the calculation mode is as follows:
(II) solving Process
The marine predator optimization algorithm mainly comprises three stages of initialization, optimization and FADs effect.
(1) Initialization of
As with many bottom layer thinking natural-based algorithms, marine predator algorithms also require the construction of an original population with initial solutions randomly distributed within the search space.
Wherein,and->Is the lower and upper limits of the variable, rand is a random variable, whose value is in the range 0 to 1.
According to the theory of survival of the fittest, the top predators in nature should be better at foraging. When predators are looking for food, prey is also looking for food, and therefore two matrices need to be defined. The optimal solution is selected as the top predator, and an Elite matrix is constructed, and the matrix array represents the searching process and the hunting object searching process. The second matrix is a Prey matrix, which has the same dimensions as ellite, and predators update based on this matrix. At the end of each iteration, if predators with higher fitness values appear, the predators at the current top are replaced and the elite matrix is updated accordingly. The Elite matrix and the Prey matrix are defined as follows:
Wherein,representing top predator->First->Dimension->Variable(s)>Representation->First->Dimension->And a variable.
(2) Optimization
Marine predator algorithms are divided into three main phases of use, simulating the prey cycle of predators and prey according to the different speeds of each phase. These three phases include:
high speed ratio of prey to predator (v.gtoreq.10). This occurs during the first 1/3 stage of optimization, and the predator's best strategy is stationary in place. The mathematical model in this case is:
wherein the method comprises the steps ofIs a vector based on a normally distributed random number representing brownian motion. Sign->Representing a multiplication term by term.R is [0,1 ]]Is a uniform random number vector in (a). When step size orThis occurs in the first third of the iterations when the speed of movement is high to achieve high exploration capacity. Iter is the current iteration and Max_iter is the maximum iteration.
The speed ratio of prey to predator is similar (v.apprxeq.1), where both prey and predator are looking for their prey. Wherein predators follow Brownian motion and prey follow Lewy motion, during which half of the population is used for development and the other half is used for exploration. The mathematical model for the developed population is as follows:
Wherein,is a random number vector of the Lewy motion, +.>And->The model for the population math used for exploring is as follows:
by passing throughAnd->Simulating Brownian motion of predators based on the product of (2) and prey based on the captureThe step of the predator adjusts the position of the predator, CF is an adaptive parameter for controlling the moving step length of the predator, and the mathematical model is as follows:
low speed ratio of prey to predator (v=0.1), which occurs at the last 1/3 of the optimization, the best strategy for predator is the lewy sport, the predator's location update model is as follows:
and->Multiplication simulates the predator to perform a Levels movement, thereby updating the predator's location.
（3）FADs
Another point that leads to changes in marine predator behavior is environmental problems such as vortex formation or fish gathering device (FAD) effects. FAD is considered to be a local optimum. The trapping of locally optimal solutions is avoided by taking into account the large jumps during the simulation. Thus, using the FAD effect, a model can be built:
wherein FADs represent the probability of affecting the optimization process, typically taking 0.2.Is a binary array vector containing 0 and 1, this vector being obtained by multiplying the binary array vector by the binary array vector in the range of 0,1]Between generating randomA number, the random number is less than 0.2, which is set to 0, otherwise, is set to 1.r is [0,1 ] ]Random number +.>Is an upper and lower vector containing dimensions, r1 and r2 are +.>Random index of the matrix.
In conclusion, the invention constructs the regional comprehensive energy system operation optimization model considering the shared energy storage. Firstly, researching physical models and equipment characteristics of energy production, conversion and storage equipment; secondly, respectively constructing an operation optimization target aiming at the regional comprehensive energy system and the energy storage aggregator so as to minimize the operation cost of each main body; thirdly, considering the system balance, energy storage frequency division and the operation characteristics of the equipment, and analyzing the constraint conditions of an operation optimization model; and finally, solving the operation optimization model by using a marine predator algorithm, improving the solving capability of the algorithm, and avoiding sinking into local optimum.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
Referring to fig. 3, the present embodiment provides an integrated energy system optimizing apparatus 30, including:
the first optimizing module 31 is configured to obtain optimal energy storage transaction information of the target area comprehensive energy system and the energy storage aggregator in a period to be optimized; the energy storage aggregate performs energy storage transaction with a plurality of regional comprehensive energy systems, and the target regional comprehensive energy system is one regional comprehensive energy system;
The second optimizing module 32 is configured to establish a first objective function with the minimum running cost of the target area integrated energy system in the period to be optimized as a target according to the optimal energy storage transaction information; establishing constraint conditions of a first objective function, and solving the first objective function to obtain an optimal unit output strategy of a target comprehensive energy system in a period to be optimized;
and the scheduling module 33 is used for optimally scheduling the target comprehensive energy system based on the optimal unit output strategy.
As a possible implementation, the first optimization module 31 is specifically configured to:
and establishing a second objective function by taking the minimum running cost of the energy storage polymer in the period to be optimized as a target, and solving the second objective function to obtain the optimal energy storage transaction information of the energy storage polymer and the comprehensive energy system of each region.
As one possible implementation, the second objective function is:
；
in the method, in the process of the invention,cost of purchasing energy storage use right for energy storage aggregate to comprehensive energy system of each area, +.>The charge and discharge loss cost generated by the actual scheduling of the energy storage aggregator;The charge and discharge loss cost generated by the actual dispatching of the comprehensive energy system of each region;And renting the energy storage service to the energy storage aggregator for the comprehensive energy system of each region.
As one possible implementation manner, the optimal energy storage transaction information of the energy storage aggregator and the comprehensive energy source system of each region includes:
the energy storage aggregators purchase energy storage using rights from the comprehensive energy systems of all areas and lease the optimal transaction strategies of the energy storage service from the energy storage aggregators by the leasing energy systems of all areas.
As one possible implementation, the first objective function is:
；
in the method, in the process of the invention,the operation and maintenance cost of the renewable energy unit is realized;The fuel consumption cost and the climbing cost of the unit are;Calling cost for interruptible load;A fee paid to the energy storage aggregator for leasing the energy storage;The cost of purchasing electricity from the regional power grid;Punishment cost for wind and light abandonment;Is discharged into carbon
The cost is high;the daily chemical life cycle cost is set;And renting the fee for the energy storage use right.
As one possible implementation, the constraint condition of the first objective function includes:
balance constraints, including electrical system balance constraints, thermal system balance constraints, and cold system balance constraints;
the energy storage equipment frequency division constraint comprises high-frequency constraint of a super capacitor, secondary low-frequency constraint of a lithium battery, lowest-frequency constraint of a heat storage system and lowest-frequency constraint of a cold storage system;
The equipment network constraints include energy supply equipment operation constraints and grid energy supply constraints.
As one possible implementation, the algorithm for solving the first objective function is any one of the following optimization algorithms: genetic algorithm, tabu search algorithm, simulated annealing algorithm, sparrow search algorithm, marine predator algorithm.
Fig. 4 is a schematic diagram of an electronic device 40 according to an embodiment of the present invention. As shown in fig. 4, the electronic device 40 of this embodiment includes: a processor 41, a memory 42 and a computer program 43, such as an integrated energy system optimization program, stored in the memory 42 and executable on the processor 41. The steps in the above-described respective embodiments of the integrated energy system optimization method are implemented by the processor 41 when executing the computer program 43, such as steps S201 to S204 shown in fig. 2. Alternatively, the processor 41, when executing the computer program 43, performs the functions of the modules/units of the above-described device embodiments, such as the functions of the modules 31 to 33 shown in fig. 3.
By way of example, the computer program 43 may be partitioned into one or more modules/units, which are stored in the memory 42 and executed by the processor 41 to complete the present invention. One or more of the modules/units may be a series of computer program instruction segments capable of performing particular functions for describing the execution of the computer program 43 in the electronic device 40.
The electronic device 40 may be a computing device such as a desktop computer, a notebook computer, a palm computer, and a cloud server. Electronic device 40 may include, but is not limited to, a processor 41, a memory 42. It will be appreciated by those skilled in the art that fig. 4 is merely an example of electronic device 40 and is not intended to limit electronic device 40, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., electronic device 40 may also include input-output devices, network access devices, buses, etc.
The processor 41 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 42 may be an internal storage unit of the electronic device 40, such as a hard disk or memory of the electronic device 40. The memory 42 may also be an external storage device of the electronic device 40, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device 40. Further, the memory 42 may also include both internal and external storage units of the electronic device 40. The memory 42 is used to store computer programs and other programs and data required by the electronic device 40. The memory 42 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/electronic device and method may be implemented in other manners. For example, the apparatus/electronic device embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the steps of each method embodiment described above may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the 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 scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (8)
1. A method for optimizing an integrated energy system, comprising:
acquiring optimal energy storage transaction information of a target area comprehensive energy system and an energy storage aggregator in a period to be optimized; the energy storage polymer performs energy storage transaction with a plurality of regional comprehensive energy systems, and the target regional comprehensive energy system is one regional comprehensive energy system;
according to the optimal energy storage transaction information, a first objective function is established by taking the minimum running cost of the target area comprehensive energy system in the period to be optimized as a target;
establishing constraint conditions of the first objective function, and solving the first objective function to obtain an optimal unit output strategy of the target comprehensive energy system in the period to be optimized;
Optimizing and scheduling a target comprehensive energy system based on the optimal unit output strategy;
the obtaining the optimal energy storage transaction information of the target area comprehensive energy system and the energy storage aggregator in the period to be optimized comprises the following steps:
establishing a second objective function by taking the minimum running cost of the energy storage polymer in the period to be optimized as a target, and solving to obtain the optimal energy storage transaction information of the energy storage polymer and the comprehensive energy system of each region; the optimal energy storage transaction information of the energy storage aggregate and the comprehensive energy system of each region comprises the following steps: the energy storage aggregators purchase energy storage using rights from the comprehensive energy systems of all areas and lease the optimal transaction strategies of the energy storage service from the energy storage aggregators by the leasing energy systems of all areas.
2. The integrated energy system optimization method of claim 1, wherein the second objective function is:
；
in the method, in the process of the invention,cost of purchasing energy storage use right for energy storage aggregate to comprehensive energy system of each area, +.>The charge and discharge loss cost generated by the actual scheduling of the energy storage aggregator;The charge and discharge loss cost generated by the actual dispatching of the comprehensive energy system of each region;And renting the energy storage service to the energy storage aggregator for the comprehensive energy system of each region.
3. The integrated energy system optimization method of claim 1 or 2, wherein the first objective function is:
；
in the method, in the process of the invention,the operation and maintenance cost of the renewable energy unit is realized;The fuel consumption cost and the climbing cost of the unit are;Calling cost for interruptible load;A fee paid to the energy storage aggregator for leasing the energy storage;The cost of purchasing electricity from the regional power grid;Punishment cost for wind and light abandonment;Is discharged into carbon
The cost is high;the daily chemical life cycle cost is set;And renting the fee for the energy storage use right.
4. The integrated energy system optimization method of claim 3, wherein the constraints of the first objective function include:
balance constraints, including electrical system balance constraints, thermal system balance constraints, and cold system balance constraints;
the energy storage equipment frequency division constraint comprises high-frequency constraint of a super capacitor, secondary low-frequency constraint of a lithium battery, lowest-frequency constraint of a heat storage system and lowest-frequency constraint of a cold storage system;
the equipment network constraints include energy supply equipment operation constraints and grid energy supply constraints.
5. The integrated energy system optimization method of claim 3, wherein the algorithm for solving the first objective function is any one of the following optimization algorithms: genetic algorithm, tabu search algorithm, simulated annealing algorithm, sparrow search algorithm, marine predator algorithm.
6. An integrated energy system optimization device, comprising:
the first optimization module is used for acquiring optimal energy storage transaction information of the target area comprehensive energy system and the energy storage aggregator in the period to be optimized; the energy storage polymer performs energy storage transaction with a plurality of regional comprehensive energy systems, and the target regional comprehensive energy system is one regional comprehensive energy system;
the second optimization module is used for establishing a first objective function with the minimum running cost of the target area comprehensive energy system in the period to be optimized as a target according to the optimal energy storage transaction information; establishing constraint conditions of the first objective function, and solving the first objective function to obtain an optimal unit output strategy of the target comprehensive energy system in the period to be optimized;
the scheduling module is used for optimally scheduling the target comprehensive energy system based on the optimal unit output strategy;
the obtaining the optimal energy storage transaction information of the target area comprehensive energy system and the energy storage aggregator in the period to be optimized comprises the following steps:
establishing a second objective function by taking the minimum running cost of the energy storage polymer in the period to be optimized as a target, and solving to obtain the optimal energy storage transaction information of the energy storage polymer and the comprehensive energy system of each region; the optimal energy storage transaction information of the energy storage aggregate and the comprehensive energy system of each region comprises the following steps: the energy storage aggregators purchase energy storage using rights from the comprehensive energy systems of all areas and lease the optimal transaction strategies of the energy storage service from the energy storage aggregators by the leasing energy systems of all areas.
7. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 5 when the computer program is executed.
8. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 5.
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| CN115689035A (en) * | 2022-11-08 | 2023-02-03 | 国网四川省电力公司经济技术研究院 | Cooperative optimization method for park level comprehensive energy system based on shared energy storage |
| CN115688448A (en) * | 2022-11-08 | 2023-02-03 | 国网综合能源服务集团有限公司 | Optimal scheduling method for multi-region comprehensive energy system considering shared energy storage |
| CN116342166A (en) * | 2023-03-31 | 2023-06-27 | 华南理工大学 | Energy game regulation and control method and equipment based on multi-region sharing |
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| CN115689035A (en) * | 2022-11-08 | 2023-02-03 | 国网四川省电力公司经济技术研究院 | Cooperative optimization method for park level comprehensive energy system based on shared energy storage |
| CN115688448A (en) * | 2022-11-08 | 2023-02-03 | 国网综合能源服务集团有限公司 | Optimal scheduling method for multi-region comprehensive energy system considering shared energy storage |
| CN116342166A (en) * | 2023-03-31 | 2023-06-27 | 华南理工大学 | Energy game regulation and control method and equipment based on multi-region sharing |
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| 区域能源互联网多能流协同优化调度策略研究;郭宴秀;万方学位论文;全文 * |
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