CN112465240B - Cooperative game-based multi-park energy scheduling optimization method for comprehensive energy system - Google Patents
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Abstract
The invention relates to a cooperative game-based multi-park energy scheduling optimization method for a comprehensive energy system, which comprises the following steps of: 1) acquiring a comprehensive energy system structure comprising multiple parks, and acquiring electric energy transaction modes between the parks and a power distribution network and among the parks; 2) constructing a multi-park energy scheduling cooperation game optimization model according to the comprehensive energy system equipment output model and the park operation cost model; 3) and solving the multi-park energy scheduling cooperative game optimization model to obtain the optimal scheduling scheme of the comprehensive energy system. Compared with the prior art, the method has the advantages of improving the energy utilization rate, relieving the energy supply pressure, reducing the daily operation cost of the park and the load peak-valley difference of the power grid and the like.
Description
Technical Field
The invention relates to the field of control of an integrated energy system, in particular to a cooperative game-based multi-park energy scheduling optimization method for the integrated energy system.
Background
The capacity of a single park is limited, and by forming a park interconnection system, namely sharing load and sharing reserve capacity with adjacent parks, the system has the advantages of enhancing the reliability of the system, expanding the power supply range, improving the consumption rate of new energy and the like. However, most of the existing research only optimizes the electric energy of multiple parks, and neglects that in the comprehensive energy market, various energy sources such as cold, heat and gas can also fall into the broad resource category of demand side and participate in energy trading, thereby realizing the collaborative optimization of the comprehensive energy network.
The development of various energy storage technologies promotes the consumption of new energy, the existing wind energy storage mode has the problems of limited storage capacity, insufficient economy, incapability of large-scale use and the like except for pumped storage, the electric energy can be stored in a natural gas mode in a large scale due to the development of an electricity-to-gas (P2G) technology, the coupling effect of various forms of energy in the stages of production, transmission, use and the like is stronger and stronger, the research on an electric-heat coupled comprehensive energy system is very comprehensive at present, however, the research on an electricity, heat, cold and comprehensive energy system is less, and in the existing park comprehensive energy scheduling method, the utilization rate of energy is not high, and the optimal resource allocation cannot be achieved
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a cooperative game-based multi-park energy scheduling optimization method for an integrated energy system.
The purpose of the invention can be realized by the following technical scheme:
a cooperative game-based multi-park energy scheduling optimization method for an integrated energy system comprises the following steps:
1) acquiring a comprehensive energy system structure comprising multiple parks, and acquiring electric energy transaction modes between the parks and a power distribution network and among the parks;
2) constructing a multi-park energy scheduling cooperation game optimization model according to the comprehensive energy system equipment output model and the park operation cost model;
3) and solving the multi-park energy scheduling cooperation game optimization model to obtain the optimal scheduling scheme of the comprehensive energy system.
Step 1) in, this comprehensive energy system contain a plurality of gardens, every garden is connected with the distribution network respectively to can directly carry out the electric energy transaction with the distribution network, also can carry out the electric energy transaction between every garden simultaneously.
In the step 1), each park comprises distributed energy sources, energy storage equipment and electric heating loads.
In the step 2), the output model of the integrated energy system equipment comprises a gas turbine output model, a gas boiler output model, an energy conversion equipment model and an energy storage equipment model, and the energy conversion equipment model comprises an electric boiler model, an absorption type refrigerator model and an electric refrigerator model.
The expression of the gas turbine output model is as follows:
P ht (t)＝Q mt (t)θ ht K oph
wherein, P mt (t) exhaust waste heat quantity, P, of the gas turbine for a period t e (t) the electric power output of the gas turbine for a time period t, θ e (t) Power Generation efficiency of gas turbine for time period t, θ L Is the heat loss coefficient, P, of the gas turbine ht (t) is the refrigerating capacity of the bromine refrigerator in time period t, K oph Is the heating coefficient of the bromine refrigerator, theta ht The recovery rate of the flue gas of the bromine refrigerator is obtained;
the expression of the gas boiler output model is as follows:
P nb (t)＝η nb λ gas γ nb
wherein, P nb (t) and γ nb Thermal power and gas consumption rate, eta, respectively, of the gas boiler at t-period nb For heat production efficiency, λ, of gas-fired boilers gas Is the heat value of natural gas;
in the energy conversion equipment model, the expression of the electric boiler model is as follows:
Q EB (t)＝η EB ·P EB (t)
wherein Q is EB (t) the thermal power output by the electric boiler in the period of t; p EB (t) the electric power consumed by the electric boiler for a period of t; eta EB The electric heat conversion efficiency of the electric boiler;
the expression of the absorption chiller model is:
Q AC (t)＝K COP,AC ·Q input (t)
wherein Q is AC (t) is the cold power output from the absorption refrigerator during t periods, Q input (t) is the thermal power input to the absorption refrigerator during t periods, K COP,AC The operating performance coefficient of the absorption refrigerator is t time period;
the expression of the electric refrigerator model is as follows:
Q EC (t)＝K COP,EC ·P EC (t)
wherein Q is EC (t) is the cold power output by the electric refrigerator during the period of t, P EC (t) is the electric power consumed by the electric refrigerator during the period t, K COP,EC The operation performance coefficient of the electric refrigerator is t time period;
the expression of the energy storage equipment model is as follows:
wherein S is soc (t)、S soc (t-1) the states of charge of the battery at times t and t-1, respectively, σ the self-discharge rate of the battery, ρ cha 、ρ dis Efficiency of charging and discharging the accumulator, P, respectively cha (t)、P dis (t) the charging and discharging power of the storage battery in a period of t, respectively, Δ t is the time interval of the period of t, X t 、Y t Are variables representing the state of charge and the state of discharge of the battery, respectively, and X t ∈{0，1}，Y t ∈{0，1}，E bat Is the rated capacity of the storage battery.
In the step 2), the park operation cost model comprises a distributed energy cost model, an electricity purchasing cost model, a gas cost model and an energy storage equipment maintenance cost model.
The expression of the distributed energy cost model is as follows:
wherein, the first and the second end of the pipe are connected with each other,
and
respectively outputting electric power for photovoltaic and wind power generation equipment in the park n in the period of t, K pv And K wt Respectively representing the unit electric quantity operation and maintenance costs of photovoltaic and wind power generation equipment;
the expression of the electricity purchasing cost model is as follows:
wherein, a t 、b t Respectively are the dynamic electricity price coefficient,
the total power purchasing is carried out for the multi-park in the time period t,
purchasing electric power for park n during time period t, c ele (t) is the dynamic electricity price,
purchasing electricity cost for the park n;
the expression of the gas cost model is as follows:
wherein, c gas In order to achieve the price of the natural gas,
in order to meet the gas purchase cost of the park n,
for the n gas turbines in the park to consume the amount of natural gas,
consuming natural gas quantity for n gas boilers in the park;
the expression of the energy storage equipment maintenance cost model is as follows:
wherein, K EES For the cost of operating and maintaining the electric energy storage device in unit electric quantity,
and
and respectively charging and discharging power for the equipment.
In the step 2), the multi-park energy scheduling cooperative game optimization model takes the minimum total cost of multi-park combined scheduling as an objective function, and the method comprises the following steps:
wherein N is the total number of the garden and T is the total number of the time periods.
In the step 2), the constraint conditions of the multi-park energy scheduling cooperative game optimization model comprise energy conservation constraint, equipment output constraint, energy storage equipment constraint and mutual power constraint among parks, and the energy conservation constraint comprises electric load power conservation, heat load power conservation and cold load power conservation.
The expression of the electrical load power conservation constraint is as follows:
wherein, P T (t) is the pumped storage power station output, P net (t) is the sum of the power purchasing power from the park to other parks,
for the n electrical loads of the park,
the electric heating equipment in the park consumes electric power,
the power consumption of n electric refrigeration equipment in the park is achieved;
the expression of the heat load power conservation constraint is as follows:
wherein the content of the first and second substances,
for the thermal power of n electric heating equipment in the garden,
for the thermal power of the n gas turbines in the park,
is the thermal power of a gas boiler in a park,
the heat release power of the n heat storage tank in the park area,
the heat storage tank in the park is charged with heat power,
for the n heat load of the park,
the heat power is consumed for the n absorption refrigerators in the park;
the expression of the cold load power conservation constraint is as follows:
wherein the content of the first and second substances,
the refrigerating power of the n electric refrigerating equipment in the park,
in order to absorb the refrigerating power of the refrigerator,
n cold loads for the campus;
the expression of the equipment output constraint is as follows:
wherein the content of the first and second substances,
is the output power of the class j device,
is the maximum output of the j-th class devicePower;
the expression of the energy storage device constraint is as follows:
wherein the content of the first and second substances,
and
respectively storing energy of the electric energy storage and the thermal energy storage in a time period t,
and
respectively storing energy of the electric energy storage and the thermal energy storage in a t-1 time period,
respectively as the minimum value and the maximum value of the electric energy storage capacity and the maximum value of the thermal energy storage capacity,
and
efficiency, η, of charging and discharging, respectively, of electrical energy storage TES 、
Respectively the heat storage energy storage rate, the heat charging efficiency and the heat discharging efficiency of the heat storage energy;
the expression of the interactive power constraint between the parks is as follows:
wherein, P t mn For power interaction between the mth and nth campus,
the minimum and maximum values of the interaction power are respectively.
Compared with the prior art, the invention has the following advantages:
the invention establishes a mathematical model according with the reality based on the coupling relation among the electric load, the heat load and the cold load, can effectively improve the energy utilization rate and relieve the energy supply pressure by utilizing the combined cooling, heating and power supply comprehensive energy system, has limited capacity of a single park, and can reduce the daily operation cost of the park and reduce the load peak-valley difference of a power grid by forming a park interconnection system, namely sharing the load and sharing the spare capacity with the adjacent parks and considering the influence of market demand on the electricity price of the park under a dynamic electricity price mechanism by considering that the electricity price of the park is influenced by the market demand and providing an energy sharing structure of multiple parks in the comprehensive energy system, wherein the parks mutually exchange electric energy.
Drawings
FIG. 1 is a schematic diagram of a multi-campus power transaction.
FIG. 2 is a view showing the internal structure of a park.
Fig. 3 shows the load of 3 parks in the example, wherein fig. 3a shows the load of park 1, fig. 3b shows the load of park 2, and fig. 3c shows the load of park 3.
Figure 4 is a campus electricity purchase diagram.
Fig. 5 shows dynamic electricity prices for electricity purchase in a park.
Figure 6 shows the power interaction between the parks.
FIG. 7 is a flow chart of the method of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
As shown in fig. 7, the invention provides a cooperative game-based multi-park energy scheduling optimization method for an integrated energy system, a multi-park day-ahead electric energy trading structure researched by the invention is shown in fig. 1, and a market main body mainly comprises a power distribution network and parks distributed in the power distribution network. The power distribution network can sell power to the park and can also purchase power to the park, and the power selling and purchasing price is determined by the power distribution network. And determining an electric energy transaction mode and a dispatching plan on the 2 nd day by taking the minimum running cost as a target according to the load demand and the running constraint of the park. The trade electricity price between gardens is given according to the distribution network and sells the electricity price, is less than the distribution network and sells the electricity price, is higher than the distribution network and purchases the electricity price.
The market body includes a power distribution grid and a campus containing a comprehensive energy system (CCHP system); the trading mode between garden and distribution network includes two kinds:
1) the park trades directly with the distribution network.
2) Electric energy can be interacted between the parks, the parks can trade with the power distribution network, and the parks determine the trading priority level according to the electricity price.
1. Park force equipment and cost analysis
As shown in figure 2, in the park researched by the invention, energy is obtained from the outside through a power distribution network and natural gas, a fan, a photovoltaic and other distributed power supplies are arranged in the park, an energy storage part stores electric energy and thermal energy, the three parks have the same structure, and the distributed power supplies and loads have different conditions. According to the invention, a dynamic electricity price mode is adopted for purchasing electricity prices from the power distribution network in the park, the electricity prices are related to the total load of the power distribution network, and the electricity prices are higher when the total load is larger. Therefore, when each park purchases electricity from the power distribution network, the electricity purchase price is influenced by the operation arrangement of the park and the operation strategies of other parks. Therefore, in order to reduce the operation cost to the maximum extent, the operation modes of internal distributed power supplies, output equipment and energy storage need to be coordinated mutually among a plurality of parks to make the optimal cooperation strategy of the parks.
1.1CCHP equipment output model
1) Gas turbine
The gas turbine is the core of the coordinated dispatching of the comprehensive energy system, the waste heat discharged during power generation can meet the requirement of the multi-energy load by refrigerating or heating through the bromine refrigerator, and the mathematical model is as follows:
P ht (t)＝Q mt (t)θ ht K oph
in the formula, P mt (t) exhaust waste heat quantity of the gas turbine for a period t; p is e (t) the electrical power output of the gas turbine for a time period t; theta e (t) the power generation efficiency of the gas turbine for a time period t; theta L A gas turbine heat dissipation loss coefficient; p ht (t) is the refrigerating capacity of the bromine refrigerator in a time period t; k oph The heating coefficient of the bromine refrigerator is shown; theta.theta. ht The recovery rate of the flue gas of the bromine refrigerator is shown.
2) Gas boiler
When the thermal power provided by the gas turbine can not meet the thermal load demand, the thermal power can be provided by the gas boiler, and the mathematical model is as follows:
P nb (t)＝η nb λ gas γ nb
in the formula: p nb (t) and γ nb Respectively thermal power and gas consumption rate of the gas boiler at t time period; eta nb The heat production efficiency of the gas boiler is improved. Lambda [ alpha ] gas Is the heat value of natural gas.
3) Energy conversion equipment model
The energy conversion equipment in the embodiment comprises an electric boiler, an absorption refrigerator and an electric refrigerator, and specifically comprises the following components:
Q EB (t)＝η EB ·P EB (t)
in the formula, Q EB (t) the thermal power output by the electric boiler in the period of t; p EB (t) the electric power consumed by the electric boiler for a period of t; eta EB The electric heat conversion efficiency of the electric boiler.
Q AC (t)＝K COP,AC ·Q input (t)
In the formula, Q AC (t) the cold power output by the absorption refrigerator in the period of t; q input (t) the thermal power input by the absorption refrigerator in the period t; k COP,AC The coefficient of performance of the absorption chiller operating for the period t.
Q EC (t)＝K COP,EC ·P EC (t)
In the formula, Q EC (t) the cold power output by the electric refrigerator in the period of t; p EC (t) the electric power consumed by the electric refrigerator for a period of t; k is COP,EC The operation performance coefficient of the electric refrigerator is t time period.
4) Energy storage device model
In the formula, S soc (t)、S soc (t-1) the charge states of the stored energy at the time t and the time t-1 respectively; sigma is the self-discharge rate of the storage battery; ρ is a unit of a gradient cha 、ρ dis Respectively charging and discharging efficiency of the storage battery; p cha (t)、P dis (t) the charging and discharging power of the storage battery at the time period t respectively; x t 、Y t Respectively, a charged state and a discharged state of the battery, wherein X t ∈{0，1}，Y t ∈{0，1}，E bat Is the rated capacity of the storage battery.
2. Park operation cost model
The operation cost of the park of the invention comprises the external energy purchasing cost and the operation and maintenance cost of internal equipment, and does not comprise the investment cost of various equipment and the like.
1) Distributed energy costs
In the formula:
and
respectively outputting electric power for the photovoltaic and wind power generation equipment in the t period; k pv And K wt Respectively representing the unit electric quantity operation and maintenance costs of photovoltaic and wind power generation equipment; Δ t is the t period time interval.
2) Cost of electricity purchase
Each park adopts a dynamic electricity price mode from the power grid for electricity purchasing, and the park electricity purchasing cost is as follows:
in the formula, a t ，b t The dynamic electricity price coefficients are respectively taken by dividing three stages according to peak-valley, and different coefficients can influence the final optimized scheduling result.
3) Cost of combustion gas
The gas costs are derived primarily from the gas turbine and the gas boiler, and the costs can be expressed as:
in the formula, c gas Is the natural gas price.
4) Energy storage device maintenance cost
The park is provided with electric and thermal energy storage equipment, and the operation and maintenance cost of the thermal energy storage equipment is lower than that of the electric energy storage equipment because the thermal energy storage is mostly water as a heat storage medium, so the thermal energy storage equipment is not considered in the invention. The operation and maintenance cost of the electric energy storage in the time period t is as follows:
in the formula, K EES Operating and maintaining cost for unit electric quantity of the electric energy storage device;
and
and respectively charging and discharging power for the equipment.
3. Multi-park combined scheduling optimization method
The participants of the cooperative game maximize the self benefits in a cooperative win-win mode, information among the participants can be exchanged, and the surplus power can be mutually used by a cooperative union through information mutual sharing between the surplus power park and the small power park. The main research content of the method is the problem of maximizing the alliance income or minimizing the alliance cost.
The single park generates electricity through a self distributed power supply and a CCHP unit, and energy is exchanged from a power grid and a gas grid, so that the self requirement is met; but a plurality of different parks can form a cooperative union through information sharing, and mutually use redundant energy, so that the electric energy sold to a power grid by each park at a lower price can be avoided in the overall view; therefore, the problem of minimization of the scheduling cost of the multiple parks can be regarded as a cooperative game optimization model, and the total cost function of the combined scheduling of the multiple parks is the sum of the scheduling costs of the multiple parks:
the constraint conditions include respective constraint conditions of the three parks and common constraint conditions of the three parks, and the constraint conditions are as follows for park 1:
1) the energy conservation constraint comprises the conservation of electric load power, the conservation of heat load power and the conservation of cold load power.
2) Device force constraints
Wherein j represents any type of device except for the user loads of the types in fig. 1;
the output power of the j-th equipment;
the maximum output power of the j-th class device.
3) Energy storage device restraint
In the formula (I), the compound is shown in the specification,
and
energy storage energy of the electric energy storage and the thermal energy storage in a time period t is respectively stored;
the minimum value and the maximum value of the electric energy storage capacity and the maximum value of the thermal energy storage capacity are respectively;
and
charging and discharging efficiencies for electrical energy storage, respectively; 1-. eta. TES ，
Respectively, the loss rate of the thermal energy storage delta t period, and the charging and discharging of the thermal energy storageAnd (4) thermal efficiency.
4) Inter-campus interaction power constraints
In the formula (I), the compound is shown in the specification,
the minimum and maximum values of the interaction power are respectively.
Examples
In order to verify the effectiveness of the method, simulation is carried out by adopting a yalnip toolbox and a cplex solver under the matlab compiling environment.
Suppose there are 3 parks in a regional grid, each of which is equipped with a CCHP system, wind and photovoltaic power generation equipment, and electricity, heat and cold energy storage. The CCHP system comprises the following equipment parameters: gas turbine power generation efficiency
Efficiency of waste heat recovery
The conversion efficiencies of the heat pump, the electric refrigeration and the absorption refrigerator are respectively
The limit value of the electric heating and cooling energy storage capacity is
The electric heating and cooling energy storage charging and discharging efficiency is
The region divides one day into 6 pieces according to time-of-use electricity priceAnalyzing time periods, wherein the peak time periods are 10: 00-15: 00 and 18: 00-21: 00, and the electricity price is 0.82 on a dry basis/kWh; the flat time period is 7: 00-10: 00, 15: 00-18: 00 and 21: 00-24: 00, and the electricity price is 0.53 Ry/kWh; the valley time period is 0: 00-7: 00, the electricity price is 0.25 rah/kWh, and the load of each park is shown in figure 3.
The new energy output conditions of the three parks are different, wherein a fan is arranged in the park 1, a photovoltaic is arranged in the park 2, and a fan is arranged in the park 3;
and (3) simulation results:
as shown in fig. 4 and 5, the peak time periods of electricity purchasing of three parks are concentrated, which results in that the dynamic electricity prices of electricity purchasing of the parks are at the peak value, and the maximum advantage of the dynamic electricity prices compared with the time-of-use electricity prices is that the load on the side of the power grid can be adjusted more flexibly and accurately. The peak electricity usage periods for the three parks are concentrated around time period 20, which results in the peak total load for the three parks at that time period, and hence the dynamic electricity prices at maximum for time period 20.
As shown in fig. 6, when the electric power between the parks is positive, it means that the park purchases electricity from the former to the latter, and when the electric power is negative, it means that the park sells electricity from the former to the latter; as seen in the figure, between parks 1, 2, time period 5-7, because the total load of the park 1 is larger in this time period, in order to reduce the total energy cost, the park 1 buys electricity to 2; and in the rest period, the park 1 sells electricity to the park 2, because the output of the new energy of the park 1 is greater than that of the park 2, the energy consumption cost is lower.
Taking time period 12-20 as an example, there is a situation where campus 1 sells electricity to campus 2 while campus 2 sells electricity to campus 3, because between campuses 1, 2, 3, the energy cost for campuses 2 and 3 is higher than campus 1, while the energy cost for campuses 3 is higher than campus 2.
The multi-campus cooperative gaming versus single-campus optimization cost pairs are shown in table 1.
TABLE 1 optimized cost comparison
| | Park | 1 | |
|
Total cost of |
| Single park optimization | 23564 | 18659 | 13456 | 55679 | |
| Multi-campus gaming | 22432 | 17589 | 11084 | 51105 |
No interactive power exists between the parks in the single-park optimization scene, and other operating conditions are consistent with those in the multi-park scene. In the multi-park cooperation game model developed by the invention, when the park optimizes and distributes the energy sources of cooling, heating and power, the influence of other park strategy arrangements on the park needs to be considered, and the own strategy needs to be continuously adjusted according to the adversary strategy. In the comparative example, assume that the parks adopt the CCHP mode to supply energy, but do not carry out the game between the parks, each park is independently optimized, and the influence of other parks is not considered in every park when the decision-making. The table above S shows the daily operating costs of the campus during unoptimized, single-campus optimization, and multi-campus game optimization in the CCHP mode. It can be seen from the table that the cost of the campus is further reduced when the game optimization model of the present invention is applied to the campus. Thus, the campus is willing to participate in game optimization in order to reduce daily turn-around costs.
The invention provides a cooperative game-based multi-park energy scheduling optimization method for a comprehensive energy system based on a park energy utilization system comprising a distributed power supply and CCHP, and the method is verified through example analysis to obtain the following conclusion:
1. the energy supply mode of CCHP is adopted in the park, so that the cascade utilization of energy can be realized, and the operation cost is reduced;
2. compared with the time-of-use electricity price, the electricity purchasing method adopting the dynamic electricity price can reflect the electricity purchasing dynamic state of the park and flexibly adjust the electricity purchasing cost so as to enhance the capacity of participating in the peak shaving auxiliary service market of the park;
3. compared with the independent optimal scheduling of the parks, the cooperative game-based multi-park cooperative scheduling strategy can reduce the daily operation cost of the parks.
Claims (5)
1. A cooperative game-based multi-park energy scheduling optimization method for an integrated energy system is characterized by comprising the following steps:
1) acquiring a comprehensive energy system structure comprising multiple parks, and acquiring electric energy transaction modes between the parks and a power distribution network and among the parks;
2) the multi-park energy scheduling cooperation game optimization model is constructed according to an integrated energy system equipment output model and a park operation cost model, the integrated energy system equipment output model comprises a gas turbine output model, a gas boiler output model, an energy conversion equipment model and an energy storage equipment model, the energy conversion equipment model comprises an electric boiler model, an absorption type refrigerating machine model and an electric refrigerating machine model, and the expression of the gas turbine output model is as follows:
P ht (t)＝Q mt (t)θ ht K oph
wherein, P mt (t) exhaust waste heat quantity, P, of the gas turbine for a period t e (t) the electrical power output of the gas turbine for a period t, θ e (t) is the period of tFuel gasPower generation efficiency of turbine, theta L For the heat loss coefficient, P, of the gas turbine ht (t) refrigerating capacity of bromine refrigerator, K oph Is the heating coefficient of the bromine refrigerator, theta ht The recovery rate of the flue gas of the bromine refrigerator is obtained;
the expression of the gas boiler output model is as follows:
P nb (t)＝η nb λ gas γ nb
wherein, P nb (t) and γ nb Respectively thermal power and gas consumption rate, eta, of the gas-fired boiler at t period nb For gas-fired boilers to produce heat with efficiency, lambda gas Is the heat value of natural gas;
in the energy conversion equipment model, the expression of the electric boiler model is as follows:
Q EB (t)＝η EB ·P EB (t)
wherein Q is EB (t) the thermal power output by the electric boiler in the period of t; p EB (t) the electric power consumed by the electric boiler for a period of t; eta EB The electric heat conversion efficiency of the electric boiler;
the expression of the absorption chiller model is:
Q AC (t)＝K COP,AC ·Q input (t)
wherein Q is AC (t) is the cold power output from the absorption refrigerator during t periods, Q input (t) is the thermal power input to the absorption refrigerator during t periods, K COP,AC The operating performance coefficient of the absorption refrigerator is t time period;
the expression of the electric refrigerator model is as follows:
Q EC (t)＝K COP,EC ·P EC (t)
wherein Q is EC (t) is the cold power output by the electric refrigerator during the period of t, P EC (t) is the electric power consumed by the electric refrigerator during the period t, K COP,EC The operation performance coefficient of the electric refrigerator is t time period;
the expression of the energy storage equipment model is as follows:
wherein S is soc (t)、S soc (t-1) the states of charge of the battery at times t and t-1, respectively, σ the self-discharge rate of the battery, ρ cha 、ρ dis Efficiency of charging and discharging the accumulator, P, respectively cha (t)、P dis (t) the charging and discharging power of the storage battery in a period of t, respectively, Δ t is the time interval of the period of t, X t 、Y t Are variables representing the state of charge and the state of discharge of the battery, respectively, and X t ∈{0，1}，Y t ∈{0，1}，E bat The rated capacity of the storage battery;
the park operation cost model comprises a distributed energy cost model, an electricity purchasing cost model, a gas cost model and an energy storage equipment maintenance cost model, and the expression of the distributed energy cost model is as follows:
wherein the content of the first and second substances,
and
respectively outputting electric power for photovoltaic and wind power generation equipment in the park n in the period of t, K pv And K wt Respectively representing the unit electric quantity operation and maintenance costs of photovoltaic and wind power generation equipment;
the expression of the electricity purchasing cost model is as follows:
wherein, a t 、b t Respectively are the dynamic electricity price coefficient,
the total power purchasing is carried out for the multi-park in the time period t,
purchasing electric power for park n during time period t, c ele (t) is a dynamic electricity price,
the electricity purchasing cost for the park n;
the expression of the gas cost model is as follows:
wherein, c gas In order to be the price of the natural gas,
in order to meet the gas purchase cost of the park n,
the natural gas quantity is consumed by the gas turbine in the park n,
consuming natural gas quantity for n gas boilers in the park;
the expression of the energy storage equipment maintenance cost model is as follows:
wherein, K EES For the cost of operating and maintaining the electric energy storage device in unit electric quantity,
and
respectively charging and discharging power for equipment;
the multi-park energy scheduling cooperative game optimization model takes the minimum total cost of multi-park combined scheduling as an objective function, and the method comprises the following steps:
wherein N is the total number of the garden and T is the total number of the time periods;
3) and solving the multi-park energy scheduling cooperative game optimization model to obtain the optimal scheduling scheme of the comprehensive energy system.
2. The cooperative game-based multi-park energy scheduling optimization method for the integrated energy system according to claim 1, wherein in the step 1), the integrated energy system comprises a plurality of parks, each park is connected with a power distribution network, and can directly trade electric energy with the power distribution network, and meanwhile, electric energy can also trade among the parks.
3. The cooperative game-based energy scheduling optimization method for multiple parks of an integrated energy system according to claim 1, wherein in the step 1), each park includes distributed energy resources, energy storage devices and electric heating loads.
4. The method for optimizing the multi-campus energy scheduling of the integrated energy system based on the cooperative game as claimed in claim 1, wherein in the step 2), the constraint conditions of the multi-campus energy scheduling cooperative game optimization model include an energy conservation constraint, an equipment output constraint, an energy storage equipment constraint and an interaction power constraint between the parks, and the energy conservation constraint includes an electrical load power conservation, a thermal load power conservation and a cold load power conservation.
5. The cooperative game-based energy scheduling optimization method for the multiple parks of the integrated energy system according to claim 4, wherein the expression of the power conservation constraint of the electrical load is as follows:
wherein, P T (t) is the pumped storage power station output, P net (t) is the sum of the power purchased by the park to other parks,
is an electric load of n number of the garden,
for the n electric heating equipment in the park to consume electric power,
the power consumption of n electric refrigeration equipment in the park is achieved;
the expression of the heat load power conservation constraint is as follows:
wherein the content of the first and second substances,
for the thermal power of n electric heating equipment in the garden,
for the thermal power of the n gas turbines in the park,
is the thermal power of a gas boiler in a park area,
the heat release power of the n heat storage tank in the park area,
the heat storage tank in the park is charged with heat power,
for the n heat load of the park,
the heat power of the absorption refrigerator in the park is consumed;
the expression of the cold load power conservation constraint is as follows:
wherein the content of the first and second substances,
the refrigerating power of the n electric refrigerating equipment in the park,
in order to absorb the refrigerating power of the refrigerating machine,
n cold loads for the park;
the expression of the equipment output constraint is as follows:
wherein, the first and the second end of the pipe are connected with each other,
is the output power of the class j device,
the maximum output power of the j-th class device;
the expression of the energy storage device constraint is as follows:
wherein the content of the first and second substances,
and
respectively storing energy of the electric energy storage and the thermal energy storage in a time period t,
and
respectively storing energy of the electric energy storage and the thermal energy storage in a t-1 time period,
respectively as the minimum value and the maximum value of the electric energy storage capacity and the maximum value of the thermal energy storage capacity,
and
efficiency of charging and discharging, eta, respectively, for electrical energy storage TES 、
Respectively is a heat storageEnergy storage rate, heat charging and heat discharging efficiency of heat storage;
the expression of the interactive power constraint between the parks is as follows:
wherein the content of the first and second substances,
for power interaction between the mth and nth campus,
the minimum and maximum values of the interaction power are respectively.
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