CN113065759A - Comprehensive energy system optimal scheduling method and system considering energy quality - Google Patents

Abstract

The invention relates to a comprehensive energy system optimal scheduling method and system considering energy quality, which comprises the following steps: obtaining various energy sources

The coefficients and the various energy loads at various time intervals corresponding to the large time scale are substituted into a pre-established large time scale optimization model for solving to obtain a scheduling plan at each time interval; and performing rolling adjustment on the scheduling plan at each time interval to obtain the scheduling plan at each moment corresponding to the small time scale in each time interval. The technical scheme provided by the invention considers the energy quality and adopts double-time scale optimization to accurately reflect the running state of the comprehensive energy system in real time, thereby realizing scientific dispatching management of the related equipment of the comprehensive energy systemAnd the low-carbon economic operation of the comprehensive energy system has reference significance for the comprehensive energy optimization operation work.

Description

Comprehensive energy system optimal scheduling method and system considering energy quality

Technical Field

The invention relates to the field of optimization operation of an integrated energy system, in particular to an energy quality considered integrated energy system optimization scheduling method and system.

Background

In recent years, with the increasing energy demand, global energy crisis problems and environmental problems are prominent, and higher requirements on cost reduction and efficiency improvement of energy systems are required.

The comprehensive energy system relates to the coupling of various cold, heat, electricity and gas energy sources, comprises various devices, has complex operation condition of the whole system, and is particularly important for improving the utilization efficiency of the energy sources and reducing the operation cost of the system by modeling and optimizing the system.

The method for evaluating the energy utilization rate by the energy efficiency and optimizing the operation of the comprehensive energy system based on the energy utilization rate is available, but the energy utilization rate evaluation by the energy efficiency reflects the balance of different energy quantities and the utilization level of the quantity, and reflects the external loss of the quantity; the thermal efficiency of energy utilization is evaluated according to the quantitative relation of quantitative conversion according to the first law of thermodynamics, and the problem of energy derogation caused by the irreversible process cannot be reflected, so that the optimization of the operation of the comprehensive energy system can cause the optimization operation result of the comprehensive energy system to be unreasonable.

The improvement of the energy utilization rate of the comprehensive energy system is critical to reduce the energy depreciation, that is, the improvement of the utilization of the quality of various energy sources of the comprehensive energy system, so that the operation optimization of the comprehensive energy system is more reasonable, the energy quality needs to be considered as an optimization consideration, and based on this, a comprehensive energy system operation optimization method capable of dynamically adjusting the output condition of the comprehensive energy system and considering the utilization of the quality of the energy sources is urgently needed to be researched.

Disclosure of Invention

Aiming at the defects of the prior art, the invention aims to provide the comprehensive energy system optimization scheduling method and system considering the energy quality.

The purpose of the invention is realized by adopting the following technical scheme:

the invention provides a comprehensive energy system optimal scheduling method considering energy quality, which comprises the following steps:

obtaining various energy sources

The coefficients and the various energy loads at various time intervals corresponding to the large time scale are substituted into a pre-established large time scale optimization model for solving to obtain a scheduling plan at each time interval;

rolling and adjusting the scheduling plan at each time interval to obtain a scheduling plan at each moment corresponding to the small time scale in each time interval;

wherein the large time scale is greater than the small time scale;

said large timeThe scale optimization model is based on various energy loads and various energy sources

Coefficient is lowest by running cost

The loss is minimized to determine a dispatch plan for the target.

The invention provides a comprehensive energy system optimization scheduling system considering energy quality, which comprises:

an acquisition module for acquiring various energy sources

The coefficients and the various energy loads at various time intervals corresponding to the large time scale are substituted into a pre-established large time scale optimization model for solving to obtain a scheduling plan at each time interval;

the adjusting module is used for performing rolling adjustment on the scheduling plan at each time interval to obtain the scheduling plan at each moment corresponding to the small time scale in each time interval;

wherein the large time scale is greater than the small time scale;

the large time scale optimization model is based on various energy loads and various energy sources

Coefficient is lowest by running cost

The loss is minimized to determine a dispatch plan for the target.

Compared with the closest prior art, the invention has the following beneficial effects:

the technical scheme provided by the invention can be used for obtaining various energy sources

The coefficient and the load of various energy sources under various time periods corresponding to the large time scale are substituted into the pre-established large time scale optimizationSolving in the model to obtain a scheduling plan at each time interval; performing rolling adjustment on the scheduling plan at each time interval to obtain a scheduling plan at each moment corresponding to a small time scale in each time interval, wherein the large time scale is larger than the small time scale; the large time scale optimization model is based on various energy loads and various energy sources

Coefficient is lowest by running cost

The loss is minimized to determine a dispatch plan for the target. According to the scheme, the energy quality is considered, the double-time-period optimization is adopted, the running state of the comprehensive energy system is accurately reflected in real time, scientific dispatching management of relevant equipment of the comprehensive energy system and efficient energy utilization of the comprehensive energy system are realized, and the reference significance is provided for the comprehensive energy optimization running work.

Drawings

FIG. 1 is a flow chart of a method for optimizing and scheduling an integrated energy system that takes into account energy quality;

FIG. 2 is a block diagram of an integrated energy system optimization scheduling system that takes into account energy quality;

fig. 3 is a diagram of an integrated energy system according to an embodiment of the present invention.

Detailed Description

The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example 1:

the invention provides an energy quality-considered comprehensive energy system optimization scheduling method, as shown in fig. 1, comprising the following steps:

step 101, obtaining various energy sources

The coefficients and the various energy loads at various time intervals corresponding to the large time scale are substituted into a pre-established large time scale optimization model for solving to obtain a scheduling plan at each time interval;

step 102, rolling and adjusting the scheduling in each time interval to obtain a scheduling plan of each time corresponding to a small time scale in each time interval;

wherein the large time scale is greater than the small time scale;

the large time scale optimization model is based on various energy loads and various energy sources

Coefficient is lowest by running cost

The loss is minimized to determine a dispatch plan for the target.

Specifically, the dispatch plan includes: the energy storage/release power regulation values of the storage battery, the ice storage, the heat storage tank and the gas storage tank, and the power regulation value of the comprehensive energy system for purchasing electricity from the power grid and the power regulation value for purchasing gas from the gas grid;

the energy types include: electricity, cold, heat, and natural gas.

Specifically, the construction of the large time scale optimization model includes:

make various energy sources load and various energy sources

The coefficient is the input of the large time scale optimization model, and the scheduling plan is made to be large timeOutputting a scale optimization model;

to minimize operating costs and

establishing an objective function of an optimization model with a large time scale for a target with minimum loss;

and constructing a system energy network power supply balance constraint, a system energy network heat supply balance constraint, a system energy network air supply balance constraint, a system energy network cold supply balance constraint, an energy storage equipment capacity constraint, a unit output constraint and a unit climbing capacity constraint for an objective function of the large-time-scale optimization model.

Further, the objective function of the large time scale optimization model is calculated as follows:

F＝ω₁·C_IES+ω₂·E_loss

wherein F is the objective function value of the large time scale optimization model, omega₁For the weight corresponding to the running cost, ω₂Is composed of

Weight corresponding to the loss, C_IESFor the lowest operating cost of the integrated energy system within the optimum duration, E_lossFor optimizing minimum of comprehensive energy system in time length

And (4) loss.

Further, said C_IESThe calculation formula of (a) is as follows:

C_IES＝min(C_db+C_gas+C_p+C_om)

in the formula, C_dbCost for purchasing electricity from the grid for the integrated energy system within an optimized duration, C_gasCost for the gas purchase from the gas network for the integrated energy system within an optimized duration, C_pFor optimizing the operating costs of the heat supply network in the time-span integrated energy system, C_omThe operation and maintenance cost of the comprehensive energy system within the optimized time length is realized;

said E_lossMeter (2)The formula is as follows:

in the formula (I), the compound is shown in the specification,

inputting for the t period in the optimized duration for the integrated energy system

Output of the integrated energy system in the t-th time period within the optimized time length

And T belongs to (1-T), wherein T is the total time period contained in the optimization time length.

Further, said C_dbIs calculated as follows:

in the formula, c_db(t) the electricity price in the t-th period of the optimized duration, P_i(t) the power purchased from the power grid at the t time period in the optimized time period by the ith combined cooling heating and power subsystem in the comprehensive energy system, delta t is the time period of the time period, i belongs to (1-N), and N is the total number of the combined cooling heating and power subsystems in the comprehensive energy system;

said C is_gasIs calculated as follows:

in the formula, c_gasIs gas value, P_GT,i(t) generating power of the micro gas turbine in the ith combined cooling heating and power subsystem in the integrated energy system in the t period of the optimized time lengthElectric power, Q_GB,i(t) is the heat production power of the gas boiler in the ith combined cooling heating and power subsystem in the comprehensive energy system in the tth time period within the optimized time length, eta_GT,iThe power generation efficiency, eta, of the micro gas turbine in the ith combined cooling heating and power subsystem in the integrated energy system_GB,iThe heat generation efficiency of a gas boiler in the ith combined cooling heating and power subsystem in the comprehensive energy system is obtained;

the above-mentioned

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

for supplying the electric network to the integrated energy system in the t-th time period within the optimized time period

For providing solar energy to the integrated energy system at the tth time interval within the optimized duration

For providing the gas network to the integrated energy system at the tth time interval within the optimized duration

The above-mentioned

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

corresponding to the electric load of the integrated energy system in the tth time period within the optimum time period

For cooling load of integrated energy system at t-th time interval in optimized time length

Corresponding to the thermal load of the integrated energy system during the t-th period of the optimum duration

Further, the

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

the purchased electric power rho of the integrated energy system in the t-th time period within the optimized time length^eBeing electric energy

A coefficient; the above-mentioned

Is calculated as follows:

λ(t)＝1+1/3[T_a(t)/T_sum]⁴-4/3[T_a(t)/T_sum]

wherein I (t) is the intensity of solar radiation in the t-th period of the optimized duration, S_STCIs the area of a solar heat collector in an integrated energy system, S_PVLambda (t) is the area of the photovoltaic panel in the integrated energy system for the solar light at the tth time period within the optimized time period

Coefficient, T_a(T) is the ambient temperature of the integrated energy system at the tth time period within the optimization time period, T_sumIs the temperature of the sun;

the above-mentioned

Is calculated as follows:

in the formula, pi_gIs the ratio of natural gas

G_g(t) is the gas purchasing power of the comprehensive energy system in the tth time period within the optimized time length, pi_g＝LHV_gasζ_gas，LHV_gasFor low heating value, ζ, of natural gas_gasOf natural gas

A coefficient;

the above-mentioned

And

is calculated as follows:

in the formula, L_e(t) electric load, L, of the integrated energy system at the tth time period within the optimized time period_c(t) the cooling load, L, of the integrated energy system at the tth time period within the optimized time period_h(t) is the thermal load of the integrated energy system for the tth period of the optimized duration,

is the temperature of the cold medium and is,

the temperature of the heating medium.

Further, the system energy network power supply balance constraint is calculated according to the following formula:

in the formula, P_CCHP(t) is the net generated electric power of the other power generation equipment except the new energy power generation equipment in the comprehensive energy system in the t period within the optimization time length, P_WT(t) is the wind power output power of the comprehensive energy system in the tth time period within the optimization duration, P_PV(t) photovoltaic for the integrated energy system at the tth time period within the optimization durationOutput power, P_ES(t) the storage/discharge power of a storage battery in the comprehensive energy system in the t-th time period within the optimized time length;

the calculation formula of the system energy network heat supply balance constraint is as follows:

H_GB(t)+H_EB(t)+H_WHB(t)+H_HS(t)＝L_h(t)

in the formula, H_GB(t) is the heat production power H of the gas boiler in the t period in the optimized time length in the comprehensive energy system_EB(t) is the heat production power H of the electric boiler in the t period in the optimized time length in the integrated energy system_WHB(t) is the heat production power of the waste heat boiler in the t-th period of the optimized duration in the comprehensive energy system, H_HS(t) the storage/heat release power of the heat storage tank in the comprehensive energy system in the t-th time period within the optimized time length;

the calculation formula of the system energy network air supply balance constraint is as follows:

G_PtG(t)+G_g(t)+G_GS(t)-G_Dmd(t)＝0

in the formula, G_PtG(t) is the gas production power of the electric gas conversion equipment in the comprehensive energy system in the t-th time period within the optimized time length, G_GS(t) is the storage/discharge power of the gas storage tank in the comprehensive energy system in the t period within the optimized time length G_Dmd(t) optimizing the gas usage load for the tth period of time over the duration of time;

the calculation formula of the system energy network cooling balance constraint is as follows:

C_AC(t)+C_RC(t)+C_CS(t)-L_c(t)＝0

in the formula, C_AC(t) is the refrigerating power of the electric refrigerating equipment in the comprehensive energy system in the t period within the optimized time length, C_RC(t) is the refrigeration power of the absorption refrigeration equipment in the comprehensive energy system in the t period within the optimized duration, C_CS(t) the cold storage/discharge power of the electric refrigeration equipment in the integrated energy system in the t period in the optimized time length.

Specifically, the step 102 includes:

substituting the scheduling plan in each time period into a pre-constructed small time scale rolling optimization model to obtain the scheduling plan of each time corresponding to the small time scale in each time period;

the small time scale rolling optimization model is obtained by performing multilevel construction on the basis of energy types and with the aim of minimizing the operation cost.

Further, the building of the small time scale rolling optimization model comprises:

dividing the levels of the small time scale rolling optimization model based on the energy types;

establishing an objective function of each layer of the small-time scale rolling optimization model by taking the minimum running cost as an objective;

and constructing a system energy network power supply balance constraint, a system energy network heat supply balance constraint, a system energy network air supply balance constraint, a system energy network cold supply balance constraint, an energy storage equipment capacity constraint, a unit output constraint, a unit climbing capacity constraint, a unit energy consumption constraint and a unit output constraint for the objective functions of all layers of the small time scale rolling optimization model.

Specifically, the small time scale rolling optimization model is divided into a cold/heat energy optimization layer, a natural gas energy optimization layer and an electric energy optimization layer;

the time lengths of the small time scales corresponding to the cold/heat energy optimization layer, the natural gas energy optimization layer and the electric energy optimization layer are sequentially decreased.

Further, the objective function of the cold/heat optimization layer of the small time scale rolling optimization model is calculated as follows:

in the formula, F_g,1(t ') cost of natural gas at time t', F_e,1(t ') is the cost of change of the consumer at time t',

to optimize the start of the t-th period in time, k₁Corresponding small for cold/heat energy optimization layerThe duration of the time scale is such that,

the last moment corresponding to the small time scale corresponding to the cold/heat energy optimization layer in the tth time period in the optimization time length is obtained;

the calculation formula of the objective function of the natural gas energy optimization layer of the small time scale rolling optimization model is as follows:

in the formula, F_g,2(x ') is the cost of the natural gas at time x', F_e,2(x') is the cost of change, k, of the consumer at time x₂The length of time for the corresponding small time scale of the natural gas energy optimization layer,

the last moment corresponding to the small time scale corresponding to the natural gas energy optimization layer in the tth time period in the optimization time length is set;

the calculation formula of the objective function of the electric energy optimization layer of the small time scale rolling optimization model is as follows:

in the formula, F_g,3(z ') is the cost of natural gas at time z', F_e,3(z ') is the cost of change of the consumer at time z', F_ES(z ') is the charge-discharge cost of the fuel cell at time z', k₃The duration of the corresponding small time scale for the power optimization layer,

the last time corresponding to the small time scale corresponding to the electric energy optimization layer in the tth time period in the optimization time length is obtained.

Further, said F_g,1(t') is calculated as follows:

in the formula, R_gas(t ') is the gas value at time t', F_MT(t) Natural gas Power consumption of a gas turbine in an Integrated energy System at the tth time period within an optimized time duration, F_GB(t) is the natural gas power consumption of the gas boiler in the comprehensive energy system in the t-th time period within the optimized time length, delta F_MT(t ') is the adjustment of the natural gas consumption power of the gas turbine at time t' in the integrated energy system, Δ F_GB(t ') is an adjustment amount of natural gas consumption power of the gas boiler at the time t' in the integrated energy system,

for the unit adjustment cost of the heat generation power of the gas turbine in the comprehensive energy system,

for the unit adjustment cost, delta P, of the heat production power of the gas boiler in the comprehensive energy system_MT(t ') is the adjustment quantity of the heat generation power of the gas turbine at the time t' in the integrated energy system, delta P_GB(t ') is the adjustment quantity of the heat production power of the gas boiler in the comprehensive energy system at the moment t', and delta t is the time duration of the moment;

said F_e,1(t') is calculated as follows:

in the formula (I), the compound is shown in the specification,

for the unit adjustment cost of the heat generating power of the electric boiler in the comprehensive energy system,

for the unit adjustment cost, delta P, of the cooling power of the electric refrigerator in the integrated energy system_EB(t ') is the adjustment quantity of the heat production power of the electric boiler in the integrated energy system at the time t', delta P_AC(t ') is the adjustment quantity of the refrigerating power of the electric refrigerator in the comprehensive energy system at the moment t';

said F_g,2(x') is calculated as follows:

F_g,2(x')＝R_gas(x')·[G_g(t)+ΔG_g(x')]·Δt

in the formula, R_gas(x ') is the gas value at time x', G_g(t) is the gas purchasing power of the integrated energy system in the tth time period within the optimization time length, delta G_g(x ') is the adjustment quantity of the gas purchasing power of the comprehensive energy system at the moment x';

said F_e,2(x') is calculated as follows:

F_e,2(x')＝μ'_PtG·ΔP_PtG(x')²·Δt

of formula (II) to'_PtGFor the unit adjustment cost, delta P, of the gas production power of the electric gas conversion equipment of the integrated energy system_PtG(x ') is the adjustment quantity of the gas production power of the electric gas conversion equipment of the comprehensive energy system at the moment x';

said F_g,3(z') is calculated as follows:

in the formula, R_gas(z ') is the gas value at time z', F_FC(t) Natural gas consumption Power, Δ F, for the fuel cell in the Integrated energy System at the tth time period within the optimized time duration_FC(z ') is the adjustment of the natural gas power consumption of the gas turbine at time z' in the integrated energy system,

cost, delta P, for unit adjustment of heat production power of a gas turbine in an integrated energy system_FC(z ') is the adjustment amount of the heat production power of the gas turbine in the integrated energy system at the moment z';

said F_e,3(z') is calculated as follows:

in the formula, R_gid(z ') is the electricity price at time z',

the purchased electric power R of the integrated energy system in the t-th time period within the optimized time length_gid(z ') is the adjustment amount of the purchased electric power of the integrated energy system at the moment z',

the cost is adjusted for the unit of the purchased power of the comprehensive energy system;

said F_ES(z') is calculated as follows:

in the formula (I), the compound is shown in the specification,

cost, Δ P, per unit adjustment of fuel cell storage/discharge power in an integrated energy system_c(z ') is the adjustment amount of the stored electric power of the fuel cell in the integrated energy system at the time z', delta P_f(z ') is an adjustment amount of the discharge power of the fuel cell at the time z' in the integrated energy system.

Further, the calculation formula of the unit output constraint is as follows:

in the formula, P_α，minIs the maximum capacity power, P, of the alpha type capacity equipment in the comprehensive energy system_α(t) is the capacity power of the alpha type capacity equipment in the comprehensive energy system in the t time period within the optimization duration, P_α，maxThe minimum capacity of the alpha type capacity equipment in the comprehensive energy systemPower, P_α(X) is the capacity power of the alpha type capacity equipment in the comprehensive energy system at the moment X, delta P_α(X) is the adjustment quantity of the capacity power of the alpha type capacity equipment in the comprehensive energy system at the moment X, and X is a moment of the t-th time period in the optimization duration;

the calculation formula of the unit energy consumption constraint is as follows:

F_α(X)＝F_α(t)+ΔF_α(X)

in the formula, F_α(t) is the energy consumption power of the alpha type energy production equipment in the comprehensive energy system in the t time period within the optimization duration, F_α(X) is the energy consumption power of the alpha type energy production equipment in the comprehensive energy system at the moment X, and delta F_αAnd (X) is the adjustment quantity of the energy consumption power of the alpha type energy production equipment in the comprehensive energy system at the moment X.

Example 2:

the invention provides an integrated energy system optimization scheduling system considering energy quality, as shown in fig. 2, comprising:

an acquisition module for acquiring various energy sources

The coefficients and the various energy loads at various time intervals corresponding to the large time scale are substituted into a pre-established large time scale optimization model for solving to obtain a scheduling plan at each time interval;

the adjusting module is used for performing rolling adjustment on the scheduling plan at each time interval to obtain the scheduling plan at each moment corresponding to the small time scale in each time interval;

wherein the large time scale is greater than the small time scale;

the large time scale optimization model is based on various energy loads and various energy sources

Coefficient is lowest by running cost

The loss is minimized to determine a dispatch plan for the target.

Specifically, the dispatch plan includes: the energy storage/release power regulation values of the storage battery, the ice storage, the heat storage tank and the gas storage tank, and the power regulation value of the comprehensive energy system for purchasing electricity from the power grid and the power regulation value for purchasing gas from the gas grid;

the energy types include: electricity, cold, heat, and natural gas.

Specifically, the system further includes a first building module for pre-building the large time scale optimization model, where the first building module includes:

a setting unit for making the load of various energy sources and various energy sources

The coefficient is the input of the large time scale optimization model, and the scheduling plan is the output of the large time scale optimization model;

a first objective function construction unit for minimizing the sum of running costs

Establishing an objective function of an optimization model with a large time scale for a target with minimum loss;

the first constraint condition construction unit is used for constructing a system energy network power supply balance constraint, a system energy network heat supply balance constraint, a system energy network air supply balance constraint, a system energy network cold supply balance constraint, an energy storage device capacity constraint, a unit output constraint and a unit climbing capacity constraint for an objective function of the large-time-scale optimization model.

Further, the objective function of the large time scale optimization model is calculated as follows:

F＝ω₁·C_IES+ω₂·E_loss

wherein F is the objective function value of the large time scale optimization model, omega₁For right of running costHeavy, omega₂Is composed of

Weight corresponding to the loss, C_IESFor the lowest operating cost of the integrated energy system within the optimum duration, E_lossFor optimizing minimum of comprehensive energy system in time length

And (4) loss.

Further, said C_IESThe calculation formula of (a) is as follows:

C_IES＝min(C_db+C_gas+C_p+C_om)

in the formula, C_dbCost for purchasing electricity from the grid for the integrated energy system within an optimized duration, C_gasCost for the gas purchase from the gas network for the integrated energy system within an optimized duration, C_pFor optimizing the operating costs of the heat supply network in the time-span integrated energy system, C_omThe operation and maintenance cost of the comprehensive energy system within the optimized time length is realized;

said E_lossIs calculated as follows:

in the formula (I), the compound is shown in the specification,

inputting for the t period in the optimized duration for the integrated energy system

Output of the integrated energy system in the t-th time period within the optimized time length

And T belongs to (1-T), wherein T is the total time period contained in the optimization time length.

Further, said C_dbIs calculated as follows:

in the formula, c_db(t) the electricity price in the t-th period of the optimized duration, P_i(t) the power purchased from the power grid at the t time period in the optimized time period by the ith combined cooling heating and power subsystem in the comprehensive energy system, delta t is the time period of the time period, i belongs to (1-N), and N is the total number of the combined cooling heating and power subsystems in the comprehensive energy system;

said C is_gasIs calculated as follows:

in the formula, c_gasIs gas value, P_GT,i(t) is the generated power of the micro gas turbine in the ith combined cooling heating and power subsystem in the comprehensive energy system in the t time period within the optimized time length, Q_GB,i(t) is the heat production power of the gas boiler in the ith combined cooling heating and power subsystem in the comprehensive energy system in the tth time period within the optimized time length, eta_GT,iThe power generation efficiency, eta, of the micro gas turbine in the ith combined cooling heating and power subsystem in the integrated energy system_GB,iThe heat generation efficiency of a gas boiler in the ith combined cooling heating and power subsystem in the comprehensive energy system is obtained;

the above-mentioned

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

for optimizing the comprehensive energy of the power grid in the t-th time periodProvided by a source system

For providing solar energy to the integrated energy system at the tth time interval within the optimized duration

For providing the gas network to the integrated energy system at the tth time interval within the optimized duration

The above-mentioned

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

corresponding to the electric load of the integrated energy system in the tth time period within the optimum time period

For cooling load of integrated energy system at t-th time interval in optimized time length

Corresponding to the thermal load of the integrated energy system during the t-th period of the optimum duration

Further, the

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

the purchased electric power rho of the integrated energy system in the t-th time period within the optimized time length^eBeing electric energy

A coefficient; the above-mentioned

Is calculated as follows:

λ(t)＝1+1/3[T_a(t)/T_sum]⁴-4/3[T_a(t)/T_sum]

wherein I (t) is the intensity of solar radiation in the t-th period of the optimized duration, S_STCIs the area of a solar heat collector in an integrated energy system, S_PVLambda (t) is the area of the photovoltaic panel in the integrated energy system for the solar light at the tth time period within the optimized time period

Coefficient, T_a(T) is the ambient temperature of the integrated energy system at the tth time period within the optimization time period, T_sumIs the temperature of the sun;

the above-mentioned

Is calculated as follows:

in the formula, pi_gIs the ratio of natural gas

G_g(t) is the gas purchasing power of the comprehensive energy system in the tth time period within the optimized time length, pi_g＝LHV_gasζ_gas，LHV_gasFor low heating value, ζ, of natural gas_gasOf natural gas

A coefficient;

the above-mentioned

And

is calculated as follows:

in the formula, L_e(t) electric load, L, of the integrated energy system at the tth time period within the optimized time period_c(t) cooling of the integrated energy system at the tth time period within the optimized time periodLoad, L_h(t) is the thermal load of the integrated energy system for the tth period of the optimized duration,

is the temperature of the cold medium and is,

the temperature of the heating medium.

Further, the system energy network power supply balance constraint is calculated according to the following formula:

in the formula, P_CCHP(t) is the net generated electric power of the other power generation equipment except the new energy power generation equipment in the comprehensive energy system in the t period within the optimization time length, P_WT(t) is the wind power output power of the comprehensive energy system in the tth time period within the optimization duration, P_PV(t) is the photovoltaic output power of the integrated energy system in the tth time period within the optimization time length, P_ES(t) the storage/discharge power of a storage battery in the comprehensive energy system in the t-th time period within the optimized time length;

the calculation formula of the system energy network heat supply balance constraint is as follows:

H_GB(t)+H_EB(t)+H_WHB(t)+H_HS(t)＝L_h(t)

in the formula, H_GB(t) is the heat production power H of the gas boiler in the t period in the optimized time length in the comprehensive energy system_EB(t) is the heat production power H of the electric boiler in the t period in the optimized time length in the integrated energy system_WHB(t) is the heat production power of the waste heat boiler in the t-th period of the optimized duration in the comprehensive energy system, H_HS(t) the storage/heat release power of the heat storage tank in the comprehensive energy system in the t-th time period within the optimized time length;

the calculation formula of the system energy network air supply balance constraint is as follows:

G_PtG(t)+G_g(t)+G_GS(t)-G_Dmd(t)＝0

in the formula, G_PtG(t) is the gas production power of the electric gas conversion equipment in the comprehensive energy system in the t-th time period within the optimized time length, G_GS(t) is the storage/discharge power of the gas storage tank in the comprehensive energy system in the t period within the optimized time length G_Dmd(t) optimizing the gas usage load for the tth period of time over the duration of time;

the calculation formula of the system energy network cooling balance constraint is as follows:

C_AC(t)+C_RC(t)+C_CS(t)-L_c(t)＝0

in the formula, C_AC(t) is the refrigerating power of the electric refrigerating equipment in the comprehensive energy system in the t period within the optimized time length, C_RC(t) is the refrigeration power of the absorption refrigeration equipment in the comprehensive energy system in the t period within the optimized duration, C_CS(t) the cold storage/discharge power of the electric refrigeration equipment in the integrated energy system in the t period in the optimized time length.

Specifically, the adjusting module is configured to:

substituting the scheduling plan in each time period into a pre-constructed small time scale rolling optimization model to obtain the scheduling plan of each time corresponding to the small time scale in each time period;

the small time scale rolling optimization model is obtained by performing multilevel construction on the basis of energy types and with the aim of minimizing the operation cost.

Further, the system further comprises a second building module for pre-building the small time scale rolling optimization model, wherein the second building module is used for:

the dividing unit is used for dividing the levels of the small time scale rolling optimization model based on the energy types;

the second objective function construction unit is used for establishing objective functions of all layers of the small-time scale rolling optimization model by taking the minimum running cost as a target;

and the second constraint condition construction unit is used for constructing a system energy network power supply balance constraint, a system energy network heat supply balance constraint, a system energy network air supply balance constraint, a system energy network cold supply balance constraint, an energy storage device capacity constraint, a unit output constraint, a unit climbing capacity constraint, a unit energy consumption constraint and a unit output constraint for the objective functions of all layers of the small-time-scale rolling optimization model.

Further, the small time scale rolling optimization model is divided into a cold/heat energy optimization layer, a natural gas energy optimization layer and an electric energy optimization layer;

the time lengths of the small time scales corresponding to the cold/heat energy optimization layer, the natural gas energy optimization layer and the electric energy optimization layer are sequentially decreased.

Further, the objective function of the cold/heat optimization layer of the small time scale rolling optimization model is calculated as follows:

in the formula, F_g,1(t ') cost of natural gas at time t', F_e,1(t ') is the cost of change of the consumer at time t',

to optimize the start of the t-th period in time, k₁The duration of the corresponding small time scale for the cold/heat optimization layer,

the last moment corresponding to the small time scale corresponding to the cold/heat energy optimization layer in the tth time period in the optimization time length is obtained;

the calculation formula of the objective function of the natural gas energy optimization layer of the small time scale rolling optimization model is as follows:

in the formula, F_g,2(x ') is the cost of the natural gas at time x', F_e,2(x') is the cost of change, k, of the consumer at time x₂Optimizing layer mapping for natural gas energyThe length of time on the small time scale of (c),

the last moment corresponding to the small time scale corresponding to the natural gas energy optimization layer in the tth time period in the optimization time length is set;

the calculation formula of the objective function of the electric energy optimization layer of the small time scale rolling optimization model is as follows:

in the formula, F_g,3(z ') is the cost of natural gas at time z', F_e,3(z ') is the cost of change of the consumer at time z', F_ES(z ') is the charge-discharge cost of the fuel cell at time z', k₃The duration of the corresponding small time scale for the power optimization layer,

the last time corresponding to the small time scale corresponding to the electric energy optimization layer in the tth time period in the optimization time length is obtained.

Further, said F_g,1(t') is calculated as follows:

in the formula, R_gas(t ') is the gas value at time t', F_MT(t) Natural gas Power consumption of a gas turbine in an Integrated energy System at the tth time period within an optimized time duration, F_GB(t) is the natural gas power consumption of the gas boiler in the comprehensive energy system in the t-th time period within the optimized time length, delta F_MT(t ') is the adjustment of the natural gas consumption power of the gas turbine at time t' in the integrated energy system, Δ F_GB(t ') is an adjustment amount of natural gas consumption power of the gas boiler at the time t' in the integrated energy system,

for the unit adjustment cost of the heat generation power of the gas turbine in the comprehensive energy system,

for the unit adjustment cost, delta P, of the heat production power of the gas boiler in the comprehensive energy system_MT(t ') is the adjustment quantity of the heat generation power of the gas turbine at the time t' in the integrated energy system, delta P_GB(t ') is the adjustment quantity of the heat production power of the gas boiler in the comprehensive energy system at the moment t', and delta t is the time duration of the moment;

said F_e,1(t') is calculated as follows:

in the formula (I), the compound is shown in the specification,

for the unit adjustment cost of the heat generating power of the electric boiler in the comprehensive energy system,

for the unit adjustment cost, delta P, of the cooling power of the electric refrigerator in the integrated energy system_EB(t ') is the adjustment quantity of the heat production power of the electric boiler in the integrated energy system at the time t', delta P_AC(t ') is the adjustment quantity of the refrigerating power of the electric refrigerator in the comprehensive energy system at the moment t';

said F_g,2(x') is calculated as follows:

F_g,2(x')＝R_gas(x')·[G_g(t)+ΔG_g(x')]·Δt

in the formula, R_gas(x ') is the gas value at time x', G_g(t) is the gas purchasing power of the integrated energy system in the tth time period within the optimization time length, delta G_g(x ') is the adjustment quantity of the gas purchasing power of the comprehensive energy system at the moment x';

said F_e,2(x') is calculated as follows:

F_e,2(x')＝μ'_PtG·ΔP_PtG(x')²·Δt

of formula (II) to'_PtGFor the unit adjustment cost, delta P, of the gas production power of the electric gas conversion equipment of the integrated energy system_PtG(x ') is the adjustment quantity of the gas production power of the electric gas conversion equipment of the comprehensive energy system at the moment x';

said F_g,3(z') is calculated as follows:

in the formula, R_gas(z ') is the gas value at time z', F_FC(t) Natural gas consumption Power, Δ F, for the fuel cell in the Integrated energy System at the tth time period within the optimized time duration_FC(z ') is the adjustment of the natural gas power consumption of the gas turbine at time z' in the integrated energy system,

cost, delta P, for unit adjustment of heat production power of a gas turbine in an integrated energy system_FC(z ') is the adjustment amount of the heat production power of the gas turbine in the integrated energy system at the moment z';

said F_e,3(z') is calculated as follows:

in the formula, R_gid(z ') is the electricity price at time z',

the purchased electric power R of the integrated energy system in the t-th time period within the optimized time length_gid(z ') is the adjustment amount of the purchased electric power of the integrated energy system at the moment z',

the cost is adjusted for the unit of the purchased power of the comprehensive energy system;

said F_ES(z') is calculated asThe following:

in the formula (I), the compound is shown in the specification,

cost, Δ P, per unit adjustment of fuel cell storage/discharge power in an integrated energy system_c(z ') is the adjustment amount of the stored electric power of the fuel cell in the integrated energy system at the time z', delta P_f(z ') is an adjustment amount of the discharge power of the fuel cell at the time z' in the integrated energy system.

Further, the calculation formula of the unit output constraint is as follows:

in the formula, P_α，minIs the maximum capacity power, P, of the alpha type capacity equipment in the comprehensive energy system_α(t) is the capacity power of the alpha type capacity equipment in the comprehensive energy system in the t time period within the optimization duration, P_α，maxIs the minimum capacity power, P, of the alpha type capacity equipment in the integrated energy system_α(X) is the capacity power of the alpha type capacity equipment in the comprehensive energy system at the moment X, delta P_α(X) is the adjustment quantity of the capacity power of the alpha type capacity equipment in the comprehensive energy system at the moment X, and X is a moment of the t-th time period in the optimization duration;

the calculation formula of the unit energy consumption constraint is as follows:

F_α(X)＝F_α(t)+ΔF_α(X)

in the formula, F_α(t) is the energy consumption power of the alpha type energy production equipment in the comprehensive energy system in the t time period within the optimization duration, F_α(X) is the energy consumption power of the alpha type energy production equipment in the comprehensive energy system at the moment X, and delta F_αAnd (X) is the adjustment quantity of the energy consumption power of the alpha type energy production equipment in the comprehensive energy system at the moment X.

Example 3:

in order to solve the problem that the energy depreciation of the comprehensive energy system is not considered in the optimization process, the operation of the comprehensive energy system is optimized by using the comprehensive energy system optimization scheduling method considering the energy quality, which is provided by the invention, the method adopts double-time scale optimization, accurately reflects the operation state of the comprehensive energy system in real time, realizes scientific scheduling management of the related equipment of the comprehensive energy system and low-carbon economic operation of the comprehensive energy system, and has reference significance for the comprehensive energy optimization operation work.

During actual modeling, the optimization duration is set to be one day, the scheduling duration of the large-time-scale optimization model is set to be 1 hour, the small-time-scale rolling optimization model is provided with three layers, the first control sublayer is used for optimizing the cold/heat energy with longer scheduling duration, the second control sublayer is used for optimizing the natural gas energy with longer scheduling duration, and the third control sublayer is used for optimizing the electric energy with shorter scheduling duration.

The method comprises the following specific steps:

step A: collecting parameters required for optimizing the comprehensive energy system;

including but not limited to: energy type, energy purchase price, equipment type, equipment utilization efficiency, load data, and energy of various types

Coefficient, temperature of the pipes in the heat network; the pressure of the pipes in the air network.

The integrated energy system shown in fig. 3 includes a plurality of cooling, heating and power cogeneration subsystems, each cooling, heating and power cogeneration subsystem is communicated with an electricity, heat, gas and water network, so that it can be seen that the energy types of the integrated energy system include electricity, natural gas, cold and heat;

the devices in the cooling, heating and power cogeneration subsystems include but are not limited to: an electric refrigerator (AC), a gas turbine (MT), a Waste Heat Boiler (WHB), an Absorption Refrigerator (AR), a Gas Boiler (GB), an Electric Boiler (EB), a wind power device (WT), a photovoltaic device (PV), a Fuel Cell (FC), an electric power conversion device (PtG), a storage battery (ES), an ice storage (CS), a heat storage tank (HS), a gas storage tank (GS), and the like;

the daily load data includes: cold, hot, electrical, gas loads.

And B: establishing a large-time-scale optimization model of the comprehensive energy system based on power, tide and flow equations of an electric network, a thermal network and a gas network;

firstly: to optimize the running cost of the integrated energy system for the duration of time to a minimum sum

Establishing an optimization model with a large time scale for a target with the lowest loss;

the calculation formula of the objective function of the optimization model with the large time scale is as follows:

F＝ω₁·C_IES+ω₂·E_loss

wherein F is the objective function value of the optimization model with large time scale, omega₁For the weight corresponding to the running cost, ω₂Is composed of

Weight corresponding to the loss, C_IESMinimum operating cost of the integrated energy system for optimum duration, E_lossMinimization of integrated energy systems for duration optimization

Damage;

the operation cost of the integrated energy system comprises the electricity purchasing cost of the system from a power grid, the gas purchasing cost from a natural gas pipe network and the operation and maintenance cost of the system, so the operation cost C_IESThe calculation formula of (a) is as follows:

C_IES＝min(C_db+C_gas+C_p+C_om)

in the formula, C_dbCost for purchasing electricity from the grid for the integrated energy system within an optimized duration, C_gasCost for the gas purchase from the gas network for the integrated energy system within an optimized duration, C_pFor optimizing the operating costs of the heat supply network in the time-span integrated energy system, C_omFor optimizing time duration comprehensive energy systemThe operation and maintenance cost.

Wherein, the C_dbIs calculated as follows:

in the formula, c_db(t) electricity price for the tth period of the optimized duration, P_iAnd (T) is the power purchased from the power grid by the ith combined cooling heating and power subsystem in the comprehensive energy system in the optimized time period tth time period, delta T is the time period of the time period, T belongs to the time period from 1 to T, T is the total time period contained in the optimized time period, i belongs to the time period from 1 to N, and N is the total number of the combined cooling heating and power subsystems contained in the comprehensive energy system.

Said C is_gasIs calculated as follows:

in the formula, c_gasIs gas value, P_GT,i(t) is the generated power of the micro gas turbine in the ith combined cooling heating and power subsystem in the comprehensive energy system in the t time period of the optimization time length, Q_GB,i(t) is the heat production power of the gas boiler in the ith combined cooling heating and power subsystem in the comprehensive energy system in the tth time period of the optimization time length, eta_GT,iThe power generation efficiency, eta, of the micro gas turbine in the ith combined cooling heating and power subsystem in the integrated energy system_GB,iThe heat generation efficiency of the gas boiler in the ith combined cooling heating and power subsystem in the comprehensive energy system.

The heat pump is a main heat source, occupies most of the operation cost of the heat supply network, and if the energy required by the heat supply network is calculated, the heat quantity in each pipe network needs to be obtained, which can be expressed as:

in the formula, H is the energy required by the heat pipeline operation in the comprehensive energy system within the optimized duration, c_pFor heat pipe intermediariesSpecific heat capacity of mass, m_jIs the mass flow of the thermal conduit,

for the temperature of the inlet side of the jth heat pipe in the integrated energy system during the tth period of the optimized duration,

j belongs to (1-M) for the temperature of the return side of the jth heat pipeline in the comprehensive energy system in the tth time period of the optimization time, wherein M is the total number of heat pipelines in the comprehensive energy system;

said C is_pIs calculated as follows:

C_p＝c_r(t)·H

in the formula, c_r(t) is the purchase price per calorie for the tth period of the optimized duration.

Said C is_omIs calculated as follows:

in the formula (I), the compound is shown in the specification,

the unit maintenance cost P of the kth equipment in the ith combined cooling heating and power subsystem in the comprehensive energy system in the t-th time period of the optimization duration_i,kThe rated capacity of the kth equipment in the ith combined cooling heating and power subsystem in the comprehensive energy system is represented by K (from 1 to K)_i)，K_iThe total number of the devices contained in the ith combined cooling heating and power subsystem in the integrated energy system.

Due to the fact that

The definition of the impairment is input

And output

A difference of (a) so that E_lossIs calculated as follows:

in the formula (I), the compound is shown in the specification,

inputting for the integrated energy system in the t period of the optimized duration

Output of the integrated energy system in the tth time period of the optimized duration

Because the input energy comprises the consumed solar energy, natural gas and the like, the device can not only save energy but also reduce the energy consumption

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

for optimizing duration, the electric network providing to the comprehensive energy system at the tth time interval

For optimizing duration of solar energy provided to integrated energy system at tth time interval

For optimizing duration, the t time period, the gas network provides to the comprehensive energy system

Wherein, the

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

the purchased electric power rho of the comprehensive energy system in the tth time period of the optimization duration^eBeing electric energy

A coefficient;

in solar energy

Not only strongly correlated with the intensity of its radiation, but also strongly correlated with the temperature of the heat source (sun) and the ambient temperature at that time, so that

Is calculated as follows:

λ(t)＝1+1/3[T_a(t)/T_sum]⁴-4/3[T_a(t)/T_sum]

wherein I (t) is the t-th of the optimization time lengthIntensity of solar radiation, S, of a time period_STCIs the area of a solar heat collector in an integrated energy system, S_PVFor the area of the photovoltaic panel in the integrated energy system, lambda (t) is the sunlight in the tth time period of the optimization duration

Coefficient, T_a(T) is the ambient temperature of the integrated energy system at the tth period of the optimization duration, T_sumIs the temperature of the sun.

Ratio of chemical fuel

Usually with its lower calorific value and

coefficient representation, different types of fuel

The coefficients are slightly different, so that

Is calculated as follows:

in the formula, pi_gIs the ratio of natural gas

G_g(t) is the gas purchasing power of the comprehensive energy system in the tth time period of the optimization duration, pi_g＝LHV_gasζ_gas，LHV_gasFor low heating value, ζ, of natural gas_gasOf natural gas

And (4) the coefficient.

Because the output energy comprises electric energy, cold energy and heat energy, the device can be used for generating electricity, cold energy and heat energy

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

corresponding to the electrical load of the integrated energy system during the tth period of the optimum duration

For cooling load of integrated energy system at t-th time of optimized duration

Corresponding to the thermal load of the integrated energy system during the tth period of the optimization duration

Wherein, the

And

is calculated as follows:

in the formula, L_e(t) electric load, L, of the integrated energy system at the tth period of the optimization duration_c(t) the cooling load, L, of the integrated energy system at the tth time period of the optimization duration_h(t) the thermal load of the integrated energy system during the tth period of the optimization time,

is the temperature of the cold medium and is,

the temperature of the heating medium.

And then: constructing a constraint for an objective function of the optimization model with a large time scale;

the constraints include, but are not limited to: the system energy network power supply balance constraint, the system energy network heat supply balance constraint, the system energy network air supply balance constraint, the system energy network cold supply balance constraint, the energy storage equipment capacity constraint, the unit output constraint and the unit climbing capacity constraint.

The calculation formula of the system energy network power supply balance constraint is as follows:

in the formula, P_CCHP(t) is the net generated electric power of other power generation equipment except the new energy power generation equipment in the comprehensive energy system in the t period of the optimization time, P_WT(t) is the wind power output power P of the comprehensive energy system in the tth time period of the optimization duration_PV(t) is the photovoltaic output power of the integrated energy system at the tth time period of the optimization duration, P_ESAnd (t) the storage/discharge power of a storage battery in the comprehensive energy system in the tth time period of the optimized time length.

The calculation formula of the system energy network heat supply balance constraint is as follows:

H_GB(t)+H_EB(t)+H_WHB(t)+H_HS(t)＝L_h(t)

in the formula, H_GB(t) is the heat production power H of the gas boiler in the t period of the optimized time length in the comprehensive energy system_EB(t) heat production power H of the t period of the electric boiler in the optimized duration for the integrated energy system_WHB(t) is the heat production power of the waste heat boiler in the t-th time period of the optimized time length in the comprehensive energy system, H_HSAnd (t) the storage/release power of the heat storage tank in the comprehensive energy system in the tth time period of the optimized time length.

The calculation formula of the system energy network air supply balance constraint is as follows:

G_PtG(t)+G_g(t)+G_GS(t)-G_Dmd(t)＝0

in the formula, G_PtG(t) is the gas production power of the electric gas conversion equipment in the comprehensive energy system in the tth time period of the optimization time, G_GS(t) is the storage/discharge power of the gas storage tank in the comprehensive energy system in the tth time period of the optimized time length G_Dmd(t) optimizing the air usage load for the tth period of time.

The calculation formula of the system energy network cooling balance constraint is as follows:

C_AC(t)+C_RC(t)+C_CS(t)-L_c(t)＝0

in the formula, C_AC(t) is the refrigerating power of the electric refrigerating equipment in the comprehensive energy system in the t period of the optimized duration, C_RC(t) is the refrigerating power of the absorption refrigerating machine in the comprehensive energy system in the t period of the optimization duration, C_CSAnd (t) the cold storage/discharge power of the electric refrigeration equipment in the integrated energy system in the tth time period of the optimized time length.

In order to ensure the reliability of the long-time scheduling, the energy of the energy storage device needs to be within the upper limit and the lower limit of the device capacity, and the remaining storage capacity should be equal from beginning to end every day, so the calculation formula of the energy storage device capacity constraint is as follows:

E_θ(0)＝E_θ(T)

in the formula (I), the compound is shown in the specification,

respectively the minimum and maximum charge energy states of the theta energy storage equipment in the comprehensive energy system, E_θ(t) is the energy storage of the theta energy storage device in the comprehensive energy system in the t period of the optimization duration, C_θRated energy storage for the theta-th energy storage device in the integrated energy system, E_θ(0)、E_θAnd (T) the energy storage of the theta energy storage device in the comprehensive energy system at the starting time and the last time of the optimization duration respectively.

The calculation formula of the unit output constraint is as follows:

P_α，min≤P_α(t)≤P_α，max

in the formula, P_α，minIs the maximum capacity power, P, of the alpha type capacity equipment in the comprehensive energy system_α(t) is the capacity power of the alpha type capacity equipment in the comprehensive energy system in the t time period of the optimization duration, P_α，maxIs the minimum capacity power of the alpha type capacity equipment in the comprehensive energy system.

The calculation formula of the unit climbing capacity constraint is as follows:

P_α，dn≤P_α(t+1)-P_α(t)≤P_α，up

in the formula, P_α(t +1) is the energy production power of the alpha type energy production equipment in the comprehensive energy system in the t +1 th time period of the optimization time length, P_α，dnIs the lower limit value of the climbing capability of the alpha-type capacity equipment in the comprehensive energy system, P_α，upThe climbing capacity upper limit value of the alpha-type capacity equipment in the comprehensive energy system;

and C: substituting the cold, heat, electricity and gas loads of each time period in the optimized duration into the model to obtain a scheduling plan of each time period;

the dispatch plan includes: the energy storage system comprises the energy production power of equipment such as a gas turbine, a gas boiler, a waste heat boiler, an electric boiler and an absorption refrigerator for electric gas conversion in each time period of the optimized duration, the energy charging/consuming power of energy storage equipment in each time period of the optimized duration, and the power of the comprehensive energy system for purchasing electricity from a power grid and the power of purchasing gas from a gas grid in each time period of the optimized duration.

The step A to the step C realize the optimization scheduling of the large time scale of the comprehensive energy system, and on the basis, a rolling optimization model of the small time scale of the comprehensive energy system is established;

firstly: dividing the levels of the small time scale rolling optimization model based on the energy types;

for example, if a certain integrated energy system exchanges four energy sources, such as cold/heat, electricity, natural gas, biomass energy and the like, the small-time scale rolling optimization model is a 4-layer small-time scale rolling optimization model;

in this embodiment, the small time scale rolling optimization model of the integrated energy system includes 3 layers, where the first layer is used to optimize the cold/heat energy with longer scheduling duration and every k₁The time length is optimized once, the second layer is used for optimizing and scheduling the natural gas energy with short time length every k₂One time optimized, third layer for optimizing electric energy every k with short scheduling time₃Optimizing the duration once;

here, the optimized time domain of the first layer is set to k₁With a predicted time window of t₀+k₁～t₀+3k₁Adjusting the time window to t₀+k₁～t₀+2k₁；

Here, the optimized time domain of the second layer is set to k₂With a predicted time window of t₀+k₂～t₀+3k₂Adjusting the time window to t₀+k₂～t₀+2k₂

Here, the optimized time domain of the third layer is set to k₃With a predicted time window of t₀+k₃～t₀+3k₃Adjusting the time window to t₀+k₃～t₀+2k₃，k₁＞k₂＞k₃。

Thus, according to the real-time of the systemOperating characteristics, based on the optimized scheduling result under large time scale, for the heat energy/cold energy related equipment, every k₁Time optimized once every k for natural gas energy related equipment₂Time optimized once every k for power-related devices₃The time is optimized once, the output of the energy supply and the energy storage equipment of the system is adjusted in time, and the economical quality of the system is improved until the execution of all time periods is finished.

Subsequently, the first layer is called a cold/heat energy optimization layer, the second layer is called a natural gas energy optimization layer, and the third layer is called an electric energy optimization layer;

secondly, the method comprises the following steps: establishing an objective function of each layer of the small-time scale rolling optimization model by taking the minimum running cost as an objective;

specifically, the calculation formula of the objective function corresponding to the cold/heat energy optimization layer of the small time scale rolling optimization model is as follows:

in the formula, F_g,1(t ') cost of natural gas at time t', F_e,1(t ') is the cost of change of the consumer at time t',

to optimize the starting time of the tth period of time, k₁The duration of the corresponding small time scale for the cold/heat optimization layer,

the last moment corresponding to the small time scale corresponding to the cold/heat energy optimization layer in the tth time period in the optimization time length is obtained;

wherein the cost F of natural gas at time t_g,1(t') is calculated as follows:

in the formula, R_gas(t')Gas value at time t', F_MT(t) Natural gas Power consumption of gas turbine in the Integrated energy System at the tth time period of the optimized duration, F_GB(t) is the natural gas power consumption of the gas boiler in the integrated energy system in the tth time period of the optimization time length, delta F_MT(t ') is the adjustment of the natural gas consumption power of the gas turbine at time t' in the integrated energy system, Δ F_GB(t ') is an adjustment amount of natural gas consumption power of the gas boiler at the time t' in the integrated energy system,

for the unit adjustment cost of the heat generation power of the gas turbine in the comprehensive energy system,

for the unit adjustment cost, delta P, of the heat production power of the gas boiler in the comprehensive energy system_MT(t ') is the adjustment quantity of the heat generation power of the gas turbine at the time t' in the integrated energy system, delta P_GB(t ') is the adjustment quantity of the heat production power of the gas boiler in the comprehensive energy system at the moment t', and delta t is the time duration of the moment;

change cost F of the consumer at time t_e,1(t') is calculated as follows:

in the formula (I), the compound is shown in the specification,

for the unit adjustment cost of the heat generating power of the electric boiler in the comprehensive energy system,

for the unit adjustment cost, delta P, of the cooling power of the electric refrigerator in the integrated energy system_EB(t ') is the adjustment quantity of the heat production power of the electric boiler in the integrated energy system at the time t', delta P_AC(t ') is the adjustment amount of the refrigerating power of the electric refrigerator in the integrated energy system at the time t'.

Based on the gas suction and release state of the gas storage tank before the day, the output of each unit of the system is adjusted according to the natural gas load and the equipment change of the slow control layer at the moment x', and the calculation formula of the target function corresponding to the natural gas energy optimization layer is as follows:

in the formula, F_g,2(x ') is the cost of the natural gas at time x', F_e,2(x') is the cost of change, k, of the consumer at time x₂The length of time for the corresponding small time scale of the natural gas energy optimization layer,

the last moment corresponding to the small time scale corresponding to the natural gas energy optimization layer in the tth time period in the optimization time length is set;

wherein the cost F of natural gas at time x_g,2(x') is calculated as follows:

F_g,2(x')＝R_gas(x')·[G_g(t)+ΔG_g(x')]·Δt

in the formula, R_gas(x ') is the gas value at time x', G_g(t) gas purchasing power, delta G, of the integrated energy system in the tth time period of the optimization duration_g(x ') is the adjustment quantity of the gas purchasing power of the comprehensive energy system at the moment x';

time x' change cost F of the consumer_e,2(x') is calculated as follows:

F_e,2(x')＝μ'_PtG·ΔP_PtG(x')²·Δt

of formula (II) to'_PtGFor the unit adjustment cost, delta P, of the gas production power of the electric gas conversion equipment of the integrated energy system_PtG(x ') is the adjustment quantity of the gas production power of the electric gas conversion equipment of the comprehensive energy system at the moment x'.

Based on the charging and discharging states of the storage battery in the day ahead, the optimization result of the large time scale is corrected according to the new energy fluctuation at the moment z' and the power change of the demand side and the two sub-layers, and the calculation formula of the objective function corresponding to the electric energy optimization layer is as follows:

in the formula, F_g,3(z ') is the cost of natural gas at time z', F_e,3(z ') is the cost of change of the consumer at time z', F_ES(z ') is the charge-discharge cost of the fuel cell at time z', k₃The duration of the corresponding small time scale for the power optimization layer,

the last moment corresponding to the small time scale corresponding to the electric energy optimization layer in the tth time period in the optimization time length is obtained;

wherein the cost F of natural gas at time z_g,3(z') is calculated as follows:

in the formula, R_gas(z ') is the gas value at time z', F_FC(t) is the natural gas consumption power of the fuel cell in the comprehensive energy system in the t period of the optimization time, delta F_FC(z ') is the adjustment of the natural gas power consumption of the gas turbine at time z' in the integrated energy system,

cost, delta P, for unit adjustment of heat production power of a gas turbine in an integrated energy system_FC(z ') is the adjustment amount of the heat production power of the gas turbine in the integrated energy system at the moment z';

time z' change cost F of the consumer_e,3(z') is calculated as follows:

in the formula, R_gid(z ') is the electricity price at time z',

for the electricity purchasing power R of the comprehensive energy system in the t-th time period of the optimization duration_gid(z ') is the adjustment amount of the purchased electric power of the integrated energy system at the moment z',

the cost is adjusted for the unit of the purchased power of the comprehensive energy system;

time z' charge-discharge cost F of fuel cell_ES(z') is calculated as follows:

in the formula (I), the compound is shown in the specification,

cost, Δ P, per unit adjustment of fuel cell storage/discharge power in an integrated energy system_c(z ') is the adjustment amount of the stored electric power of the fuel cell in the integrated energy system at the time z', delta P_f(z ') is an adjustment amount of the discharge power of the fuel cell at the time z' in the integrated energy system.

And finally: and constructing a system energy network power supply balance constraint, a system energy network heat supply balance constraint, a system energy network air supply balance constraint, a system energy network cold supply balance constraint, an energy storage equipment capacity constraint, a unit output constraint, a unit climbing capacity constraint, a unit energy consumption constraint and a unit output constraint for the objective functions of all layers of the small time scale rolling optimization model.

The system energy network power supply balance constraint, the system energy network heat supply balance constraint, the system energy network air supply balance constraint, the system energy network cold supply balance constraint, the energy storage equipment capacity constraint and the unit climbing capacity constraint are completely consistent with the same constraint expression form in the large-time-scale optimization model, and the corresponding time changes correspondingly;

the calculation formula of the unit output constraint is as follows:

in the formula, P_α，minIs the maximum capacity power, P, of the alpha type capacity equipment in the comprehensive energy system_α(t) is the capacity power of the alpha type capacity equipment in the comprehensive energy system in the t time period of the optimization duration, P_α，maxIs the minimum capacity power, P, of the alpha type capacity equipment in the integrated energy system_α(X) is the capacity power of the alpha type capacity equipment in the comprehensive energy system at the moment X, delta P_αAnd (X) is the adjustment quantity of the capacity power of the alpha type capacity equipment in the comprehensive energy system at the moment X, and X is a moment corresponding to the small time scale in the tth period of the optimization duration.

The calculation formula of the unit energy consumption constraint is as follows:

F_α(X)＝F_α(t)+ΔF_α(X)

in the formula, F_α(t) is the energy consumption power of the alpha type energy production equipment in the t period of the optimization duration in the comprehensive energy system, F_α(X) is the energy consumption power of the alpha type energy production equipment in the comprehensive energy system at the moment X, and delta F_αAnd (X) is the adjustment quantity of the energy consumption power of the alpha type energy production equipment in the comprehensive energy system at the moment X.

Step D: and substituting the scheduling plan in each time period into a pre-established small time scale rolling optimization model, solving the rolling optimization model, and obtaining the scheduling plan at each time corresponding to the small time scale in each time period.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (15)

1. An integrated energy system optimization scheduling method considering energy quality, the method comprising:

obtaining various energy sources

The coefficients and the various energy loads at various time intervals corresponding to the large time scale are substituted into a pre-established large time scale optimization model for solving to obtain a scheduling plan at each time interval;

rolling and adjusting the scheduling plan at each time interval to obtain a scheduling plan at each moment corresponding to the small time scale in each time interval;

wherein the large time scale is greater than the small time scale;

the large time scale optimization model is based on various energy loads and various energy sources

Coefficient is lowest by running cost

The loss is minimized to determine a dispatch plan for the target.

2. The method of claim 1, wherein the dispatch plan comprises: the energy storage/release power regulation values of the storage battery, the ice storage, the heat storage tank and the gas storage tank, and the power regulation value of the comprehensive energy system for purchasing electricity from the power grid and the power regulation value for purchasing gas from the gas grid;

the energy types include: electricity, cold, heat, and natural gas.

3. The method of claim 1, wherein the building of the large time scale optimization model comprises:

order all kindsEnergy load and various energy sources

The coefficient is the input of the large time scale optimization model, and the scheduling plan is the output of the large time scale optimization model;

to minimize operating costs and

establishing an objective function of an optimization model with a large time scale for a target with minimum loss;

and constructing a system energy network power supply balance constraint, a system energy network heat supply balance constraint, a system energy network air supply balance constraint, a system energy network cold supply balance constraint, an energy storage equipment capacity constraint, a unit output constraint and a unit climbing capacity constraint for an objective function of the large-time-scale optimization model.

4. The method of claim 3, wherein the objective function of the large time scale optimization model is calculated as follows:

F＝ω₁·C_IES+ω₂·E_loss

wherein F is the objective function value of the large time scale optimization model, omega₁For the weight corresponding to the running cost, ω₂Is composed of

Weight corresponding to the loss, C_IESFor the lowest operating cost of the integrated energy system within the optimum duration, E_lossFor optimizing minimum of comprehensive energy system in time length

And (4) loss.

5. The method of claim 4, wherein C is_IESThe calculation formula of (a) is as follows:

C_IES＝min(C_db+C_gas+C_p+C_om)

in the formula, C_dbCost for purchasing electricity from the grid for the integrated energy system within an optimized duration, C_gasCost for the gas purchase from the gas network for the integrated energy system within an optimized duration, C_pFor optimizing the operating costs of the heat supply network in the time-span integrated energy system, C_omThe operation and maintenance cost of the comprehensive energy system within the optimized time length is realized;

said E_lossIs calculated as follows:

in the formula (I), the compound is shown in the specification,

inputting for the t period in the optimized duration for the integrated energy system

Output of the integrated energy system in the t-th time period within the optimized time length

And T belongs to (1-T), wherein T is the total time period contained in the optimization time length.

6. The method of claim 5, wherein C is_dbIs calculated as follows:

in the formula, c_db(t) the electricity price in the t-th period of the optimized duration, P_i(t) when the ith combined cooling, heating and power subsystem in the comprehensive energy system is optimizedThe power purchased from the power grid in the tth time period within the long time period, delta t is the time length of the time period, i belongs to (1-N), and N is the total number of the combined cooling, heating and power subsystems in the comprehensive energy system;

said C is_gasIs calculated as follows:

in the formula, c_gasIs gas value, P_GT,i(t) is the generated power of the micro gas turbine in the ith combined cooling heating and power subsystem in the comprehensive energy system in the t time period within the optimized time length, Q_GB,i(t) is the heat production power of the gas boiler in the ith combined cooling heating and power subsystem in the comprehensive energy system in the tth time period within the optimized time length, eta_GT,iThe power generation efficiency, eta, of the micro gas turbine in the ith combined cooling heating and power subsystem in the integrated energy system_GB,iThe heat generation efficiency of a gas boiler in the ith combined cooling heating and power subsystem in the comprehensive energy system is obtained;

the above-mentioned

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

for supplying the electric network to the integrated energy system in the t-th time period within the optimized time period

For providing solar energy to the integrated energy system at the tth time interval within the optimized duration

For providing the gas network to the integrated energy system at the tth time interval within the optimized duration

The above-mentioned

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

corresponding to the electric load of the integrated energy system in the tth time period within the optimum time period

For cooling load of integrated energy system at t-th time interval in optimized time length

Corresponding to the thermal load of the integrated energy system during the t-th period of the optimum duration

7. The method of claim 6, wherein the method is as set forth in claim 6

Is calculated as follows:

in the formula (I), the compound is shown in the specification,

the purchased electric power rho of the integrated energy system in the t-th time period within the optimized time length^eBeing electric energy

A coefficient;

the above-mentioned

Is calculated as follows:

λ(t)＝1+1/3[T_a(t)/T_sum]⁴-4/3[T_a(t)/T_sum]

wherein I (t) is the intensity of solar radiation in the t-th period of the optimized duration, S_STCIs the area of a solar heat collector in an integrated energy system, S_PVLambda (t) is the area of the photovoltaic panel in the integrated energy system for the solar light at the tth time period within the optimized time period

Coefficient, T_a(T) is the ambient temperature of the integrated energy system at the tth time period within the optimization time period, T_sumIs the temperature of the sun;

the above-mentioned

Is calculated as follows:

in the formula, pi_gIs the ratio of natural gas

G_g(t) is the gas purchasing power of the comprehensive energy system in the tth time period within the optimized time length, pi_g＝LHV_gasζ_gas，LHV_gasFor low heating value, ζ, of natural gas_gasOf natural gas

A coefficient;

the above-mentioned

And

is calculated as follows:

in the formula, L_e(t) is an integrated energy systemElectric load, L, at the t-th time interval within the optimized time duration_c(t) the cooling load, L, of the integrated energy system at the tth time period within the optimized time period_h(t) is the thermal load of the integrated energy system for the tth period of the optimized duration,

is the temperature of the cold medium and is,

the temperature of the heating medium.

8. The method of claim 7, wherein the system energy network power balance constraint is calculated as follows:

in the formula, P_CCHP(t) is the net generated electric power of the other power generation equipment except the new energy power generation equipment in the comprehensive energy system in the t period within the optimization time length, P_WT(t) is the wind power output power of the comprehensive energy system in the tth time period within the optimization duration, P_PV(t) is the photovoltaic output power of the integrated energy system in the tth time period within the optimization time length, P_ES(t) the storage/discharge power of a storage battery in the comprehensive energy system in the t-th time period within the optimized time length;

the calculation formula of the system energy network heat supply balance constraint is as follows:

H_GB(t)+H_EB(t)+H_WHB(t)+H_HS(t)＝L_h(t)

in the formula, H_GB(t) is the heat production power H of the gas boiler in the t period in the optimized time length in the comprehensive energy system_EB(t) is the heat production power H of the electric boiler in the t period in the optimized time length in the integrated energy system_WHB(t) is the heat production power of the waste heat boiler in the t-th period of the optimized duration in the comprehensive energy system, H_HS(t) in an integrated energy systemThe storage/release power of the heat storage tank in the tth time period in the optimized time length;

the calculation formula of the system energy network air supply balance constraint is as follows:

G_PtG(t)+G_g(t)+G_GS(t)-G_Dmd(t)＝0

in the formula, G_PtG(t) is the gas production power of the electric gas conversion equipment in the comprehensive energy system in the t-th time period within the optimized time length, G_GS(t) is the storage/discharge power of the gas storage tank in the comprehensive energy system in the t period within the optimized time length G_Dmd(t) optimizing the gas usage load for the tth period of time over the duration of time;

the calculation formula of the system energy network cooling balance constraint is as follows:

C_AC(t)+C_RC(t)+C_CS(t)-L_c(t)＝0

in the formula, C_AC(t) is the refrigerating power of the electric refrigerating equipment in the comprehensive energy system in the t period within the optimized time length, C_RC(t) is the refrigeration power of the absorption refrigeration equipment in the comprehensive energy system in the t period within the optimized duration, C_CS(t) the cold storage/discharge power of the electric refrigeration equipment in the integrated energy system in the t period in the optimized time length.

9. The method of claim 8, wherein the rolling adjustment of the scheduling plan at each time interval to obtain the scheduling plan at each time corresponding to the small time scale in each time interval comprises:

substituting the scheduling plan in each time period into a pre-constructed small time scale rolling optimization model to obtain the scheduling plan of each time corresponding to the small time scale in each time period;

the small time scale rolling optimization model is obtained by performing multilevel construction on the basis of energy types and with the aim of minimizing the operation cost.

10. The method of claim 9, wherein the building of the small-time-scale rolling optimization model comprises:

dividing the levels of the small time scale rolling optimization model based on the energy types;

establishing an objective function of each layer of the small-time scale rolling optimization model by taking the minimum running cost as an objective;

and constructing a system energy network power supply balance constraint, a system energy network heat supply balance constraint, a system energy network air supply balance constraint, a system energy network cold supply balance constraint, an energy storage equipment capacity constraint, a unit output constraint, a unit climbing capacity constraint, a unit energy consumption constraint and a unit output constraint for the objective functions of all layers of the small time scale rolling optimization model.

11. The method of claim 10, wherein the small time scale rolling optimization model is divided into a cold/heat energy optimization layer, a natural gas energy optimization layer, and an electric energy optimization layer;

the time lengths of the small time scales corresponding to the cold/heat energy optimization layer, the natural gas energy optimization layer and the electric energy optimization layer are sequentially decreased.

12. The method of claim 11, wherein the objective function of the cold/heat optimization layer of the small time scale rolling optimization model is calculated as follows:

in the formula, F_g,1(t ') cost of natural gas at time t', F_e,1(t ') is the cost of change of the consumer at time t',

to optimize the start of the t-th period in time, k₁The duration of the corresponding small time scale for the cold/heat optimization layer,

for optimizing the small time scale corresponding to the optimized layer of cold/heat energy in the t-th period of timeThe last moment;

the calculation formula of the objective function of the natural gas energy optimization layer of the small time scale rolling optimization model is as follows:

in the formula, F_g,2(x ') is the cost of the natural gas at time x', F_e,2(x') is the cost of change, k, of the consumer at time x₂The length of time for the corresponding small time scale of the natural gas energy optimization layer,

the last moment corresponding to the small time scale corresponding to the natural gas energy optimization layer in the tth time period in the optimization time length is set;

the calculation formula of the objective function of the electric energy optimization layer of the small time scale rolling optimization model is as follows:

in the formula, F_g,3(z ') is the cost of natural gas at time z', F_e,3(z ') is the cost of change of the consumer at time z', F_ES(z ') is the charge-discharge cost of the fuel cell at time z', k₃The duration of the corresponding small time scale for the power optimization layer,

the last time corresponding to the small time scale corresponding to the electric energy optimization layer in the tth time period in the optimization time length is obtained.

13. The method of claim 12, wherein F is_g,1(t') is calculated as follows:

in the formula, R_gas(t ') is the gas value at time t', F_MT(t) Natural gas Power consumption of a gas turbine in an Integrated energy System at the tth time period within an optimized time duration, F_GB(t) is the natural gas power consumption of the gas boiler in the comprehensive energy system in the t-th time period within the optimized time length, delta F_MT(t ') is the adjustment of the natural gas consumption power of the gas turbine at time t' in the integrated energy system, Δ F_GB(t ') is an adjustment amount of natural gas consumption power of the gas boiler at the time t' in the integrated energy system,

for the unit adjustment cost of the heat generation power of the gas turbine in the comprehensive energy system,

for the unit adjustment cost, delta P, of the heat production power of the gas boiler in the comprehensive energy system_MT(t ') is the adjustment quantity of the heat generation power of the gas turbine at the time t' in the integrated energy system, delta P_GB(t ') is the adjustment quantity of the heat production power of the gas boiler in the comprehensive energy system at the moment t', and delta t is the time duration of the moment;

said F_e,1(t') is calculated as follows:

in the formula (I), the compound is shown in the specification,

for the unit adjustment cost of the heat generating power of the electric boiler in the comprehensive energy system,

for the unit adjustment cost, delta P, of the cooling power of the electric refrigerator in the integrated energy system_EB(t') is an integrated energy systemAdjustment quantity of heat production power, delta P, of medium electric boiler at time t_AC(t ') is the adjustment quantity of the refrigerating power of the electric refrigerator in the comprehensive energy system at the moment t';

said F_g,2(x') is calculated as follows:

F_g,2(x')＝R_gas(x')·[G_g(t)+ΔG_g(x')]·Δt

in the formula, R_gas(x ') is the gas value at time x', G_g(t) is the gas purchasing power of the integrated energy system in the tth time period within the optimization time length, delta G_g(x ') is the adjustment quantity of the gas purchasing power of the comprehensive energy system at the moment x';

said F_e,2(x') is calculated as follows:

F_e,2(x')＝μ'_PtG·ΔP_PtG(x')²·Δt

of formula (II) to'_PtGFor the unit adjustment cost, delta P, of the gas production power of the electric gas conversion equipment of the integrated energy system_PtG(x ') is the adjustment quantity of the gas production power of the electric gas conversion equipment of the comprehensive energy system at the moment x';

said F_g,3(z') is calculated as follows:

in the formula, R_gas(z ') is the gas value at time z', F_FC(t) Natural gas consumption Power, Δ F, for the fuel cell in the Integrated energy System at the tth time period within the optimized time duration_FC(z ') is the adjustment of the natural gas power consumption of the gas turbine at time z' in the integrated energy system,

cost, delta P, for unit adjustment of heat production power of a gas turbine in an integrated energy system_FC(z ') is the adjustment amount of the heat production power of the gas turbine in the integrated energy system at the moment z';

said F_e,3(z') is calculated as follows:

in the formula, R_gid(z ') is the electricity price at time z',

the purchased electric power R of the integrated energy system in the t-th time period within the optimized time length_gid(z ') is the adjustment amount of the purchased electric power of the integrated energy system at the moment z',

the cost is adjusted for the unit of the purchased power of the comprehensive energy system;

said F_ES(z') is calculated as follows:

in the formula (I), the compound is shown in the specification,

cost, Δ P, per unit adjustment of fuel cell storage/discharge power in an integrated energy system_c(z ') is the adjustment amount of the stored electric power of the fuel cell in the integrated energy system at the time z', delta P_f(z ') is an adjustment amount of the discharge power of the fuel cell at the time z' in the integrated energy system.

14. The method of claim 12, wherein the crew contribution constraint is calculated as follows:

in the formula, P_α，minIs the maximum capacity power, P, of the alpha type capacity equipment in the comprehensive energy system_α(t) is the comprehensive energyCapacity power, P, of the alpha-type capacity equipment in the source system at the t-th time period within the optimized duration_α，maxIs the minimum capacity power, P, of the alpha type capacity equipment in the integrated energy system_α(X) is the capacity power of the alpha type capacity equipment in the comprehensive energy system at the moment X, delta P_α(X) is the adjustment quantity of the capacity power of the alpha type capacity equipment in the comprehensive energy system at the moment X, and X is a moment of the t-th time period in the optimization duration;

the calculation formula of the unit energy consumption constraint is as follows:

F_α(X)＝F_α(t)+ΔF_α(X)

in the formula, F_α(t) is the energy consumption power of the alpha type energy production equipment in the comprehensive energy system in the t time period within the optimization duration, F_α(X) is the energy consumption power of the alpha type energy production equipment in the comprehensive energy system at the moment X, and delta F_αAnd (X) is the adjustment quantity of the energy consumption power of the alpha type energy production equipment in the comprehensive energy system at the moment X.

15. An integrated energy system optimization scheduling system considering energy quality, the system comprising:

an acquisition module for acquiring various energy sources

The coefficients and the various energy loads at various time intervals corresponding to the large time scale are substituted into a pre-established large time scale optimization model for solving to obtain a scheduling plan at each time interval;

the adjusting module is used for performing rolling adjustment on the scheduling plan at each time interval to obtain the scheduling plan at each moment corresponding to the small time scale in each time interval;

wherein the large time scale is greater than the small time scale;

the large time scale optimization model is based on various energy loads and various energy sources

Coefficient is lowest in running costAnd

the loss is minimized to determine a dispatch plan for the target.

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