CN112446546B - Comprehensive energy system two-stage optimal configuration method considering energy reliability - Google Patents
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Abstract
The invention relates to a two-stage optimal configuration method of a comprehensive energy system considering energy reliability, which comprises the following steps: establishing an electric-gas combined comprehensive energy system model; establishing a two-stage optimal configuration model of the electric-gas combined comprehensive energy system; according to the Rayleigh distribution of the wind speed, a probability distribution model of the generated energy is obtained and added into the constraint of the optimization model; determining the influence of equipment random faults on a system, establishing two energy reliability indexes and adding the two energy reliability indexes into optimization model constraints; and solving an optimal configuration scheme of the electric-gas combined comprehensive energy system by using a CPLEX solver. The method can reduce the influence of the uncertainty of the energy of the comprehensive energy system, effectively improve the utilization of the energy of the system, reduce the input cost of the system and ensure that the system has sustainability and economy.
Description
Technical Field
The invention belongs to the technical field of comprehensive energy optimization, and relates to a two-stage optimization configuration method of a comprehensive energy system considering energy reliability.
Background
Energy is an important foundation for human survival and development, along with the development of society, energy demands are gradually increased, and simultaneously, the price of non-renewable energy sources such as petroleum, coal, natural gas and the like is increased, and meanwhile, environmental pollution, greenhouse effect and other environmental problems threaten the healthy development of the human society, and energy and environmental problems facing the economic and social development become important challenges facing the human.
In order to relieve energy pressure and improve environmental problems, the comprehensive energy system combining different forms of energy and energy storage and power generation systems is constructed, so that the energy utilization efficiency can be effectively improved, and the energy supply cost is reduced, so that many researches are developed around the optimization planning and design of the comprehensive energy system. In the planning and design of a comprehensive energy system, researches indicate that uncertainty and correlation of renewable energy output such as wind, light and the like bring great complexity to the design of the system, and if the factors are ignored, a secondary decision risk is introduced in the planning stage of the system; meanwhile, it is generally considered that the interruption of the operation of the system elements is a main cause of unreliable supply of energy from the energy source equipment.
Aiming at the optimal configuration considering the reliability of energy sources, the prior art mainly focuses on two aspects: on one hand, the uncertainty of the output of wind power or photovoltaic is analyzed, more technologies establish a wind power or photovoltaic prediction model, and the influence on the system operation in a typical scene is obtained through scene reduction; on the other hand, the analysis of the uncertainty of energy supply caused by equipment faults is that more technologies propose related indexes for measuring the instability of the system caused by equipment faults. But there are fewer techniques related to optimizing the system for device capacity and operating strategy while taking into account renewable energy uncertainty and device fault uncertainty factors.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a two-stage optimal configuration method of a comprehensive energy system, which considers the reliability of energy, and simultaneously considers the uncertainty of wind power generation and the uncertainty of equipment fault functions, thereby effectively improving the utilization of system energy.
The invention relates to a two-stage optimal configuration method of a comprehensive energy system considering energy reliability, which comprises the following steps:
step 1: establishing an electric-gas combined comprehensive energy system model;
the electric-gas combined comprehensive energy system model comprises an energy conversion model without considering an energy storage module and an energy conversion model with considering the energy storage module;
the energy storage module includes: an electrical energy storage device, a cold energy storage device, and a hot energy storage device;
the energy conversion includes: the electric energy, the cold energy and the heat energy are converted by the energy conversion equipment; the energy conversion device includes: wind power generator, electric refrigerator, electric boiler, combined cooling heating and power device and gas boiler;
the energy conversion model without considering the energy storage module is as follows:
wherein ,PELE,t The electric power output by the system for the period t;the power purchasing power and the power selling power of the system in the t period are respectively; />Inputting electric power of an electric refrigerator and an electric boiler for a period t respectively; />Inputting natural gas power of the cogeneration device for a period t; />The power generation efficiency of the combined cooling heating power device is achieved; p (P) WT,t The power generated by the wind driven generator;
wherein ,PCOOL,t The cold power output by the system is t time periods;the electric power of the electric refrigerator and the natural gas power of the combined heat and power generation device are respectively input in the t period; />The refrigeration efficiency of the electric refrigerator and the combined cooling heating and power device are respectively;
wherein ,PHEAT,t The thermal power output by the system is t time period;inputting natural gas power of a gas boiler for a period t; />The heat efficiency of the electric boiler, the combined cooling heating and power device and the gas boiler are respectively;
wherein ,the air purchase amount of the system is t time period; h L Low heat value for natural gas combustion;
the energy conversion model considering the energy storage module is as follows:
ΔS m,t ＝S m,t -S m,t-1
E m,t ＝P m,t Δt-ΔS m,t
wherein, m is { ele, cool, heat }, m is electricity when ele, cold when m is cool, and heat when m is heat;respectively charging and discharging energy power of the energy storage device in the period of t; />The energy charging and discharging efficiency of the energy storage device is respectively t time periods m; ΔS m,t The energy storage device stores the energy variation for the period t; s is S m,t 、S m,t-1 M energy respectively stored by the energy storage device in the time periods t and t-1; p (P) m,t To take the m power output by the energy storage module t period system into consideration, P m,t ∈{P ELE,t ,P COOL,t ,P HEAT,t }；
Step 2: establishing a two-stage optimal configuration model of the electric-gas combined comprehensive energy system;
step 2.1: the method aims at the lowest running and maintenance cost of configuration installation and operation of energy equipment in engineering, and establishes a two-stage optimal configuration model objective function of an electric-gas combined comprehensive energy system as follows:
wherein ,CT The total input cost of the comprehensive energy system is; c (C) TI Investment cost for the one-time installation equipment of the system; c (C) TO Annual operating costs for the system over the operational life; p is p s Probability of occurrence for a typical day; s is the number of typical days; τ is the coefficient of the equivalent annual investment cost change value, and r is the discount rate; y is the service life of the system;
step 2.2: taking the capacity of system installation equipment as a decision variable optimized in the first stage, and minimizing the total input cost of the electric-gas combined comprehensive energy system as an objective function:
f 1 ＝minC TI
wherein n is { AC, EB, CCHP, GB, WT }; n represents energy conversion equipment, wherein n represents a wind power generator when being WT, an electric refrigerator when being AC, an electric boiler when being EB, a cogeneration device when being CCHP, and a gas boiler when being GB;the installation status of the kth energy conversion device n and the qth m energy storage means, respectively,/->1 indicates that the device is installed, 0 indicates that the device is not installed; />The installation cost for the kth energy conversion device n; />The installation cost for the q-th m energy storage device;
step 2.3: the operation conditions of energy conversion equipment and an energy storage device of the system are used as decision variables for second-stage optimization, and typical daily operation cost in the service life of the electric-gas combined comprehensive energy system is minimized as an objective function:
f 2 ＝minC TO
C TO ＝C ELE +C GAS +C FO +C TAX
wherein ,CELE The difference between the electricity purchasing and selling costs of the system is obtained; c (C) GAS The gas purchasing cost of the system; c (C) FO The cost of operation and maintenance for the system equipment; c (C) PEN Penalty cost for the system's load shedding;
wherein ,the prices of the purchased and sold electric energy in the period t are respectively; />The price of natural gas for the period t; />Maintenance costs for the operation of the kth energy conversion device n; />Inputting the power of the kth energy conversion device n for the t period, < >> The operation maintenance cost for the q-th m energy storage device; />Respectively charging and discharging m energy power of the q-th m energy storage device in the t period; c m Penalty cost for off-load of m energy; />Is the expected value of the absence of m energy;
step 2.4: the constraint conditions of a two-stage optimization configuration model for constructing the electric-gas combined comprehensive energy system are as follows:
wherein ,the maximum value of the electric power purchased and sold by the system is respectively; />The electricity purchasing and selling states of the system are respectively t time periods, and the system is in a +.>Ensuring that the system cannot purchase electricity and sell electricity at the same time;
wherein ,the maximum value of natural gas power is purchased for the system;
wherein ,for the operating state of the kth energy conversion device n +.>1 indicates that the equipment is in an operating state, and 0 indicates that the equipment is in a shutdown state; />Outputting power of m energy for the kth energy conversion device n of the t period; />The upper limit and the lower limit of m power are output by the kth energy conversion device n in the t period respectively;
wherein ,respectively charging and discharging energy power of the (m) energy storage device in the (q) th period of the t period; />Respectively charge and discharge energy working states of the (q) th m energy storage device,/>1 shows that the energy storage device is in a working state, so that the energy storage device can not charge and discharge energy at the same time; />The maximum and minimum charging power of the energy storage device of the (m) th time period of the t time period respectively; />The maximum energy release power and the minimum energy release power of the (m) energy storage device are respectively the (q) th time period; />Energy stored for the qth m energy storage device of the t period; />The upper limit and the lower limit of the energy stored by the q-th m energy storage device in the t period are respectively;
wherein ：m energy reserve power for the kth energy conversion device n for the t period; />Reserve power for the qth m energy storage device of the t period；
Step 3: obtaining a probability distribution model of the generated energy according to the Rayleigh distribution of the wind speed and adding the probability distribution model into constraint conditions of the two-stage optimization configuration model;
the generating capacity probability distribution model is as follows:
wherein ：rated output power of the wind driven generator; v r 、v in 、v out Rated wind speed and cut-in and cut-out wind speed respectively;
step 4: determining the influence of equipment random faults on a system, establishing two energy reliability indexes and adding the two energy reliability indexes into constraint conditions of a two-stage optimization configuration model;
the two energy reliability indexes are an energy shortage rate and an energy supplement rate;
the energy shortage and supply rate is as follows:
wherein ,is the energy shortage rate of m energy, < >>The installation state of the fault device gamma outputting m energy for the t period; />The probability of failure of the device gamma outputting m energy for the t period; />Outputting m energy power and standby power for the fault equipment gamma in the t period respectively; r is R m,t Standby power for t period m energy;
the energy supplement rate is as follows:
wherein ,energy supplement rate for m energy;
the two energy reliability indexes are added into the optimization model constraint:
wherein ,the upper limit of the energy shortage rate and the lower limit of the energy supplement rate are respectively.
Step 5: and solving an optimal configuration scheme of the electric-gas combined comprehensive energy system by using a particle swarm algorithm.
Step 5.1: inputting electric, cold and heat load data and equipment parameters of the comprehensive energy system, setting the particle number and the iteration number of an algorithm, and generating an initial population of optimal configuration;
step 5.2: calculating the system configuration cost, and simultaneously calling the CPLEX solver to calculate the system operation cost, and updating the particle population and the optimal solution;
step 5.3: and stopping calculating the output optimal solution when the upper limit of the iteration times or convergence is reached.
According to the two-stage optimal configuration method of the comprehensive energy system considering the energy reliability, the established two-stage optimal configuration model simultaneously considers the uncertainty of wind power generation and the uncertainty of equipment fault functions, so that the influence of the uncertainty of the system energy on the system output can be effectively reduced, the utilization of the system energy is effectively improved, and the system has sustainability and economy.
Drawings
FIG. 1 is a flow chart of a two-stage optimal configuration method of a comprehensive energy system considering energy reliability;
FIG. 2 is a block diagram of an electrical-gas integrated energy system;
FIG. 3 is a flow chart of an optimal configuration scheme for solving an electric-gas combined comprehensive energy system by using a particle swarm algorithm;
FIG. 4a is a spring and autumn load curve;
FIG. 4b is a winter load curve;
FIG. 4c is a summer load curve;
FIG. 4d is a typical seasonal wind power output profile.
Detailed Description
The following describes in further detail the embodiments of the present invention with reference to the drawings and examples. The following examples are provided to illustrate the invention and are a part of, but not all of, the examples.
As shown in fig. 1, a flow chart of a two-stage optimization configuration method of a comprehensive energy system considering energy reliability according to the present invention is shown in fig. 1, and the steps of the method of the present invention are as follows:
step 1: establishing an electric-gas combined comprehensive energy system model shown in fig. 2;
the electric-gas combined comprehensive energy system model comprises: the energy conversion model of the energy storage module is not considered and the energy conversion model of the energy storage module is considered;
the energy storage module includes: an electrical energy storage device, a cold energy storage device, and a hot energy storage device;
the energy conversion includes: the electric energy, the cold energy and the heat energy are converted by the energy conversion equipment; the energy conversion device includes: wind power generator, electric refrigerator, electric boiler, combined cooling heating and power device and gas boiler;
the energy conversion model without considering the energy storage module is as follows:
wherein ,PELE,t The electric power output by the system for the period t;the power purchasing power and the power selling power of the system in the t period are respectively; />Inputting electric power of an electric refrigerator and an electric boiler for a period t respectively; />Inputting natural gas power of the CCHP for a period t; />The power generation efficiency of CCHP; p (P) WT,t The power generated by the wind driven generator;
wherein ,PCOOL,t The cold power output by the system is t time periods;the electric power input into the electric refrigerator and the natural gas power input into the CCHP are respectively in t time periods; />Refrigeration efficiency of the electric refrigerator and the CCHP respectively;
wherein ,PHEAT,t The thermal power output by the system is t time period;inputting natural gas power of a gas boiler for a period t; />The thermal efficiency of the electric boiler, the CCHP and the gas boiler are respectively;
wherein ,the air purchase amount of the system is t time period; h L Low heat value for natural gas combustion;
the energy conversion model considering the energy storage module is as follows:
ΔS m,t ＝S m,t -S m,t-1
E m,t ＝P m,t Δt-ΔS m,t
wherein, m is { ele, cool, heat }, m is electricity when ele, cold when m is cool, and heat when m is heat;respectively charging and discharging energy power of the energy storage device in the period of t; />The energy charging and discharging efficiency of the energy storage device is respectively t time periods m; ΔS m,t The energy storage device stores the energy variation for the period t; s is S m,t 、S m,t-1 M energy respectively stored by the energy storage device in the time periods t and t-1; p (P) m,t To take the m power output by the energy storage module t period system into consideration, P m,t ∈{P ELE,t ,P COOL,t ,P HEAT,t }；
Step 2: establishing a two-stage optimal configuration model of the electric-gas combined comprehensive energy system;
step 2.1: the method aims at the lowest running and maintenance cost of configuration installation and operation of energy equipment in engineering, and establishes a two-stage optimal configuration model objective function of an electric-gas combined comprehensive energy system as follows:
wherein ,CT The total input cost of the comprehensive energy system is; c (C) TI Investment cost for the one-time installation equipment of the system; c (C) TO Annual operating costs for the system over the operational life; p is p s Probability of occurrence for a typical day; s is the number of typical days; τ is the coefficient of the equivalent annual investment cost change value, and r is the discount rate; y is the service life of the system;
step 2.2: taking the capacity of system installation equipment as a decision variable optimized in the first stage, and minimizing the total input cost of the electric-gas combined comprehensive energy system as an objective function:
f 1 ＝min C TI
wherein n is { AC, EB, CCHP, GB, WT }; n represents energy conversion equipment, wherein n represents a wind power generator when being WT, an electric refrigerator when being AC, an electric boiler when being EB, a cogeneration device when being CCHP, and a gas boiler when being GB;the installation status of the kth energy conversion device n and the qth m energy storage means, respectively,/->1 indicates that the device is installed, 0 indicates that the device is not installed; />The installation cost for the kth energy conversion device n; />The installation cost for the q-th m energy storage device;
step 2.3: the operation conditions of energy conversion equipment and an energy storage device of the system are used as decision variables for second-stage optimization, and typical daily operation cost in the service life of the electric-gas combined comprehensive energy system is minimized as an objective function:
f 2 ＝minC TO
C TO ＝C ELE +C GAS +C FO +C TAX
wherein ,CELE The difference between the electricity purchasing and selling costs of the system is obtained; c (C) GAS The gas purchasing cost of the system; c (C) FO The cost of operation and maintenance for the system equipment; c (C) PEN Penalty cost for the system's load shedding;
wherein ,respectively t time periodsPrice of electric energy purchased and sold; />The price of natural gas for the period t; />Maintenance costs for the operation of the kth energy conversion device n; />Inputting the power of the kth energy conversion device n for the t period, < >> The operation maintenance cost for the q-th m energy storage device; />Respectively charging and discharging m energy power of the q-th m energy storage device in the t period; c m Penalty cost for off-load of m energy; />Is the expected value of the absence of m energy;
step 2.4: the constraint conditions of a two-stage optimization configuration model for constructing the electric-gas combined comprehensive energy system are as follows:
wherein ,respectively systemsMaximum value of electric power purchased and sold; />The electricity purchasing and selling states of the system are respectively t time periods, and the system is in a +.>Ensuring that the system cannot purchase electricity and sell electricity at the same time;
wherein ,the maximum value of natural gas power is purchased for the system;
wherein ,for the operating state of the kth energy conversion device n +.>1 indicates that the equipment is in an operating state, and 0 indicates that the equipment is in a shutdown state; />Outputting power of m energy for the kth energy conversion device n of the t period;the upper limit and the lower limit of m power are output by the kth energy conversion device n in the t period respectively;
wherein ,respectively charging and discharging energy power of the (m) energy storage device in the (q) th period of the t period; />Respectively charge and discharge energy working states of the (q) th m energy storage device,/>1 shows that the energy storage device is in a working state, so that the energy storage device can not charge and discharge energy at the same time; />The maximum and minimum charging power of the energy storage device of the (m) th time period of the t time period respectively; />The maximum energy release power and the minimum energy release power of the (m) energy storage device are respectively the (q) th time period; />Energy stored for the qth m energy storage device of the t period; />The upper limit and the lower limit of the energy stored by the q-th m energy storage device in the t period are respectively;
wherein ：m energy reserve power for the kth energy conversion device n for the t period; />Reserve power for the mth m energy storage device in the t period;
step 3: obtaining a probability distribution model of the generated energy according to the Rayleigh distribution of the wind speed and adding the probability distribution model into constraint conditions of the two-stage optimization configuration model;
the generating capacity probability distribution model is as follows:
wherein ：rated output power of the wind driven generator; v r 、v in 、v out Rated wind speed and cut-in and cut-out wind speed respectively;
step 4: determining the influence of equipment random faults on a system, establishing two energy reliability indexes and adding the two energy reliability indexes into constraint conditions of a two-stage optimization configuration model;
the two energy reliability indexes are an energy shortage rate and an energy supplement rate;
the energy shortage and supply rate is as follows:
wherein ,is the energy shortage rate of m energy, < >>The installation state of the fault device gamma outputting m energy for the t period; />The probability of failure of the device gamma outputting m energy for the t period; />Outputting m energy power and standby power for the fault equipment gamma in the t period respectively; r is R m,t Standby power for t period m energy;
the energy supplement rate is as follows:
wherein ,energy supplement rate for m energy;
the two energy reliability indexes are added into the optimization model constraint:
wherein ,the upper limit of the energy shortage rate and the lower limit of the energy supplement rate are respectively.
Step 5: and solving an optimal configuration scheme of the electric-gas combined comprehensive energy system by using a particle swarm algorithm, wherein a specific solving flow is shown in figure 3. Comprising the following steps:
step 5.1: inputting electric, cold and heat load data and equipment parameters of the comprehensive energy system, setting the particle number and the iteration number of an algorithm, and generating an initial population of optimal configuration;
step 5.2: calculating the system configuration cost, and simultaneously calling the CPLEX solver to calculate the system operation cost, and updating the particle population and the optimal solution;
step 5.3: and stopping calculating the output optimal solution when the upper limit of the iteration times or convergence is reached.
As shown in FIG. 4, the wind power output and load curve of the typical season of the combined electric and gas energy system shown in FIG. 2 is shown.
Taking a northern area as an example, the invention provides a two-stage optimal configuration method of a comprehensive energy system considering energy reliability, which comprises the steps of constructing a two-stage optimal configuration model of the electric-gas combined comprehensive energy system according to steps 1-4, adopting time-sharing electricity price to purchase electricity, wherein the peak time is 8:00-14:00, 19:00-22:00, the price is 1.2 yuan/kW.h, the flat time is 14:00-19:00, the price is 0.8 yuan/kW.h, the valley time is 22:00-8:00, and the price is 0.4 yuan/kW.h; the electricity selling price is 0.64 yuan/kW.h; the price of the purchased natural gas is 2.93 yuan/m 3 . The loss load penalty cost of electricity, cold and heat energy is 8.05, 3.04 and 3.59 yuan/kW.h respectively. The service life of the integrated energy system constructed in the method is 20 years, the discount rate is 1%, and the installation and operation costs of each energy device and the energy storage device are shown in an annex table 1. The probability of occurrence in the spring, autumn, winter and summer on typical days is 0.4, 0.4 and 0.2 respectively.
TABLE 1 capital cost and operating parameters for plant
According to the step 1, the energy storage modules are respectively considered and not considered, the reliability index described in the step 4 is respectively introduced into the energy storage modules and the reliability index is not introduced into the energy storage modules, and the setting scene is shown in the table 2.
Table 2 scene settings
According to step 5, the algorithm shown in fig. 3 is adopted, and the solving and optimizing results are shown in tables 3 and 4.
TABLE 3 device configuration quantity and Capacity results for each scenario
Table 4 optimization results in various scenarios
As can be seen from tables 3 and 4, compared with the scenario 1, the scenario 2 considers two reliability indexes, the number of installed electric boilers, electric refrigerators and energy storage modules is increased, meanwhile, the number of combined heat and power generation devices, gas boilers and wind driven generators is reduced, compared with the configuration scheme of the scenario 1, the scenario 2 reduces the investment cost by 2490 ten thousand yuan, the annual operation cost is slightly 22.13 ten thousand yuan higher than that of the scenario 1, but the shortage of electric, cold and heat energy is greatly reduced, about one tenth of the scenario 1, the punishment cost of 35.59 ten thousand yuan is reduced, the punishment cost of the scenario 1 is 91.23%, and the optimization result is that the configuration of the scenario 2 reduces the total input cost of the system by 2732.89 ten thousand yuan compared with the operation scheme; compared with the configuration scheme of the scene 3, the investment cost of the scene 4 is increased by 630 ten thousand, but the annual operation cost is reduced by 161.05 ten thousand, the shortage of electric, cold and heat energy is effectively reduced, the penalty cost of 37.9 ten thousand yuan is reduced, the penalty cost of the scene 3 is 86.74%, and the optimization result is that the configuration of the scene 4 reduces the total input cost of the system by 2960.16 ten thousand yuan compared with the operation scheme. Therefore, after the reliability index is added in the constraint of the optimization model, the shortage energy of the system can be effectively reduced, so that the system is more stable and reliable, the total input cost of the system can be reduced, and meanwhile, the stability and economy of the system are ensured.
The foregoing technical solutions and accompanying drawings provided in the embodiments of the present invention are provided for further illustration of the present invention and not for limitation, and it should be further explained that those skilled in the art should still be aware that modifications can be made to the technical solutions described in the foregoing embodiments or equivalent substitutions can be made to some or all of the technical features thereof, and these modifications or substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the present invention.
Claims (5)
1. The two-stage optimal configuration method of the comprehensive energy system considering the energy reliability is characterized by comprising the following steps of:
step 1: establishing an electric-gas combined comprehensive energy system model;
step 2: establishing a two-stage optimal configuration model of the electric-gas combined comprehensive energy system;
step 3: obtaining a probability distribution model of the generated energy according to the Rayleigh distribution of the wind speed and adding the probability distribution model into constraint conditions of the two-stage optimization configuration model;
step 4: determining the influence of equipment random faults on a system, establishing two energy reliability indexes and adding the two energy reliability indexes into constraint conditions of a two-stage optimization configuration model;
step 5: solving an optimal configuration scheme of the electric-gas combined comprehensive energy system by utilizing a particle swarm algorithm;
the step 2 comprises the following steps:
step 2.1: the method aims at the lowest running and maintenance cost of configuration installation and operation of energy equipment in engineering, and establishes a two-stage optimal configuration model objective function of an electric-gas combined comprehensive energy system as follows:
wherein ,CT The total input cost of the comprehensive energy system is; c (C) TI Investment cost for the one-time installation equipment of the system; c (C) TO Annual operating costs for the system over the operational life; p is p s Probability of occurrence for a typical day; s is the number of typical days; τ is the coefficient of the equivalent annual investment cost change value, and r is the discount rate; y is the service life of the system;
step 2.2: taking the capacity of system installation equipment as a decision variable optimized in the first stage, and minimizing the total input cost of the electric-gas combined comprehensive energy system as an objective function:
f 1 ＝minC TI
wherein n is { AC, EB, CCHP, GB, WT }; n represents energy conversion equipment, wherein n represents a wind power generator when being WT, an electric refrigerator when being AC, an electric boiler when being EB, a cogeneration device when being CCHP, and a gas boiler when being GB;the installation status of the kth energy conversion device n and the qth m energy storage means, respectively,/->1 indicates that the device is installed, 0 indicates that the device is not installed; />The installation cost for the kth energy conversion device n; />The installation cost for the q-th m energy storage device;
step 2.3: the operation conditions of energy conversion equipment and an energy storage device of the system are used as decision variables for second-stage optimization, and typical daily operation cost in the service life of the electric-gas combined comprehensive energy system is minimized as an objective function:
f 2 ＝minC TO
C TO ＝C ELE +C GAS +C FO +C TAX
wherein ,CELE The difference between the electricity purchasing and selling costs of the system is obtained; c (C) GAS The gas purchasing cost of the system; c (C) FO The cost of operation and maintenance for the system equipment; c (C) PEN Penalty cost for the system's load shedding;
wherein ,the prices of the purchased and sold electric energy in the period t are respectively; />The price of natural gas for the period t; />Maintenance costs for the operation of the kth energy conversion device n;/>inputting the power of the kth energy conversion device n for the t period, < >> The operation maintenance cost for the q-th m energy storage device; />Respectively charging and discharging m energy power of the q-th m energy storage device in the t period; c m Penalty cost for off-load of m energy; />Is the expected value of the absence of m energy;
step 2.4: the constraint conditions of a two-stage optimization configuration model for constructing the electric-gas combined comprehensive energy system are as follows:
wherein ,the maximum value of the electric power purchased and sold by the system is respectively; />The electricity purchasing and selling states of the system are respectively t time periods, and the system is in a +.>Ensuring that the system cannot purchase electricity and sell electricity at the same time;
wherein ,the maximum value of natural gas power is purchased for the system;
wherein ,for the operating state of the kth energy conversion device n +.>1 indicates that the equipment is in an operating state, and 0 indicates that the equipment is in a shutdown state; />Outputting power of m energy for the kth energy conversion device n of the t period; />The upper limit and the lower limit of m power are output by the kth energy conversion device n in the t period respectively;
wherein ,respectively charging and discharging energy power of the (m) energy storage device in the (q) th period of the t period; />Respectively charge and discharge energy working states of the (q) th m energy storage device,/>1 shows that the energy storage device is in a working state, so that the energy storage device can not charge and discharge energy at the same time; />The maximum and minimum charging power of the energy storage device of the (m) th time period of the t time period respectively; />The maximum energy release power and the minimum energy release power of the (m) energy storage device are respectively the (q) th time period; />Energy stored for the qth m energy storage device of the t period; />The upper limit and the lower limit of the energy stored by the q-th m energy storage device in the t period are respectively;
wherein ：m energy reserve power for the kth energy conversion device n for the t period; />Reserve power for the mth energy storage device of the t period.
2. The two-stage optimization configuration method of the integrated energy system considering energy reliability according to claim 1, wherein the electric-gas combined integrated energy system model in step 1 comprises: the energy conversion model of the energy storage module is not considered and the energy conversion model of the energy storage module is considered;
the energy storage module includes: an electrical energy storage device, a cold energy storage device, and a hot energy storage device;
the energy conversion includes: the electric energy, the cold energy and the heat energy are converted by the energy conversion equipment; the energy conversion device includes: wind power generator, electric refrigerator, electric boiler, combined cooling heating and power device and gas boiler;
the energy conversion model without considering the energy storage module is as follows:
wherein ,PELE,t The electric power output by the system for the period t;the power purchasing power and the power selling power of the system in the t period are respectively; />Inputting electric power of an electric refrigerator and an electric boiler for a period t respectively; />Inputting natural gas power of the cogeneration device for a period t; />The power generation efficiency of the combined cooling heating power device is achieved; p (P) WT,t The power generated by the wind driven generator;
wherein ,PCOOL,t The cold power output by the system is t time periods;the electric power of the electric refrigerator and the natural gas power of the combined heat and power generation device are respectively input in the t period; />The refrigeration efficiency of the electric refrigerator and the combined cooling heating and power device are respectively;
wherein ,PHEAT,t The thermal power output by the system is t time period;inputting natural gas power of a gas boiler for a period t;the heat efficiency of the electric boiler, the combined cooling heating and power device and the gas boiler are respectively;
wherein ,the air purchase amount of the system is t time period; h L Low heat value for natural gas combustion;
the energy conversion model considering the energy storage module is as follows:
ΔS m,t ＝S m,t -S m,t-1
E m,t ＝P m,t Δt-ΔS m,t
wherein, m is { ele, cool, heat }, m is electricity when ele, cold when m is cool, and heat when m is heat;respectively charging and discharging energy power of the energy storage device in the period of t; />The energy charging and discharging efficiency of the energy storage device is respectively t time periods m; ΔS m,t The energy storage device stores the energy variation for the period t; s is S m,t 、S m,t-1 M energy respectively stored by the energy storage device in the time periods t and t-1; p (P) m,t To take the m power output by the energy storage module t period system into consideration, P m,t ∈{P ELE,t ,P COOL,t ,P HEAT,t }。
3. The two-stage optimization configuration method of the integrated energy system considering energy reliability according to claim 1, wherein the wind power generation capacity probability distribution model added with the optimization model constraint in the step 3 is as follows:
wherein ：rated output power of the wind driven generator; v r 、v in 、v out Rated wind speed and cut-in and cut-out wind speed respectively.
4. The two-stage optimization configuration method of the comprehensive energy system considering the energy reliability according to claim 1, wherein the two energy reliability indexes added with the optimization model constraint in the step 4 are an energy shortage rate and an energy supplement rate;
the energy shortage and supply rate is as follows:
wherein ,is the energy shortage rate of m energy, < >>The installation state of the fault device gamma outputting m energy for the t period;the probability of failure of the device gamma outputting m energy for the t period; />Outputting m energy power and standby power for the fault equipment gamma in the t period respectively; r is R m,t Standby power for t period m energy;
the energy supplement rate is as follows:
wherein ,energy supplement rate for m energy;
the two energy reliability indexes are added into the optimization model constraint:
wherein ,respectively supplementing the upper limit of the energy shortage rate and the energyLower limit of the rate.
5. The two-stage optimization configuration method of the integrated energy system considering energy reliability according to claim 1, wherein the step 5 is specifically:
step 5.1: inputting electric, cold and heat load data and equipment parameters of the comprehensive energy system, setting the particle number and the iteration number of an algorithm, and generating an initial population of optimal configuration;
step 5.2: calculating the system configuration cost, and simultaneously calling the CPLEX solver to calculate the system operation cost, and updating the particle population and the optimal solution;
step 5.3: and stopping calculating the output optimal solution when the upper limit of the iteration times or convergence is reached.
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