A method and device for evaluating the reliability of a regional integrated energy system

Abstract

The invention relates to a reliability assessment method and device for a regional integrated energy system, and belongs to the technical field of regional integrated energy. The reliability assessment method for the regional integrated energy system comprises: respectively establishing an electric load demand response model and a thermal load demand response model, and establishing a RIES load reduction optimization model based on the electric load demand response model and the thermal load demand response model, with the sum of the energy purchase cost, the load reduction penalty cost and the demand response cost being minimized as the optimization target; establishing a RIES reliability index, and evaluating the reliability level of the RIES after calculating the RIES reliability index by using a sequential Monte Carlo simulation method combined with the RIES load reduction optimization model, wherein the RIES reliability index at least includes an expected energy shortage time, an expected energy shortage and an energy supply availability rate, thereby improving the energy supply reliability of the regional integrated energy system.

Description

Technical Field

[0001] The present invention relates to the field of regional integrated energy technology, and in particular to a reliability assessment method and device for a regional integrated energy system. Background Art

[0002] Faced with the gradual depletion of fossil energy and the increasing demand for energy by mankind, how to optimize the energy structure and achieve consumption transformation has become an urgent problem to be solved in today's world. The regional integrated energy system with the power system as the core, by coupling various energy sources such as electricity, gas, and heat, has the advantages of realizing the complementary and mutual assistance of different energy sources, energy cascade utilization, and compensating for the random volatility of renewable energy output, which is conducive to promoting the large-scale consumption of renewable energy.

[0003] At present, most studies on reliability assessment only consider single load demand response. Few studies consider the impact of comprehensive electricity and heat demand response on the reliability of regional integrated energy system (RIES). In addition, when considering demand response, the impact of user's electricity comfort on system energy supply is rarely considered. In fact, user comfort will directly affect the user's enthusiasm for participating in the response, thereby affecting the operation of RIES. In terms of reliability assessment indicators, most of them ignore the differences in the impact of different energy shortages on users. It is necessary to improve the calculation method of reliability assessment indicators according to the operating characteristics of different energy sources. Summary of the invention

[0004] In view of this, it is necessary to provide a regional integrated energy system reliability assessment method and device to solve the technical problems in the prior art that only a single load demand response is considered and the impact of electricity comfort on the energy supply of the integrated energy system is less considered.

[0005] In order to solve the above problems, the present invention provides a regional integrated energy system reliability assessment method, comprising the following steps:

[0006] Establishing an electric load demand response model and a thermal load demand response model respectively, and establishing a RIES load reduction optimization model based on the electric load demand response model and the thermal load demand response model with the sum of the purchased energy cost, the load reduction penalty cost and the demand response cost being minimized as the optimization target;

[0007] After the RIES reliability index is calculated by using the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model, the reliability level of RIES is evaluated, wherein the RIES reliability index at least includes the expected energy shortage time, the expected energy shortage and the energy supply availability.

[0008] In a possible implementation, the electric load demand response model is:

[0009]

[0010] C dre，t =β e c ele P dr，t ,

[0011]

[0012] Among them, T is the total scheduling period, P dre，up，t is the reduction of flexible electric load at time t, P dre，down，t is the increase of flexible electric load at time t, C dre，t To provide financial compensation to users, β e is the unit subsidy coefficient of flexible electric load, c ele is the electricity purchase price, P dr，t is the change in the load demand response at time t, r is the power comfort level, P Le，t is the electric load at time t;

[0013] The heat load demand response model is:

[0014] T in，t+1 =T in，t e -Δt / τ +(RQ t +T out，t )(1-e -Δt / τ )

[0015] τ=R·C air ,

[0016]

[0017]

[0018] Among them, T in,t is the indoor temperature of the building at time t, T out,t is the outdoor temperature of the building at time t, Q t is the heating power of the building at time t, R is the thermal resistance of the building, C air is the indoor air heat capacity, λ PMV is the relationship between indoor temperature and PMV value, τ is the variable.

[0019] In a possible implementation, the calculation formula of the optimization target is:

[0020]

[0021] Among them, P NET,t is the amount of electricity purchased from the external power grid at time t, GNET,t is the amount of natural gas purchased from the external gas grid at time t, c gas is the gas purchase price, α e is the load reduction penalty unit price, α h is the penalty unit price for heat load reduction, L cute,t is the load reduction at time t, L Cuth,t is the heat load reduction at time t.

[0022] In a possible implementation, the calculation formula for the expected energy shortage time is:

[0023]

[0024]

[0025]

[0026]

[0027] Among them, LOLE e is the expected power shortage time, t MC is the duration of the Monte Carlo simulation, N is the number of samples, and F Le (X i ) is the system status X i The resulting electrical load reduction, ΔL ecut,i To reduce the power of the electric load at the i-th sampling time, LOLE h is the expected time of insufficient heat energy, F Lh (X i ) is the system status X i Heat load reduction, ΔL hcut,i is the rigid heat load reduction power at the i-th sampling, ΔL hfcut,i is the flexible heat load reduction power at the i-th sampling time.

[0028] In a possible implementation, the energy supply shortage expectation is calculated as follows:

[0029]

[0030]

[0031] Among them, EENS e EENS h is the expected insufficient heat supply of the system, t MC is the duration of the Monte Carlo simulation, N is the number of samples, and F Le (X i ) is the system status X iThe resulting electrical load reduction, ΔL ecut,i To reduce the power of the electric load at the i-th sampling time, LOLE h is the expected time of insufficient heat energy, F Lh (X i ) is the system status X i Heat load reduction, ΔL hcut,i is the rigid heat load reduction power at the i-th sampling, ΔL hfcut,i is the flexible heat load reduction power at the i-th sampling time.

[0032] In a possible implementation, the calculation formula for the energy supply availability rate is:

[0033]

[0034]

[0035] Among them, γ e is the power supply availability, γ h is the heating availability rate, LOLE e Expected for low power time, LOLE h Expected for insufficient heat time.

[0036] In a possible implementation, after the RIES reliability index is calculated by using the sequential Monte Carlo simulation method in combination with the RIES load reduction optimization model, the reliability level of the RIES is evaluated, including:

[0037] Step 1: Input the system parameters of RIES, initialize the system parameters and component states, and set the Sequential Monte Carlo simulation time and simulation years;

[0038] Step 2: Use the sequential Monte Carlo simulation method to sample and obtain the duration of equipment trouble-free operation within the study period, take the component with the shortest duration of equipment trouble-free operation as the faulty device, and obtain the trouble-free working time and the cumulative simulation time;

[0039] Step 3: Obtain the repair time after the equipment failure, calculate the outage time and reduction amount of the electric and heating load during the failure period, and obtain the cumulative simulation time;

[0040] Step 4: When the cumulative simulation time is greater than the number of simulation years, the RIES reliability index is calculated and the process proceeds to step 6; when the cumulative simulation time is less than or equal to the number of simulation years, the process proceeds to step 5;

[0041] Step 5, when the cumulative simulation time crosses the year, calculate the RIES reliability index; when the cumulative simulation time crosses the year but does not cross the year, extract the new fault-free operation duration of the component, and return to step 2;

[0042] Step 6: Output the RIES reliability index and evaluate the reliability level of RIES.

[0043] In a possible implementation, the calculation formula for the fault-free operation duration of the equipment is:

[0044]

[0045] Among them, t ttf is the duration of trouble-free operation, σ is the equipment failure rate, and R is a random number in the interval [0, 1].

[0046] In a possible implementation, the calculation formula for the repair time after the equipment failure is:

[0047]

[0048] Among them, t ttr is the trouble-free operation duration, μ is the equipment repair rate.

[0049] In a second aspect, the present invention further provides a regional integrated energy system reliability assessment device, comprising:

[0050] A load reduction optimization model establishment module is used to establish an electric load demand response model and a thermal load demand response model respectively, and establish a RIES load reduction optimization model based on the electric load demand response model and the thermal load demand response model with the sum of the purchased energy cost, the load reduction penalty cost and the demand response cost being minimized as the optimization target;

[0051] The regional integrated energy system evaluation module is used to establish the RIES reliability index. After the RIES reliability index is calculated by the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model, the reliability level of RIES is evaluated, wherein the RIES reliability index at least includes the expected energy shortage time, the expected energy shortage and the energy supply availability.

[0052] The beneficial effect of the present invention is that the reliability assessment method and device of the regional integrated energy system provided by the present invention respectively establish an electric load demand response model and a heat load demand response model according to load characteristics, thereby improving the system heating reliability and power supply reliability. Reasonable adjustment of user electricity comfort can effectively improve system reliability. Based on the electric load demand response model and the heat load demand response model, a RIES load reduction optimization model is established. After the RIES reliability index is calculated by the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model, the reliability level of RIES is evaluated. By adjusting the flexible electric load and changing the electric load demand curve, the power supply reliability of the regional integrated energy system is significantly improved. Since the electric load demand response changes the electric load demand curve, the output of the electric boiler equipment is adjusted to improve the heating reliability of the regional integrated energy system. At the same time, the heat load demand response also improves the power supply reliability of the regional integrated energy system. At the same time, the electric and heat load demand responses are considered, and the flexible load is fully tapped to participate in the system response, which effectively improves the RIES energy supply reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A flow chart of an embodiment of a method for evaluating the reliability of a regional integrated energy system provided by the present invention;

[0054] Figure 2 A schematic diagram of the RIES structure of the regional integrated energy system reliability assessment method provided by the present invention;

[0055] Figure 3 Photovoltaic output curves of typical days in each season for the regional integrated energy system reliability assessment method provided by the present invention;

[0056] Figure 4 A typical daily load curve in winter for the regional integrated energy system reliability assessment method provided by the present invention;

[0057] Figure 5 Typical winter day energy price and outdoor temperature curves for the regional integrated energy system reliability assessment method provided by the present invention;

[0058] Figure 6 The electric load reduction curves of typical winter days under different scenarios of the regional integrated energy system reliability assessment method provided by the present invention;

[0059] Figure 7 The heat load reduction curves of typical winter days under different scenarios of the regional integrated energy system reliability assessment method provided by the present invention;

[0060] Figure 8 The typical day of the regional integrated energy system reliability assessment method provided by the present invention only considers the flexible electric load adjustment of the electric load demand response scenario;

[0061] Fig. 9 The heating heat load curve of the winter typical day basic scenario and the heating heat load demand response scenario considering only the heat load demand response scenario of the regional integrated energy system reliability assessment method provided by the present invention

[0062] Fig.10 Indoor temperature curves for the winter typical day basic scenario and the scenario considering only the heat load demand response of the regional integrated energy system reliability assessment method provided by the present invention

[0063] Fig.11 Thermal power curve of electric boilers for the winter typical day basic scenario and only considering the thermal load demand response scenario of the regional integrated energy system reliability assessment method provided by the present invention

[0064] Fig.12 The changes in the expected indicators of insufficient energy supply of the system under different electricity comfort levels of the regional comprehensive energy system reliability assessment method provided by the present invention;

[0065] Fig.13 A schematic structural diagram of an embodiment of a regional integrated energy system reliability assessment device provided by the present invention. DETAILED DESCRIPTION

[0066] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0067] A specific embodiment of the present invention discloses a method for evaluating the reliability of a regional integrated energy system. Figure 1 This is a flow chart of the regional integrated energy system reliability assessment method provided by the embodiment of the present invention. Figure 1 ,The regional integrated energy system reliability assessment method includes the following steps:

[0068] S101, respectively establishing an electric load demand response model and a thermal load demand response model, and establishing a RIES load reduction optimization model based on the electric load demand response model and the thermal load demand response model, with the sum of the purchased energy cost, the load reduction penalty cost and the demand response cost being minimized as the optimization target;

[0069] S102, establishing a RIES reliability index, and evaluating the reliability level of RIES after calculating the RIES reliability index using a sequential Monte Carlo simulation method combined with a RIES load reduction optimization model, wherein the RIES reliability index at least includes the expected energy shortage time, the expected energy shortage, and the energy supply availability.

[0070] During implementation, according to the load characteristics, an electric load demand response model and a thermal load demand response model are established respectively. Based on the electric load demand response model and the thermal load demand response model, a RIES load reduction optimization model is established with the minimum sum of the energy purchase cost, the load reduction penalty cost and the demand response cost as the optimization goal; a RIES reliability index is established, and the RIES reliability index is calculated using the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model to evaluate the reliability level of RIES. Among them, the RIES reliability index at least includes the expected energy shortage time, the expected energy supply shortage and the energy supply availability, which improves the energy supply reliability of the regional integrated energy system.

[0071] Compared with the prior art, the regional integrated energy system reliability assessment method provided in this embodiment establishes electric load and heat load demand response models respectively according to load characteristics, improves the system heating reliability and power supply reliability, and reasonably adjusts the user's electricity comfort level to effectively improve the system reliability. Based on the electric load demand response model and the heat load demand response model, a RIES load reduction optimization model is established with the minimum sum of the purchased energy cost, the load reduction penalty cost and the demand response cost as the optimization goal, and the flexible load is fully explored to participate in the system response, which can effectively improve the RIES energy supply reliability, establish a RIES reliability index, and use the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model to calculate the RIES reliability index, and then evaluate the RIES reliability level, thereby improving the regional integrated energy system energy supply reliability.

[0072] In some embodiments, in step S100, the regional integrated energy system (RIES) is provided with energy input by the upper power grid, natural gas grid and photovoltaic unit (photovoltaic, PV), and provides electricity and heat energy to users through transformer (transformer, T), combined heating and power (combined heating and power, CHP), gas boiler (gas boiler, GB), electric boiler (electric boiler, EB) energy conversion equipment and energy storage equipment, wherein the energy storage equipment includes electricity storage (electricity storage, ES), heat storage (heat storage, HS) and gas storage (gas storage, GS). For a schematic diagram of the RIES structure, please refer to Figure 2 .

[0073] According to the load characteristics, the electric load demand response model and the heat load demand response model are established respectively. The electric load demand response mainly includes price type and incentive type. In the regional integrated energy system, in order to fully tap the regulation potential of the demand side load, considering that the heating heat load transmission has a delay, and the user has a fuzzy perception of temperature changes, the heating heat load can be used as a flexible load to participate in the system response adjustment. The flexible electric load is highly flexible and can be adjusted according to the energy price and system equipment status changes. In order to ensure the consistency of the total electric load within the research period, it should meet the following requirements:

[0074]

[0075] Among them, T is the total scheduling period, P dre,up,t is the reduction of flexible electric load at time t, P dre,down,t is the increase in flexible electric load at time t;

[0076] When users participate in demand response, they will be given a certain amount of economic compensation C dre，t , and its calculation formula is:

[0077] C dre，t =β e c ele P dr，t ,

[0078] Among them, C dre，t To provide financial compensation to users, β e is the unit subsidy coefficient of flexible electric load, c ele is the electricity purchase price, P dr，t is the change in the electric load demand response at time t;

[0079] When users do not participate in the system power demand response, they use electricity in the most comfortable way for themselves, and the power comfort is the best at this time. When users participate in the system power demand response, the change of power consumption plan affects the user's power comfort. The power comfort r is defined to describe the degree of change in power consumption. The calculation formula is:

[0080]

[0081] Among them, r is the electricity comfort level, P Le，t is the electrical load at time t.

[0082] In real life, users are less sensitive to small temperature changes, and temperature changes within the comfortable temperature range will not affect the user's thermal comfort. Therefore, the winter heating heat load is used as a flexible heat load to participate in the response, and the remaining heat loads are used as rigid heat loads and do not participate in the response. The building thermodynamic model is used to model the winter heating heat load. Through the relationship between the building's outdoor temperature, indoor temperature and heating power, a heat load demand response model is established. The heat load demand response model is:

[0083] T in，t+1 =T in，t e -Δt / τ +(RQ t +T out，t )(1-e -Δt / τ )

[0084] τ=R·C air ,

[0085]

[0086] Among them, T in,t is the indoor temperature of the building at time t, T out,t is the outdoor temperature of the building at time t, Q t is the heating power of the building at time t, R is the thermal resistance of the building, C air is the indoor air heat capacity;

[0087] According to the temperature range of human comfort, the PMV index is used to evaluate the user's satisfaction with the indoor temperature change. in and PMV value (denoted as λ PMV ) is:

[0088]

[0089] Among them, λ PMV is the relationship between indoor temperature and PMV value;

[0090] According to the ISO7730 standard, when the PMV value is in the range of [-0.5, 0.5], the indoor temperature is relatively comfortable, and it can be concluded that the comfortable temperature range is 24.8℃~27.3℃.

[0091] In some embodiments, in order to avoid load reduction caused by system equipment failure or other factors as much as possible, an incentive-based demand response is used to increase the enthusiasm of users to participate in the response, thereby improving the reliability level of the system. Considering the demand response of electric load and thermal load, based on the electric load demand response model and the thermal load demand response model, a RIES load reduction optimization model is established with the minimum sum of the purchased energy cost, the load reduction penalty cost and the demand response cost as the optimization goal. The constraints of the RIES load reduction optimization model include at least the tie line constraint, the energy conversion equipment output constraint, the energy storage constraint, the power balance constraint and the equipment failure topology constraint; the calculation formula of the optimization goal is:

[0092]

[0093] Among them, P NET,t is the amount of electricity purchased from the external power grid at time t, G NET,t is the amount of natural gas purchased from the external gas grid at time t, c gas is the gas purchase price, α e is the load reduction penalty unit price, α h is the penalty unit price for heat load reduction, L cute,t is the load reduction at time t, L Cuth,t is the heat load reduction at time t;

[0094] The output constraints of its energy conversion equipment are:

[0095] H GB,t =η GB G GB,t ,

[0096] H EB,t =η EB P EB,t ,

[0097]

[0098]

[0099] Among them, H GB,t is the thermal power output of the gas boiler at time t, H EB,t is the thermal power output of the electric boiler at time t, H CHP,t is the thermal power output of the cogeneration unit at time t, P EB,t is the electric power consumed by the electric boiler at time t, G GB,t is the amount of natural gas consumed by the gas boiler at time t, G CHP,t is the amount of natural gas consumed by the cogeneration unit at time t, η GB is the energy conversion coefficient of the gas boiler, η EB is the energy conversion coefficient of the electric boiler, is the power generation efficiency of the cogeneration unit, is the heating efficiency of the cogeneration unit, P CHP,t is the power generation of the cogeneration unit at time t, V GV is the calorific value of natural gas;

[0100] Electric energy storage ES, thermal energy storage HS, and gas energy storage GS are modeled using a unified energy storage model, and their energy storage constraints are:

[0101]

[0102] Where S(t) is the stored energy of the energy storage device at time t; λ los is the energy loss rate of the energy storage device, λ cha is the energy storage efficiency of the energy storage device, λ dis is the energy release efficiency of the energy storage device, Δt is the optimal scheduling time interval, P t cha is the energy storage power at time t, P t dis is the energy release power at time t;

[0103] The constructed RIES includes electricity, heat and gas power balance constraints, and its system power balance constraints are:

[0104]

[0105]

[0106]

[0107] Among them, P L,t is the actual demand load at time t, H L,t is the actual required heat load at time t, P PV,t is the photovoltaic output power at time t, is the charge capacity of the energy storage device at time t, is the discharge amount of the energy storage device at time t, is the heat storage capacity of the heat storage equipment at time t, is the heat release of the heat storage device at time t, is the gas storage capacity of the gas storage equipment at time t, is the gas discharge volume of the gas storage equipment at time t;

[0108] When a device S in RIES k When a fault occurs, the device and the devices S1, S2, …, S1 affected by the fault will be y The output energy is 0, and the device failure topology constraint is:

[0109] Pt (S i )=0,i=1,2,…y,

[0110] Among them, P t (S i ) is the device S i The output at time t, and y is the number of devices affected by the faulty device.

[0111] In some embodiments, in step S200, existing studies often directly use power system reliability evaluation indicators, while the operation characteristics of thermal systems are quite different from those of power systems. In order to quantify the reliability level of RIES power supply and heat supply and consider the thermal inertia of the thermal system, the power system reliability evaluation indicators are extended to the thermal system. At the same time, the calculation method of the reliability evaluation indicators is improved according to the thermal load inertia. The system energy shortage time expectation (Loss Of Load Expectation, LOLE), the system energy shortage expectation (Expected Electric Not Supply, EENS), and the service availability index (Service Availability Index, SAI) are used to comprehensively describe the reliability of the regional comprehensive energy system. The system energy shortage time expectation at least includes the power shortage time expectation and the thermal energy shortage time expectation. The system energy shortage expectation at least includes the system power shortage expectation and the system thermal supply shortage expectation. The energy supply availability includes at least the power supply availability and the heating availability.

[0112] Low power time expectation LOLE e It indicates the time during the study period when the power supply of the system is insufficient to meet the user's power load demand. The calculation formula is:

[0113]

[0114]

[0115] Among them, LOLE e is the expected power shortage time, t MC is the duration of the Monte Carlo simulation, N is the number of samples, and F Le (X i ) is the system status X i The resulting electrical load reduction, ΔL ecut,i is the load reduction power at the i-th sampling time, F Le (X i )=0 means no load reduction occurs, F Le (X i )=1 indicates that electric load reduction occurs;

[0116] Heat energy deficiency time expectation LOLE h It indicates the time during the study period when the heat load demand of users is not met due to insufficient heating of the system. The calculation formula is:

[0117]

[0118]

[0119] Among them, LOLE h is the expected time of insufficient heat energy, F Lh (X i ) is the system status X i Heat load reduction, ΔL hcut,i is the rigid heat load reduction power at the i-th sampling, ΔL hfcut,i is the flexible heat load reduction power at the i-th sampling time, F Lh (X i )=0 means no load reduction occurs, F Lh (X i )=1 means heat load reduction occurs;

[0120] Insufficient system power supply EENS e It represents the expected value of the power shortage of the system during the study period, and its calculation formula is:

[0121]

[0122] Among them, EENS e The expected power shortage of the system, t MC is the duration of the Monte Carlo simulation, N is the number of samples, and F Le (X i ) is the system status X i The resulting electrical load reduction, ΔL ecut,i is the power reduction of the electric load at the i-th sampling time;

[0123] Insufficient heat supply in the system EENS h It represents the expected value of the thermal energy shortage of the system during the study period, and its calculation formula is:

[0124]

[0125] Among them, LOLE h is the expected time of insufficient heat energy, F Lh (X i ) is the system status X i Heat load reduction, ΔL hcut,i is the rigid heat load reduction power at the i-th sampling, ΔL hfcut,iis the flexible heat load reduction power at the i-th sampling time;

[0126] Whether the flexible heat load is reduced is determined based on the change in indoor temperature. When the temperature is not within the set range, the flexible heat load is reduced. The reduction amount is the difference between the theoretical heating power and the actual heating power. The calculation formula for the flexible heat load reduction power is:

[0127]

[0128] Among them, ΔL hfcut,t Power reduction for flexible heat load, L Fhr,t is the theoretical thermal power provided by the system to the user at time t, T set,min To set the minimum indoor temperature, T set,max To set the maximum indoor temperature, the minimum heating power required from the current temperature to the set temperature range is the theoretical heating power. in,t ≤T in,min When the theoretical thermal power is:

[0129]

[0130] Combined with the calculation formula of theoretical thermal power, the flexible heat load reduction is obtained, and the calculation formula is:

[0131]

[0132] Among them, ΔL hfcut,t is the power reduction for flexible heat load, R is the thermal resistance;

[0133] The energy supply availability index represents the ratio of the system's effective energy supply hours to the required energy supply hours. The energy supply availability is calculated as follows:

[0134]

[0135]

[0136] Among them, γ e is the power supply availability, γ h is the heating availability rate, LOLE e Expected for low power time, LOLE h Expected for insufficient heat time.

[0137] In some embodiments, considering that the output of different equipment in RIES has a time sequence, a state model of the equipment is established, and the time sequence Monte Carlo simulation method is used to sample the fault-free operation duration of the equipment and the repair time after the equipment failure. The calculation formula for the fault-free operation duration of the equipment is:

[0138]

[0139] Among them, t ttf is the duration of trouble-free operation, σ is the equipment failure rate, and R is a random number in the interval [0, 1];

[0140] The calculation formula for the repair time after equipment failure is:

[0141]

[0142] Among them, t ttr is the trouble-free operation duration, μ is the equipment repair rate.

[0143] After calculating the RIES reliability index using the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model, the reliability level of RIES is evaluated. The specific evaluation steps are as follows:

[0144] Step 1: Input the RIES system parameters, initialize the system parameters and component states, and set the Sequential Monte Carlo simulation time t MC = 0 and simulation year y = 1;

[0145] Step 2: Use the sequential Monte Carlo simulation method to sample and obtain the equipment trouble-free operation duration t within the study period. ttf , taking the device with the shortest duration of trouble-free operation as the faulty device, we get the trouble-free working time z=min(t ttf ) and the cumulative simulation time t MC =t MC +z;

[0146] Step 3: Obtain the repair time t after the equipment failure ttr After calculating the outage duration and reduction amount of electric and thermal load during the fault period, the cumulative simulation time t MC =t MC +z+t ttr ;

[0147] Step 4: When the cumulative simulation time is greater than the number of simulation years, the RIES reliability index is calculated, the simulation ends, and the process goes to step 6. When the cumulative simulation time is less than or equal to the number of simulation years, the process goes to step 5.

[0148] Step 5: Determine whether the simulation time crosses the year. When the cumulative simulation time crosses the year, calculate the reliability index of RIES for that year. When the cumulative simulation time crosses the year, extract the new fault-free operation duration of the equipment and return to step 2.

[0149] Step 6: Output the RIES reliability index and evaluate the reliability level of RIES.

[0150] In some embodiments, taking the park RIES as an example, the RIES includes 3 cogeneration units CHP, 2 transformers T, 1 gas boiler GB and 1 electric boiler EB, and also includes 1 electric and thermal energy storage device and 2 gas storage devices. For the parameters of the specific devices in the RIES, please refer to Table 1;

[0151] Table 1

[0152]

[0153]

[0154] The energy storage efficiency and energy discharge efficiency of its energy storage equipment are both 0.9. The maximum charging and discharging power of the electric energy storage ES and thermal energy storage HS are both 500kW, and the maximum charging and discharging power of the gas energy storage GS are both 400kW. For the photovoltaic output curves of typical days in summer, spring, autumn and winter, please refer to Figure 3 , typical daily load curve in winter, please refer to Figure 4 , where heating heat load and rigid heat load need to be considered for typical days in winter, and only rigid heat load is considered in other seasons; the maximum input power of electric energy at the energy input end is 4800kW, and the failure rate and repair time at the power input end are 0.9 times / a and 20h respectively; the maximum input amount of natural gas at the energy input end is 4500kW, and the failure rate and repair time at the natural gas input end are 0.82 times / a and 7.32h respectively; based on the typical day, the adjustment coefficient is used to characterize the energy price and load situation throughout the year. For the load and energy price adjustment coefficients, please refer to Table 2.

[0155] Table 2

[0156]

[0157] For typical winter day price curves and outdoor temperatures, see Figure 5 .

[0158] In order to reflect the impact of comprehensive electric and thermal demand response on RIES reliability and verify the effectiveness of the model and method, four operation scenarios are set, and the RIES reliability index is calculated and analyzed. Scenario 1: basic scenario, without considering demand response; Scenario 2: only considering electric load demand response; Scenario 3: only considering thermal load demand response; Scenario 4: considering both electric load demand response and thermal load demand response. In Scenario 1, when flexible thermal load is not considered to participate in demand response, the reliability index is calculated according to the constant indoor temperature mode, and the indoor temperature is a constant value of 26°C; in Scenario 3, when flexible thermal load participates in response, the reliability index is calculated within the range of indoor temperature that meets the comfortable temperature. The reliability index of RIES under different scenarios is shown in Table 3.

[0159] Table 3

[0160]

[0161] As shown in Table 3, scenario 2 takes into account the load demand response. By adjusting the flexible load, the load demand curve is changed. Compared with scenario 1, the power supply reliability of the RIES system is significantly improved. Compared with scenario 1, the power supply shortage in scenario 2 is less than the expected EENS. e Reduced by 7220.69kW, the power shortage time is expected to be LOLE e In addition, since the electric load demand response changes the electric load demand curve, the system heating reliability is improved by adjusting the output of the electric boiler equipment. Compared with scenario 1, the RIES heat supply shortage expected index EENS in scenario 2 is h and the expected index of insufficient heat time LOLE h All of them have decreased, among which LOLE h The expected index of insufficient heat supply and insufficient heat time in RIES decreased by 3.28h / a. After considering the heat load demand response in scenario 3, the expected index of insufficient heat supply and insufficient heat time in RIES decreased more significantly compared with scenario 2. The expected index of insufficient heat supply decreased by 11342.42kW compared with scenario 1, a relative decrease of 29.53%, and the expected index of insufficient heat time decreased by 7.91h / a. At the same time, the heat load demand response also improved the power supply reliability of the system. Compared with scenario 1, the EENS in scenario 3 decreased by 1.38h / a. e LOLE e , but the decline is not as large as that in scenario 2. The results of scenario 4 show that, compared with scenarios 1 and 2, the response of electricity and heat load demand is considered at the same time, and the flexible load is fully exploited to participate in the system response, which effectively improves the RIES energy supply reliability. Compared with scenario 1, the EENS in scenario 4 is e A reduction of 10812.8kW, a relative reduction of 40.52%, EENS h A reduction of 15758.63kW, a relative reduction of 41.03%.

[0162] In order to deeply analyze the impact of flexible electricity and heat loads participating in demand response on RIES reliability, the impact of flexible load changes on electricity and heat load reduction is analyzed based on a typical winter day with a gas boiler GB failure and a transformer failure; please refer to Figure 6 , Figure 7 ,pass Figure 6 and Figure 7It can be seen that when the gas boiler GB and transformer in RIES fail, the user's energy demand will not be met, and the electricity and heat loads will be undersupplied; in scenario 1, the electricity load was reduced between 18:00 and 22:00, with the maximum electricity load reduction reaching 641 kW, and the heat load was reduced between 17:00 and 23:00, with the maximum heat load reduction reaching 518 kW.

[0163] See also Figure 8 ,pass Figure 8 , the change of flexible electric load in scenario 2 shows that the flexible electric load in the period of 17:00-23:00 is adjusted to the period of 11:00-15:00 when the photovoltaic output is sufficient and the rest of the period, which improves the electric load curve. Figure 6 and Figure 7 It can be seen that after considering the electric load demand response, the electric load reduction in scenario 2 is greatly reduced compared with scenario 1, and the maximum load reduction is reduced from 641kW to 76kW. At the same time, the system heating reliability is also slightly improved. This is because the flexible electric load participates in the demand response between 18:00-22:00, which reduces the electricity demand in this period, thereby improving the system power supply reliability level. When the electric load demand is relatively small, the system heating reliability is improved by increasing the output of the electric boiler EB.

[0164] See also Fig. 9 , Fig.10 , Fig.11 ,like Fig. 9 , Fig.10 , Fig.11 As shown in the figure, the heating heat load curve, indoor temperature curve and electric boiler output curve of a typical winter day in scenario 1 and scenario 3 are given respectively; combined with Figure 6 and Figure 7 It can be seen that after considering the heat load demand response of thermal comfort, the heat load reduction in scenario 3 is greatly reduced compared with scenario 1. The heat load reduction period is shortened from 17:00-23:00 to 21:00-22:00. At the same time, the electric load reduction is reduced at 18:00 and 22:00. This is mainly because in scenario 1, the indoor temperature is a fixed value of 26℃, while in scenario 3, the indoor temperature fluctuates between 24.8℃ and 27.3℃, so the heating heat load also changes, thereby increasing the flexible adjustable capacity of the heat load; for example, the indoor heating thermal power is reduced by lowering the indoor temperature from 19:00 to 24:00, thereby reducing the heat load reduction.

[0165] from Fig. 9It can be seen that the heating heat load curve is improved compared with scenario 1 during the period of sufficient photovoltaic output (11:00-16:00). The heating load demand is met by increasing the output of electric boilers, while the absorption of photovoltaic power generation is improved. In the remaining periods, the heating heat load demand decreases to varying degrees. At 20:00, the spatial heat load decreases by 445kW, and the energy purchase cost is reduced by reducing the output of electric boilers.

[0166] To analyze the impact of different electricity comfort levels on RIES reliability, please refer to Fig.12 ,That Fig.12 The changes in the impact of different electricity comfort values ​​on the expected indicators of insufficient electricity and heat supply are given, such as Fig.12 As shown in the figure, as the value of electricity comfort increases, the expected value of insufficient power supply and insufficient heat supply of the system also increases, and the system reliability level becomes lower. When r decreases from 1 to 0.6, EENS e Significantly reduced, EENS h There are also small changes. This is because the proportion of flexible electric loads participating in system response continues to increase, and the flexible adjustment of load energy consumption periods has a positive effect on RIES reliability. When the electrical comfort level r<0.6, EENS e EENS h There is no obvious change, because when a system component fails, the system operation is constrained by the interconnection lines and the equipment capacity is limited and cannot meet the load demand, resulting in load reduction. Therefore, reasonable adjustment of user electricity comfort can effectively improve system reliability.

[0167] A specific embodiment of the present invention, based on the above regional integrated energy system reliability assessment method, the present invention also discloses a regional integrated energy system reliability assessment device accordingly, please refer to Fig.13 , the regional integrated energy system reliability assessment device 1300 includes a load reduction optimization model establishment module 1301 and a regional integrated energy system assessment module 1302;

[0168] The load reduction optimization model establishment module 1301 is used to establish electric load and thermal load demand response models according to load characteristics, consider electric load and thermal load demand response, take the sum of purchased energy cost, load reduction penalty cost and demand response cost as the minimum as the optimization goal, take the tie line constraint, energy conversion equipment output constraint, energy storage constraint, power balance constraint and equipment failure topology constraint as constraint conditions, and establish the RIES load reduction optimization model;

[0169] The regional integrated energy system evaluation module 1302 is used to establish the RIES reliability index. After calculating the RIES reliability index using the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model, the reliability level of the RIES is evaluated. The RIES reliability index at least includes the expected energy shortage time, the expected energy shortage and the energy supply availability.

[0170] In summary, the regional integrated energy system reliability assessment method and device provided by the present invention respectively establish an electric load demand response model and a thermal load demand response model according to load characteristics, thereby improving the system heating reliability and power supply reliability. Based on the electric load demand response model and the thermal load demand response model, a RIES load reduction optimization model is established with the minimum sum of the purchased energy cost, the load reduction penalty cost and the demand response cost as the optimization goal, and the flexible load is fully exploited to participate in the system response, which can effectively improve the RIES energy supply reliability, establish a RIES reliability index, and use the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model to calculate the RIES reliability index, and then evaluate the reliability level of RIES, thereby improving the energy supply reliability of the regional integrated energy system.

[0171] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A regional integrated energy system reliability assessment method, characterized in that: include: Establishing an electric load demand response model and a thermal load demand response model respectively, and establishing a RIES load reduction optimization model based on the electric load demand response model and the thermal load demand response model with the sum of the purchased energy cost, the load reduction penalty cost and the demand response cost being minimized as the optimization target; The RIES reliability index is established. After the RIES reliability index is calculated by using the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model, the reliability level of RIES is evaluated. The RIES reliability index at least includes the expected energy shortage time, the expected energy shortage time and the energy supply availability. The calculation formula of the expected energy shortage time is: ， ， ， ， in, Expected for power shortage time, is the duration of the Monte Carlo simulation, is the number of samplings, The system status is The electricity load reduction occurs. For the The load cuts power during the sampling period. For the insufficient time of heat energy, The system status is The heat load reduction is generated. For the Rigid heat load reduction power during sampling, For the Flexible heat load reduction power during the second sampling; The energy supply shortage expectation calculation formula is: ， ， in, Insufficient power supply for the system is expected. Insufficient heat supply for the system. is the duration of the Monte Carlo simulation, is the number of samplings, The system status is The electricity load reduction occurs. For the The load cuts power during the sampling period. For the insufficient time of heat energy, The system status is The heat load reduction is generated. For the Rigid heat load reduction power during sampling, For the Flexible heat load reduction power during the second sampling; The calculation formula for energy availability is: ， ， in, is the power supply availability, is the heat availability rate, Expected for power shortage time, Expected for insufficient heat time.

2. The regional integrated energy system reliability assessment method according to claim 1, characterized in that: The electric load demand response model is: ， ， ， in, is the total scheduling period, for The amount of flexible electrical load reduction at any given moment, for The increase in flexible electrical load at each moment, To provide financial compensation to users, is the unit subsidy coefficient of flexible electric load, is the electricity purchase price, for The change in the electric load demand response at each moment, For the comfort of electricity use, for Electric load at any time; The heat load demand response model is: ， ， ， , in, for The indoor temperature of the building at the time, for The outdoor temperature of the building at the time, for The heating power of the building at the time, is the thermal resistance of the building, is the indoor air heat capacity, is the relationship between indoor temperature and PMV value, is a variable.

3. The regional integrated energy system reliability assessment method according to claim 1, characterized in that: The calculation formula of the optimization objective is: , in, For the moment The amount of electricity purchased from the external grid, For the moment The amount of natural gas purchased from the external gas grid, is the gas purchase price, Penalty price for electricity load reduction, Penalty unit price for heat load reduction, for The amount of electricity load reduction at any given moment, for Time heat load reduction.

4. The regional integrated energy system reliability assessment method according to claim 1, characterized in that: After the RIES reliability index is calculated by using the sequential Monte Carlo simulation method in combination with the RIES load reduction optimization model, the reliability level of RIES is evaluated, including: Step 1: Input the system parameters of RIES, initialize the system parameters and component states, and set the Sequential Monte Carlo simulation time and simulation years; Step 2: Use the sequential Monte Carlo simulation method to sample and obtain the duration of equipment trouble-free operation within the study period, take the component with the shortest duration of equipment trouble-free operation as the faulty device, and obtain the trouble-free working time and the cumulative simulation time; Step 3: Obtain the repair time after the equipment failure, calculate the outage time and reduction amount of the electric and heating load during the failure period, and obtain the cumulative simulation time; Step 4: When the cumulative simulation time is greater than the number of simulation years, the RIES reliability index is calculated and the process proceeds to step 6; when the cumulative simulation time is less than or equal to the number of simulation years, the process proceeds to step 5; Step 5, when the cumulative simulation time crosses the year, calculate the RIES reliability index; when the cumulative simulation time crosses the year but does not cross the year, extract the new fault-free operation duration of the component, and return to step 2; Step 6: Output the RIES reliability index and evaluate the reliability level of RIES.

5. The regional integrated energy system reliability assessment method according to claim 4 is characterized in that: The calculation formula for the trouble-free operation duration of the equipment is: ， in, is the trouble-free operation duration, is the equipment failure rate, is a random number in the interval [0, 1].

6. The regional integrated energy system reliability assessment method according to claim 4 is characterized in that: The calculation formula for the repair time after the equipment failure is: ， in, is the trouble-free operation duration, is the equipment repair rate.

7. A regional integrated energy system reliability assessment device, characterized in that: include: A load reduction optimization model establishment module is used to establish an electric load demand response model and a thermal load demand response model respectively, and establish a RIES load reduction optimization model based on the electric load demand response model and the thermal load demand response model with the sum of the purchased energy cost, the load reduction penalty cost and the demand response cost being minimized as the optimization target; The regional integrated energy system evaluation module is used to establish the RIES reliability index. After the RIES reliability index is calculated by the sequential Monte Carlo simulation method combined with the RIES load reduction optimization model, the reliability level of RIES is evaluated. The RIES reliability index at least includes the expected energy shortage time, the expected energy shortage time and the energy supply availability. The calculation formula of the expected energy shortage time is: ， ， ， ， in, Expected for power shortage time, is the duration of the Monte Carlo simulation, is the number of samplings, The system status is The electricity load reduction occurs. For the The load cuts power during the sampling period. For the insufficient time of heat energy, The system status is The heat load reduction is generated. For the Rigid heat load reduction power during sampling, For the Flexible heat load reduction power during the second sampling; The energy supply shortage expectation calculation formula is: ， ， in, Insufficient power supply for the system is expected. Insufficient heat supply for the system. is the duration of the Monte Carlo simulation, is the number of samplings, The system status is The electricity load reduction occurs. For the The load cuts power during the sampling period. For the insufficient time of heat energy, The system status is The heat load reduction is generated. For the Rigid heat load reduction power during sampling, For the Flexible heat load reduction power during the second sampling; The calculation formula for energy availability is: ， ， in, is the power supply availability, is the heat availability rate, Expected for power shortage time, Expected for insufficient heat time.

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