Energy efficiency power plant modeling and power source planning method and system

Abstract

The application discloses a kind of energy efficiency power plant modeling and power supply planning method and system, based on multidimensional modeling system, respectively constructs the general model of energy efficiency class, can be cut class, can be transferred class and can be translated class energy efficiency power plant;Based on general model, modeling is carried out respectively, to obtain air conditioner energy efficiency power plant model and electric vehicle energy efficiency power plant model;With the minimum present value of total investment and operating cost of system in planning period as the goal, the external characteristics in air conditioner energy efficiency power plant model and electric vehicle energy efficiency power plant model are abstracted as a new type of power supply, a power supply planning-operation checking two-stage model is constructed, the output power of each type of traditional power supply construction scale and air conditioner load and electric vehicle load response power system dispatching is obtained according to the power supply planning-operation checking two-stage model, and the construction of air conditioner energy efficiency power plant model and electric vehicle energy efficiency power plant model is analyzed to realize power supply planning. The benefit analysis of energy efficiency power plant.

Description

Technical Field

[0001] This invention belongs to the field of power system power planning technology, specifically relating to a method and system for energy efficiency power plant modeling and power planning. Background Technology

[0002] In traditional power planning problems, power sources are typically considered the sole source of flexibility in the power system, with the goal of meeting user load demands. However, with the rapid development of smart grids and the increasing proportion of distributed energy sources in the grid, demand-side energy aggregation will provide the power system with abundant flexibility resources. Nevertheless, demand-side flexibility resources often suffer from limited response capacity, dispersed response times, and low dispatchability, thus limiting their potential to fully participate in power system operation and dispatch. Furthermore, the diverse types and characteristics of demand-side resources make it difficult to describe their response characteristics using a unified and accurate mathematical model, hindering the ability to uniformly describe the response of various demand resources within a single power planning mathematical model.

[0003] Therefore, adopting the demand-side resource aggregation management model of energy-efficient power plants in the field of power planning, by optimizing users' electricity consumption patterns and encouraging users to carry out energy-efficient renovations, can form a comprehensive action plan for demand-side transformation in a specific industry, region, or enterprise, effectively promoting flexible and controllable operation on the load side. The application of the energy-efficient power plant concept can, to some extent, unify users' electricity consumption behavior, enabling aggregated resources to possess relatively stable external characteristics, and thus participate in the power balance of the power system.

[0004] Based on their operating modes, energy efficiency power plants can be classified into four categories: energy efficiency-type power plants, energy efficiency-reducible power plants, energy efficiency-transferable power plants, and energy efficiency-shiftable power plants. Energy efficiency-type power plants improve energy utilization by reducing the power consumption of energy-efficient loads such as industrial production and residential buildings. Energy efficiency-reducible power plants aggregate loads of the same type and with similar parameters, allowing users to reduce their power consumption in response to load interruption commands from the grid dispatch center, with the reduced power serving as the equivalent output of the power plant. Energy efficiency-transferable power plants aggregate transferable loads, enabling them to increase power consumption during off-peak periods and decrease it during peak periods, providing the power system with the necessary peak-shaving potential. Energy efficiency-shiftable power plants aggregate transferable loads; due to their fixed load duration and adjustable start time, their external response characteristics manifest as an overall shift in the power consumption curve.

[0005] Different classifications of energy-efficient power plants can achieve preliminary aggregation of different types of demand-side resources, but applying them to the field of power planning still presents significant challenges. On the one hand, the essence of an energy-efficient power plant remains a synthesis of a series of nodal measures, not a stable power production entity; simply treating it as a power source is inappropriate. On the other hand, the benefit analysis of energy-efficient power plants in the field of power planning still requires further unified modeling of energy-efficient power plants, considering their benefits in the power system by abstracting them into a class of equivalent power sources.

[0006] Therefore, when considering demand-side resources in the field of power planning, it is necessary to aggregate various demand-side resources using the concept of energy-efficient power plants and to explore in depth the electricity consumption characteristics of demand-side resources during the response process. At the same time, in the process of making power planning decisions, it is necessary to characterize the external characteristics of energy-efficient power plants from different perspectives, to include them as a type of high-efficiency energy in the power planning decision-making process, and to comprehensively consider their benefits in power system operation and dispatch, so as to maximize the potential of demand-side flexible resources. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to provide an energy-efficient power plant modeling and power planning method and system to address the shortcomings of the prior art, and to solve the technical problem of modeling the external characteristics of demand-side resources in power planning models.

[0008] The present invention adopts the following technical solution:

[0009] A method for energy-efficient power plant modeling and power planning includes the following steps:

[0010] S1. Establish a multi-dimensional modeling system for energy-efficient power plants;

[0011] S2. Based on the multi-dimensional modeling system obtained in step S1, construct general models for energy-efficient power plants, energy-efficient power plants that can be reduced, energy-efficient power plants that can be transferred, and energy-efficient power plants that can be translated.

[0012] S3. Based on the general model obtained in step S2, model the air conditioning load of typical industrial and commercial users and the electric vehicle load of typical residential users respectively, and obtain the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model.

[0013] S4. With the goal of minimizing the present value of the total system investment and operating costs during the planning period, the external characteristics of the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model obtained in step S3 are abstracted into a new type of power source. A two-stage model of power planning and operation verification is constructed. Based on the two-stage model of power planning and operation verification, the construction scale of each type of traditional power source and the output power of air conditioning load and electric vehicle load in response to power system dispatch are obtained. The construction of the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model is analyzed to achieve power planning.

[0014] Specifically, in step S1, the response capacity, response power, economy, reliability, flexibility and environmental protection of the energy efficiency power plant are used to construct a multi-dimensional modeling system for the energy efficiency power plant.

[0015] Furthermore, the response capacity of energy-efficient power plants:

[0016]

[0017] in, s represents the response potential of the energy efficiency power plant; c represents the user controllability coefficient of the energy efficiency power plant; and a represents the user willingness coefficient of the energy efficiency power plant.

[0018] Response power of energy-efficient power plants:

[0019]

[0020] Among them, E EPP P represents the equivalent power generation of an energy-efficient power plant. t EPP The equivalent power generation of the energy-efficient power plant at time t; T is the number of time points within the dispatch cycle; The maximum response power that can be responded to within a scheduling cycle;

[0021] Economic efficiency of energy-efficient power plants:

[0022]

[0023] Among them, C EPP Compensation costs for energy-efficient power plants; c EPP The compensation price per unit of electricity generated by energy-efficient power plants;

[0024] Reliability of energy-efficient power plants:

[0025]

[0026] The flexibility of energy-efficient power plants is reflected in their response speed when participating in system dispatch, which is on the order of seconds and minutes.

[0027] Environmental friendliness of energy-efficient power plants:

[0028]

[0029] Among them, BF EPP The environmental benefits generated by energy-efficient power plants; Penalty per unit emission of pollutant i; The reduction in pollutant emissions is due to the use of energy-efficient power plants; N Em This represents the total number of pollutants.

[0030] Specifically, in step S2, the total equivalent power generation P of energy-efficient power plants is... t EPP,EF for:

[0031]

[0032] in, N represents the operating state of energy efficiency load i at time t; EF This refers to the number of energy efficiency-related loads within the power plant.

[0033] The equivalent power generation that can be reduced is:

[0034]

[0035] Among them, P t EPP,SF P represents the equivalent power generation of a portable energy-efficient power plant at time t. t EPP,SF,fore P represents the initial power consumption of a portable energy-efficient power plant at time t. t EPP,SF,after The power consumption after transfer at time t for a transferable energy-efficient power plant.

[0036] The power consumption of portable energy-efficient power plants is:

[0037]

[0038] Among them, P t EPP,SF,in P represents the input power of a portable energy-efficient power plant at time t. t EPP,SF,out The output power of a portable energy-efficient power plant at time t;

[0039] The equivalent power generation capacity that can be shifted is:

[0040]

[0041] Among them, P t EPP,TS,in P represents the power transferred into a portable energy-efficient power plant at time t. t EPP,TS,outThis represents the power output removed from a portable energy-efficient power plant at time t.

[0042] Specifically, in step S3, the relationship between the power consumption of a single air conditioner operating under different modes and the ambient temperature, energy efficiency ratio, and operating time is characterized using a thermodynamic equivalent model, resulting in a power consumption calculation model for a single air conditioner. Based on this, the power consumption mode of multiple air conditioners aggregated within the energy efficiency power plant is characterized. The upper and lower bounds of the aggregated power of the air conditioner cluster are determined according to the operating duty cycle of different air conditioners and the probability distribution of air conditioner parameters within the cluster. Combined with the unified modeling of the energy efficiency power plant, the upper and lower limits of the equivalent power generation of the air conditioner energy efficiency power plant and the corresponding external characteristic parameters are obtained.

[0043] Furthermore, the air conditioning energy efficiency power plant model includes N AR,C Taiwan refrigeration air conditioner and N AR,H Taiwanese-made heating and air conditioning system, upper limit of the aggregated power of the air conditioning system. and the lower realm P t Air,agg They are respectively:

[0044]

[0045]

[0046] Where E[X1], E[X2], E[Y1], and E[Y2] are the expected values ​​of random variables X1, X2, Y1, and Y2, respectively; The outdoor temperature in cooling / heating mode; θ C,set / θ H,set This is the air conditioner temperature setting value in cooling / heating mode; δ i N represents the temperature dead zone width of the air conditioner. AR,C N represents the number of air conditioners used for cooling; AR,H This refers to the number of heating air conditioners; This refers to the energy efficiency ratio in air conditioning cooling / heating modes. The equivalent thermal resistance in air conditioning cooling / heating mode;

[0047] The range of values ​​for equivalent power generation is:

[0048]

[0049] in, The upper limit of the power output of the air conditioning energy efficiency power plant; P t EPP,AR The equivalent power generation of the air conditioning energy efficiency power plant at time t.

[0050] Specifically, in step S3, a probability distribution model of electric vehicle travel characteristic parameters is established; the disordered charging curve of the electric vehicle cluster is obtained through Monte Carlo simulation; an operating domain model of a single electric vehicle is established, and then the off-grid and grid-connected electric behavior of the cluster electric vehicles is considered to establish the cluster operating domain of the electric vehicles; and an energy efficiency power plant model of the electric vehicle cluster is established by combining the disordered charging curve of the electric vehicle cluster and the cluster operating domain.

[0051] Furthermore, the disordered charging curve of the electric vehicle cluster is as follows:

[0052]

[0053] in, The disordered charging power of the electric vehicle cluster at time t; The disordered charging power of the electric vehicle i at time t;

[0054] The equivalent power generation capacity of an electric vehicle energy efficiency power plant is:

[0055]

[0056] Among them, P t EPP,EV The equivalent power generation of the electric vehicle energy efficiency power plant at time t; P represents the disordered charging power of the electric vehicle cluster at time t. t EV,agg,ch P represents the charging power of the electric vehicle cluster at time t. t EV,agg,dis Let be the discharge power of the electric vehicle cluster at time t;

[0057] The energy obtained by electric vehicle energy efficiency power plants in V2G mode and disordered charging mode is:

[0058]

[0059] Where, η ch / η dis The charging / discharging efficiency of electric vehicles.

[0060] Specifically, in step S4, the present value of the total system investment and operating costs during the planning period is minimized. Operating costs include fixed operating costs, fuel costs, start-up and shutdown costs, renewable energy curtailment penalties, and energy efficiency plant call-up costs. The two-stage power planning-operation verification model is constructed as follows:

[0061] minobj = cost inv +cost fix +cost fuel +cost sud +cost curt+cost EPP

[0062] Among them, cost inv This refers to the total investment cost during the planning period; cost fix The total fixed operating cost during the planning period; cost fuel The total fuel cost during the planning period; cost sud The total start-up and shutdown cost during the planning period; cost curt Penalties for curtailment of renewable energy during the planning period; cost EPP This refers to the cost of decommissioning energy-efficient power plants during the planning period.

[0063] Secondly, embodiments of the present invention provide an energy efficiency power plant modeling and power planning system, comprising:

[0064] Build modules to establish a multi-dimensional modeling system for energy efficiency power plants;

[0065] The general module, based on the multi-dimensional modeling system obtained from the building module, constructs general models for energy efficiency power plants, energy efficiency power plants that can be reduced, energy efficiency power plants that can be transferred, and energy efficiency power plants that can be translated.

[0066] The load module, based on the general model obtained from the general module, models the air conditioning load of typical industrial and commercial users and the electric vehicle load of typical residential users, respectively, to obtain the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model.

[0067] The planning module aims to minimize the present value of the total system investment and operating costs within the planning period. It abstracts the external characteristics of the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model obtained from the load module into a new type of power source. It constructs a two-stage model of power source planning and operation verification. Based on the two-stage model, it obtains the construction scale of various types of traditional power sources and the output power of air conditioning load and electric vehicle load in response to power system dispatch. It analyzes and determines the construction of air conditioning energy efficiency power plant model and electric vehicle energy efficiency power plant model to achieve power source planning.

[0068] Compared with the prior art, the present invention has at least the following beneficial effects:

[0069] An energy efficiency power plant modeling and power planning method is proposed. Based on the external characteristics of energy efficiency power plants, four general models of energy efficiency power plants are constructed to ensure that the method is applicable to the modeling of various types of energy efficiency power plants. Subsequently, a model is established based on two common types of energy efficiency power plant loads to prove the effectiveness of the general modeling method. Finally, the two specific types of energy efficiency power plants are added to the power investment decision as a new type of power source, which facilitates intuitive analysis of the utilization of energy efficiency power plants and the optimization benefits of energy efficiency power plants on the power structure.

[0070] Furthermore, starting from the six dimensions of traditional power sources—capacity, power output, flexibility, reliability, economy, and environmental friendliness—a mathematical model is constructed based on the virtual power plant's ability to reduce load demand, provide ramp-up capability, load supply capability, carbon emission reduction capability, and construction cost. This model is then used as an equivalent of a new type of power source for analysis in the power planning model.

[0071] Furthermore, based on the potential size and periodic characteristics of different demand-side resources in response, the response power is modeled to obtain the capacity and power changes of its output power during the scheduling cycle, thereby providing a more intuitive analysis of the dispatch situation of different types of energy-efficient power plants.

[0072] Furthermore, firstly, based on the first-order thermodynamic equivalent model of the air conditioner, the first-order differential equation of the indoor temperature where the air conditioner is located is derived. Substituting the upper and lower limits of the acceptable temperature for the user into the equation, the start-up and shutdown times of the air conditioner can be obtained. On this basis, the duty cycle is calculated using the start-up and shutdown times of each individual air conditioner, thus characterizing the aggregated power of the air conditioner group from a statistical perspective. Then, inequality transformation is used to perform interval processing on the logarithmic function, which is difficult to calculate, to obtain the upper and lower limits of the aggregated power of the air conditioner. After probability and statistical processing, the small variance normal distribution of the simulated value of the aggregated power of the air conditioner around the benchmark value of the aggregated power is obtained. Taking the benchmark value, the aggregated power of the air conditioner cluster is obtained. Thus, the output characteristics of the discrete individual air conditioners can be aggregated to obtain the output power characteristics of the air conditioning energy efficiency power plant with larger power values ​​and obvious economies of scale.

[0073] Furthermore, in order to make air conditioning energy efficiency power plants equivalent to conventional power sources, the difference between the benchmark value of air conditioning aggregated power and the lower bound of aggregated power is taken as the maximum technical output of the equivalent conventional power source, so that it can be directly put into operation as a conventional power source in the power planning model.

[0074] Furthermore, based on the probability density function of the daily departure and return times of electric vehicles, the average daily mileage and electricity consumption of electric vehicles can be obtained. Combined with the Monte Carlo simulation method, the statistically deterministic charge-discharge curve of a single electric vehicle can be obtained, and the operating domain can be derived. Since the individual electric vehicles in the cluster will experience step energy values ​​during grid connection and off-grid processes, the cluster's energy response value will also be limited to the sum of the step values. By analyzing the energy response pattern of the electric vehicle cluster using statistical methods, a demand response model for an electric vehicle energy efficiency power plant can be easily established. Based on the sum of the step energy of electric vehicles at each time after the cluster, the upper limit of the demand response capacity and the charging and discharging status in the energy efficiency power plant model can be obtained.

[0075] Furthermore, since the travel status of a single electric vehicle user is uncertain and the power for charging and discharging is limited, the scale effect of electric vehicle clusters and the similarity of travel patterns among different electric vehicles can be used to establish an equivalent model of electric vehicle energy efficiency power plants through statistical methods. Based on the charging and discharging time interval in the disordered charging mode of electric vehicles, electric vehicle energy efficiency power plants in V2G mode can be regarded as a type of energy storage device connected to the grid, and then an equivalent energy storage model can be constructed according to the operating domain.

[0076] Furthermore, based on the construction of two typical energy efficiency power plant models, a two-stage model of point-based planning and operation verification considering the construction of energy efficiency power plants can be established. This model can intuitively reflect the role of energy efficiency power plant construction in electricity substitution, and can also better analyze the resource allocation of air conditioning load and energy efficiency power plant load under the background of actual power planning.

[0077] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0078] In summary, this invention, starting from the broader context of power planning, proposes a method for systematically constructing energy-efficient power plant models to address the emerging issue of demand-side resource management. It also analyzes the allocation of demand-side resources in conjunction with a power planning model. First, energy-efficient power plants are categorized into four main types based on their response modes. Second, detailed modeling is performed for two specific energy-efficient power plants: air conditioning and electric vehicles. Finally, this model is combined with a two-stage power planning model to derive the benefit analysis of energy-efficient power plants.

[0079] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0080] Figure 1 This is a schematic diagram of the process of the present invention;

[0081] Figure 2 This is a schematic diagram of the energy operation area, where (a) represents the energy operation area (t) of a single electric vehicle. i,s <t i,d (a) represents the energy operating range (t) of a single electric vehicle. i,s >t i,d );

[0082] Figure 3 A comparison chart of the results of new installations;

[0083] Figure 4 A comparison chart of newly installed power generation capacity;

[0084] Figure 5 A comparison chart showing the operation status of newly installed units;

[0085] Figure 6 This is a comparison chart of changes in the power consumption of newly installed units. Detailed Implementation

[0086] This invention provides a method for modeling energy-efficient power plants and planning power sources. Starting from the response mode of a typical energy-efficient power plant, the method models the energy-efficient power plant based on the external characteristics of conventional power sources, and optimizes it in a two-stage power planning investment decision model to obtain the optimal demand-side resource scheduling strategy.

[0087] Please see Figure 1 This invention provides a modeling method for energy-efficient power plants and a power planning method. Following the modeling approach of traditional power plants, it models energy-efficient power plants from dimensions such as capacity, power output, economy, reliability, flexibility, and environmental friendliness. Based on the classification of energy-efficient power plants and the characteristics of different categories, a general model is established for each type. For two common types of energy-efficient power plants in current power systems: air conditioning loads and electric vehicle loads, this invention starts with individual load models, constructs a load aggregation model within a certain range, and correspondingly summarizes the energy-efficient power plant model for load aggregation. Finally, considering the power balance capability, peak-shaving capability, and participation cost that energy-efficient power plants can provide, a power planning model considering energy-efficient power plants is constructed. The method includes the following steps:

[0088] S1. Establish a multi-dimensional modeling system for energy efficiency power plants.

[0089] First, based on the actual operating mechanism and corresponding characteristics of demand-side resources, they are divided into the following four categories:

[0090] Energy efficiency power plants: Their operation is characterized by a series of energy-saving measures, such as installing high-efficiency equipment in industrial production, carrying out energy-saving renovations on buildings, installing energy-saving lighting systems, and using high-efficiency electrical appliances, to reduce power consumption and improve energy utilization.

[0091] Energy-efficient power plants that can reduce their own power consumption: Their response characteristics are that they can respond to load interruption commands issued by the power grid dispatching system and reduce their own power consumption, and their working time and power demand are flexible and controllable;

[0092] Portable energy-efficient power plants: While ensuring that the total electricity consumption remains unchanged within a cycle, they can realize the transfer of electricity demand over time, reducing electricity consumption during peak periods and increasing electricity consumption during off-peak periods, thus providing the peak-shaving capacity required by the power system;

[0093] Shiftable energy efficiency power plants: Electricity consumption is constrained by certain living or work processes, with a fixed load duration. The start time of operation has a certain degree of flexibility, but operation cannot be interrupted. Specifically, this is manifested in the overall shift of the power consumption curve.

[0094] The model for energy-efficient power plants in power planning is constructed from the following six dimensions: capacity, power output, economy, reliability, flexibility, and environmental friendliness. Specifically, it considers the response potential of energy-efficient power plants, the available power supply within a dispatch cycle, the dispatch cost for participating in demand response, the ability to provide response potential, the time scale of response, and the ability to reduce the overall pollutant emissions of the power planning scheme.

[0095] First, characterize the response capacity of energy-efficient power plants.

[0096] The response potential of an energy-efficient power plant is typically influenced by multiple factors, including theoretical response potential, user controllability, and user willingness. Theoretical response potential refers to the maximum theoretical response capacity of an energy-efficient power plant under a given control strategy. User controllability refers to the response capacity after considering the impact of incentive mechanisms, the presence or absence of terminal control equipment / communication channels, and the reliability of terminal control equipment / communication. User willingness refers to the achievable response capacity after considering the subjective influence of user intentions. The response potential of an energy-efficient power plant is expressed by the following formula:

[0097]

[0098] in, s represents the response potential of the energy-efficient power plant; c represents the user controllability coefficient of the energy-efficient power plant; and a represents the user willingness coefficient of the energy-efficient power plant.

[0099] Second, characterize the response power of energy-efficient power plants.

[0100] The power output of an energy-efficient power plant represents its maximum responsive electrical energy within a dispatch cycle, i.e., its maximum equivalent power generation within the dispatch cycle, expressed as:

[0101]

[0102] Among them, E EPP P represents the equivalent power generation of an energy-efficient power plant. t EPP The equivalent power generation of the energy-efficient power plant at time t; T is the number of time points within the dispatch cycle; This represents the maximum response power that can be generated within a single scheduling cycle.

[0103] Third, describe the economic efficiency of energy-efficient power plants.

[0104] The economic efficiency of an energy-efficient power plant typically refers to the operating costs of participating in demand response and load regulation. Compensation is usually provided to the power plant based on contracts or agreements with users, and the calculation method for this compensation is as follows:

[0105]

[0106] Among them, CEPP Compensation costs for energy-efficient power plants; c EPP This is the compensation price per unit of electricity generated by energy-efficient power plants.

[0107] Fourth, characterize the reliability of energy-efficient power plants.

[0108] The reliability of an energy-efficient power plant can be defined as its ability to provide response potential, typically expressed probabilistically. The response reliability of an energy-efficient power plant is influenced by multiple levels of factors, including equipment, users, and the plant cluster. Statistical analysis of historical response data from energy-efficient power plants yields the probability level of their response potential, leading to a multi-state potential model.

[0109]

[0110] Fifth, characterize the flexibility of energy-efficient power plants.

[0111] The flexibility of energy-efficient power plants is reflected in their response speed in participating in system dispatch. Typically, the response speed of energy-efficient power plants is in the range of seconds to minutes, which can usually meet the changes in load demand in the field of power planning.

[0112] Sixth, to depict the environmental friendliness of energy-efficient power plants.

[0113] The deployment of energy-efficient power plants can effectively reduce the power generation on the supply side, especially the power generation of traditional thermal power units, thereby reducing pollutant emissions. The environmental benefits of deploying energy-efficient power plants are expressed as follows:

[0114]

[0115] Among them, BF EPP The environmental benefits generated by energy-efficient power plants; Penalty per unit emission of pollutant i; The reduction in pollutant emissions is due to the use of energy-efficient power plants; N Em This represents the total number of pollutants.

[0116] S2. Classify energy efficiency power plants and construct general models for different types of energy efficiency power plants.

[0117] Based on their operating methods, energy efficiency power plants are classified into four types: energy efficiency type, reduceable type, transferable type, and relocatable type. Among them, energy efficiency type energy efficiency power plants are considered in terms of their equivalent power generation; reduceable type energy efficiency power plants are considered in terms of their response capacity and the upper limit of their response power; transferable type energy efficiency power plants are considered in terms of their upper limit of response capacity and the power balance characteristics within a day; and relocatable type energy efficiency power plants are considered in terms of the fixed duration of their response.

[0118] For energy-efficient loads, their equivalent power generation is the power difference between ordinary electrical equipment and high-efficiency energy-saving equipment providing the same function. The equivalent power generation of a single energy-efficient load is:

[0119]

[0120] in, Let i be the equivalent power generation of energy-efficient load i at time t; The power consumption at time t before energy-saving retrofitting of energy-efficiency load i; The power consumption at time t after energy-saving renovation of energy-efficient load i.

[0121] The total equivalent power generation P of energy efficiency power plants t EPP,EF for:

[0122]

[0123] in, N represents the operating state of energy efficiency load i at time t; EF This refers to the number of energy efficiency loads within the power plant.

[0124] For energy-efficient power plants with similar internal equipment parameters, considering the randomness of user electricity consumption behavior and the possibility of simultaneous operation of energy-saving equipment, equation (7) can be approximately expressed as:

[0125]

[0126] The main role of energy-efficient power plants in the power system is to permanently reduce the load value during operation, but they are not very meaningful for the optimal dispatch of the power system.

[0127] For loads with energy efficiency that can be reduced, the load power can be partially or completely reduced according to the needs of grid dispatch, thereby reducing the peak load of the power system. The power generation of power plants with energy efficiency that can be reduced is the load reduction power.

[0128] The load reduction power is constrained by the following formula:

[0129]

[0130] Among them, P t EPP,IR The power reduction value at time t for energy-efficient power plants that can reduce energy consumption. This is the upper limit for power reduction at time t of energy-efficient power plants.

[0131] The amount of electricity saved by load reduction within a day is sufficient to meet:

[0132]

[0133] in, This sets the upper limit for power reduction for energy-efficient power plants with energy-saving capacity. For energy-efficient power plants with energy-saving capacity that can be transferred, they can realize the transfer of power demand over time, as long as the total power consumption remains unchanged within the dispatch cycle.

[0134] Its equivalent power generation is expressed as:

[0135]

[0136] Among them, P t EPP,SF P represents the equivalent power generation of a portable energy-efficient power plant at time t. t EPP,SF,fore P represents the initial power consumption of a portable energy-efficient power plant at time t. t EPP,SF,after This represents the power consumption of a portable energy-efficient power plant after the transfer at time t.

[0137] The expression for the power consumption of the energy-efficient power plant after the transfer is:

[0138]

[0139] Among them, P t EPP,SF,in P represents the input power of a portable energy-efficient power plant at time t. t EPP,SF,out This represents the output power of a portable energy-efficient power plant at time t.

[0140] Therefore, we can conclude that:

[0141]

[0142] The transfer-in and transfer-out power should meet the following constraints:

[0143]

[0144]

[0145]

[0146] in, This represents the state transitioning to at time t; The state at time t represents the transition state; / P t EPP,SF These are the upper and lower limits of the transfer power.

[0147] The amount of electricity transferred in and out should be balanced, and the total amount of electricity transferred should not exceed the upper limit for electricity transfer.

[0148]

[0149] in, This is the upper limit for the transfer of electricity from energy-efficient power plants with transferable energy efficiency.

[0150] The power transfer time of an energy-efficient power plant must meet the following constraints:

[0151]

[0152] in, The earliest / latest transfer time.

[0153] For energy-efficient power plants that can be shifted, they have a fixed operating duration, but the start time of operation is flexible, enabling the overall shift of power consumption along the time axis. The expression for the equivalent power generation is:

[0154]

[0155] Among them, P t EPP,TS P represents the equivalent power generation of a portable energy-efficient power plant at time t. t EPP,TS,fore P represents the initial power consumption of a portable energy-efficient power plant at time t. t EPP,TS,after This represents the power consumption of a relocatable energy-efficient power plant after relocation at time t.

[0156] The expression for the power consumption after translation is:

[0157]

[0158] Among them, P t EPP,TS,in P represents the power transferred into a portable energy-efficient power plant at time t. t EPP,TS,out This represents the power output removed from a portable energy-efficient power plant at time t.

[0159] Therefore, the power generation expression for a translation-type energy-efficient power plant is obtained:

[0160]

[0161] Considering the continuous operating time of a portable energy-efficient power plant, the power input and output at time t will be affected by previous times. Therefore, its output power is constrained by the following equation:

[0162]

[0163]

[0164]

[0165]

[0166]

[0167] Among them, h max The operating duration of the energy efficiency power plant; T is the number of hours in a day; v t,t′ To characterize the state variables of an energy efficiency power plant transitioning from startup at time t to startup at time t′, if the energy efficiency power plant started up at time t before the transition and at time t′ after the transition, then v t,t′ =1; v represents the power at time h+1 within the operating curve of the energy efficiency power plant; t The operating state of the energy efficiency power plant at time t before the translation; The earliest / latest move-in time.

[0168] S3. Detailed modeling of two typical loads: air conditioning and electric vehicles.

[0169] S301, Aggregate air conditioning loads and model air conditioning energy efficiency power plants;

[0170] First, the relationship between the power consumption of a single air conditioner operating under different modes and ambient temperature, energy efficiency ratio, and operating time is characterized using an equivalent thermal parameters (ETP) model, thus deriving a calculation model for the power consumption of a single air conditioner. Based on this, the power consumption mode of multiple air conditioners aggregated within an energy-efficient power plant is characterized, and the upper and lower bounds of the aggregated power of the air conditioner cluster are determined according to the operating duty cycles of different air conditioners and the probability distribution of air conditioner parameters within the cluster.

[0171] The ETP of a single air conditioner in heating and cooling modes is shown in equations (27) and (28):

[0172]

[0173]

[0174] Where, θ t / Let be the indoor and outdoor temperatures at time t, in °C; C be the equivalent heat capacity of the indoor unit, in kW·h / °C; R be the outdoor temperature at time t. H / R C Q is the equivalent thermal resistance of the air conditioner, expressed in °C / kW. H / Q C Heating and cooling power, measured in W and Q. H and Q C It is proportional to the power consumption, i.e., QH =η H P H Q C =η C P C ,η H and η C The energy efficiency ratio (EER) for air conditioning heating and cooling modes; q t The variable ε represents the on / off state of the air conditioning load, with a value of 0 indicating shutdown and a value of 1 indicating startup; ε is a sufficiently small time delay, which can be equal to the simulation time step in a discrete simulation environment; θ + / θ - The upper and lower limits of the indoor temperature that the user can accept under normal air conditioning conditions are related to the set temperature of the air conditioner as follows:

[0175]

[0176] Where, θ set δ represents the temperature setpoint of the air conditioner; δ represents the temperature dead zone width of the air conditioner.

[0177] To keep the length concise, we will take the heating mode as an example for further derivation below.

[0178] For the heating mode, the air conditioner's operating time T is obtained by solving equation (27). on and shutdown duration T off They are respectively:

[0179]

[0180]

[0181] Summarized as follows:

[0182]

[0183]

[0184] The power consumption of a single air conditioner is easy to obtain through its physical model, but for energy efficiency power plants, the total power consumption of multiple air conditioners is of greater concern.

[0185] N AR The aggregate power of the air conditioners at time t is expressed as:

[0186]

[0187] Among them, P t AR,agg The aggregate power of the air conditioner at time t is only related to the air conditioner that is turned on at time t; P i ARLet be the rated power of the i-th air conditioner; This represents the operating status of the air conditioner at time t (the i-th time).

[0188] Under steady-state conditions, the average power consumption of a single air conditioner is related to the duty cycle of its on-time period within the entire operating cycle. The probability that air conditioner i is in the on-time state is... Its duty cycle can be expressed as:

[0189]

[0190] Considering the number of air conditioners N AR If the air conditioner is large enough and each unit operates independently, when the outside temperature is constant, according to the law of large numbers, N AR The aggregate power of an air conditioner can be approximately expressed as:

[0191]

[0192] Substituting equations (30) and (31) into the above equation, we get:

[0193]

[0194] Further inequality transformations yield:

[0195]

[0196] For the heating mode, substituting equations (32) and (33) into the above equation yields:

[0197]

[0198] Following the same derivation process as above, for the air conditioning load in cooling mode, we get

[0199]

[0200] The air conditioning parameters within a certain area are independent and distributed according to a given probability density function. Based on equations (39) and (40), the parameters containing N are approximately obtained. AR,C Taiwan refrigeration air conditioner and N AR,H The upper and lower bounds of the aggregated power of the Taiwanese-made heating and air conditioning cluster are as follows:

[0201]

[0202]

[0203] Where E[X1], E[X2], E[Y1], and E[Y2] are the expected values ​​of random variables X1, X2, Y1, and Y2, respectively, and the calculation formulas are as follows:

[0204]

[0205]

[0206]

[0207]

[0208] In the non-scheduled scenario, the simulated value of the aggregated power of the air conditioning cluster follows a small-variance normal distribution around a baseline value, as shown below:

[0209]

[0210] The equivalent power generation of an air-conditioning energy efficiency power plant is the difference between the baseline value and the actual value of the aggregated power, that is:

[0211]

[0212] Among them, P t EPP,AR Let t be the equivalent power generation of the air conditioning energy efficiency power plant at time t.

[0213] The range of values ​​for equivalent power generation is:

[0214]

[0215] in, The upper limit of the power output of the air conditioning energy efficiency power plant is calculated using the following formula:

[0216]

[0217] S302, Aggregate electric vehicle loads and model electric vehicle energy efficiency power plants.

[0218] First, by conducting statistical analysis on the travel patterns and energy consumption characteristics of electric vehicles, a probability distribution model of relevant parameters of electric vehicle travel characteristics is established.

[0219] Then, through Monte Carlo simulation, the disordered charging curve of the electric vehicle cluster was obtained;

[0220] Considering the vehicle-to-grid (V2G) interaction capability of electric vehicles, an operating domain model for a single electric vehicle is established.

[0221] Furthermore, considering the off-grid and grid-connected electric vehicle behavior of the cluster, a cluster operation domain for electric vehicles is established;

[0222] Finally, by integrating the disordered charging curves of the electric vehicle cluster and the V2G operating domain, an energy efficiency power plant model for electric vehicles is established.

[0223] According to surveys, the daily departure and return times of private cars generally follow a certain normal distribution:

[0224]

[0225]

[0226] in, Let μ be the daily departure time of the electric vehicle, i.e., the time it leaves the charging station. d =8.92, σ d =3.24; Let μ be the daily return trip time of the electric vehicle, i.e., the time it takes to arrive at the charging station. s =17.92, σ s =3.41.

[0227] The daily mileage of electric vehicles follows a log-normal distribution, with the following probability density:

[0228]

[0229] Where dis represents the daily driving distance of the electric vehicle, taken as μ. dis =3.6, σ dis =0.88.

[0230] Electricity consumption E per day con Calculated from mileage:

[0231]

[0232] Where, ρ 100 This represents the constant power consumption per 100 kilometers of driving.

[0233] The charging time of electric vehicles under disordered charging conditions is related to the user's daily electricity consumption and the charging power, as expressed by:

[0234]

[0235] Among them, t ch Charging time; P ch,rate η is the rated charging power; η is the charging efficiency.

[0236] With the development of power electronics and control technologies, electric vehicles under V2G control can be regarded as a kind of power storage device, participating in system peak shaving by adjusting the charging and discharging state and power.

[0237] Electric vehicles exchange electrical energy with the power grid through charging stations; the charging power P of a single electric vehicle... i EV,ch satisfy:

[0238]

[0239] in, In charging state; P ch,rate The rated charging power of the charging pile;

[0240] single electric vehicle discharge power P i EV,dis satisfy:

[0241]

[0242] in, In discharge state; P dis,rate The rated discharge power of the charging pile.

[0243] The following formula restricts electric vehicles from charging and discharging simultaneously:

[0244]

[0245] Combination Figure 2 (a) describes the energy operating range of a single electric vehicle in V2G mode, from which the calculation method for the upper and lower limits of energy of a single electric vehicle can be obtained:

[0246]

[0247]

[0248]

[0249]

[0250] in, These represent the upper and lower limits of the electrical energy of electric vehicle i; The initial electrical energy value when the electric vehicle i-trip is connected to the power grid after the trip; For users' battery energy requirements before travel; t i,s t is the time when electric vehicle i is connected to the power grid. i,d The time when the electric vehicle i leaves the power grid and begins its journey; These are the lower energy limits pushed forward from the grid connection period and the lower energy limits pushed forward from the off-grid period; η represents the upper and lower limits of the energy of electric vehicle i at time t; EV,ch / η EV,dis This refers to charging efficiency and discharging efficiency. For some electric vehicles, t may occur. i,s >t i,d The situation.

[0251] At this time, the energy operating range of a single electric vehicle in V2G mode is as follows: Figure 2 As shown in (b). The upper and lower limits of electric vehicle energy at this point can be calculated using the following equations:

[0252]

[0253]

[0254]

[0255]

[0256] The charging and discharging power of an electric vehicle is limited by the battery's electrical energy, as expressed by the following formula:

[0257]

[0258]

[0259] Among them, P i,t Let be the power of the i-th vehicle during time period t.

[0260] The summation of the energy boundaries of individual electric vehicles gives the aggregate energy boundary of the electric vehicle cluster as follows:

[0261]

[0262]

[0263] Where, N EV For the number of electric vehicle clusters; W i,t Let represent the grid connection status of vehicle i during time period t. The value is 0 when the vehicle is connected to the grid and 1 when it is disconnected from the grid. The value is determined based on the grid connection and disconnection times in the electric vehicle travel characteristics.

[0264] The i-th electric vehicle will cause a step jump in the energy value of the electric vehicle cluster during its grid-connected and off-grid periods. The energy step value is:

[0265]

[0266] Taking N EV The impact of grid-connected and off-grid electric vehicles on the energy of the aggregated model, with a total energy step value of:

[0267]

[0268] The charging and discharging power of the electric vehicle cluster meets the following constraints:

[0269]

[0270]

[0271]

[0272] Among them, P t EV,agg,ch P represents the charging power of the electric vehicle cluster at time t. t EV,agg,dis Let be the discharge power of the electric vehicle cluster at time t; The charging status of the electric vehicle fleet; This represents the discharge state of the electric vehicle cluster.

[0273] Thus, the energy constraint of the electric vehicle cluster is obtained as follows:

[0274]

[0275]

[0276] For containing N EV For a cluster of electric vehicles, the travel characteristic parameters of each electric vehicle are extracted based on the parameter distribution in the electric vehicle travel characteristics. The charging load of each individual electric vehicle is calculated using Monte Carlo simulation. Then, the N... EV The superposition of the charging loads of individual electric vehicles constitutes the disordered charging curve of an electric vehicle cluster. The calculation formula is:

[0277]

[0278] in, The disordered charging power of the electric vehicle cluster at time t; The disordered charging power of vehicle i at time t.

[0279] The equivalent power generation of an electric vehicle energy efficiency power plant is the difference between the disordered charging power and the actual charging power, that is:

[0280]

[0281] Among them, P t EPP,EV Let be the equivalent power generation of the electric vehicle energy efficiency power plant at time t.

[0282] Electric vehicle energy efficiency power plants should obtain consistent energy from the grid in both V2G and disordered charging modes, that is:

[0283]

[0284] S4. Construct a power planning model that considers energy-efficient power plants.

[0285] With the goal of minimizing the present value of the total system investment and operating costs during the planning period, a two-stage model of power planning and operation verification is constructed based on the construction and response of energy-efficient power plants.

[0286] The model aims to minimize the present value of the total system investment and operating costs during the planning period. Operating costs include fixed operating costs, fuel costs, start-up and shutdown costs, renewable energy curtailment penalties, and energy efficiency plant call-up costs. The expression is:

[0287] min obj = cost inv +cost fix +cost fuel +cost sud +cost curt +cost EPP (81)

[0288] Among them, cost inv This refers to the total investment cost during the planning period; cost fix The total fixed operating cost during the planning period; cost fuel The total fuel cost during the planning period; cost sud The total start-up and shutdown cost during the planning period; cost curt Penalties for curtailment of renewable energy during the planning period; cost EPP This refers to the cost of decommissioning energy-efficient power plants during the planning period.

[0289] Cost in investment inv The sum of investment costs for various types of power plants, where energy storage units take into account both capacity investment costs and electricity investment costs; fixed operating costs. fix This includes expenses such as insurance premiums, fixed operation and maintenance costs, personnel salaries and administrative expenses for various types of power plants; fuel costs. fuel This refers to the fuel purchase cost of thermal power units during the planning period; start-up and shutdown costs. sud This includes the sum of start-up and shutdown costs of thermal power units during the planning period; and the cost of renewable energy curtailment penalties. curt This includes penalties for water, wind, and solar power curtailment. Energy efficiency power plant deployment cost. EPP This includes compensation costs for various energy efficiency power plant dispatching processes, calculated as follows:

[0290]

[0291] in, The equivalent positive power generation of energy-efficient power plant i at time t on a typical day k in year y (only the positive power is compensated); is the compensation coefficient for energy efficiency power plant i.

[0292] The constraints in the model consider investment and construction variables, installed capacity adequacy constraints, renewable energy installed capacity ratio constraints, system carbon emission constraints, renewable energy absorption rate constraints, regional power balance constraints, cross-sectional transmission power constraints, operational constraints of various traditional power sources, and operational constraints of energy-efficient power plants. For the operational constraints of energy-efficient power plants, the specific operational constraints of various types of energy-efficient power plants are analyzed in steps S2, S3, and S4.

[0293] In another embodiment of the present invention, an energy efficiency power plant modeling and power planning system is provided. This system can be used to implement the above-mentioned energy efficiency power plant modeling and power planning method. Specifically, the energy efficiency power plant modeling and power planning system includes a construction module, a general module, a load module, and a planning module.

[0294] Among them, the construction module establishes a multi-dimensional modeling system for energy efficiency power plants;

[0295] The general module, based on the multi-dimensional modeling system obtained from the building module, constructs general models for energy efficiency power plants, energy efficiency power plants that can be reduced, energy efficiency power plants that can be transferred, and energy efficiency power plants that can be translated.

[0296] The load module, based on the general model obtained from the general module, models the air conditioning load of typical industrial and commercial users and the electric vehicle load of typical residential users, respectively, to obtain the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model.

[0297] The planning module aims to minimize the present value of the total system investment and operating costs within the planning period. It abstracts the external characteristics of the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model obtained from the load module into a new type of power source. It constructs a two-stage model of power source planning and operation verification. Based on the two-stage model, it obtains the construction scale of various types of traditional power sources and the output power of air conditioning load and electric vehicle load in response to power system dispatch. It analyzes and determines the construction of air conditioning energy efficiency power plant model and electric vehicle energy efficiency power plant model to achieve power source planning.

[0298] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of energy efficiency power plant modeling and power planning methods, including:

[0299] A multi-dimensional modeling system for energy-efficient power plants is established. Based on this system, general models for energy-efficient power plants, energy-efficient power plants that can be reduced, energy-efficient power plants that can be transferred, and energy-efficient power plants that can be moved are constructed. Based on these general models, air conditioning loads for typical industrial and commercial users and electric vehicle loads for typical residential users are modeled to obtain air conditioning energy-efficient power plant models and electric vehicle energy-efficient power plant models. With the goal of minimizing the present value of total system investment and operating costs during the planning period, the external characteristics of the air conditioning energy-efficient power plant models and electric vehicle energy-efficient power plant models are abstracted into a new type of power source. A two-stage model of power planning and operation verification is constructed. Based on this model, the construction scale of various types of traditional power sources and the output power of air conditioning load and electric vehicle load in response to power system dispatch are obtained. The construction of air conditioning energy-efficient power plant models and electric vehicle energy-efficient power plant models is analyzed to achieve power planning.

[0300] In another embodiment of the present invention, a storage medium is also provided, specifically a computer-readable storage medium (memory). This computer-readable storage medium is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0301] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the energy efficiency power plant modeling and power planning method in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor in the following steps:

[0302] A multi-dimensional modeling system for energy-efficient power plants is established. Based on this system, general models for energy-efficient power plants, energy-efficient power plants that can be reduced, energy-efficient power plants that can be transferred, and energy-efficient power plants that can be moved are constructed. Based on these general models, air conditioning loads for typical industrial and commercial users and electric vehicle loads for typical residential users are modeled to obtain air conditioning energy-efficient power plant models and electric vehicle energy-efficient power plant models. With the goal of minimizing the present value of total system investment and operating costs during the planning period, the external characteristics of the air conditioning energy-efficient power plant models and electric vehicle energy-efficient power plant models are abstracted into a new type of power source. A two-stage model of power planning and operation verification is constructed. Based on this model, the construction scale of various types of traditional power sources and the output power of air conditioning load and electric vehicle load in response to power system dispatch are obtained. The construction of air conditioning energy-efficient power plant models and electric vehicle energy-efficient power plant models is analyzed to achieve power planning.

[0303] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0304] Case Analysis

[0305] To verify the effectiveness of the method proposed in this invention, the XJTU-ROTS system was selected for calculation and analysis, and several improvements were made. To fully utilize the peak-shaving and valley-filling capabilities of energy-efficient power plants, the scale of existing renewable energy units was increased. Before planning, the system's peak load was 10421MW, and the power supply situation within the system is shown in Table 1.

[0306] Table 1. System's Existing Power Supply and Resources

[0307]

[0308] The system cross-sectional parameters are shown in Table 2.

[0309] Table 2 System cross-sectional parameters

[0310]

[0311]

[0312] The system includes energy efficiency power plants for air conditioners and electric vehicles that can be accessed. The parameters for the air conditioner energy efficiency power plant are shown in Table 3, and the parameters for the electric vehicle energy efficiency power plant are shown in Table 4.

[0313] Table 3 Air Conditioning Energy Efficiency Power Plant Parameters

[0314]

[0315] Table 4 Energy Efficiency of Electric Vehicles and Power Plant Parameters

[0316]

[0317] A five-year power planning was carried out for the above system, with an annual load growth rate of 10%, requiring that the installed capacity of new energy sources account for more than 39% by the end of the planning period.

[0318] To study the impact of considering energy-efficient power plants on power plant investment, a planning example without considering energy-efficient power plants was set up for comparison. The new power plant commissioning results for the two examples are as follows:

[0319] Table 4 Results of New Power Plant Commissioning (Considering Energy Efficiency Power Plants)

[0320]

[0321]

[0322] Table 5 Results of New Power Plant Commissioning (excluding energy efficiency power plants)

[0323]

[0324] Because energy-efficient power plants have the capacity to provide backup power, the commissioning of thermal power plants decreased by 900MW after considering them. Under the boundary condition constraint of the proportion of renewable energy installed capacity, the total installed capacity of renewable energy also decreased by 650MW accordingly. In the example without considering energy-efficient power plants, due to the lack of demand-side regulation capacity, 20MW of energy storage units were put into operation. The comparison of the new installed capacity results of the two examples is shown in the figure below. Figure 3 As shown.

[0325] Typical scenarios of energy efficiency power plants participating in peak shaving and valley filling at the end of the planning period will be selected for demonstration, such as... Figure 4 As shown in the diagram, the electric vehicle energy efficiency power plant generates electricity during the evening peak hours of 17-20 hours (equivalent power generation is positive), and the corresponding electricity is transferred to the early morning hours of 4-6 hours for replenishment (equivalent power generation is negative). Its specific operation can be seen in [the diagram / illustration]. Figure 5 .

[0326] During the 17-20 hour period, thermal power plants reach their maximum output, while wind power output is relatively low, resulting in a power deficit that needs to be supplemented by pumped storage and energy-efficient power plants. However, pumped storage is limited by its maximum generating capacity and maximum water storage capacity, making it unable to meet the entire power deficit during this period. Therefore, expensive demand-side resources need to be utilized for supplementation. Compared to air conditioning energy-efficient power plants, electric vehicle energy-efficient power plants have lower utilization costs. Therefore, from an optimal economic perspective, the system prioritizes the use of electric vehicle energy-efficient power plants, shifting the charging load from peak hours to the off-peak hours in the early morning, thus achieving peak shaving and valley filling.

[0327] The power generation variation of a typical intraday electric vehicle energy efficiency power plant is as follows: Figure 6As shown in the figure, the charging and discharging power is represented by a bar chart and plotted on the secondary axis; the power generation of the power plant is represented by a line chart and plotted on the primary axis. The main driving force for the change in power generation is the step power generation caused by the grid connection and off-grid connection of electric vehicles, which is affected by the travel patterns of electric vehicles. Throughout the entire process of electric vehicle energy efficiency power plants participating in V2G dispatch, the power generation remains within the upper and lower bounds, demonstrating the correctness of the model.

[0328] In summary, this invention provides a method and system for modeling energy-efficient power plants and planning power sources. Based on the comprehensive establishment of an energy-efficient power plant model, it is applied to an actual power planning model for case analysis. The results show that the commissioning of energy-efficient power plants can effectively reduce the construction scale of traditional flexible units, especially thermal power units. At the same time, it can also alleviate the peak-shaving pressure of the system through the function of power transfer, thereby improving the overall level of power planning schemes in terms of environmental protection and system friendliness.

Claims

1. A method for modeling energy-efficient power plants and planning power sources, characterized in that, Includes the following steps: S1. Establish a multi-dimensional modeling system for energy-efficient power plants, including their response capacity, response power, economic efficiency, reliability, flexibility, and environmental friendliness. in, The response potential of energy-efficient power plants; The theoretical response potential of energy-efficient power plants; The user controllability coefficient for energy efficiency power plants; This represents the user willingness coefficient for energy-efficient power plants. Response power of energy-efficient power plants: in, This refers to the equivalent power generation of an energy-efficient power plant. For energy efficiency power plants Equivalent power generation at any given moment; This represents the number of moments within the scheduling period. The maximum response power that can be responded to within a scheduling cycle; Economic efficiency of energy-efficient power plants: in, Compensation costs for energy-efficient power plants; The compensation price per unit of electricity generated by energy-efficient power plants; Reliability of energy-efficient power plants: The flexibility of energy-efficient power plants is reflected in their response speed when participating in system dispatch, which is on the order of seconds and minutes. Environmental friendliness of energy-efficient power plants: in, The environmental benefits generated by energy-efficient power plants; pollutants Unit emission penalties; Because of energy efficiency power plant dispatching, but rather pollutants. Reduced emissions; This represents the total number of pollutants. S2. Based on the multi-dimensional modeling system obtained in step S1, construct general models for energy-efficient power plants, energy-efficient power plants that can be reduced, energy-efficient power plants that can be transferred, and energy-efficient power plants that can be translated. S3. Based on the general model obtained in step S2, model the air conditioning load of typical industrial and commercial users and the electric vehicle load of typical residential users respectively, and obtain the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model. S4. With the objective of minimizing the present value of the total system investment and operating costs within the planning period, the external characteristics of the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model obtained in step S3 are abstracted into a new type of power source. A two-stage power planning-operation verification model is constructed. Based on the two-stage power planning-operation verification model, the construction scale of each type of traditional power source and the output power of air conditioning load and electric vehicle load in response to power system dispatch are obtained. The construction of the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model is analyzed to achieve power planning and minimize the present value of the total system investment and operating costs within the planning period. The operating costs include fixed operating costs, fuel costs, start-up and shutdown costs, renewable energy curtailment penalties, and energy efficiency power plant dispatch costs. The two-stage power planning-operation verification model is constructed as follows: in, This represents the total investment cost during the planning period. This refers to the total fixed operating costs during the planning period. This represents the total fuel cost during the planning period. The total start-up and shutdown cost during the planning period; Penalties for curtailment of renewable energy during the planning period; This refers to the cost of decommissioning energy-efficient power plants during the planning period.

2. The method for energy efficiency power plant modeling and power planning according to claim 1, characterized in that, In step S2, the total equivalent power generation of energy-efficient power plants is... for: in, Energy efficiency load exist The running status at any given moment; This refers to the number of energy efficiency-related loads within the power plant. The equivalent power generation that can be reduced is: in, For portable energy-efficient power plants Equivalent power generation at any given moment; For portable energy-efficient power plants The original power consumption at any given time; For portable energy-efficient power plants Power consumption after time shift The power consumption of portable energy-efficient power plants is: in, For portable energy-efficient power plants The power input at any given moment; For portable energy-efficient power plants Output power at any given moment; The equivalent power generation capacity that can be shifted is: in, For relocatable energy-efficient power plants The shift power at any given time; For relocatable energy-efficient power plants The power shifted out at any given moment.

3. The method for energy efficiency power plant modeling and power planning according to claim 1, characterized in that, In step S3, a thermodynamic equivalent model is used to characterize the relationship between the power consumption of a single air conditioner under different operating modes and the ambient temperature, energy efficiency ratio, and operating time, thus deriving a power consumption calculation model for a single air conditioner. Based on this, the power consumption mode of multiple air conditioners aggregated within the energy efficiency power plant is characterized. The upper and lower bounds of the aggregated power of the air conditioner cluster are determined according to the operating duty cycle of different air conditioners and the probability distribution of air conditioner parameters within the cluster. Combined with the unified modeling of the energy efficiency power plant, the upper and lower limits of the equivalent power generation of the air conditioner energy efficiency power plant and the corresponding external characteristic parameters are obtained.

4. The energy efficiency power plant modeling and power planning method according to claim 3, characterized in that, The air conditioning energy efficiency power plant model includes Taiwan refrigeration air conditioner and Taiwanese-made heating and air conditioning system, upper limit of the aggregated power of the air conditioning system. and the lower realm They are respectively: in, , , , Random variables , , , The expected value of the mathematical expression; This refers to the outdoor temperature in cooling / heating mode. This is the air conditioner temperature setting value in cooling / heating mode; The temperature dead zone width of the air conditioner; This refers to the number of air conditioners used for cooling. This refers to the number of heating air conditioners; This refers to the energy efficiency ratio in air conditioning cooling / heating modes. The equivalent thermal resistance in air conditioning cooling / heating mode; The range of values ​​for equivalent power generation is: in, The upper limit of the output of the air conditioning energy efficiency power plant; For air conditioning energy efficiency power plants Equivalent power generation at any given time.

5. The method for energy efficiency power plant modeling and power planning according to claim 1, characterized in that, In step S3, a probability distribution model of electric vehicle travel characteristic parameters is established; the disordered charging curve of the electric vehicle cluster is obtained through Monte Carlo simulation; an operating domain model of a single electric vehicle is established, and then the off-grid and grid-connected electric behavior of the cluster electric vehicles is considered to establish the cluster operating domain of the electric vehicles; and an energy efficiency power plant model of the electric vehicle cluster is established by combining the disordered charging curve of the electric vehicle cluster and the cluster operating domain.

6. The method for energy efficiency power plant modeling and power planning according to claim 5, characterized in that, The disordered charging curve of the electric vehicle cluster is as follows: in, For electric vehicle clusters Disordered charging power at any given moment; For electric vehicles exist Disordered charging power at any given moment; The equivalent power generation capacity of an electric vehicle energy efficiency power plant is: in, For electric vehicle energy efficiency power plants Equivalent power generation at any given moment; For electric vehicle clusters Disordered charging power at any given moment; For electric vehicle clusters The charging power at any given time; For electric vehicle clusters Discharge power at any given moment; The energy obtained by electric vehicle energy efficiency power plants in V2G mode and disordered charging mode is: in, The charging / discharging efficiency of electric vehicles.

7. A power plant modeling and power planning system for energy efficiency, characterized in that, include: The system constructs modules to establish a multi-dimensional modeling system for energy-efficient power plants, encompassing their response capacity, response power, economic efficiency, reliability, flexibility, and environmental friendliness. The response capacity of an energy-efficient power plant is also included. in, The response potential of energy-efficient power plants; The theoretical response potential of energy-efficient power plants; The user controllability coefficient for energy efficiency power plants; This represents the user willingness coefficient for energy-efficient power plants. Response power of energy-efficient power plants: in, This refers to the equivalent power generation of an energy-efficient power plant. For energy efficiency power plants Equivalent power generation at any given moment; This represents the number of moments within the scheduling period. The maximum response power that can be responded to within a scheduling cycle; Economic efficiency of energy-efficient power plants: in, Compensation costs for energy-efficient power plants; The compensation price per unit of electricity generated by energy-efficient power plants; Reliability of energy-efficient power plants: The flexibility of energy-efficient power plants is reflected in their response speed when participating in system dispatch, which is on the order of seconds and minutes. Environmental friendliness of energy-efficient power plants: in, The environmental benefits generated by energy-efficient power plants; pollutants Unit emission penalties; Because of energy efficiency power plant dispatching, but rather pollutants. Reduced emissions; This represents the total number of pollutants. The general module, based on the multi-dimensional modeling system obtained from the building module, constructs general models for energy efficiency power plants, energy efficiency power plants that can be reduced, energy efficiency power plants that can be transferred, and energy efficiency power plants that can be translated. The load module, based on the general model obtained from the general module, models the air conditioning load of typical industrial and commercial users and the electric vehicle load of typical residential users, respectively, to obtain the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model. The planning module aims to minimize the present value of total system investment and operating costs within the planning period. It abstracts the external characteristics of the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model obtained from the load module into a new type of power source. A two-stage power planning-operation verification model is constructed. Based on this model, the construction scale of various types of traditional power sources and the output power of air conditioning load and electric vehicle load in response to power system dispatch are derived. The construction of the air conditioning energy efficiency power plant model and the electric vehicle energy efficiency power plant model is analyzed to achieve power planning, minimizing the present value of total system investment and operating costs within the planning period. Operating costs include fixed operating costs, fuel costs, start-up and shutdown costs, renewable energy curtailment penalties, and energy efficiency power plant dispatch costs. The two-stage power planning-operation verification model is constructed as follows: in, This represents the total investment cost during the planning period. This refers to the total fixed operating costs during the planning period. This represents the total fuel cost during the planning period. The total start-up and shutdown cost during the planning period; Penalties for curtailment of renewable energy during the planning period; This refers to the cost of decommissioning energy-efficient power plants during the planning period.

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