Virtual power plant control method based on multi-element load aggregation

Abstract

The invention provides a virtual power plant control method based on multi-element load aggregation, belongs to the field of virtual power plant control, solves the technical problem of virtual power plant control, and provides a virtual power plant control method based on multi-element load aggregation according to the scheme. Constructing a characteristic model of the virtual power plant; according to the response characteristics of the reducible load, the transferable load and the adjustable load, comprehensive demand response resources of the virtual power plant are determined; according to electricity, heat and gas, the quantity of various energy sources responded by the virtual power plant is determined, and a control model is constructed; and controlling the virtual power plant according to the constructed control model. According to the method, the comprehensive utilization rate of flexible resources such as distributed energy resources, controllable loads and electric vehicles can be improved, and the absorption problem of renewable energy sources can be relieved.

Description

Technical Field

[0001] The present invention relates to the field of virtual power plant control, and in particular to a virtual power plant control method based on multi-load aggregation. Background Art

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The descriptions herein may include concepts that may be explored, but not necessarily concepts that have been previously thought of or explored. Therefore, unless otherwise noted herein, the content described in this section is not prior art with respect to the specification and claims of this application, and is not admitted to be prior art by inclusion in this section.

[0003] With the continuous construction of smart grids and the vigorous development of energy Internet technology, the participation of renewable energy and demand-side resources in power system operation planning has become the mainstream trend in the development of the power industry.

[0004] In order to fully tap the potential of decentralized energy resources, decentralized and diverse renewable energy units, energy storage systems (ESS) and user loads are gathered and integrated into a "virtual power plant". The concept of virtual power plant breaks the traditional concept of physical power plants and the boundaries between the power generation side and the power consumption side. By participating in the coordinated optimization of the power system, it promotes the consumption of renewable energy, enhances the reliability of power grid power supply, and achieves energy conservation and emission reduction.

[0005] Virtual power plant is an energy collaborative management system that uses advanced information and communication technologies and software systems to achieve the aggregation and coordinated optimization of multiple energy resources such as renewable energy generation, ESS, and controllable loads, so as to participate in the power market and power grid operation as a "special power plant". Virtual power plants make full use of advanced technical means such as network communication, intelligent measurement, data mining, intelligent decision-making, and information security to monitor and analyze the operation of the power grid.

[0006] Virtual power plants greatly reduce environmental pollution by utilizing renewable energy and energy-saving technologies, and build a clean and sustainable power energy network with high efficiency, coordination and interactivity. As an important technical solution for distributed resource management, virtual power plants (VPPs) can realize flexible control of a large number of distributed energy sources. Through coordinated control of grid dispatching and distributed energy output, they can not only ensure the safe and stable operation of the grid but also promote the participation of distributed resources in the energy market. It is a feasible way for the energy Internet to achieve interactivity and intelligence on the energy user side.

[0007] However, the interactive relationship between multiple types of adjustable resources in virtual power plants under the aggregation of multiple loads is complex, the prediction accuracy of distributed energy output and multiple loads is low, and the spot electricity price fluctuates greatly. These factors seriously restrict the improvement of the supply and demand coordination capabilities of virtual power plants, pose a potential threat to the safe and stable operation of virtual power plants, and result in low calculation efficiency of virtual power plant reliability assessment.

[0008] Therefore, how to effectively control the virtual power plant is a technical problem that needs to be solved. Summary of the invention

[0009] In order to solve the technical problems of controlling virtual power plants in the prior art, an object of the present invention is to provide a virtual power plant control method based on multi-load aggregation.

[0010] To solve the above technical problems, in a first aspect, according to some embodiments, the present invention provides a virtual power plant control method based on multi-load aggregation, comprising:

[0011] Construct a characteristic model of a virtual power plant based on the existing wind power generation system / photovoltaic power generation system;

[0012] Determining the comprehensive demand response resources of the virtual power plant according to the response characteristics of the curtailable load, the transferable load, and the adjustable load;

[0013] According to electricity, heat and gas, the quantities of various energy sources to which the virtual power plant responds are determined and a control model is constructed, and the parameters of the electricity, heat and gas are determined to include: line constraints, load constraints of the integrated demand response resources, energy network constraints, energy coupling equipment and energy storage constraints;

[0014] The virtual power plant is controlled according to the constructed control model.

[0015] In some embodiments, the characteristic model of the virtual power plant is constructed based on the existing wind power generation system / photovoltaic power generation system, specifically including:

[0016] The wind power generation system has a wind power output power P at time t. wpp,t It can be characterized as a function of intermittent wind speed, expressed as

[0017] Formula 1:

[0018]

[0019] Among them, v t is the real-time wind speed, v in is the cut-in wind speed, v out is the cut-out wind speed, v rated is the rated wind speed, P ratedis the rated power of the wind turbine; the natural wind v of the wind power output follows the Weibull distribution, and its probability density function f w (v) Using formula 2:

[0020]

[0021] where φ is the shape parameter, is a scale parameter; and / or,

[0022] The power of the photovoltaic power generation system at each moment is expressed as P PV,t , through the power conversion function, P PV,t The solar radiation θ at that moment t It is linearly related and is expressed by formula 3:

[0023] P PV,t =η PV S PV θ t (3)

[0024] Among them, η PV is the energy conversion efficiency, and S PV is the total area of ​​PV panels;

[0025] Solar irradiance is characterized by a Beta distribution f B (θ), expressed using Formula 4:

[0026]

[0027] Where Γ is the Gamma function, ξ and ψ are the parameters of the Beta distribution.

[0028] In some embodiments, the method further includes energy storage device state characteristics, specifically including:

[0029] X refers to energy storage devices such as electricity storage and heat storage, and its state characteristics are characterized by SoC, which is expressed as Formula 5:

[0030]

[0031] Among them, SoC X,t is the energy storage state of the energy storage device during time period t, They are charging power and charging efficiency respectively; are discharge power and discharge efficiency respectively;

[0032] The output power of the energy storage device is expressed as Formula 6:

[0033]

[0034] in, is a 0-1 variable;

[0035] The electric heat pump consumes electrical energy to provide heat energy to the end user. Its input-output characteristic is shown in Formula 7:

[0036]

[0037] Among them, COP is the heating coefficient of the electric heat pump, P HP,t Input power for the electric heat pump, Q HP,t It is the heating power of the electric heat pump.

[0038] In some embodiments, determining the comprehensive demand response resources of the virtual power plant according to the response characteristics of the curtailable load, the transferable load, and the adjustable load includes:

[0039] The response characteristic of the curtailable load is expressed as shown in Formula 8:

[0040]

[0041] Among them, S re is the translation load user set; β i represents the maximum reduction ratio allowed for the i-th reducible user;

[0042] The response characteristic of the transferable load user is shown in Formula 9:

[0043]

[0044] Among them, S trans User collection for translation load; and They represent the upper and lower limits of the allowable power of the i-th transferable load respectively;

[0045] The transferable load requires that the total amount of load remains unchanged within a certain period of time, subject to the constraints of formula 10, as shown below:

[0046]

[0047] The adjustable load (SL) response characteristic is expressed as shown in the following formula 11:

[0048]

[0049] Among them, S shift A collection of adjustable load users; and are the adjustable load values ​​moved in and removed during period t, respectively;

[0050]

[0051] Among them, x i,m,t is a 0-1 variable, x i,m,t =1 means that the ith adjustable load has a load shifted from period m to period t, a 0-1 variable; is the load value of the i-th adjustable load at the working period of t=1: is the load value of the i-th adjustable load in the period t=l+1;

[0052] Considering the load adjustment time margin, the constraints are:

[0053] x i,t,t′ =0|tt|≥d i (13)

[0054] Among them, d i is the adjustment time margin of the i-th adjustable load.

[0055] In some embodiments, determining the quantity of various energy sources that the virtual power plant responds to and building a model based on electricity, heat, and gas specifically includes:

[0056] In the comprehensive demand response transaction, the virtual power plant needs to determine the quantity of various energy sources it responds to based on the electricity price, heat price and gas price released by the dispatch center to maximize the operating benefits of the virtual power plant. The control model is established as shown in Formula 14:

[0057]

[0058] Among them, E W,t , H W,t , G W,t They represent the electricity, heat and gas purchased by the virtual power plant in the external market at time t, which can be directly or after being converted into certain energy forms and then distributed to users. L,E,t , L,H,t , L,G,t Represents the predetermined price of electricity, heat and gas respectively. L,t , H L,t , G L,t They represent the amount of electricity, heat and gas traded between the virtual power plant and users in the internal market at time t, respectively, W,E,t , W,H,t , W,G,t Respectively represent the current market transaction prices of electricity, heat and gas.

[0059] In some embodiments, the line constraint satisfies the constraint shown in Formula 15:

[0060]

[0061] Among them, E W,min , H W,min, G W,min They represent the lower limits of the transmission power of electricity, heat and gas in the virtual power plant, respectively. Wmax , H Wmax , G Wmax They respectively represent the lower limits of transmission power of electricity, heat and gas in the virtual power plant.

[0062] In some embodiments, the load constraint of the integrated demand response resource satisfies the constraint shown in Formula 16:

[0063]

[0064] Among them, E L,t , H L,t , G L,t They represent the total load of electricity, heat and gas of the virtual power plant at time t, E L,0,t , H L,0,t , G L,0,t They represent the uncontrollable loads of electricity, heat and gas of the virtual power plant at time t, respectively. L,dr,t , H L,dr,t , G L,dr,t They represent the controllable loads of electricity, heat and gas of the virtual power plant at time t respectively;

[0065] The controllable loads include: load constraints that can be translated, load constraints that can be reduced, and load constraints that can be converted;

[0066] The shiftable load constraint refers to adjusting the time period of user energy consumption in the comprehensive demand response without changing the total energy consumption, which is in accordance with Formula 17:

[0067]

[0068] Among them, D shift+,n,t , D shfft-,n,t They represent the load added and reduced by the virtual power plant in period t, D shift+,n,max , D shift-,n,max They represent the maximum value of load increase and load reduction of the virtual power plant in period t, D shift,n,min represents the minimum value of the virtual power plant to increase and reduce load during period t

[0069] The reducible load constraint means that in the comprehensive demand response, the user can reduce the use of energy by shutting down a certain amount of energy in a specific time period. The reducible load constraint satisfies the formula shown in Formula 18:

[0070]

[0071] Among them, D cut,n,t represents the load that can be reduced by the virtual power plant in period t, D cut,n,min , D cut,n,maxRespectively represent the lower and upper limits of its value;

[0072] The convertible load constraint means that in the comprehensive demand response, the virtual power plant converts the energy form to flexibly meet the energy demand of the user, and the conversion complies with formula 19, as shown below:

[0073]

[0074] Among them, D E,conv,n,t It represents the convertible electric load of the virtual power plant in period t, and its upper and lower limits are D E,conv,n,max and D E,conv,n,min , D H ,conv,n,l is the heat load after conversion, and the conversion efficiency is γ n,t .

[0075] In some embodiments, the energy network constraints specifically include power network constraints and natural gas network constraints;

[0076] The power system in the virtual power plant satisfies the power network constraints in the following formulas 20, 21, 22, 22, and 23, as shown below:

[0077]

[0078]

[0079]

[0080]

[0081] Among them, P w,t and Q w,t are the active power and reactive power injected into node w during period t, P wz,t and Q wz,t They represent the active power and reactive power from node w to node z during period t, respectively. wz,t represents the current from node w to node z during period t, v w,t represents the voltage at node w, They represent the collection of lines and nodes in the power network respectively;

[0082] The natural gas system includes gas source, compressor, natural gas pipeline and gas load. The Weymouth equation is used to express the relationship between the two. The flow rate and pressure are subject to certain physical constraints. The gas source constraints are shown in formulas 24, 25 and 26:

[0083]

[0084]

[0085]

[0086] Among them, f p,t represents the natural gas flow rate of natural gas pipeline p during period t, f p,max and f p,min are the upper and lower limits of its value, π n,max and π n,min are the upper and lower limits of its value respectively. and Respectively represent the collection of pipelines and nodes of the natural gas system; where represents the natural gas pipeline parameters, whose values ​​depend on the physical characteristics of the pipeline, such as length, diameter and friction coefficient. Since the gas pressure will decay with the increase of transmission distance, a compressor is needed to ensure that the gas pressure is within the normal range of variation;

[0087] A thermal system refers to a system that uses water or steam as a heat transfer medium and realizes district heating by circulating in a heat supply network and a heat recovery network. The temperature in the thermal system is affected by the heat source, the medium, and the load. The amount of heat that the heat source needs to generate depends on the temperature difference between the inlet and outlet of the pipeline, as shown in Formulas 27 and 28.

[0088]

[0089]

[0090] in, represents the heat transfer medium flow rate of pipe j connected to the heat source during period t, and are the temperatures of the nodes in the heating network and the heat recovery network, and for The upper and lower limits of the value, and are the collections of pipes and nodes in the heating network respectively;

[0091] The heat in the medium is transferred to the end user through the heat exchange equipment, and the waste heat is recovered through the heat recovery network; the heat supplied by the heat exchange equipment must meet the needs of the end user, as shown in formulas 29 and 20:

[0092]

[0093]

[0094] Among them, cm j,t represents the heat transfer medium flow rate of heat exchange device j in time period t, and for The upper and lower limits of the value, and are the collections of pipes and nodes in the regenerative network respectively

[0095] In some embodiments, the energy coupling device and energy storage constraints, specifically, the energy coupling includes electricity, heat, and gas, which are coupled through an energy hub, and the energy storage system realizes load shifting by formulating a charging and discharging plan;

[0096] The energy balance constraint in the energy hub, the heat storage tank operation constraint, and the battery operation constraint are shown in the following formulas 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, and 42:

[0097]

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109] Among them, E out,t , H out,t and G out,t Respectively represent the electrical, thermal and gas output power of the energy coupling equipment, E in,t , H in,t and G in,t They represent the electrical, thermal and gas input powers of the energy coupling equipment respectively, A is the correlation matrix of each type of energy, E c,t and E dc,t Respectively represent the charging and discharging power of the energy storage device, H c,t and H dc,t Respectively represent the charging and discharging power of the heat storage equipment, G c,t and G dc,tThey represent the charging and discharging power of the gas storage equipment respectively. γ represents the conversion efficiency between various types of energy, ζ E , H Represent the charging and discharging efficiency of electrical energy storage and thermal energy storage devices respectively.

[0110] In a second aspect, the present invention further provides a virtual power plant control device based on multi-load aggregation, comprising:

[0111] A construction module is used to construct a characteristic model of a virtual power plant based on an existing wind power generation system / photovoltaic power generation system; it is also used to determine the comprehensive demand response resources of the virtual power plant based on the response characteristics of the curtailable load, the transferable load, and the adjustable load; it is also used to determine the quantity of various energy sources that the virtual power plant responds to and construct a model based on electricity, heat, and gas, and determine the parameters of the electricity, heat, and gas, including: line constraints, load constraints of the comprehensive demand response resources, energy network constraints, energy coupling equipment, and energy storage constraints;

[0112] A control module is used to control the virtual power plant according to the constructed control model.

[0113] The above technical scheme of the present invention has at least the following beneficial technical effects: the present invention uses the multi-load aggregation virtual power plant technology, and the results of the present invention effectively manage and regulate a large number of flexible resources, energy conversion resources, and multi-load resources, support the safe and economic operation of a high proportion of renewable energy systems, and promote the low-carbon transformation of energy and power systems. At the same time, with the advancement of energy and power reform and comprehensive marketization, it is necessary to innovate business models for energy end users and fully tap the value and benefits created by distributed energy for power grids and users in the future implementation of the national energy strategy. Therefore, the present invention selects multi-load coupled virtual power plants as the object and conducts a systematic study on their operation optimization in the energy and power market. The results of the present invention will help to improve the comprehensive utilization rate of distributed energy resources, controllable loads, electric vehicles and other flexible resources and alleviate the problem of renewable energy absorption, effectively stimulate the market participation of virtual power plants, improve the operating efficiency of energy and power systems and virtual power plants, and provide scientific support for the vigorous development and construction of virtual power plant projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0114] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the conventional technology, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0115] Figure 1It is a flow chart of a virtual power plant control method based on multi-load aggregation provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0116] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0117] Virtual power plants are different from traditional thermal / gas power plants. Their internal power sources contain strong uncertainties, especially wind power and photovoltaic power sources, which have low prediction accuracy for output power. For some virtual power plants that include electric vehicles and active loads, there are uncontrollable factors in the charging and discharging management of electric vehicles and the management of load-side demand, and there is a strong spatial and temporal coupling between these uncertainties, which makes it very easy for virtual power plants to have power deviations and economic losses when executing power generation plans.

[0118] To solve the above problems, an embodiment of the present invention provides a virtual power plant control method based on multi-load aggregation, such as Figure 1 As shown, including:

[0119] S101: construct a characteristic model of a virtual power plant based on an existing wind power generation system / photovoltaic power generation system;

[0120] S102: Determine the comprehensive demand response resources of the virtual power plant according to the response characteristics of the curtailable load, the transferable load, and the adjustable load;

[0121] S103: According to electricity, heat and gas, the quantities of various energy sources to which the virtual power plant responds are determined and a control model is constructed, and the parameters of the electricity, heat and gas are determined to include: line constraints, load constraints of the integrated demand response resources, energy network constraints, energy coupling equipment and energy storage constraints;

[0122] S104: Control the virtual power plant according to the constructed control model.

[0123] The details are described below.

[0124] The virtual power plant ensures smooth data communication transmission from the physical layer, data link layer and other levels through information exchange between the dispatching control center and each unit within the jurisdiction, monitors the status of each power generation unit within the jurisdiction in real time, and remotely optimizes and manages each power generation unit within the jurisdiction online. Combined with historical meteorological data and related forecast information, the output power of each renewable energy power generation unit within the jurisdiction is predicted, as well as the power consumption units within the jurisdiction, and the change pattern of load under the influence of various factors is analyzed. In order to build a complete historical database, provide assistance for the control center to predict output and dispatch optimization, and collect, store and process the operating data of each unit within the jurisdiction in real time, such as the output and operating efficiency of the power generation unit, and the law of change of the power consumption unit over time. Establish models such as the operating cost, power generation income and pollution emissions of the virtual power plant, formulate power generation plans through optimized decisions, and sign transaction contracts.

[0125] Wind energy has been developed on a large scale over the years. In the long run, the production capacity of wind power plants (WPP) can already compete with traditional energy. Wind power generation uses the torque generated by the wind acting on the impeller to convert wind energy into mechanical energy, which is then transmitted to the wind turbine through the transmission system and converted into electrical energy. The wind turbine starts to work when the wind speed just reaches the cut-in wind speed, and the wind turbine blades just start to rotate. Wind power will continue to increase with the increase of wind speed. When the wind speed reaches the rated wind speed, if the wind speed continues to increase, the power generation will no longer increase because it reaches the rated power. When the wind speed reaches the cut-out wind speed, the wind turbine gradually stops rotating and no longer generates electricity.

[0126] When the installed capacity is determined, the maximum wind power output at each moment is determined by the actual conditions such as weather and environment. wpp,t It can be represented as a function of intermittent wind speed,

[0127]

[0128] Among them, v t is the real-time wind speed, v in is the cut-in wind speed, v out is the cut-out wind speed, v rated is the rated wind speed, P rated is the rated power of the wind turbine. The uncertainty of wind power output is caused by the uncertainty of wind speed. The natural wind v usually follows the Weibull distribution, and its probability density function f w (v) is:

[0129]

[0130] where φ is the shape parameter, is the scale parameter.

[0131] Photovoltaic power generation has the characteristics of no noise, large total energy, no pollution, no restrictions on resource distribution areas, and can generate electricity on site. Therefore, actively exploring and promoting solar energy is an effective measure to solve the current energy crisis and achieve sustainable development. Photovoltaic power generation is based on the photovoltaic effect of semiconductor interfaces, which directly converts light energy into electrical energy.

[0132] The power of a photovoltaic station (PV) at each moment can be expressed as P PV,t . Through the power conversion function, P PV,t The solar radiation θ at that time t Linear correlation:

[0133] P PV,t =η PV S PV θ t (3)

[0134] Among them, η PV is the energy conversion efficiency, and S PV is the total area of ​​photovoltaic panels.

[0135] The uncertainty of photovoltaic power generation is directly related to the intensity of solar irradiation.

[0136] Solar irradiance is usually characterized as a Beta distribution f B (θ):

[0137]

[0138] Where Γ is the Gamma function, ξ and ψ are the parameters of the Beta distribution.

[0139] To balance the fluctuations of uncontrollable units, virtual power plants are usually equipped with some battery energy systems (BES). When the virtual power plant has excess electricity, the battery energy system stores the excess electricity; when the virtual power plant is under-supplied, it releases the electricity. To increase the flexibility of the cogeneration virtual power plant, a thermal energy system (TES) is introduced on top of the traditional virtual power plant architecture.

[0140] Due to the similar characteristics of power storage devices and heat storage devices, X is used to refer to energy storage devices such as power storage and heat storage. Its state characteristics are characterized by SoC, which can be expressed as:

[0141]

[0142] Among them, SoC X,t is the energy storage state of ESS (energy storage device) during period t, They are charging power and charging efficiency respectively. are discharge power and discharge efficiency respectively. Since ESS cannot charge and discharge at the same time, the output power of ESS is:

[0143]

[0144] in, It is a 0-1 variable.

[0145] The electric heat pump consists of a condenser (heat exchanger), a compressor, an evaporator and a throttle valve. When working, the compressor is driven by electric energy to operate, so that low-temperature water absorbs a large amount of heat energy from the low-temperature environment and releases heat to the high-temperature environment. It has the characteristics of fast switching, virtual energy storage, and a large load ratio, thereby reducing the waste of primary energy and achieving green and low-carbon.

[0146] The electric heat pump consumes electrical energy to provide heat energy to the end user. Its input-output characteristic can be expressed as:

[0147]

[0148] Among them, COP is the heating coefficient of the electric heat pump, P HP,t Input power for the electric heat pump, Q HP,t It is the heating power of the electric heat pump.

[0149] The demand response characteristics of the virtual power plant are manifested as virtual power increase and decrease capabilities similar to those of traditional power plants. The difference between the actual power of the VPP (virtual power plant) and the baseline power is the response quantity of the VPP, which can be regarded as the "product" of the VPP participating in market transactions.

[0150] The response capability of VPP comes from internal interactive resources. Through comprehensive demand response, users adjust the power consumption plan of terminal equipment according to the adjustment instructions assigned by the VPP control center, and use interruptible, transferable and adjustable loads to change the energy load curve. In addition, the control center also has information on the energy supply side, energy conversion equipment and energy users, and can adjust energy supply and energy demand in a timely manner according to market operation requirements. In actual response, affected by the user's willingness to respond, the actual response load provided by some users has a certain degree of uncertainty, which makes the combined gas-electric VPP have a profit risk.

[0151] Taking into account the different technical characteristics of user terminal equipment, the comprehensive demand response resources are divided into three categories: reducible load (RL), transferable load (TL) and shiftable load (SL), and a resource response characteristic model is established, as described below:

[0152] (1) Reducible load (RL): Under various energy prices or incentive-based demand response, users send requests to end users through the virtual power plant control center to reduce or interrupt loads. Users can provide response loads to the gas-fired VPP by reducing or interrupting loads, effectively promoting peak shaving and valley filling during peak energy consumption periods. Common interruptible loads include temperature control loads, lighting loads, and distributed power sources on the power supply side. After the user-side reducible load responds, the purchased electricity volume decreases, which is regarded as providing a negative response power volume; the reducible load on the power supply side reduces the user's power generation, and after being equivalent to the user side, the provided positive response power volume. The response characteristics of the reducible load are:

[0153]

[0154] Among them, S re is the translation load user set; β i It represents the maximum reduction ratio allowed for the i-th reducible user.

[0155] (2) Transferable load (TL): Within a certain period of time, various types of loads are transferred to other periods according to energy demand, and the total amount remains unchanged within the entire scheduling cycle T. Among them, for industrial users, without affecting the production plan, part of the energy load can be transferred to another period to effectively achieve the effect of peak energy avoidance. For residential users, when using electricity and gas energy equipment, the use time is adjusted to transfer the load. For commercial users, due to the characteristics of the industry, except for ice storage air conditioners, electric vehicle battery replacement stations and other equipment, load transfer is rarely carried out. Since it is not constrained by the continuity of the energy consumption process, the response characteristics of transferable load users are more flexible, and the response characteristics are:

[0156]

[0157] Among them, S trans User collection for translation load; and They represent the upper and lower limits of the allowable power of the i-th transferable load respectively.

[0158] Transferable loads require that the total amount of load remains constant within a certain period of time, subject to the following constraints:

[0159]

[0160] (3) Adjustable load (SL): load demand time or power size can be changed according to plan. It is different from interruptible load. This type of load mainly includes air conditioning and moderation. The response characteristics of this type of load are:

[0161]

[0162] Among them, S shiftA collection of adjustable load users; and are the adjustable load values ​​moved in and removed during period t respectively.

[0163]

[0164] Among them, x i,m,t is a 0-1 variable, x i,m,t =1 means that the ith adjustable load has a load shifted from period m to period t, a 0-1 variable; is the load value of the i-th adjustable load at the working period of t=1: is the load value of the i-th adjustable load in the period t=l+1.

[0165] Considering the load adjustment time margin, the constraints are:

[0166] x i,t,t′ =0|tt|≥d i (13)

[0167] Among them, d i is the adjustment time margin of the i-th adjustable load.

[0168] 1.2 Virtual Power Plant Optimization Control Method

[0169] In the comprehensive demand response transaction, the virtual power plant needs to determine the amount of various energy sources it responds to based on the electricity price, heat price and gas price released by the dispatch center to maximize the operating benefits of the virtual power plant. The model is shown in the following formula:

[0170]

[0171] Among them, E W,t , H W,t , G W,t They represent the electricity, heat and gas purchased by the virtual power plant in the external market at time t, which can be directly or after being converted into certain energy forms and then distributed to users. L,E,t , L,H,t , L,G,t Respectively represent the transaction price. L,t , H L,t , G L,t They represent the amount of electricity, heat and gas traded between the virtual power plant and users in the internal market at time t, respectively, W,E,t , W,H,t , W,G,t Respectively represent the transaction price.

[0172] (1) Line constraints

[0173] The amount of energy purchased by the virtual power plant needs to meet the energy needs of users on the one hand, and the physical constraints of the energy network on the other hand. For example, the purchased electricity cannot exceed the maximum transmission capacity of the transmission line, so the following constraints must be met:

[0174]

[0175] Among them, E W,min , H W,min , G W,min They represent the lower limits of the transmission power of electricity, heat and gas in the virtual power plant, respectively. Wmax , H Wmax , G Wmax They respectively represent the lower limits of transmission power of electricity, heat and gas in the virtual power plant.

[0176] (2) Comprehensive demand response load constraints

[0177] Virtual power plants can call on users' controllable loads by shedding loads, and some uncontrollable loads need to be met at all times. Various types of energy loads must meet the following constraints:

[0178]

[0179] Among them, E L,t , H L,t , G L,t They represent the total load of electricity, heat and gas of the virtual power plant at time t, E L,0,t , H L,0,t , G L,0,t They represent the uncontrollable loads of electricity, heat and gas of the virtual power plant at time t, respectively. L,dr,t , H L,dr,t , G L,dr,t They represent the controllable loads of electricity, heat and gas of the virtual power plant at time t respectively.

[0180] 1) Translational load constraints

[0181] Shiftable load refers to adjusting the time period of user energy consumption in comprehensive demand response without changing the total energy consumption. This process can be expressed by the following constraints:

[0182]

[0183] Among them, D shift+,n,t , D shfft-,n,t They represent the load added and reduced by the virtual power plant in period t, D shift+,n,max , D shift-,n,max They represent the maximum value of load increase and load reduction of the virtual power plant in period t, D shift,n,min It represents the minimum value of load increase and load reduction of the virtual power plant in period t.

[0184] 2) Load constraints can be reduced

[0185] Reducible load means that in the integrated demand response, users can reduce energy use by turning off a certain number of devices such as lighting, heating and cooling during a specific period of time. The capacity of the reducible load meets the following constraints:

[0186]

[0187] Among them, D cut,n,t represents the load that can be reduced by the virtual power plant in period t, D cut,n,min , D cut,n,max Respectively represent the lower and upper limits of its value.

[0188] 3) Convertible load constraints

[0189] Convertible load means that in the integrated demand response, the virtual power plant can convert energy forms to flexibly meet the energy needs of users, such as converting natural gas into electricity and heat through CHP, and converting electricity into natural gas through P2G. The following balance constraints must be met during the conversion:

[0190]

[0191] Among them, D E,conv,n,t It represents the convertible electric load of the virtual power plant in period t, and its upper and lower limits are D E,conv,n,max and D E,conv,n,min , D H,conv,n,l is the heat load after conversion, and the conversion efficiency is γ n,t .

[0192] (3) Energy network constraints

[0193] According to the trading mechanism of virtual power plants participating in comprehensive demand response constructed in the previous section, ISO needs to process the quotations and quantities of virtual power plants and energy suppliers, and conduct centralized clearing under the condition of meeting energy network security constraints. Therefore, it is necessary to model the power system, natural gas system and thermal system of the virtual power plant. 1) Power network constraints

[0194] The power system in the virtual power plant satisfies the following power flow constraints, as shown below:

[0195]

[0196]

[0197]

[0198]

[0199] Among them, P w,t and Q w,t are the active power and reactive power injected into node w during period t, P wz,t and Q wz,t They represent the active power and reactive power from node w to node z during period t, respectively. wz,t represents the current from node w to node z during period t, v w,t represents the voltage at node w, They represent the collection of lines and nodes in the power network respectively.

[0200] 2) Natural gas network constraints

[0201] The natural gas system includes gas sources, compressors, natural gas pipelines and gas loads. The two main factors that affect the safe and stable operation of the system are flow and pressure. The Weymouth equation can be used to express the relationship between the two. At the same time, flow and pressure are subject to certain physical constraints, as shown below:

[0202]

[0203]

[0204]

[0205] Among them, f p,t represents the natural gas flow rate of natural gas pipeline p during period t, f p,max and f p,min are the upper and lower limits of its value, π n,max and π n,min are the upper and lower limits of its value respectively. and Represent the collection of pipelines and nodes of the natural gas system respectively. In addition, represents the natural gas pipeline parameters, whose values ​​depend on the physical characteristics of the pipeline, such as length, diameter and friction coefficient. Since the gas pressure will decay with the increase of transmission distance, a compressor is required to ensure that the gas pressure is within the normal range of variation.

[0206] Thermal systems mainly use water or steam as heat transfer media, and realize district heating by circulating in the heat supply network and the heat recovery network. In actual operation, the thermal system is generally regulated by controlling the temperature or flow of the medium. The temperature in the thermal system is affected by the heat source, the medium and the load. Generally, the temperature of the pipe inlet and outlet is used as the temperature of the thermal system. The heat that the heat source needs to generate depends on the temperature difference between the pipe inlet and outlet, as shown in the following formula.

[0207]

[0208]

[0209] in, represents the heat transfer medium flow rate of pipe j connected to the heat source during period t, and are the temperatures of the nodes in the heating network and the heat recovery network, and for The upper and lower limits of the value, and are the collections of pipes and nodes in the heating network respectively.

[0210] The heat in the medium is transferred to the end user through the heat exchange equipment, and then the waste heat is recovered through the heat recovery network. The heat supplied by the heat exchange equipment must meet the needs of the end user, as shown below.

[0211]

[0212]

[0213] Among them, cm j,t represents the heat transfer medium flow rate of heat exchange device j in time period t, and for The upper and lower limits of the value, and are the collections of pipes and nodes in the regenerative network respectively.

[0214] (4) Energy coupling equipment and energy storage constraints

[0215] In a virtual power plant, electricity, heat, and gas are coupled through an energy hub, such as CHP, electric boilers, and P2G. CHP can convert natural gas into electricity and heat; electric boilers can provide heat by consuming electricity; and P2G equipment can convert electricity into natural gas. In addition, the energy storage system in the virtual power plant can achieve load shifting by formulating charging and discharging plans. The energy balance constraints, heat storage tank operation constraints, and battery operation constraints in the energy hub are shown below.

[0216]

[0217]

[0218]

[0219]

[0220]

[0221]

[0222]

[0223]

[0224]

[0225]

[0226]

[0227]

[0228] Among them, E out,t , H out,t and G out,t Respectively represent the electrical, thermal and gas output power of the energy coupling equipment, E in,t , H in,t and G in,t They represent the electrical, thermal and gas input powers of the energy coupling equipment respectively, A is the correlation matrix of each type of energy, E c,t and E dc,t Respectively represent the charging and discharging power of the energy storage device, H c,t and H dc,t Respectively represent the charging and discharging power of the heat storage equipment, G c,t and G dc,t They represent the charging and discharging power of the gas storage equipment respectively. γ represents the conversion efficiency between various types of energy, ζ E , H Represent the charging and discharging efficiency of electrical energy storage and thermal energy storage devices respectively.

[0229] The present invention also provides a virtual power plant control device based on multi-load aggregation, comprising:

[0230] A construction module is used to construct a characteristic model of a virtual power plant based on an existing wind power generation system / photovoltaic power generation system; it is also used to determine the comprehensive demand response resources of the virtual power plant based on the response characteristics of the curtailable load, the transferable load, and the adjustable load; it is also used to determine the quantity of various energy sources that the virtual power plant responds to and construct a model based on electricity, heat, and gas, and determine the parameters of the electricity, heat, and gas, including: line constraints, load constraints of the comprehensive demand response resources, energy network constraints, energy coupling equipment, and energy storage constraints;

[0231] A control module is used to control the virtual power plant according to the constructed control model.

[0232] The present invention uses the multi-load aggregation virtual power plant technology. The results of the present invention effectively manage and regulate a large number of flexible resources, energy conversion resources, and multi-load resources, support the safe and economic operation of a high proportion of renewable energy systems, and promote the low-carbon transformation of energy and power systems. At the same time, with the advancement of energy and power reform and comprehensive marketization, it is necessary to innovate business models for energy end users and fully tap the value and benefits created by distributed energy for power grids and users in the future implementation of the national energy strategy. Therefore, the present invention selects multi-load coupled virtual power plants as the object and conducts a systematic study on their operational optimization in the energy and power market. The results of the present invention will help to improve the comprehensive utilization rate of distributed energy resources, controllable loads, electric vehicles and other flexible resources and alleviate the problem of renewable energy absorption, effectively stimulate the market participation of virtual power plants, improve the operating efficiency of energy and power systems and virtual power plants, and provide scientific support for the vigorous development and construction of virtual power plant projects.

[0233] Obviously, the described embodiments are only some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0234] It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, and do not constitute a limitation of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalent forms of such scope and boundaries.

Claims

1. A virtual power plant control method based on multi-load aggregation, characterized in that: include: Construct a characteristic model of a virtual power plant based on the existing wind power generation system / photovoltaic power generation system; Determining the comprehensive demand response resources of the virtual power plant according to the response characteristics of the curtailable load, the transferable load, and the adjustable load; According to electricity, heat and gas, the quantities of various energy sources to which the virtual power plant responds are determined and a control model is constructed, and the parameters of the electricity, heat and gas are determined to include: line constraints, load constraints of the integrated demand response resources, energy network constraints, energy coupling equipment and energy storage constraints; The virtual power plant is controlled according to the constructed control model.

2. The method according to claim 1, characterized in that The characteristic model of the virtual power plant is constructed based on the existing wind power generation system / photovoltaic power generation system, specifically including: The wind power generation system has a wind power output power P at time t. wpp,t It can be characterized as a function of intermittent wind speed, expressed as formula 1: Among them, v t is the real-time wind speed, v in is the cut-in wind speed, v out is the cut-out wind speed, v rated is the rated wind speed, Prated is the rated power of the wind turbine; the natural wind v of the wind power output follows the Weibull distribution, and its probability density function f w (v) Using formula 2: where φ is the shape parameter, is a scale parameter; and / or, The power of the photovoltaic power generation system at each moment is expressed as P PV,t , through the power conversion function, P PV,t The solar radiation θ at that moment t It is linearly related and is expressed by formula 3: P PV,t =the PV S PV i t (3) Among them, η PV is the energy conversion efficiency, and S PV is the total area of ​​PV panels; Solar irradiance is characterized by a Beta distribution f B (θ), expressed using Formula 4: Where Γ is the Gamma function, ξ and ψ are the parameters of the Beta distribution.

3. The method according to claim 1, characterized in that The method also includes energy storage device state characteristics, specifically including: X refers to energy storage devices such as electricity storage and heat storage, and its state characteristics are characterized by SoC, which is expressed as Formula 5: Among them, SoC X,t is the energy storage state of the energy storage device during time period t, They are charging power and charging efficiency respectively; are discharge power and discharge efficiency respectively; The output power of the energy storage device is expressed as Formula 6: in, is a 0-1 variable; The electric heat pump consumes electrical energy to provide heat energy to the end user. Its input-output characteristic is shown in Formula 7: Among them, COP is the heating coefficient of the electric heat pump, P HP,t Input power for the electric heat pump, Q HP,t It is the heating power of the electric heat pump.

4. The method according to claim 1, characterized in that: According to the response characteristics of the curtailable load, the transferable load, and the adjustable load, the comprehensive demand response resources of the virtual power plant are determined, including: The response characteristic of the curtailable load is expressed as shown in Formula 8: Among them, S re is the translation load user set; β i represents the maximum reduction ratio allowed for the i-th reducible user; The response characteristic of the transferable load user is shown in Formula 9: Among them, S trans User collection for translation load; and They represent the upper and lower limits of the allowable power of the i-th transferable load respectively; The transferable load requires that the total amount of load remains unchanged within a certain period of time, subject to the constraints of formula 10, as shown below: The adjustable load (SL) response characteristic is expressed as shown in the following formula 11: Among them, S shift A collection of adjustable load users; and are the adjustable load values ​​moved in and removed during period t, respectively; Among them, x i,m,t is a 0-1 variable, x i,m,t =1 means that the ith adjustable load has a load shifted from period m to period t, a 0-1 variable; is the load value of the i-th adjustable load at the working period of t=1: is the load value of the i-th adjustable load in the period t=l+1; Considering the load adjustment time margin, the constraints are: x i,t,t′ =0 |t-t|≥d i (13) Among them, d i is the adjustment time margin of the i-th adjustable load.

5. The method according to claim 1, characterized in that Determining the quantity of various energy sources that the virtual power plant responds to and building a model based on electricity, heat, and gas specifically includes: In the comprehensive demand response transaction, the virtual power plant needs to determine the quantity of various energy sources it responds to based on the electricity price, heat price and gas price released by the dispatch center to maximize the operating benefits of the virtual power plant. The control model is established as shown in Formula 14: Among them, E W,t , H W,t , G W,t They represent the electricity, heat and gas purchased by the virtual power plant in the external market at time t, which can be directly or after being converted into certain energy forms and then distributed to users. L,E,t , L,H,t , L,G,t Represents the predetermined price of electricity, heat and gas respectively. L,t , H L,t , G L,t They represent the amount of electricity, heat and gas traded between the virtual power plant and users in the internal market at time t, respectively, W,E,t , W,H,t , W,G,t Respectively represent the current market transaction prices of electricity, heat and gas.

6. The method according to claim 1, characterized in that The line constraints satisfy the constraints shown in formula 15: Among them, E W,min , H W,min , G W,min They represent the lower limits of the transmission power of electricity, heat and gas in the virtual power plant, respectively. Wmax , H Wmax , G Wmax They respectively represent the lower limits of transmission power of electricity, heat and gas in the virtual power plant.

7. The method according to claim 1, characterized in that The load constraint of the comprehensive demand response resource satisfies the constraint shown in Formula 16: Among them, E L,t , H L,t , G L,t They represent the total load of electricity, heat and gas of the virtual power plant at time t, E L,0,t , H L,0,t , G L,0,t They represent the uncontrollable loads of electricity, heat and gas of the virtual power plant at time t, respectively. L,dr,t , H L,dr,t , G L,dr,t They represent the controllable loads of electricity, heat and gas of the virtual power plant at time t respectively; The controllable loads include: load constraints that can be translated, load constraints that can be reduced, and load constraints that can be converted; The shiftable load constraint refers to adjusting the time period of user energy consumption in the comprehensive demand response without changing the total energy consumption, which is in accordance with Formula 17: Among them, D shift+,n,t , D shfft-,n,t They represent the load added and reduced by the virtual power plant in period t, D shift+,n,max , D shift-,n,max They represent the maximum value of load increase and load reduction of the virtual power plant in period t, D shift,n,min represents the minimum value of the virtual power plant to increase and reduce load during period t The reducible load constraint means that in the comprehensive demand response, the user can reduce the use of energy by shutting down a certain amount of energy in a specific time period. The reducible load constraint satisfies the formula shown in Formula 18: Among them, D cut,n,t represents the load that can be reduced by the virtual power plant in period t, D cut,n,min , D cut,n,max Respectively represent the lower and upper limits of its value; The convertible load constraint means that in the comprehensive demand response, the virtual power plant converts the energy form to flexibly meet the energy demand of the user, and the conversion complies with formula 19, as shown below: Among them, D E,conv,n,t It represents the convertible electric load of the virtual power plant in period t, and its upper and lower limits are D E,conv,n,max and D E,conv,n,min , D H ,conv,n,l is the heat load after conversion, and the conversion efficiency is γ n,t .

8. The method according to claim 1, characterized in that The energy network constraints specifically include power network constraints and natural gas network constraints; The power system in the virtual power plant satisfies the power network constraints in the following formulas 20, 21, 22, 22, and 23, as shown below: Among them, P w,t and Q w,t are the active power and reactive power injected into node w during period t, P wz,t and Q wz,t They represent the active power and reactive power from node w to node z during period t, respectively. wz,t represents the current from node w to node z during period t, v w,t represents the voltage at node w, They represent the collection of lines and nodes in the power network respectively; The natural gas system includes gas source, compressor, natural gas pipeline and gas load. The Weymouth equation is used to express the relationship between the two. The flow rate and pressure are subject to certain physical constraints. The gas source constraints are shown in formulas 24, 25 and 26: Among them, f p,t represents the natural gas flow rate of natural gas pipeline p during period t, f p,max and f p,min are the upper and lower limits of its value, π n,max and π n,min are the upper and lower limits of its value respectively. and Respectively represent the collection of pipelines and nodes of the natural gas system; where represents the natural gas pipeline parameters, whose values ​​depend on the physical characteristics of the pipeline, such as length, diameter and friction coefficient. Since the gas pressure will decay with the increase of transmission distance, a compressor is needed to ensure that the gas pressure is within the normal range of variation; A thermal system refers to a system that uses water or steam as a heat transfer medium and realizes district heating by circulating in a heat supply network and a heat recovery network. The temperature in the thermal system is affected by the heat source, the medium, and the load. The amount of heat that the heat source needs to generate depends on the temperature difference between the inlet and outlet of the pipeline, as shown in Formulas 27 and 28. in, represents the heat transfer medium flow rate of pipe j connected to the heat source during period t, and are the temperatures of the nodes in the heating network and the heat recovery network, and for The upper and lower limits of the value, and are the collections of pipes and nodes in the heating network respectively; The heat in the medium is transferred to the end user through the heat exchange equipment, and the waste heat is recovered through the heat recovery network; the heat supplied by the heat exchange equipment must meet the needs of the end user, as shown in Formula 29 and Formula 30: Among them, cm j,t represents the heat transfer medium flow rate of heat exchange device j in time period t, and for The upper and lower limits of the value, and are the collections of pipes and nodes in the regenerative network respectively.

9. The method according to claim 1, characterized in that: The energy coupling equipment and energy storage constraints, specifically, the energy coupling includes electricity, heat, and gas, which are coupled through an energy hub, and the energy storage system realizes load shifting by formulating a charging and discharging plan; The energy balance constraint in the energy hub, the heat storage tank operation constraint, and the battery operation constraint are shown in the following formulas 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, and 42: Among them, E out,t , H out,t and G out,t Respectively represent the electrical, thermal and gas output power of the energy coupling equipment, E in,t , H in,t and G in,t They represent the electrical, thermal and gas input powers of the energy coupling equipment respectively, A is the correlation matrix of each type of energy, E c,t and E dc,t Respectively represent the charging and discharging power of the energy storage device, H c,t and H dc,t Respectively represent the charging and discharging power of the heat storage equipment, G c,t and G dc,t They represent the charging and discharging power of the gas storage equipment respectively. γ represents the conversion efficiency between various types of energy, ζ E , H Represent the charging and discharging efficiency of electrical energy storage and thermal energy storage devices respectively.

10. A virtual power plant control device based on multi-load aggregation, characterized in that: include: A construction module, used to construct a characteristic model of a virtual power plant based on an existing wind power generation system / photovoltaic power generation system; It is also used to determine the comprehensive demand response resources of the virtual power plant according to the response characteristics of the curtailable load, the transferable load, and the adjustable load; It is also used to determine the quantity of various energy sources that the virtual power plant responds to and build a model based on electricity, heat and gas, and determine the parameters of the electricity, heat and gas including: line constraints, load constraints of the integrated demand response resources, energy network constraints, energy coupling equipment and energy storage constraints; A control module is used to control the virtual power plant according to the constructed control model.

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