A two-stage optimization configuration method for generalized energy storage based on building adjustable resources

Abstract

The present invention discloses a two-stage optimization configuration method for generalized energy storage based on building adjustable resources, which is used to smooth out power system power fluctuations and reduce energy storage configuration costs, and belongs to the field of power systems. The present invention includes the following steps: (1) Based on the central air conditioning regulation characteristics, a generalized energy storage model for central air conditioning is proposed; (2) Based on the charging and discharging characteristics of building charging piles, a generalized energy storage model for building charging piles is proposed; (3) A generalized energy storage model for building lithium battery energy storage is proposed; (4) A two-stage optimization configuration method for generalized energy storage based on commercial building loads is proposed, which effectively reduces the lithium battery energy storage cost while smoothing the voltage fluctuations of the distribution network. The two-stage optimization configuration method for energy storage proposed by the present invention is based on the adjustable resources of commercial buildings. The method can effectively optimize the configuration capacity of lithium battery energy storage and better solve the energy management problem of adjustable resources inside buildings.

Description

Technical Field

[0001] The invention relates to a generalized energy storage two-stage optimization configuration method based on building adjustable resources, belonging to the technical field of electric power. Background Art

[0002] As the global carbon neutrality process advances, low-carbon buildings will become a trend in the future development of buildings. Through energy management systems, commercial buildings can aggregate controllable loads and participate in the energy interaction of the power system to improve the utilization rate of renewable energy and the economic operation of the power grid. Building controllable loads can participate in the electric energy market through demand response, but in fact, because they have similar characteristics to energy storage, we can adopt the coordinated operation of controllable loads and energy storage systems to reduce the impact of renewable energy volatility on the power grid and the investment and operation costs of lithium battery energy storage. Summary of the invention

[0003] In view of the above problems, the present invention proposes a two-stage optimization configuration method of generalized energy storage based on building adjustable resources. This method is different from the traditional controllable load demand response mode. Instead, it constructs a generalized energy storage model of building adjustable resources and a two-stage generalized energy storage optimization configuration model, which provides technical support for the low-carbon operation of buildings.

[0004] To achieve the above objectives, the present invention adopts the following technical solutions:

[0005] A two-stage optimization configuration method for generalized energy storage based on building adjustable resources, characterized in that it includes the following steps:

[0006] (1) Based on the regulation characteristics of central air conditioning, a generalized energy storage model of central air conditioning is proposed;

[0007] (2) Based on the charging and discharging characteristics of building charging piles, a generalized energy storage model of building charging piles is proposed;

[0008] (3) A generalized energy storage model for building lithium battery energy storage was proposed;

[0009] (4) A two-stage optimization configuration method for generalized energy storage based on commercial building loads is proposed, which can effectively reduce the cost of lithium battery energy storage while smoothing the voltage fluctuations of the distribution network.

[0010] Specifically, the step (1) comprises the following steps:

[0011] There are many adjustable parameters in the central air-conditioning system, and they are connected to each other through the medium of cooling capacity. The adjustable quantities of the air conditioner are temperature and flow, including chilled water outlet temperature, chilled water flow and terminal fan air volume. The adjustable quantities are connected to the electrical quantities through cooling capacity. The electrical quantities are the electric power consumed by each part and the real-time adjustable power, including adjustable power and adjustable power. Among them, the refrigerator power, chilled water pump power and fan power are respectively restricted by the chilled water outlet temperature, chilled water flow and fan air volume; in addition, the electrical quantity of the air conditioner is also affected by the start-stop control and the external environment. Sudden start or stop will obtain the maximum adjustable power. The outdoor temperature, indoor temperature and indoor personnel flow will affect the actual power of each part of the air-conditioning system.

[0012] As the cold source of the central air-conditioning system, the refrigeration system, together with the chilled water pump and related motors, consumes nearly 50% of the electricity of the entire building. For grid dispatching, the power model of the refrigeration system is as follows:

[0013]

[0014]

[0015] in, is the cooling capacity delivered to the area, c a is the specific heat capacity of air, ε e is the heat transfer efficiency of the refrigerator, EER t is the energy efficiency ratio of the refrigerator, is the air volume supplied by the fan, T t sa is the supply air temperature, is the room temperature in the user area, P t ch Indicates the power of the refrigeration system.

[0016] At the end of each user area, there is an air handling unit for heat exchange between chilled water and indoor air. The wind system power model is as follows:

[0017]

[0018]

[0019] Among them, P t f is the wind turbine electrical power, c 0-3 is the coefficient of performance of the fan, It is the sum of the air supply volumes of fans in all areas at time t.

[0020] The thermal parameter model for each user area is as follows:

[0021]

[0022] Among them, C l and R l are the regional heat capacity and thermal resistance, T t out Indicates the outdoor temperature, Heat gain for the area.

[0023] Solving the differential equation above, we can get the change process of air temperature in the area. The above formula can be expressed as:

[0024]

[0025] According to the room thermal parameter model, when the system is in steady state, From this we can get The air supply volume and air supply temperature in steady state are solved by the following optimization problem:

[0026]

[0027] The system steady-state power is further calculated through the above optimization problem results:

[0028]

[0029] in is the supply air temperature of the central air conditioning system in steady state; T l set Ideal temperature set for the user; M is the cooling capacity of each area of ​​the system in steady state; a,max is the maximum air supply volume of the single-zone cooling system; T sa,min , T sa,max Indicates the minimum and maximum values ​​of the supply air temperature, P t HVAC,s , P t ch,s , P t f,s They respectively represent the total power of the central air-conditioning system, the total power of the refrigeration system and the total power of the fan in steady state.

[0030] In order to calculate the relevant parameters of the virtual energy storage model, the upper and lower limits of the power of the central air-conditioning system are solved by solving the following optimization problem:

[0031]

[0032] Among them, δ represents the maximum deviation allowed between the regional room temperature and the set temperature.

[0033] The upper and lower limits of charge and discharge power are expressed as follows:

[0034]

[0035] Among them, P t VES,max , P t VES,min Respectively represent the maximum and minimum values ​​of the virtual energy storage charging and discharging power, P t HVAC,max , P t HVAC,min They respectively represent the maximum and minimum power values ​​of the central air-conditioning system obtained by the previous optimization solution.

[0036] The charge and discharge power is expressed as follows:

[0037] P t VES =P t HVAC -P t HVAC,s (52)

[0038] Among them, P t VES Indicates the charging and discharging power value of the virtual energy storage, the charging power is positive and the discharging power is negative.

[0039] According to the room temperature change process in the previous article, the corresponding transformation can be equivalent to the virtual energy storage state change process:

[0040]

[0041] make Substituting in and rearranging, the above formula can be expressed as

[0042]

[0043] The parameters are expressed as follows:

[0044]

[0045]

[0046]

[0047] And X t,l The maximum and minimum values ​​of are expressed as follows:

[0048]

[0049] Finally, the general energy storage model of the central air-conditioning system is obtained, and the energy conversion process is as follows:

[0050] Adding the energy storage state change equations of user areas 1 to L gives

[0051]

[0052] Order SOC t =∑ l X t,l , γ=∑ l γ l , The above formula can be converted to

[0053]

[0054]

[0055] Among them, SOC t Indicates the energy storage value of the central air-conditioning universal energy storage model, It indicates the maximum and minimum value of energy storage

[0056] Considering the energy storage power constraint:

[0057] P t VES,min ≤P t VES ≤P t VES,max (62)

[0058] Considering the energy storage constraint:

[0059]

[0060] Considering the comfort and room heat loss, according to the characteristics of central air conditioning, the generalized energy storage model of central air conditioning is constructed as follows:

[0061]

[0062] Specifically, the step (2) comprises the following steps:

[0063] Through electric vehicle charging and discharging technology, electric vehicles can achieve energy interaction with the power grid. As a carrier for electric vehicles to achieve energy interaction, building charging piles have also become supporting infrastructure for commercial buildings in recent years. For electric vehicles participating in power grid dispatching, the battery state of charge can be divided into three parts: normal driving state SOC n , Standby driving state quantity SOC r and the dispatchable state quantity SOC BCP , normal driving state quantity SOC n It is used to meet the daily driving needs of users. The standby driving state quantity SOCr is reserved for dealing with emergency incidents, and the remaining part can be used for scheduling discharge to the power grid.

[0064] SOC n +SOCr +SOC BCP =1 (65)

[0065]

[0066] Among them, d T is the estimated daily mileage of the electric vehicle, D T It is the mileage that an electric vehicle can travel on a single charge after it is fully charged. The available dispatchable state of charge of an electric vehicle is a static indicator that describes the discharge capacity of an electric vehicle. Assuming that the daily driving pattern of a household electric vehicle remains unchanged, when the standby driving state of charge is determined, the dispatchable state of charge SOC BCP Is a fixed value.

[0067] At present, the charging and discharging power of electric vehicles can vary within a certain range if conditions permit. This also increases the flexibility of electric vehicles in participating in energy storage regulation. The minimum charging power P t BCP,k,ch,min With the maximum discharge power P t BCP,k,dch,min is the factory setting value of the electric vehicle, and the maximum charging power P t BCP,k,ch,max and minimum discharge power P t BCP ,k,dch,min Meet the following conditions

[0068]

[0069] Among them, SOC t BCP,k represents the dispatchable state of charge of the kth charging pile at time t, and Indicates the upper and lower limits of the state of charge at time t, E ev Indicates the battery capacity of a single electric vehicle.

[0070] Only when the electric vehicle is in a stopped state, that is, within the dispatchable period, and has dispatchable battery power, can it truly respond to dispatch. For building charging piles, the overall dispatchable power is the sum of the adjustable power of the electric vehicles on the piles, expressed as follows:

[0071]

[0072] Among them, P t BCP,ch is the total adjustable charging power, P t BCP,dch is the total adjustable discharge power, P t BCP,k,ch is the charging power of the kth charging pile, P tBCP,k,dch is the discharge power of the kth charging pile, N BCP The number of electric vehicles connected to the charging station network.

[0073] Then the maximum and minimum values ​​of the total charging power and discharge power of the building charging pile are calculated as follows:

[0074]

[0075] For the total charge of electric vehicles on the grid, the following relationship is satisfied

[0076]

[0077] Among them, η BCP Indicates the charging and discharging efficiency of the charging pile.

[0078] make Then the above formula can be transformed into

[0079]

[0080] Therefore, the generalized energy storage model of building charging pile is constructed as follows:

[0081]

[0082] in, and It is the charge amount when the charging pile starts to participate in energy storage regulation and ends energy storage regulation.

[0083] Specifically, the step (3) comprises the following steps:

[0084] Similar to electric vehicles, the total charge of building lithium battery energy storage satisfies the following relationship:

[0085]

[0086] Among them, η SBS Indicates the charging and discharging efficiency of building lithium battery energy storage, E SBS Indicates the total energy storage capacity of the building's lithium battery.

[0087] make Then the above formula can be transformed into

[0088]

[0089] Therefore, the building lithium battery energy storage model is as follows:

[0090]

[0091] in, and are the charges of the lithium battery at time t and time t-1, respectively. is the charge and discharge power of the lithium battery energy storage at time t, and They are the maximum and minimum charging and discharging power of lithium battery energy storage, and It is the storage capacity of lithium battery when it starts to participate in energy storage regulation and ends energy storage regulation, P SBS,max and P SBS,min is the maximum charging and discharging power of lithium battery energy storage, N SBS Indicates the amount of energy stored in a lithium battery.

[0092] Specifically, the step (4) comprises the following steps:

[0093] The two-stage generalized energy storage optimization model corresponds to two different objective functions. Under the first-stage optimization configuration considering the stability of the distribution network, the capacity configurations of central air conditioners, charging piles and lithium battery energy storage are further obtained.

[0094] The large-scale grid connection of renewable energy will aggravate the power flow fluctuation of the distribution network, which will be reflected in the voltage safety and stability of the distribution network. The configuration of the first stage is to minimize the absolute value of the voltage change of the distribution network after the connection of renewable energy and energy storage, which is expressed as follows:

[0095]

[0096] Among them, U N is the standard value of rated voltage, taken as 1.05, U i is the actual voltage of node i; n is the number of nodes in the distribution network. In the constraint condition, represents the voltage of node i at time t; V min and V max Respectively represent the upper and lower limits of the node voltage; represents the power flowing through line ij; Indicates the maximum power capacity of the line; They represent the renewable energy output, traditional unit output, generalized energy storage output, user load and network loss at time t respectively; H is the set of all nodes adjacent to node i; P i , Q i are the active and reactive powers of the connected load at node i respectively;

[0097] The configuration of the second stage is to optimize the configuration of each energy storage resource in the building based on the configuration of the first stage. The objective function is to maximize the annual net benefit, which is expressed as follows:

[0098] F2=max(B PG +B GES -CSES,B -C SES,O ) (77)

[0099] Among them, B PG represents the average annual savings in distribution network upgrade costs, B GES is the electricity market revenue of GES, C SES,B is the average annual construction cost of lithium battery energy storage, C SES,O is the annual operation and maintenance cost of SES,

[0100] The average annual savings from upgrading the distribution network are expressed as follows:

[0101]

[0102] Among them, C inv is the investment cost of upgrading the distribution network, T is the number of years of delay in upgrading the distribution network, τ is the inflation rate; d is the discount rate,

[0103] The electricity market revenue of generalized energy storage is expressed as follows:

[0104]

[0105] Among them, α t and β t is the average unit price of GES electricity during charging and discharging,

[0106] The average annual construction cost of lithium battery energy storage is expressed as follows,

[0107]

[0108] where c P and c E are the unit costs of electricity and energy storage, L is the life of lithium battery energy storage, λ is the annual bank interest rate, and the annual operation and maintenance cost of lithium battery energy storage is expressed as follows:

[0109]

[0110] where c O and c m are the unit operation and maintenance costs of lithium battery energy storage, B is the average self-discharge rate of lithium battery energy storage,

[0111] The constraints of the second-stage optimization configuration include power constraints of different types of energy storage, capacity constraints, and coupling constraints with the first-stage configuration results, which are specifically expressed as follows:

[0112]

[0113] in, and They are the central air-conditioning energy storage output power at time t, the building charging pile energy storage output power, the building lithium battery energy storage output power and the building generalized energy storage output power obtained in the first stage.

[0114] Beneficial effects:

[0115] The building adjustable resources involved in the present invention include central air conditioning, charging piles and lithium battery energy storage. Through the modeling process, in order to ensure that the user's comfort and travel mode are not affected under low-cost conditions, we can set the order of calling resources to: central air conditioning full comfort zone adjustment (air temperature comfort and air quality comfort are both equal to 1), charging pile adjustment, central air conditioning tolerable zone adjustment (air temperature comfort and air quality comfort are both in the [0,1] interval) and lithium battery energy storage adjustment. The two-stage optimization configuration method for energy storage proposed in the present invention is based on the adjustable resources of commercial buildings. This method can effectively optimize the configuration capacity of lithium battery energy storage and better solve the energy management problem of adjustable resources inside buildings. BRIEF DESCRIPTION OF THE DRAWINGS

[0116] The present invention will be further described below in conjunction with the accompanying drawings.

[0117] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0118] The present invention is a two-stage optimization configuration method for generalized energy storage based on building adjustable resources, and each step is described in detail below.

[0119] (1) Based on the two indicators of temperature comfort and air quality, a generalized energy storage model of central air conditioning considering user comfort is proposed;

[0120] (2) Considering the travel patterns of users, a generalized energy storage model for building charging piles is proposed;

[0121] (3) A generalized energy storage model for building lithium battery energy storage was proposed;

[0122] (4) A two-stage optimization configuration method for generalized energy storage based on commercial building loads is proposed, which can effectively reduce the cost of lithium battery energy storage while smoothing the voltage fluctuations of the distribution network.

[0123] Step 1: Based on the regulation characteristics of central air conditioning, a generalized energy storage model of central air conditioning is proposed.

[0124] There are many adjustable parameters in the central air-conditioning system, and they are connected to each other through the medium of cooling capacity. The adjustable quantities of the air conditioner are temperature and flow, including chilled water outlet temperature, chilled water flow and terminal fan air volume. The adjustable quantities are connected to the electrical quantities through cooling capacity. The electrical quantities are the electric power consumed by each part and the real-time adjustable power, including adjustable power and adjustable power. Among them, the refrigerator power, chilled water pump power and fan power are respectively restricted by the chilled water outlet temperature, chilled water flow and fan air volume; in addition, the electrical quantity of the air conditioner is also affected by the start-stop control and the external environment. Sudden start or stop will obtain the maximum adjustable power. The outdoor temperature, indoor temperature and indoor personnel flow will affect the actual power of each part of the air-conditioning system.

[0125] As the cold source of the central air-conditioning system, the refrigeration system, together with the chilled water pump and related motors, consumes nearly 50% of the electricity of the entire building. For grid dispatching, the power model of the refrigeration system is as follows:

[0126]

[0127]

[0128] in, is the cooling capacity delivered to the area, c a is the specific heat capacity of air, ε e is the heat transfer efficiency of the refrigerator, EER t is the energy efficiency ratio of the refrigerator, is the air volume supplied by the fan, T t sa is the supply air temperature, is the room temperature in the user area, P t ch Indicates the power of the refrigeration system.

[0129] At the end of each user area, there is an air handling unit for heat exchange between chilled water and indoor air. The wind system power model is as follows:

[0130]

[0131]

[0132] Among them, P t f is the wind turbine electrical power, c 0-3 is the coefficient of performance of the fan, It is the sum of the air supply volumes of fans in all areas at time t.

[0133] The thermal parameter model for each user area is as follows:

[0134]

[0135] Among them, C l and R l are the regional heat capacity and thermal resistance, T t out Indicates the outdoor temperature, Heat gain for the area.

[0136] Solving the differential equation above, we can get the change process of air temperature in the area. The above formula can be expressed as:

[0137]

[0138] According to the room thermal parameter model, when the system is in steady state, From this we can get The air supply volume and air supply temperature in steady state are solved by the following optimization problem:

[0139]

[0140] The system steady-state power is further calculated through the above optimization problem results:

[0141]

[0142] in It is the supply air temperature of the central air conditioning system in steady state; Ideal temperature set for the user; M is the cooling capacity of each area of ​​the system in steady state; a,max is the maximum air supply volume of the single-zone cooling system; T sa,min , T sa,max Indicates the minimum and maximum values ​​of the supply air temperature, P t HVAC,s , P t ch,s , P t f,s They respectively represent the total power of the central air-conditioning system, the total power of the refrigeration system and the total power of the fan in steady state.

[0143] In order to calculate the relevant parameters of the virtual energy storage model, the upper and lower limits of the power of the central air-conditioning system are solved by solving the following optimization problem:

[0144]

[0145] Among them, δ represents the maximum deviation allowed between the regional room temperature and the set temperature.

[0146] The upper and lower limits of charge and discharge power are expressed as follows:

[0147]

[0148] Among them, Pt VES,max , P t VES,min Respectively represent the maximum and minimum values ​​of the virtual energy storage charging and discharging power, P t HVAC,max , P t HVAC,min They respectively represent the maximum and minimum power values ​​of the central air-conditioning system obtained by the previous optimization solution.

[0149] The charge and discharge power is expressed as follows:

[0150] P t VES =P t HVAC -P t HVAC,s (93)

[0151] Among them, P t VES Indicates the charging and discharging power value of the virtual energy storage, the charging power is positive and the discharging power is negative.

[0152] According to the room temperature change process in the previous article, the corresponding transformation can be equivalent to the virtual energy storage state change process:

[0153]

[0154] make Substituting in and rearranging, the above formula can be expressed as

[0155]

[0156] The parameters are expressed as follows:

[0157]

[0158]

[0159]

[0160] And X t,l The maximum and minimum values ​​of are expressed as follows:

[0161]

[0162] Finally, the general energy storage model of the central air-conditioning system is obtained, and the energy conversion process is as follows:

[0163] Adding the energy storage state change equations of user areas 1 to L gives

[0164]

[0165] Order SOCt =∑ l X t,l , γ=∑ l γ l , The above formula can be converted to

[0166]

[0167]

[0168] Among them, SOC t Indicates the energy storage value of the central air-conditioning universal energy storage model, It indicates the maximum and minimum value of energy storage

[0169] Considering the energy storage power constraint:

[0170] P t VES,min ≤P t VES ≤P t VES,max (103)

[0171] Considering the energy storage constraint:

[0172]

[0173] Considering the comfort and room heat loss, according to the characteristics of central air conditioning, the generalized energy storage model of central air conditioning is constructed as follows:

[0174]

[0175] Step 2: Based on the charging and discharging characteristics of building charging piles, a generalized energy storage model of building charging piles is proposed.

[0176] Through electric vehicle charging and discharging technology, electric vehicles can achieve energy interaction with the power grid. As a carrier for electric vehicles to achieve energy interaction, building charging piles have also become supporting infrastructure for commercial buildings in recent years. For electric vehicles participating in power grid dispatching, the battery state of charge can be divided into three parts: normal driving state SOC n , Standby driving state quantity SOC r and the dispatchable state quantity SOC BCP , normal driving state quantity SOC n It is used to meet the daily driving needs of users. The standby driving state quantity SOCr is reserved for dealing with emergency incidents, and the remaining part can be used for scheduling discharge to the power grid.

[0177] SOC n +SOC r+SOC BCP =1 (106)

[0178]

[0179] Among them, d T is the estimated daily mileage of the electric vehicle, D T It is the mileage that an electric vehicle can travel on a single charge after it is fully charged. The available dispatchable state of charge of an electric vehicle is a static indicator that describes the discharge capacity of an electric vehicle. Assuming that the daily driving pattern of a household electric vehicle remains unchanged, when the standby driving state of charge is determined, the dispatchable state of charge SOC BCP Is a fixed value.

[0180] At present, the charging and discharging power of electric vehicles can vary within a certain range if conditions permit. This also increases the flexibility of electric vehicles in participating in energy storage regulation. The minimum charging power P t BCP,k,ch,min With the maximum discharge power P t BCP,k,dch,min is the factory setting value of the electric vehicle, and the maximum charging power P t BCP,k,ch,max and minimum discharge power P t BCP ,k,dch,min Meet the following conditions

[0181]

[0182] in, represents the dispatchable state of charge of the kth charging pile at time t, and Indicates the upper and lower limits of the state of charge at time t, E ev Indicates the battery capacity of a single electric vehicle.

[0183] Only when the electric vehicle is in a stopped state, that is, within the dispatchable period, and has dispatchable battery power, can it truly respond to dispatch. For building charging piles, the overall dispatchable power is the sum of the adjustable power of the electric vehicles on the piles, expressed as follows:

[0184]

[0185] Among them, P t BCP,ch is the total adjustable charging power, P t BCP,dch is the total adjustable discharge power, P t BCP,k,ch is the charging power of the kth charging pile, P t BCP,k,dchis the discharge power of the kth charging pile, N BCP The number of electric vehicles connected to the charging station network.

[0186] Then the maximum and minimum values ​​of the total charging power and discharge power of the building charging pile are calculated as follows:

[0187]

[0188] For the total charge of electric vehicles on the grid, the following relationship is satisfied

[0189]

[0190] Among them, η BCP Indicates the charging and discharging efficiency of the charging pile.

[0191] make Then the above formula can be transformed into

[0192]

[0193] Therefore, the generalized energy storage model of building charging pile is constructed as follows:

[0194]

[0195] in, and It is the charge amount when the charging pile starts to participate in energy storage regulation and ends energy storage regulation.

[0196] Step 3: A generalized energy storage model for building lithium battery energy storage is proposed.

[0197] Similar to electric vehicles, the total charge of building lithium battery energy storage satisfies the following relationship:

[0198]

[0199] Among them, η SBS Indicates the charging and discharging efficiency of building lithium battery energy storage, E SBS Indicates the total energy storage capacity of the building's lithium battery.

[0200] make Then the above formula can be transformed into

[0201]

[0202] Therefore, the building lithium battery energy storage model is as follows:

[0203]

[0204] in, and are the charges of the lithium battery at time t and time t-1, respectively. is the charge and discharge power of the lithium battery energy storage at time t, and They are the maximum and minimum charging and discharging power of lithium battery energy storage, and It is the storage capacity of lithium battery when it starts to participate in energy storage regulation and ends energy storage regulation, P SBS,max and P SBS,min is the maximum charging and discharging power of lithium battery energy storage, N SBS Indicates the amount of energy stored in lithium batteries

[0205] Step 4: A two-stage optimization configuration method for generalized energy storage based on commercial building loads is proposed, which can effectively reduce the cost of lithium battery energy storage while smoothing the voltage fluctuations of the distribution network.

[0206] The two-stage generalized energy storage optimization model corresponds to two different objective functions. Under the first-stage optimization configuration considering the stability of the distribution network, the capacity configurations of central air conditioners, charging piles and lithium battery energy storage are further obtained.

[0207] The large-scale grid connection of renewable energy will aggravate the power flow fluctuation of the distribution network, which will be reflected in the voltage safety and stability of the distribution network. The configuration of the first stage is to consider the minimum sum of the absolute values ​​of the distribution network voltage changes after the connection of renewable energy and energy storage. The constraints of the first stage include generalized energy storage power constraints, charge constraints, node voltage constraints, distribution network active power and reactive power constraints, which are expressed as follows:

[0208]

[0209] Among them, U N is the standard value of rated voltage, taken as 1.05, U i is the actual voltage of node i; n is the number of nodes in the distribution network. In the constraint condition, represents the voltage of node i at time t; V min and V max Respectively represent the upper and lower limits of the node voltage; represents the power flowing through line ij; Indicates the maximum power capacity of the line; They represent the renewable energy output, traditional unit output, generalized energy storage output, user load and network loss at time t respectively; H is the set of all nodes adjacent to node i; P i , Q i are the active and reactive powers of the connected load at node i respectively;

[0210] The configuration of the second stage is to optimize the configuration of each energy storage resource in the building based on the configuration of the first stage. The objective function is to maximize the annual net benefit, which is expressed as follows:

[0211] F2=max(B PG +B GES -C SES,B -C SES,O ) (118)

[0212] Among them, B PG represents the average annual savings in distribution network upgrade costs, B GES is the electricity market revenue of GES, C SES,B is the average annual construction cost of lithium battery energy storage, C SES,O is the annual operation and maintenance cost of SES,

[0213] The average annual savings from upgrading the distribution network are expressed as follows:

[0214]

[0215] Among them, C inv is the investment cost of upgrading the distribution network, T is the number of years of delay in upgrading the distribution network, τ is the inflation rate; d is the discount rate,

[0216] The electricity market revenue of generalized energy storage is expressed as follows:

[0217]

[0218] Among them, α t and β t is the average unit price of GES electricity during charging and discharging,

[0219] The average annual construction cost of lithium battery energy storage is expressed as follows,

[0220]

[0221] where c P and c E are the unit costs of electricity and energy storage, L is the life of lithium battery energy storage, λ is the annual bank interest rate, and the annual operation and maintenance cost of lithium battery energy storage is expressed as follows:

[0222]

[0223] where c O and c m are the unit operation and maintenance costs of lithium battery energy storage, B is the average self-discharge rate of lithium battery energy storage,

[0224] The constraints of the second-stage optimization configuration include power constraints of different types of energy storage, capacity constraints, and coupling constraints with the first-stage configuration results, which are specifically expressed as follows:

[0225]

[0226] in, and They are the central air-conditioning energy storage output power at time t, the building charging pile energy storage output power, the building lithium battery energy storage output power and the building generalized energy storage output power obtained in the first stage.

[0227] The building adjustable resources involved in the present invention include central air conditioning, charging piles and lithium battery energy storage. Through the modeling process, in order to ensure that the user's comfort and travel mode are not affected under low-cost conditions, we can set the order of calling resources as follows: central air conditioning full comfort zone adjustment (air temperature comfort and air quality comfort are both equal to 1), charging pile adjustment, central air conditioning tolerable zone adjustment (air temperature comfort and air quality comfort are both in the [0,1] interval) and lithium battery energy storage adjustment.

[0228] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A two-stage optimization configuration method for generalized energy storage based on building adjustable resources, characterized in that: The following steps are involved: (1) Based on the regulation characteristics of central air conditioning, a generalized energy storage model of central air conditioning is proposed; (2) Based on the charging and discharging characteristics of building charging piles, a generalized energy storage model of building charging piles is proposed; (3) Construct a generalized energy storage model for building lithium battery energy storage; (4) A two-stage optimization configuration method for generalized energy storage based on commercial building loads is proposed, which can effectively reduce the cost of lithium battery energy storage while smoothing the voltage fluctuations of the distribution network; The step (1) is carried out according to the following steps: There are many adjustable parameters in the central air-conditioning system, and they are connected to each other through the medium of cooling capacity. The adjustable quantities of the air conditioner are temperature and flow, including chilled water outlet temperature, chilled water flow and terminal fan air volume. The adjustable quantities are connected to the electrical quantities through cooling capacity. The electrical quantities are the electric power consumed by each part and the real-time adjustable power, including adjustable power and adjustable power. Among them, the refrigerator power, chilled water pump power and fan power are respectively restricted by the chilled water outlet temperature, chilled water flow and fan air volume; in addition, the electrical quantity of the air conditioner is also affected by the start-stop control and the external environment. Sudden start or stop will obtain the maximum adjustable power. The outdoor temperature, indoor temperature and indoor personnel flow will affect the actual power of each part of the air-conditioning system. As the cold source of the central air-conditioning system, the refrigeration system, together with the chilled water pump and related motors, consumes nearly 50% of the electricity of the entire building. For grid dispatching, the power model of the refrigeration system is as follows: (1) (2) in, is the cooling capacity delivered to the area, is the specific heat capacity of air, is the heat transfer efficiency of the refrigerator, is the energy efficiency ratio of the refrigerator, is the air volume supplied by the fan, is the supply air temperature, is the room temperature in the user area, Indicates the refrigeration system power, At the end of each user area, there is an air handling unit for heat exchange between chilled water and indoor air. The wind system power model is as follows: (3) (4) in, is the wind turbine electrical power, c 0-3 is the coefficient of performance of the fan, It is the sum of the air supply volume of fans in all areas at time t; The thermal parameter model for each user area is as follows: (5) in, and are the regional heat capacity and thermal resistance, Indicates the outdoor temperature, Heat gain for the area; Solving the differential equation above, we can get the change process of air temperature in the area. , , then the above formula can be expressed as: (6) According to the room thermal parameter model, when the system is in steady state, , , from which we can get , the air supply volume and air supply temperature in steady state are solved by the following optimization problem: (7) The system steady-state power is further calculated through the above optimization problem results: (8) in It is the supply air temperature of the central air conditioning system in steady state; Ideal temperature set for the user; The cooling capacity of each area of ​​the system in steady state; It is the maximum air supply volume of a single-zone cooling system; Indicates the minimum and maximum values ​​of the supply air temperature. They represent the total power of the central air-conditioning system, the total power of the refrigeration system and the total power of the fan in steady state respectively; In order to calculate the relevant parameters of the virtual energy storage model, the upper and lower limits of the power of the central air-conditioning system are solved by solving the following optimization problem: (9) in, Indicates the maximum deviation allowed between the room temperature and the set temperature in the area. The upper and lower limits of charge and discharge power are expressed as follows: (10) in, They represent the maximum and minimum values ​​of the virtual energy storage charging and discharging power, respectively. They represent the maximum and minimum power values ​​of the central air-conditioning system obtained by the previous optimization solution, The charge and discharge power is expressed as follows: (11) in, Indicates the charging and discharging power value of virtual energy storage. Charging power is positive and discharging power is negative. According to the room temperature change process in the previous article, the corresponding transformation can be equivalent to the virtual energy storage state change process: (12) make , substituting into the above formula, it can be expressed as (13) The parameters are expressed as follows: (14) (15) (16) and The maximum and minimum values ​​of are expressed as follows: (17) Finally, the general energy storage model of the central air-conditioning system is obtained, and the energy conversion process is as follows: Adding the energy storage state change equations of user area 1~L gives (18) make , , , The above formula can be converted to (19) (20) in, Indicates the energy storage value of the central air-conditioning universal energy storage model, It indicates the maximum and minimum value of energy storage. Considering the energy storage power constraint: (21) Considering the energy storage constraint: (22) Considering the comfort and room heat loss, according to the characteristics of central air conditioning, the generalized energy storage model of central air conditioning is constructed as follows: (23)； The step (2) is performed as follows: Through electric vehicle charging and discharging technology, electric vehicles can achieve energy interaction with the power grid. As a carrier for electric vehicles to achieve energy interaction, building charging piles have also become supporting infrastructure for commercial buildings in recent years. For electric vehicles participating in power grid dispatching, the battery state of charge can be divided into three parts: normal driving state SOC n , Standby driving state quantity SOC r and the dispatchable state quantity SOC BCP , normal driving state quantity SOC n It is used to meet the daily driving needs of users. The standby driving state quantity SOCr is reserved for emergency situations. The remaining part can be used for scheduling discharge to the power grid. (24) (25) in, is the estimated daily mileage of the electric vehicle, It is the mileage that an electric vehicle can travel once it is fully charged. The dispatchable state of charge of an electric vehicle is a static indicator that describes the discharge capacity of an electric vehicle. Assuming that the daily driving pattern of a household electric vehicle remains unchanged, when the standby driving state of charge is determined, the dispatchable state of charge SOC BCP is a fixed value; At present, the charging and discharging power of electric vehicles can vary within a certain range if conditions permit. This also increases the flexibility of electric vehicles in participating in energy storage regulation. The minimum charging power With maximum discharge power is the factory setting value of the electric vehicle, and the maximum charging power and minimum discharge power Meet the following conditions (26) in, represents the dispatchable state of charge of the kth charging pile at time t, and Indicates the upper and lower limits of the state of charge at time t, Indicates the battery capacity of a single electric vehicle; Only when the electric vehicle is in a stopped state, that is, within the dispatchable period, and has dispatchable battery power, can it truly respond to dispatch. For building charging piles, the overall dispatchable power is the sum of the adjustable powers of the electric vehicles on the piles, expressed as follows: (27) in, is the total adjustable charging power, is the total adjustable discharge power, is the charging power of the kth charging pile, is the discharge power of the kth charging pile, The number of electric vehicles connected to the charging pile network; Then the maximum and minimum values ​​of the total charging power and discharge power of the building charging pile are calculated as follows: (28) For the total charge of electric vehicles on the grid, the following relationship is satisfied (29) in, Indicates the charging and discharging efficiency of the charging pile; make , , then the above formula can be transformed into (30) Therefore, the generalized energy storage model of building charging pile is constructed as follows: (31) in, and It is the charge amount when the charging pile starts to participate in energy storage regulation and ends energy storage regulation; The step (3) is performed as follows: Similar to electric vehicles, the total charge of building lithium battery energy storage satisfies the following relationship: (32) in, Indicates the charging and discharging efficiency of building lithium battery energy storage, Indicates the total energy storage capacity of the building’s lithium battery, make , , then the above formula can be transformed into (33) Therefore, the building lithium battery energy storage model is as follows: (34) in, and Lithium battery energy storage in time t and time t -1 charge, PSBS Is lithium battery energy storage in time t The charge and discharge power, PSBS,max t and PSBS, min t They are the maximum and minimum charging and discharging power of lithium battery energy storage, and It is the amount of energy stored when the lithium battery starts to participate in energy storage regulation and ends energy storage regulation. P SBS,max and P SBS,min is the maximum charging and discharging power of lithium battery energy storage, N SBS Indicates the amount of energy stored in lithium batteries; The step (4) is performed as follows: The two-stage generalized energy storage optimization model corresponds to two different objective functions. Under the first-stage optimization configuration considering the stability of the distribution network, the capacity configurations of central air conditioners, charging piles and lithium battery energy storage are further obtained. The large-scale grid connection of renewable energy will aggravate the power flow fluctuation of the distribution network, which will be reflected in the voltage safety and stability of the distribution network. The configuration of the first stage is to consider the minimum sum of the absolute values ​​of the distribution network voltage changes after the connection of renewable energy and energy storage. The constraints of the first stage include generalized energy storage power constraints, charge constraints, node voltage constraints, distribution network active power and reactive power constraints, which are specifically expressed as follows: (35) in, U N is the standard value of rated voltage, which is taken as 1.05; U i For Node i The actual voltage of n is the number of nodes in the distribution network; in the constraints, Vi t Representation Node i At the moment t Voltage; V min and V max Respectively represent the upper and lower limits of the node voltage; Pij t Indicates the flow line ij Power; Pmax ij represents the maximum power capacity of the line; PR t, PG t, PGES t, PD t, PLOSS t represent the renewable energy output, traditional unit output, generalized energy storage output, user load and network loss at time t respectively; H is the total power consumption of all nodes adjacent to the node i A collection of nodes; P i , Q i They are i The active and reactive power of the connected loads at the node; The configuration of the second stage is to optimize the configuration of each energy storage resource in the building based on the configuration of the first stage. The objective function is to maximize the annual net benefit, which is expressed as follows: (36) in, B PG represents the average annual savings in distribution network upgrade costs, B GES is the electricity market revenue of GES, C SES,B is the average annual construction cost of lithium battery energy storage, C SES,O is the annual operation and maintenance cost of SES, The average annual savings from upgrading the distribution network are expressed as follows: (37) in, C inv is the investment cost of upgrading the distribution network, T is the number of years of delay in upgrading the distribution network, τ is the inflation rate; d is the discount rate, The electricity market revenue of generalized energy storage is expressed as follows: (38) in, α t and β t is the average unit price of GES electricity during charging and discharging, The average annual construction cost of lithium battery energy storage is expressed as follows, (39) in c P and c E are the unit costs of electricity and energy storage, L is the energy storage life of lithium batteries, λ is the bank's annual interest rate, The annual operation and maintenance cost of lithium battery energy storage is expressed as follows, (40) in c O and c m are the unit operation and maintenance costs of lithium battery energy storage, λ B is the average self-discharge rate of lithium battery energy storage, The constraints of the second-stage optimization configuration include power constraints of different types of energy storage, capacity constraints, and coupling constraints with the first-stage configuration results, which are specifically expressed as follows: (41) in, PVES , PBCP , PVES and PGES Separate moments t The central air conditioning energy storage output power, the building charging pile energy storage output power, the building lithium battery energy storage output power and the building generalized energy storage output power obtained in the first stage.

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