CN106960272A - Building microgrid Multiple Time Scales Optimization Scheduling containing virtual energy storage - Google Patents

Abstract

The invention discloses the building microgrid Multiple Time Scales Optimization Scheduling containing virtual energy storage, including：Building virtual energy storage system modelling, building microgrid are layered the structure of energy management framework, propose Multiple Time Scales Optimization scheduling algorithm, apply it in building microgrid Optimal Operation Model, call CPLEX to optimize scheduling under MATLAB software environments to solve, the operation result of building microgrid a few days ago and in the daytime containing virtual energy storage is obtained, the purpose of optimized operation is realized.Building microgrid Multiple Time Scales scheduling strick precaution of the present invention containing virtual energy storage can reduce the operating cost of building microgrid on the premise of temperature pleasant degree is ensured in scheduling phase a few days ago；Microgrid interconnection tie power fluctuation caused by being stabilized in the amendment stage in the daytime by predicated error a few days ago.

Description

Building microgrid Multiple Time Scales Optimization Scheduling containing virtual energy storage

Technical field

The present invention relates to the operation of micro power source network optimizationization, specifically, it is related to many time chis of building microgrid containing virtual energy storage Spend Optimization Scheduling.

Background technology

With continuing to develop for renewable energy utilization technology in recent years, increasing distributing-supplying-energy system is in building Side is integrated, forms the micro-grid system based on building, and a variety of low-carbon solutions are provided for building energy supply.According to microgrid The Optimized Operation schemes of building is formulated in the configuration of internal each unit, optimization is coordinated to comprehensive energy in microgrid and manages, Various energy resources complementation, the utilization of fully dissolving of regenerative resource, reduction microgrid operating cost can be achieved and using energy source is improved Efficiency.

However, in existing building microgrid Optimized Operation and energy management research work, not taking into full account that building freeze Quantitative mathematical relation between demand and user's temperature pleasant degree and outdoor temperature, have ignored the virtual energy storage system of Demand-side building Potentiality of the system in microgrid Optimized Operation.In fact, due to the effect of heat insulation of the building enclosures such as building construction wall, indoor and room Outer heat exchanging process is slower, and indoor temperature will not change rapidly relative to electric characteristic amount, there is certain inertia.Cause This, the refrigeration demands of building can according to the dispatching requirement of microgrid in the range of certain users'comfort with being carried out under Regulate Environment Optimize and revise.

Further, by excavating the virtual energy storage system of Demand-side building in building microgrid Optimized Operation and energy management Potentiality, the virtual energy storage system integration of building has been arrived in building microgrid Multiple Time Scales Optimized Operation Mathematical Modeling, in temperature Regulation is optimized to building room temperature in the range of degree comfort level, the management of charging and discharging to virtual energy storage can be realized, so that in day Preceding scheduling phase reduces microgrid operating cost；The microgrid interconnection setting value of generation is dispatched a few days ago in the stage tracking of amendment in the daytime, Effectively stabilize by interconnection tie power fluctuation caused by predicated error a few days ago.

[bibliography]

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The content of the invention

For prior art, the present invention utilizes the thermal storage effect of building, structure by taking summer cooling load in building microgrid as an example The virtual energy storage model based on building is built.Then, propose that a kind of building microgrid Multiple Time Scales of the system containing virtual energy storage are excellent Change dispatching method, by the way that building room temperature is adjusted in the range of temperature pleasant degree, realize the management of charging and discharging of virtual energy storage, From a few days ago/scheduling is optimized to building microgrid on Multiple Time Scales in the daytime.

In order to solve the above-mentioned technical problem, a kind of building microgrid Multiple Time Scales containing virtual energy storage proposed by the present invention are excellent Change dispatching method, comprise the following steps：

Step 1: setting up building virtual energy storage system model：

Thermal storage effect based on building, the equation of heat balance of building is obtained according to the conservation of energy, as follows：

In formula (1)：Δ Q is the variable quantity of indoor heat, and unit is J/s；ρ is atmospheric density, and unit is kg/m³；C is sky Gas specific heat capacity, unit is J/ (kg DEG C)；V is room air volume, and unit is m³；

Influence the factor of interior of building heat at least：The cold heat that indoor/outdoor temperature-difference is caused dissipates, sun heat radiation, The cooling/heating power output of human body and equipment heating and cooling/heating equipment in building, above-mentioned formula (1) is rewritten as follows：

In formula (2), the equal sign left side：

Section 1 (k_wall×F_wall×(T_out-T_in)) external wall and the heat of outdoor transmission are represented, unit is kW；Its In, k_wallFor the heat transfer coefficient of external wall, unit is W/ (m²K), when representing steady state heat transfer, each list of indoor and outdoor temperature difference The heat of wall is transmitted through in bits per second；F_wallFor external wall area, unit is m²；(T_out-T_in) it is that indoor and outdoor temperature is poor, it is single Position is K；

Section 2 (k_win×F_win×(T_out-T_in)) external window of building and the heat of outdoor transmission are represented, unit is kW：Wherein k_winFor the heat transfer coefficient of external window of building, unit is W/ (m²·K)；F_winFor the area of external window of building, unit is m²；

Section 3 I × F_win× SC represents the heat of sun heat radiation transmission, and unit is kW, and wherein I is solar radiation work( Rate, unit is kW/m², represent the heat that every square of metre per second (m/s) receives during with illumination vertical irradiation；SC is shading coefficient, its value With whether having sunshading board, glass material etc. relevant；Q_inFor the heating power of indoor airflow, including：The hair of human body and electrical equipment Heat, unit is kW；Q_clFor the refrigeration work consumption of refrigeration plant, unit is kW；

The charge-discharge electric power of virtual energy storage system based on building is as follows：

Q_VSS,t=Q '_{cl,building,t}-Q_{cl,building,t} (3)

In formula (3)：Q_VSS,tFor the charge-discharge electric power of virtual energy storage system, unit is kW, discharges just, to be charged as bearing； Q′_{cl,building,t}Not adjust the building refrigeration electrical power requirements of indoor temperature, unit is kW；Q_{cl,building,t}To consider in temperature The building refrigeration electrical power requirements of regulation indoor temperature in the range of comfort level are spent, unit is kW；

Step 2: building building microgrid layering energy management framework

Building microgrid Optimized Operation includes scheduling phase a few days ago and corrects the stage in real time in the daytime, and the scheduling phase a few days ago is Building room temperature is adjusted in the range of temperature pleasant degree, the management of charging and discharging to virtual energy storage is realized, so as to be adjusted a few days ago Spend stage reduction microgrid operating cost；In the daytime the amendment stage is that building room temperature is adjusted in the range of temperature pleasant degree The microgrid interconnection setting value of generation is dispatched in section, tracking a few days ago, so as to stabilize by dominant eigenvalues caused by predicated error a few days ago Fluctuation；

2-1) a few days ago in scheduling phase,

2-1-1) object function：

Regulation goal function is set to operating cost minimum to the building microgrid of the system containing virtual energy storage a few days ago, and its object function is such as Under：

In formula (4)：

Section 1 is the microgrid from the cost of power distribution network power purchase, P_ex,tThe electrical power exchanged for microgrid with power distribution network, unit For kW, power purchase is just, sale of electricity is negative；C_ph,tAnd C_se,tRespectively microgrid is sold from the price and microgrid of power distribution network power purchase to power distribution network The price of electricity；

Section 2 is the working service cost of each equipment in microgrid；P_PV,tAnd P_EC,tRespectively t photovoltaic is exerted oneself and freezed Electric power；C_{PV_om}And C_{EC_om}The working service cost of photovoltaic and electric refrigerating machine unit interval unit power is represented respectively；

N represents the scheduling slot sum in a complete dispatching cycle；

2-1-2) constraints：

Electric refrigerating machine is to consume the equipment that electric energy provides cold energy, is divided into screw according to the different electric refrigerating machines of working method Electric refrigerating machine, centrifugal electric refrigerating machine, compression electric refrigerating machine and piston type electric refrigerating machine；The refrigeration work consumption of electric refrigerating machine is about Shown in beam such as formula (5)：

Q_EC,t=P_EC,t×COP_EC (5)

In formula (5)：Q_EC,tExported for the refrigeration work consumption of electric refrigerating machine；P_EC,tThe electrical power consumed for electric refrigerating machine；COP_EC For the Energy Efficiency Ratio of electric refrigerating machine；

Electrical power Constraints of Equilibrium：

P_ex,t+P_PV,t=P_el,t+P_EC,t (6)

P in formula (6)_el,tFor the electric load of t；

Refrigeration duty Constraints of Equilibrium：

Q_EC,t=Q_{cl,building,t} (7)

Building thermal balance is constrained：

Δ t is the time interval of building equation of heat balance differencing in formula (8)；

The constraint of various kinds of equipment itself：

In formula (9)WithP_ex Respectively microgrid exchanges the upper and lower bound of power with power distribution network,WithP_EC Respectively make The upper and lower bound of cold power；

Building indoor temperature bound is constrained：

In formula (10)WithT_in The respectively upper limit and lower limit of building indoor temperature.

2-2) in the stage of amendment in the daytime,

2-2-1) object function：

Optimization aim setting is followed the trail of dispatches given microgrid interconnection setting value a few days ago, and object function is shown in formula (11)：

In formula (11),For t-th of moment building microgrid dispatching generation a few days ago work(is exchanged with higher level's power distribution network interconnection Rate dispatch command (the P in corresponding (4)_ex,t), the Scheduling Optimization Model a few days ago being made up of formula (4)~(11) is determined；P′_ex,tFor In the daytime the realtime power that t-th of moment building microgrid is exchanged with higher level's power distribution network interconnection is dispatched, by the tune for correcting the stage in the daytime Spend schemes generation；

2-2-2) constraints

Electric refrigerating machine is to consume the equipment that electric energy provides cold energy, is divided into screw according to the different electric refrigerating machines of working method Electric refrigerating machine, centrifugal electric refrigerating machine, compression electric refrigerating machine and piston type electric refrigerating machine；The refrigeration work consumption of electric refrigerating machine is about Shown in beam such as formula (12)：

Q_EC,t=P_EC,t×COP_EC (12)

Electrical power Constraints of Equilibrium：

P_ex,t+P_PV,t=P_el,t+P_EC,t (13)

Refrigeration duty Constraints of Equilibrium：

Q_EC,t=Q_{cl,building,t} (14)

Building thermal balance is constrained：

The constraint of various kinds of equipment itself：

Building indoor temperature bound is constrained：

Step 3: Multiple Time Scales Optimization scheduling algorithm

Double-deck in the daytime correction algorithm of the Multiple Time Scales Optimization scheduling algorithm comprising upper strata scheduling and lower layer-management, In the scheduling of upper strata, the dominant eigenvalues given in operation plan a few days ago and real-time measurement data in the daytime are primarily based on, passes through and solves In the daytime optimal scheduling model obtains the building refrigeration demand that virtual energy storage participates in correcting in the daytime；It is subsequently based in bottom management system The refrigeration demand that the virtual energy storage system of biography is not involved in a few days correcting in scheduling phase in the daytime, virtual energy storage is obtained according to formula (3) The set point of system charge-discharge electric power operation, so that schedule virtual energy-storage system follows the trail of the microgrid interconnection in operation plan a few days ago Power set point, to stabilize by interconnection tie power fluctuation caused by predicated error a few days ago；Idiographic flow is as follows：

1) system initialization：Scheduling phase a few days ago is set according to actual building micro-grid system and user's request and repaiied in the daytime The optimization aim of positive stage building microgrid and dispatching cycle, if dispatch a few days ago in optimization aim be building microgrid operating cost most It is small, as shown in formula (4), in correcting in the daytime, the dominant eigenvalues instruction followed the trail of dispatch a few days ago in is set to optimization aim, such as formula (11) shown in；

2) dispatch a few days ago：Exerted oneself according to building microgrid load, regenerative resource, outdoor environment and indoor airflow obtain heat day Before predict the outcome, by solving the operation plan a few days ago of Optimal Operation Model generation a few days ago；

3) system mode is updated：System mode is updated according to measured data in the daytime, the measured data in the daytime includes building Microgrid load, regenerative resource are exerted oneself, outdoor environment and indoor airflow obtain heat；

4) correct in the daytime：By the way that building room temperature is adjusted in the range of building indoor temperature comfort level, realize to void Intend the management of charging and discharging of energy storage, given microgrid interconnection setting value is dispatched a few days ago so as to track, microgrid interconnection is stabilized in realization The target of power swing；

Step 4: Optimized Operation is solved, scheduling scheme is obtained, instructs building microgrid to run

Multiple Time Scales Optimized Operation scheme is carried based on step 3 under MATLAB software environments, while calling CPLEX The optimized mathematical model that above-mentioned steps two are constituted is solved, building microgrid containing virtual energy storage is obtained a few days ago and in the daytime Operation result, realizes the purpose of optimized operation.

Compared with prior art, the beneficial effects of the invention are as follows：

Building microgrid Multiple Time Scales Optimization Scheduling of the invention containing virtual energy storage, first with summer in building microgrid Exemplified by cooling load, using the thermal storage effect of building, the virtual energy storage model based on building is constructed.Then, propose that one kind contains The building microgrid Multiple Time Scales Optimization Scheduling of virtual energy storage system, by the range of temperature pleasant degree to building room temperature It is adjusted, realizes the management of charging and discharging of virtual energy storage, from a few days ago/tune is optimized to building microgrid on Multiple Time Scales in the daytime Degree.The characteristics of building microgrid Multiple Time Scales Optimization Scheduling of the present invention containing virtual energy storage, is as follows：

1) equation of heat balance based on building, indoor temperature and refrigeration work consumption and the external world are constructed from the angle of the conservation of energy Quantitative mathematical relation between ambient conditions, and then construct the virtual energy storage model based on building；

2) the virtual energy storage system integration of building has been arrived in microgrid Optimized Operation Mathematical Modeling, while by temperature pleasant degree It is added in optimization constraint, the discharge and recharge optimum management of virtual energy storage is realized, so as to reduce the fortune of microgrid to a certain extent Row cost；

3) the virtual energy storage system integration of building has been arrived in building microgrid Multiple Time Scales Optimized Operation Mathematical Modeling, led to Cross and optimize regulation to building room temperature in the range of temperature pleasant degree, realize the management of charging and discharging to virtual energy storage, so that The microgrid operating cost of scheduling phase reduction a few days ago；The microgrid interconnection setting of generation is dispatched a few days ago in the stage tracking of amendment in the daytime Value, effectively stabilizes by interconnection tie power fluctuation caused by predicated error a few days ago.

To sum up, the building microgrid Multiple Time Scales Optimization Scheduling of the invention containing virtual energy storage can relax ensureing temperature The virtual energy storage potentiality that building participate in the operation of microgrid economic optimization are fully excavated on the premise of appropriateness, in the reduction of scheduling phase a few days ago The operating cost of building microgrid；Microgrid interconnection tie power fluctuation caused by being stabilized in the amendment stage in the daytime by predicated error a few days ago.

Brief description of the drawings

Fig. 1 is a kind of exemplary refrigerant building microgrid structure chart；

Fig. 2 is building microgrid Multiple Time Scales Optimization Scheduling FB(flow block) in the present invention；

Fig. 3 is embodiment intensity of illumination and outdoor temperature in the present invention；

Fig. 4 is embodiment microgrid daily load and distributed power source power curve in the present invention；

Fig. 5 is embodiment Spot Price a few days ago in the present invention；

Fig. 6 is electric energy optimizing scheduling result a few days ago；

Fig. 7 is Optimized Operation result of freezing a few days ago；

Fig. 8 is electric energy optimizing scheduling result in the daytime；

Fig. 9 is Optimized Operation result of freezing in the daytime；

Figure 10 is building microgrid dominant eigenvalues；

Embodiment

Technical solution of the present invention is described in further detail with specific embodiment below in conjunction with the accompanying drawings, described is specific Only the present invention is explained for embodiment, is not intended to limit the invention.

The present invention shows typical building micro-grid system for Fig. 1, using the thermal storage effect of building, and constructing fusion needs The building microgrid Optimization Scheduling of side virtual energy storage system is sought, is comprised the following steps：

Step 1: setting up building virtual energy storage system model

Thermal storage effect based on building, the equation of heat balance of building is obtained according to the conservation of energy, such as formula (1)：

In formula (1)：Δ Q is the variable quantity of indoor heat, and unit is J/s；ρ is atmospheric density, and unit is kg/m³；C is sky Gas specific heat capacity, unit is J/ (kg DEG C)；The rate of change of indoor temperature is multiplied by the quality of room air multiplied by with its specific heat capacity, etc. In the variable quantity of indoor heat；V is room air volume, and unit is m³；

The principal element of influence interior of building heat has：The cold heat that indoor/outdoor temperature-difference is caused dissipates, sun heat radiation, The cooling/heating power output of human body and equipment heating and cooling/heating equipment in building.By taking cooling in summer as an example, formula (1) can be with It is expressed as formula (2)：

In formula (2), the equal sign left side：

Section 1 (k_wall×F_wall×(T_out-T_in)) external wall and the heat of outdoor transmission are represented, unit is kW；Its In, k_wallFor the heat transfer coefficient of external wall, unit is W/ (m²K), when representing steady state heat transfer, each list of indoor and outdoor temperature difference The heat of wall is transmitted through in bits per second；F_wallFor external wall area, unit is m²；(T_out-T_in) it is that indoor and outdoor temperature is poor, it is single Position is K；

Section 2 (k_win×F_win×(T_out-T_in)) external window of building and the heat of outdoor transmission are represented, unit is kW：Wherein k_winFor the heat transfer coefficient of external window of building, unit is W/ (m²·K)；F_winFor the area of external window of building, unit is m²；

Section 3 I × F_win× SC represents the heat of sun heat radiation transmission, and unit is kW, and wherein I is solar radiation work( Rate, unit is kW/m², represent the heat that every square of metre per second (m/s) receives during with illumination vertical irradiation；SC is shading coefficient, its value With whether having sunshading board, glass material etc. relevant；Q_inFor the heating power of indoor airflow, unit is kW：Including human body and electricity consumption The heating of equipment；Q_clFor the refrigeration work consumption of refrigeration plant, unit is kW；

The mathematical relationship of building indoor temperature and refrigerating device refrigeration power can be obtained according to formula (2).Accordingly, it is considered to arrive The thermal storage effect of building, the refrigeration demand (equal with the refrigeration work consumption of refrigeration plant) or indoor temperature of building can be according to temperature The requirement of degree comfort level is adjusted within the specific limits, so as to externally show the energy storage discharge and recharge spy similar to energy-storage system Property.Shown in the charge-discharge electric power such as formula (3) of virtual energy storage system based on building：

Q_VSS,t=Q '_{cl,building,t}-Q_{cl,building,t} (3)

In formula (3)：Q_VSS,tFor the charge-discharge electric power of virtual energy storage system, unit is kW, discharges just, to be charged as bearing； Q′_{cl,building,t}Not adjust the building refrigeration electrical power requirements of indoor temperature, unit is kW；Q_{cl,building,t}To consider in temperature The building refrigeration electrical power requirements of regulation indoor temperature in the range of comfort level are spent, unit is kW；

Step 2: building building microgrid layering energy management framework

Carried in the present invention building microgrid Optimized Operation be divided into a few days ago economic optimization scheduling and in the daytime in real time amendment two when Between yardstick.Scheduling phase is that building room temperature is adjusted in the range of temperature pleasant degree a few days ago, and realization is filled to virtual energy storage Electric discharge management, so as to reduce microgrid operating cost in scheduling phase a few days ago；In the daytime the amendment stage is in the range of temperature pleasant degree Building room temperature is adjusted, the microgrid interconnection setting value of generation is dispatched in tracking a few days ago, so as to stabilize by predicated error a few days ago Caused interconnection tie power fluctuation.By building layering energy management framework, so as to effectively management virtual energy storage system Charge-discharge electric power, makes it participate in the Optimized Operation of building microgrid.

2-1) dispatch a few days ago：

2-1-1) object function

Regulation goal function is set to operating cost minimum to the building microgrid of the system containing virtual energy storage a few days ago, and its object function is such as Under：

In formula (4)：

Section 1 is the microgrid from the cost of power distribution network power purchase, P_ex,tThe electrical power exchanged for microgrid with power distribution network, unit For kW, power purchase is just, sale of electricity is negative；C_ph,tAnd C_se,tRespectively microgrid is sold from the price and microgrid of power distribution network power purchase to power distribution network The price of electricity.

Section 2 is the working service cost of each equipment in microgrid.P_PV,tAnd P_EC,tRespectively t photovoltaic is exerted oneself and freezed Electric power.C_{PV_om}And C_{EC_om}The working service cost of photovoltaic and electric refrigerating machine unit interval unit power is represented respectively.

N represents the scheduling slot sum in a complete dispatching cycle；

2-1-2) constraints

Electric refrigerating machine is to consume the equipment that electric energy provides cold energy, can be divided into screw electricity refrigeration according to the difference of working method Machine, centrifugal electric refrigerating machine, compression electric refrigerating machine and piston type electric refrigerating machine etc..It is (following with compression electric refrigerating machine Abbreviation electric refrigerating machine) exemplified by, its refrigeration work consumption is constrained as shown in formula (5)：

Q_EC,t=P_EC,t×COP_EC (5)

In formula (5)：Q_EC,tExported for the refrigeration work consumption of electric refrigerating machine；P_EC,tThe electrical power consumed for electric refrigerating machine；COP_EC For the Energy Efficiency Ratio of electric refrigerating machine.

Electrical power Constraints of Equilibrium：

P_ex,t+P_PV,t=P_el,t+P_EC,t (6)

P in formula (6)_el,tFor the electric load of t.

Refrigeration duty Constraints of Equilibrium：

Q_EC,t=Q_{cl,building,t} (7)

Building thermal balance is constrained：

Δ t is the time interval of building equation of heat balance differencing in formula (8)；

The constraint of various kinds of equipment itself：

In formula (9)WithP_ex Respectively microgrid exchanges the upper and lower bound of power with power distribution network,WithP_EC Respectively make The upper and lower bound of cold power；

Building indoor temperature bound is constrained：

In formula (10)WithT_in The respectively upper limit and lower limit of building indoor temperature.

2-2) correct in the daytime：

2-2-1) object function

Building microgrid is correcting the stage in the daytime, by being managed to virtual energy storage system charge-discharge electric power, and tracking is a few days ago The given microgrid interconnection setting value of scheduling, reduction predicts the outcome the deviation of (load and distributed power source) a few days ago, so as to stabilize The fluctuation of microgrid dominant eigenvalues.Optimization aim setting is followed the trail of dispatches given microgrid interconnection setting value, object function a few days ago See formula (11)：

In formula (11),For t-th of moment building microgrid dispatching generation a few days ago work(is exchanged with higher level's power distribution network interconnection Rate dispatch command (the P in corresponding (4)_ex,t), the Scheduling Optimization Model a few days ago being made up of formula (4)~(11) is determined；P′_ex,tFor In the daytime the realtime power that t-th of moment building microgrid is exchanged with higher level's power distribution network interconnection is dispatched, by the tune for correcting the stage in the daytime Spend schemes generation.

2-2-2) constraints

Electric refrigerating machine is to consume the equipment that electric energy provides cold energy, is divided into screw according to the different electric refrigerating machines of working method Electric refrigerating machine, centrifugal electric refrigerating machine, compression electric refrigerating machine and piston type electric refrigerating machine；The refrigeration work consumption of electric refrigerating machine is about Shown in beam such as formula (12)：

Q_EC,t=P_EC,t×COP_EC (12)

Electrical power Constraints of Equilibrium：

P_ex,t+P_PV,t=P_el,t+P_EC,t (13)

Refrigeration duty Constraints of Equilibrium：

Q_EC,t=Q_{cl,building,t} (14)

Building thermal balance is constrained：

The constraint of various kinds of equipment itself：

Building indoor temperature bound is constrained：

Step 3: Multiple Time Scales Optimization scheduling algorithm

It is as shown in Figure 2 that the present invention carries building microgrid Multiple Time Scales optimized algorithm.Optimization scheduling algorithm includes passing through a few days ago Ji Optimized Operation and in the daytime two stages of real-time amendment.In order to which effective schedule virtual energy-storage system participates in correcting in the daytime, bag is proposed Double-deck correction algorithm in the daytime containing upper strata scheduling and lower layer-management.Upper strata dispatch in, be primarily based in operation plan a few days ago to Fixed dominant eigenvalues and in the daytime real-time measurement data, obtain virtual energy storage by solving optimal scheduling model in the daytime and participate in the daytime The building refrigeration demand of amendment；The virtual energy storage system for being subsequently based on the upload of bottom management system is not involved in scheduling phase in the daytime The refrigeration demand in a few days corrected, the set point of virtual energy storage system charge-discharge electric power operation is obtained according to formula (3), so as to dispatch void Plan energy-storage system follows the trail of the microgrid dominant eigenvalues set point in operation plan a few days ago, to stabilize by caused by predicated error a few days ago Interconnection tie power fluctuation.

Idiographic flow is as follows：

1) system initialization：Scheduling phase a few days ago is set according to actual building micro-grid system and user's request and repaiied in the daytime The optimization aim of positive stage building microgrid and dispatching cycle, if optimization aim is that building microgrid operating cost is minimum dispatch a few days ago in (see formula (4)), in correcting in the daytime, optimization aim is set to (see formula by the dominant eigenvalues instruction followed the trail of dispatch a few days ago in (11))。

2) dispatch a few days ago：Exerted oneself according to building microgrid load, regenerative resource, outdoor environment and indoor airflow obtain heat day Before predict the outcome, by solving the operation plan a few days ago of Optimal Operation Model generation a few days ago；

3) system mode is updated：According to measured data in the daytime, (building microgrid load, regenerative resource are exerted oneself, outdoor environment And indoor airflow obtains heat), update system mode；

4) correct in the daytime：By the way that building room temperature is adjusted in the range of building indoor temperature comfort level, realize to void Intend the management of charging and discharging of energy storage, given microgrid interconnection setting value is dispatched a few days ago so as to track, microgrid interconnection is stabilized in realization The target of power swing.

Step 4: Optimized Operation is solved, scheduling scheme is obtained, instructs building microgrid to run

Multiple Time Scales Optimized Operation scheme is carried based on step 3 under MATLAB software environments, while calling CPLEX The optimized mathematical model that above-mentioned steps two are constituted is solved, building microgrid containing virtual energy storage is obtained a few days ago and in the daytime Operation result, realizes the purpose of optimized operation.

Embodiment：For the scheduling of building microgrid Multiple Time Scales Optimization Scheduling formation of the present invention containing virtual energy storage As a result analyzed.

1st, basic data

Multiple Time Scales Optimized Operation analysis in the daytime a few days ago is carried out to building microgrid in Fig. 1.Prediction data is dispatched a few days ago For hour level prediction data, it is 15min DBMSs that measured data is dispatched in the daytime.Building is set as that only office is built in building microgrid Build, long 30m, wide 20m, floor height 3m, totally three layers.External wall is laid bricks using 190mm single row of holes, the adiabatic mortars of inside and outside 25mm；Window Family is PVC material plastic windows, and glass is ordinary insulating glass.Building relevant parameter is shown in Table 1.Example chooses northern China summer One typical day, intensity of solar radiation curve and outdoor temperature is predicted a few days ago and in a few days test data is shown in Fig. 3.

The architectural modulus information table of table 1

The shading coefficient of angular relationship, part exterior window back of the body sun and glass in view of sun direct projection direction and external window of building Etc. factor, I is approximately taken_tF_winSC is 0.45I_tF_win.Atmospheric density ρ and air specific heat capacity C take 1.2kg/m respectively³And 1000J/ (kg·℃).If user's office hours is 8:00 to 20:00, the heating of building endogenous pyrogen is main to be generated heat two parts by equipment and human body Composition.To fully demonstrate effect of the building virtual energy storage in building microgrid Optimized Operation, the prominent photovoltaic at high proportion of the present invention connects Enter the influence that building micro-grid system is brought, set photovoltaic power generation capacity scale to be higher than general under equal refrigerant system capacity scale The photovoltaic power generation capacity scale of logical building.A certain typical daylight volt prediction/measured curve, day conventional electricity consumption (without refrigeration electricity consumption) Prediction/measured curve and building endogenous pyrogen prediction/measured curve are as shown in Figure 4.

The Spot Price a few days ago used a few days ago in Optimized Operation is as shown in Figure 5.Electricity price is the price from power network power purchase in figure, A certain coefficient is multiplied by as sale of electricity price using the price during sale of electricity, it is 0.8 that the coefficient is taken herein.Microgrid exchanges work(with power distribution network power network The bound of rate is respectively ± 400kW.Equipment relevant parameter is shown in Table 2 in microgrid.The present invention calls CPLEX under MATLAB environment Carried building microgrid Multiple Time Scales Optimal Operation Model is solved.

The building microgrid device parameter of table 2

2nd, dispatch a few days ago

Building microgrid is a few days ago in operation plan, if user operationally between can receive temperature ± the 2.5 of design temperature Fluctuated in the range of DEG C, the design temperature of user is 22.5 DEG C, and the non-working time is to indoor temperature no requirement (NR).Containing virtual energy storage Optimized Operation result is shown in Fig. 6 and Fig. 7 to building microgrid a few days ago.

Exerted oneself between can be seen that electric refrigerating machine operationally from Fig. 6 results.Within the subsequent office hours, Indoor Temperature Degree is fluctuated above and below 22.5 DEG C of set points, and the electrical power of electric refrigerating machine consumption also follows the change of indoor temperature and changed.From Fig. 7 As a result as can be seen that virtual energy storage system operationally between participate in building microgrid Optimized Operation a few days ago, by user's temperature Indoor temperature is adjusted in the range of comfort level the management of charging and discharging for carrying out virtual energy storage system, so as to drop to a certain extent The operating cost of lowrise space microgrid.By simulation calculation, the operation of the building microgrid of virtual energy storage Optimized Operation a few days ago is not introduced Cost is 602.4 yuan, and the operating cost for introducing the building microgrid of virtual energy storage Optimized Operation a few days ago is 578.7 yuan, compared to not The Optimized Operation operating cost for introducing virtual energy storage declines 3.93%.

Scheduling numerical results show a few days ago, can by the way that building room temperature is adjusted in the range of user's temperature pleasant degree To be managed in scheduling phase a few days ago to the charge-discharge electric power of virtual energy storage system, so that reduction building are micro- to a certain extent The operating cost of net.

3rd, correct in the daytime

From Fig. 3 and Fig. 4, building microgrid load, photovoltaic are exerted oneself, intensity of illumination, outdoor temperature and indoor airflow obtain hot There is error in the prediction data of amount, with actual metric data, it is necessary to right in correcting in the daytime in actual moving process in the daytime Power instruction is adjusted, and given microgrid interconnection setting value is dispatched a few days ago so as to track, and microgrid interconnection work(is stabilized in realization The target of rate fluctuation.The scheduling result that virtual energy storage participation building microgrid is corrected in the daytime is shown in Fig. 8 and Fig. 9.Can from Fig. 8 results Go out, significant change occur in electric refrigerating machine power and indoor temperature, namely adjust adjustable virtual energy storage system by indoor temperature Charge-discharge electric power, stabilize the target of microgrid interconnection tie power fluctuation so as to be realized in the in a few days amendment stage.

It will be seen from figure 9 that the stage is corrected in the daytime in bottom management, based on the building room generated in operation plan a few days ago Interior temperature dispatch command and in the daytime measured data, the virtual energy storage system mathematic model according to constructed by formula (2), which is calculated, obtains void Intend the refrigeration demand (see the solid black lines in Fig. 9) that energy-storage system is not involved in a few days correcting in actual motion in the daytime, and transmit System is dispatched to upper strata.In being dispatched on upper strata, virtual energy storage participation is obtained in the daytime by solving amendment optimal scheduling model in the daytime The building refrigeration demand of amendment (see the black dotted lines in Fig. 9)；It is subsequently based on the virtual energy storage system of bottom management system upload The refrigeration demand corrected in the daytime is not involved in, the set point of virtual energy storage system charge-discharge electric power operation is obtained according to formula (3).

As can be seen from Figure 9 virtual energy storage is introduced to after correcting in the daytime, and the refrigeration demand load of building is with without virtual storage Fluctuated up and down on the basis of refrigeration demand load curve during energy.The part for being higher by benchmark is cold-storage, i.e., " charge "；Less than the portion of benchmark It is divided into and lets cool, i.e., " discharges ".The difference of building refrigeration demand load is the virtual energy storage system based on building in the case of two kinds Charge-discharge electric power (formula (3)), as shown in black histogram in Fig. 9.

Multiple Time Scales Optimization Scheduling is carried for stabilizing the effect of microgrid interconnection tie power fluctuation for the checking present invention Really, setting the following two kinds contrast scene：

Scene one：According to operation plan a few days ago, amendment in real time is carried out in the daytime to system.The virtual energy storage system of scene one is not joined With correcting in real time in the daytime, when occurring in system due to the caused electricity/cold power shortage of predicated error a few days ago, all with electric energy It is used as the supplement energy.The dominant eigenvalues dispatched in the daytime under the scene are as shown in Figure 10；

Scene two：According to operation plan a few days ago, it is considered to which virtual energy storage system is that regulation goal participates in repairing in the daytime with formula (11) Just, gained microgrid dominant eigenvalues result is as shown in Figure 10.

Scene one and scene two are contrasted, is not difficult to find out, by being participated in the scheduling in the daytime of virtual energy storage charge-discharge electric power In the daytime correct, the interconnection power tracking effect of scene two is better than scene one, so that the interconnection tie power fluctuation of building microgrid There is a certain degree of reduction.By the way that building room temperature is adjusted in the range of user's temperature pleasant degree, it can be adjusted in the daytime Spend stage tracking and dispatch given microgrid interconnection setting value a few days ago, so as to stabilize the fluctuation of microgrid dominant eigenvalues.

Although above in conjunction with accompanying drawing, invention has been described, and the invention is not limited in above-mentioned specific implementation Mode, above-mentioned embodiment is only schematical, rather than restricted, and one of ordinary skill in the art is at this Under the enlightenment of invention, without deviating from the spirit of the invention, many variations can also be made, these belong to the present invention's Within protection.

Claims (1)

1. a kind of building microgrid Multiple Time Scales Optimization Scheduling containing virtual energy storage, it is characterised in that comprise the following steps：

Step 1: setting up building virtual energy storage system model：

Thermal storage effect based on building, the equation of heat balance of building is obtained according to the conservation of energy, as follows：

$\mathrm{\Δ}Q=\mathrm{\ρ}\×C\×V\×\frac{{\mathrm{dT}}_{in}}{d\mathrm{\τ}}---\left(1\right)$

In formula (1)：Δ Q is the variable quantity of indoor heat, and unit is J/s；ρ is atmospheric density, and unit is kg/m³；C is air ratio Thermal capacitance, unit is J/ (kg DEG C)；V is room air volume, and unit is m³；

Influence the factor of interior of building heat at least：The cold heat that indoor/outdoor temperature-difference is caused dissipates, sun heat radiation, building The cooling/heating power output of interior human body and equipment heating and cooling/heating equipment, above-mentioned formula (1) is rewritten as follows：

$\begin{array}{c}{k}_{wall}\×F_{wall}\×(T_{out}-T_{in})+k_{win}\×F_{win}\×(T_{out}-T_{in})\\ +I\×F_{win}\×SC+Q_{in}-Q_{cl}=\mathrm{\ρ}\×C\×V\×\frac{{\mathrm{dT}}_{in}}{d\mathrm{\τ}}\end{array}---\left(2\right)$

In formula (2), the equal sign left side：

Section 1 (k_wall×F_wall×(T_out-T_in)) external wall and the heat of outdoor transmission are represented, unit is kW；Wherein, k_wallFor the heat transfer coefficient of external wall, unit is W/ (m²K), when representing steady state heat transfer, indoor and outdoor temperature difference per unit is every The heat of wall is transmitted through in second；F_wallFor external wall area, unit is m²；(T_out-T_in) poor for indoor and outdoor temperature, unit is K；

Section 2 (k_win×F_win×(T_out-T_in)) external window of building and the heat of outdoor transmission are represented, unit is kW：Wherein k_winFor The heat transfer coefficient of external window of building, unit is W/ (m²·K)；F_winFor the area of external window of building, unit is m²；

Section 3 I × F_win× SC represents the heat of sun heat radiation transmission, and unit is kW, and wherein I is solar radiation power, single Position is kW/m², represent the heat that every square of metre per second (m/s) receives during with illumination vertical irradiation；SC is shading coefficient, and its value is with being It is no to have sunshading board, glass material etc. relevant；Q_inFor the heating power of indoor airflow, including：The heating of human body and electrical equipment, it is single Position is kW；Q_clFor the refrigeration work consumption of refrigeration plant, unit is kW；

The charge-discharge electric power of virtual energy storage system based on building is as follows：

Q_VSS,t=Q '_{cl,building,t}-Q_{cl,building,t} (3)

In formula (3)：Q_VSS,tFor the charge-discharge electric power of virtual energy storage system, unit is kW, discharges just, to be charged as bearing； Q′_{cl,building,t}Not adjust the building refrigeration electrical power requirements of indoor temperature, unit is kW；Q_{cl,building,t}To consider in temperature The building refrigeration electrical power requirements of regulation indoor temperature in the range of comfort level are spent, unit is kW；

Step 2: building building microgrid layering energy management framework

Building microgrid Optimized Operation includes scheduling phase a few days ago and corrects the stage in real time in the daytime, and the scheduling phase a few days ago is in temperature Building room temperature is adjusted in the range of degree comfort level, the management of charging and discharging to virtual energy storage is realized, so as to dispatch rank a few days ago Section reduction microgrid operating cost；In the daytime the amendment stage is that building room temperature is adjusted in the range of temperature pleasant degree, with Track dispatches the microgrid interconnection setting value of generation a few days ago, so as to stabilize by interconnection tie power fluctuation caused by predicated error a few days ago；

2-1) a few days ago in scheduling phase,

2-1-1) object function：

Regulation goal function is set to operating cost minimum to the building microgrid of the system containing virtual energy storage a few days ago, and its object function is as follows：

$\begin{array}{c}min\underset{t=1}{\overset{N}{\Σ}}\{(\frac{C_{ph,t}+C_{se,t}}{2}{P}_{ex,t}+\frac{C_{ph,t}-C_{se,t}}{2}|P_{ex,t}\left|\right)\\ +(P_{PV,t}{C}_{PV\_om}+P_{EC,t}{C}_{EC\_om})\}\end{array}---\left(4\right)$

In formula (4)：

Section 1 is the microgrid from the cost of power distribution network power purchase, P_ex,tThe electrical power exchanged for microgrid with power distribution network, unit is kW, Power purchase is just, sale of electricity is negative；C_ph,tAnd C_se,tRespectively valency of the microgrid from the price and microgrid of power distribution network power purchase to power distribution network sale of electricity Lattice；

Section 2 is the working service cost of each equipment in microgrid；P_PV,tAnd P_EC,tRespectively t photovoltaic is exerted oneself and freezed electromechanics Power；C_{PV_om}And C_{EC_om}The working service cost of photovoltaic and electric refrigerating machine unit interval unit power is represented respectively；

N represents the scheduling slot sum in a complete dispatching cycle；

2-1-2) constraints：

Electric refrigerating machine is to consume the equipment that electric energy provides cold energy, is divided into screw electricity system according to the different electric refrigerating machines of working method Cold, centrifugal electric refrigerating machine, compression electric refrigerating machine and piston type electric refrigerating machine；The refrigeration work consumption constraint of electric refrigerating machine is such as Shown in formula (5)：

Q_EC,t=P_EC,t×COP_EC (5)

In formula (5)：Q_EC,tExported for the refrigeration work consumption of electric refrigerating machine；P_EC,tThe electrical power consumed for electric refrigerating machine；COP_ECFor electricity system The Energy Efficiency Ratio of cold；

Electrical power Constraints of Equilibrium：

P_ex,t+P_PV,t=P_el,t+P_EC,t (6)

P in formula (6)_el,tFor the electric load of t；

Refrigeration duty Constraints of Equilibrium：

Q_EC,t=Q_{cl,building,t} (7)

Building thermal balance is constrained：

$\begin{array}{c}\mathrm{\Δ}t\[k_{wall}{F}_{wall}(T_{out,t}-T_{in,t})+k_{win}{F}_{win}(T_{out,t}-T_{in,t})\\ +I_t{F}_{win}SC+Q_{in,t}-Q_{EC,t}\]-\mathrm{\ρ}CV(T_{in,t+1}-T_{in,t})=0\end{array}---\left(8\right)$

Δ t is the time interval of building equation of heat balance differencing in formula (8)；

The constraint of various kinds of equipment itself：

$\left\{\begin{array}{c}\underset{\&OverBar;}{P_{ex}}<P_{ex,t}<\stackrel{\&OverBar;}{P_{ex}}\\ \underset{\&OverBar;}{P_{EC}}<P_{EC,t}<\stackrel{\&OverBar;}{P_{EC}}\end{array}\right.---\left(9\right)$

In formula (9)WithP_ex Respectively microgrid exchanges the upper and lower bound of power with power distribution network,WithP_EC Respectively refrigeration machine work( The upper and lower bound of rate；

Building indoor temperature bound is constrained：

$\underset{\&OverBar;}{T_{in}}<T_{in,t}<\stackrel{\&OverBar;}{T_{in}}---\left(10\right)$

In formula (10)WithT_in The respectively upper limit and lower limit of building indoor temperature；

2-2) in the stage of amendment in the daytime,

2-2-1) object function：

Optimization aim setting is followed the trail of dispatches given microgrid interconnection setting value a few days ago, and object function is shown in formula (11)：

$min\left\{\right|P_{ex,t}^{\&prime;}-P_{ex,t}^{set}\left|\right\}---\left(11\right)$

In formula (11),To dispatch t-th of the moment building microgrid and higher level's power distribution network Tie line Power tune of generation a few days ago Degree instruction (the P in corresponding (4)_ex,t), the Scheduling Optimization Model a few days ago being made up of formula (4)~(11) is determined；P′_ex,tFor in the daytime The realtime power that t-th of moment building microgrid is exchanged with higher level's power distribution network interconnection is dispatched, by the dispatching party for correcting the stage in the daytime Case is generated；

2-2-2) constraints

The refrigeration work consumption of electric refrigerating machine is constrained as shown in formula (12)：

Q_EC,t=P_EC,t×COP_EC (12)

Electrical power Constraints of Equilibrium：

P_ex,t+P_PV,t=P_el,t+P_EC,t (13)

Refrigeration duty Constraints of Equilibrium：

Q_EC,t=Q_{cl,building,t} (14)

Building thermal balance is constrained：

$\begin{array}{c}\mathrm{\&Delta;}t\&lsqb;k_{wall}{F}_{wall}(T_{out,t}-T_{in,t})+k_{win}{F}_{win}(T_{out,t}-T_{in,t})\\ +I_t{F}_{win}SC+Q_{in,t}-Q_{EC,t}\&rsqb;-\mathrm{\&rho;}CV(T_{in,t+1}-T_{in,t})=0\end{array}---\left(15\right)$

The constraint of various kinds of equipment itself：

$\left\{\begin{array}{c}\underset{\&OverBar;}{P_{ex}}<P_{ex,t}<\stackrel{\&OverBar;}{P_{ex}}\\ \underset{\&OverBar;}{P_{EC}}<P_{EC,t}<\stackrel{\&OverBar;}{P_{EC}}\end{array}\right.---\left(16\right)$

Building indoor temperature bound is constrained：

$\underset{\&OverBar;}{T_{in}}<T_{in,t}<\stackrel{\&OverBar;}{T_{in}}---\left(17\right)$

Step 3: Multiple Time Scales Optimization scheduling algorithm

Double-deck in the daytime correction algorithm of the Multiple Time Scales Optimization scheduling algorithm comprising upper strata scheduling and lower layer-management, on upper strata In scheduling, the dominant eigenvalues given in operation plan a few days ago and real-time measurement data in the daytime are primarily based on, by solving in the daytime Optimal scheduling model obtains the building refrigeration demand that virtual energy storage participates in correcting in the daytime；It is subsequently based on the upload of bottom management system The refrigeration demand that virtual energy storage system is not involved in a few days correcting in scheduling phase in the daytime, virtual energy storage system is obtained according to formula (3) The set point of charge-discharge electric power operation, so that schedule virtual energy-storage system follows the trail of the microgrid dominant eigenvalues in operation plan a few days ago Set point, to stabilize by interconnection tie power fluctuation caused by predicated error a few days ago；Idiographic flow is as follows：

1) system initialization：Scheduling phase a few days ago is set according to actual building micro-grid system and user's request and rank is corrected in the daytime The optimization aim of Duan Louyu microgrids and dispatching cycle, if optimization aim is that building microgrid operating cost is minimum dispatch a few days ago in, such as Shown in formula (4), in correcting in the daytime, the dominant eigenvalues instruction followed the trail of dispatch a few days ago in is set to optimization aim, such as formula (11) It is shown；

2) dispatch a few days ago：Exerted oneself according to building microgrid load, regenerative resource, that outdoor environment and indoor airflow obtain heat is a few days ago pre- Result is surveyed, by solving the operation plan a few days ago of Optimal Operation Model generation a few days ago；

3) system mode is updated：System mode is updated according to measured data in the daytime, the measured data in the daytime includes building microgrid Load, regenerative resource are exerted oneself, outdoor environment and indoor airflow obtain heat；

4) correct in the daytime：By the way that building room temperature is adjusted in the range of building indoor temperature comfort level, realize to virtual storage The management of charging and discharging of energy, given microgrid interconnection setting value is dispatched so as to track a few days ago, and microgrid dominant eigenvalues are stabilized in realization The target of fluctuation；

Step 4: Optimized Operation is solved, scheduling scheme is obtained, instructs building microgrid to run

Multiple Time Scales Optimized Operation scheme is carried based on step 3 under MATLAB software environments, while calling CPLEX to upper The optimized mathematical model for stating step 2 composition is solved, and obtains the operation of building microgrid a few days ago and in the daytime containing virtual energy storage As a result, the purpose of optimized operation is realized.