CN105931136A - Building micro-grid optimization scheduling method with demand side virtual energy storage system being fused - Google Patents

Abstract

The invention discloses a building micro-grid optimization scheduling method with a demand side virtual energy storage system being fused. The method comprises constructing a microgrid system model; constructing a building virtual energy storage system model based on building heat storage feature; integrating the virtual energy storage system to a building micro-grid optimization scheduling model, and through optimization regulation of building indoor temperature within a temperature comfort range, establishing an optimization scheduling objective function; after selecting optimization scheduling constraint conditions, calling CPLEX for optimization scheduling solving under a MATLAB software environment; and finally, obtaining a CCHP (combined supply of cooling, heating and power) building micro-grid optimization scheduling scheme and realizing charge/discharge management of the building virtual energy storage system. The building micro-grid optimization scheduling method with the demand side virtual energy storage system being fused can fully explore virtual energy storage potential of a building participating in microgrid economic optimization operation under the condition of ensuring temperature comfort level, thereby improving comprehensive energy utilization efficiency of a micro-grid assistantly, and reducing operation cost of the micro-grid to some extent.

Description

A kind of building microgrid Optimization Scheduling merging Demand-side virtual energy storage system

Technical field

The present invention relates to micro power source network optimizationization run, specifically, relate to a kind of supply of cooling, heating and electrical powers merging virtual energy storage system Building microgrid Optimization Scheduling.

Background technology

Along with the development of renewable energy utilization technology in recent years, increasing distributing-supplying-energy system is at building side collection Become, define the micro-grid system based on building, provide multiple low-carbon (LC) solution for building energy supply.Supply of cooling, heating and electrical powers Building microgrid (hereinafter referred microgrid) is by by regenerative resource, supply of cooling, heating and electrical powers (Combined cooling, heating and Power system, CCHP), energy-storage system and correlation technique be integrated in building energy supplying system the multiple-energy-source formed and combine confession Can system.The optimal scheduling scheme of microgrid is formulated in configuration according to the internal each unit of microgrid, carries out comprehensive energy in microgrid Coordination optimization and management, can realize various energy resources complementation, the utilization of fully dissolving of regenerative resource, reduce microgrid operating cost.

Demand-side controllable burden (air-conditioning, water heater, refrigerator, electric automobile etc.) has the method for operation, and flexibly and flexibility is controlled Feature, can need directly to be controlled by control centre its duty according to system, or utilize economic measure (such as Spot Price) Induction user selectively changes its energy-consuming mode, reaches dsm (demand side management, DSM) Purpose.Document carries out demand management respectively to controllable burdens such as temperature control load, electric automobiles, thus it is bent to reach to optimize load The purposes such as line, peak load shifting and mains frequency control, and user can be maintained as much as possible higher at one by energy comfort level Level.In building microgrid, due to the effect of heat insulation of the building enclosures such as building construction body of wall, indoor with outdoor heat exchange Process is relatively slow, and indoor temperature will not change rapidly relative to electric characteristic amount.Therefore, can in the period that electricity price is relatively low To heat for building/to freeze in advance, it is also possible to reduce electricity in the period that electricity price is higher and heat/refrigeration work consumption, make building to microgrid Show the charge-discharge characteristic being similar to energy-storage system, thus on the premise of not fail temperature comfort level, improve building microgrid fortune The economy of row.

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Summary of the invention

The present invention as a example by summer cooling load, utilizes the thermal storage effect of building, constructs the virtual storage of building in building microgrid Can model.Then, a kind of building microgrid Optimization Scheduling merging Demand-side virtual energy storage system is proposed, by temperature In the range of comfort level, building room temperature is adjusted, it is achieved the management of charging and discharging to virtual energy storage, reduces the operating cost of microgrid. The present invention, on the basis of existing microgrid Optimized Operation research work, excavates the virtual energy storage potentiality of Demand-side building further, auxiliary Help lifting microgrid comprehensive energy utilization ratio.

In order to solve above-mentioned technical problem, a kind of building microgrid optimization merging Demand-side virtual energy storage system that the present invention proposes Dispatching method, comprises the following steps:

Step one, micro-grid system model, including

1-1) miniature gas turbine

Shown in miniature gas turbine output such as formula (1):

P_MT,t=P_gas×η_MT (1)

In formula (1): P_MT,tFor the output of miniature gas turbine, unit is kW；P_gasConsume for miniature gas turbine Natural gas power, unit is kW；η_MTGenerating efficiency for miniature gas turbine；

1-2) Absorption Refrigerator

Absorption Refrigerator is driven by the waste heat of miniature gas turbine, shown in its refrigeration work consumption such as formula (2):

Q_AC,t=η_HE×γ_MT×P_MT,t×COP_AC (2)

In formula (2): Q_AC,tRefrigeration work consumption for Absorption Refrigerator exports, and unit is kW；γ_MTFor miniature gas turbine Hotspot stress；η_HEEfficiency for heat-exchanger rig；COP_ACEnergy Efficiency Ratio for Absorption Refrigerator；

1-3) electric refrigerating machine

Electric refrigerating machine freezes by consuming electric energy, shown in its refrigeration work consumption such as formula (3):

Q_EC,t=P_EC,t×COP_EC (3)

In formula (3): Q_EC,tRefrigeration work consumption for electric refrigerating machine exports, and unit is kW；P_EC,tThe electric work consumed for electric refrigerating machine Rate, unit is kW；COP_ECEnergy Efficiency Ratio for electric refrigerating machine；

Step 2, building virtual energy storage system modelling

Thermal storage effects based on building, obtain the equation of heat balance of building, such as formula (4) according to preservation of energy:

$\mathrm{\Δ}Q=\mathrm{\ρ}\×C\×V\×\frac{{\mathrm{dT}}_{in}}{d\mathrm{\τ}}---\left(4\right)$

In formula (4): 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 empty 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 and is multiplied by its specific heat capacity again, etc. Variable quantity in indoor heat；V is room air volume, and unit is m³；

During cooling in summer, equation of heat balances based on building build the virtual energy storage system model of building, expression formula such as formula (5):

$\begin{array}{c}{k}_{wall}\×F_{wall}\×(T_{out}-T_{in})+k_{win}\×F_{win}\×(T_{out}-T_{in})\\ +I\×F_{win}\×SC+Q_{in}-Q_{cl}=\mathrm{\ρ}\×C\×V\×\frac{{\mathrm{dT}}_{in}}{d\mathrm{\τ}}\end{array}---\left(5\right)$

The equal sign left side in formula (5):

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

Section 2 (k_win×F_win×(T_out-T_in)) representing external window of building and the heat of outdoor transmission, unit is kW: wherein k_winFor building Building the heat transfer coefficient of exterior window, 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 that sun heat radiation transmits, and unit is kW, and wherein I is solar radiation power, Unit is kW/m², represent and the heat of every square metre of acceptance per second during illumination vertical irradiation；

SC is shading coefficient: its value is 0-1；

Q_inFor the heating power of indoor airflow, unit is kW: include the heating of human body and electrical equipment；

Q_clFor the refrigeration work consumption of refrigeration plant, unit is kW；

Obtain the mathematical relationship of building indoor temperature and refrigerating device refrigeration power according to formula (5), and relax according to user indoor temperature Building refrigeration demand is adjusted by the scope of appropriateness；

Shown in the charge-discharge electric power such as formula (6) of virtual energy storage systems based on building:

Q_VSS,t=Q '_{cl,building,t}-Q_{cl,building,t} (6)

In formula (6): Q_VSS,tFor the charge-discharge electric power of virtual energy storage system, unit is kW, discharges for just, is charged as bearing；Q′_{cl,building,t} For not regulating the building refrigeration electrical power requirements of indoor temperature, unit is kW；Q_{cl,building,t}For considering in temperature pleasant degree scope The building refrigeration electrical power requirements of interior regulation indoor temperature, unit is kW；

Step 3, Optimized Operation object function build

Building virtual energy storage system model is integrated in the Optimum Regulation model of building microgrid, considers that building user can connect simultaneously The temperature regulating range being subject to, builds the economic optimization scheduling model of building microgrid；Wherein, the type of building microgrid includes electricity system Cold type building microgrid and combined cooling and power type building microgrid, the equipment of described electricity refrigeration type building microgrid includes photovoltaic, wind Machine, accumulator and electric refrigerating machine, the equipment of described combined cooling and power type building microgrid includes photovoltaic, blower fan, accumulator, micro- Type gas turbine and Absorption Refrigerator；

The object function of the economic optimization scheduling model after 3-1) electricity refrigeration type building microgrid merges virtual energy storage system is:

$\begin{array}{c}\min \underset{t=1}{\overset{N}{\Σ}}\{(\frac{C_{ph,t}+C_{se,t}}{2}{P}_{ex,t}+\frac{C_{ph,t}-C_{se,t}}{2}|P_{\mathrm{ex},t}\left|\right)\\ +(P_{WT,t}{C}_{WT\_om}+P_{PV,t}{C}_{PV\_om}\\ +\left|P_{bt,t}\right|C_{bt\_om}+P_{EC,t}{C}_{EC\_om})+\mathrm{\γ}|T_{in,t}-T_{set}\left|\right\}\end{array}---\left(7\right)$

In formula (7):

Section 1 is this microgrid cost from power distribution network power purchase, P_ex,tFor the electrical power of microgrid with power distribution network exchange, unit is kW, Power purchase is just, sale of electricity is negative；

Section 2 is the working service cost of all devices in this microgrid, P_WT,t、P_PV,t、P_bt,tAnd P_EC,tIt is respectively t wind Machine is exerted oneself, photovoltaic is exerted oneself, accumulator cell charging and discharging power and electric refrigerating machine electrical power, and unit is kW；Wherein, P_bt,t For battery discharging just, P_bt,tIt is accumulator charging for bearing；C_{WT_om}、C_{PV_om}、C_{bt_om}And C_{EC_om}Represent wind respectively Machine, photovoltaic, accumulator and the working service cost of electric refrigerating machine unit interval section unit power, unit is unit/kWh；

Section 3 is to affect the penalty function item that user's temperature pleasant degree sets, and γ is penalty factor, unit be unit/DEG C, this penalty factor It is considered as user's sensitivity to temperature pleasant degree, this penalty factor is defined as user sensitivity coefficient γ；Penalty function item sets It is multiplied by t indoor actual temperature T for γ_in,tDeviation design temperature T_setDifference；User sensitivity coefficient γ is according to different User's sensitivity selects, and the value of γ is 0-+ ∞；

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

The object function of the economic optimization scheduling model after 3-2) combined cooling and power type building microgrid merges virtual energy storage system is:

$\begin{array}{c}\min \underset{t=1}{\overset{N}{\Σ}}\{(\frac{C_{ph,t}+C_{se,t}}{2}{P}_{ex,t}+\frac{C_{ph,t}-C_{se,t}}{2}|P_{ex,t}\left|\right)\\ +(P_{WT,t}{C}_{WT\_om}+P_{PV,t}{C}_{PV\_om}+|P_{bt,t}|C_{bt\_om}\\ +P_{MT,t}{C}_{MT\_om}+{\mathrm{\γ}}_{MT}{P}_{MT,t}{C}_{AC\_om})\\ +C_{gas}{P}_{gas}+\mathrm{\γ}|T_{in,t}-T_{set}|\}\end{array}---\left(8\right)$

In formula (8):

Section 2 is the working service cost of all devices in this microgrid；P_WT,t、P_PV,t、P_bt,tAnd P_MT,tIt is respectively t Blower fan is exerted oneself, photovoltaic is exerted oneself, accumulator cell charging and discharging power and miniature gas turbine, and unit is kW；C_{MC_om}Represent micro- The working service cost of type gas turbine unit interval section unit power, unit is unit/kWh；

Section 3 is the cost that microgrid buys natural gas, P_gas,tBuying natural gas power for microgrid, unit is kW；C_gasFor purchasing Buying the price of natural gas, unit is unit/kWh；

Step 4, Optimized Operation constraints are chosen

The constraints of the Optimal Operation Model after 4-1) electricity refrigeration type building microgrid merges Demand-side virtual energy storage includes:

4-1-1) electrical power Constraints of Equilibrium:

P_ex+P_WT+P_PV+P_bt=P_el+P_EC (9)

P in formula (9)_elElectric load for t；

4-1-2) refrigeration duty Constraints of Equilibrium:

Q_EC=Q_cl,building (10)

4-1-3) building thermal balance constraint:

The building virtual energy storage system model expressed by the differential equation in formula (5) is carried out differencing process, is formed by difference equation Building thermal balance constraint equation (11) expressed

$\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(11\right)$

4-1-4) in microgrid structure, accumulator and the constraint of electric refrigerating machine self and power distribution network power purchase retrain, including:

Accumulator and the power of electric refrigerating machine and power distribution network power purchase constraint satisfaction bound retrain:

$\left\{\begin{array}{c}\underset{\&OverBar;}{P_{ex}}<P_{ex}<\stackrel{\&OverBar;}{P_{ex}}\\ \underset{\&OverBar;}{P_{bt}}<P_{bt}<\stackrel{\&OverBar;}{P_{bt}}\\ \underset{\&OverBar;}{P_{EC}}<P_{EC}<\stackrel{\&OverBar;}{P_{EC}}\end{array}\right.---\left(12\right)$

Battery power storage amount retrains: as shown in formula (13) and (14), and electricity energy storage at a whole story dispatching cycle Constraints of Equilibrium, as Shown in formula (15):

$\underset{\&OverBar;}{W_{bt}}<W_{bt,t}=W_{bt\left(0\right)}-\underset{i=1}{\overset{t}{\&Sigma;}}{P}_{bt,i}{\mathrm{\&eta;}}_{bt}\mathrm{\&Delta;}t<\stackrel{\&OverBar;}{W_{bt}}---\left(13\right)$

${\mathrm{\&eta;}}_{bt}=\left\{\begin{array}{cc}{\mathrm{\&eta;}}_{ch}& P_{bt,i}\&le;0\\ 1/{\mathrm{\&eta;}}_{dis}& P_{bt,i}>0\end{array}\right.---\left(14\right)$

In formula (13) and formula (14), W_bt,tRepresenting the electricity of accumulator t, unit is kW；W_bt(0)Initial for accumulator Electricity, unit is kW；η_ch, η_disEfficiency for charge-discharge for accumulator；In the whole day of microgrid is dispatched, accumulator is because of self discharge And the energy loss produced is ignored；

$\underset{t=1}{\overset{N}{\&Sigma;}}{P}_{bt,t}=0---\left(15\right)$

4-1-5) building indoor temperature bound constraint:

$\underset{\&OverBar;}{T_{in}}<T_{in,t}<\stackrel{\&OverBar;}{T_{in}}---\left(16\right)$

The constraints of the Optimal Operation Model after 4-2) combined cooling and power type building microgrid merges Demand-side virtual energy storage includes:

4-2-1) electrical power Constraints of Equilibrium:

P_ex,t+P_WT,t+P_PV,t+P_MT,t+P_bt,t-P_el,t=0 (17)

4-2-2) refrigeration duty Constraints of Equilibrium:

Q_AC,t=Q_{cl,building,t} (18)

4-2-3) building thermal balance constraint:

The building virtual energy storage system model expressed by the differential equation in formula (5) is carried out differencing process, is formed by difference equation Building thermal balance constraint equation (19) expressed

$\begin{array}{c}{k}_{wall}{F}_{wall}(T_{out,t}-T_{in,t})+k_{win}{F}_{win}(T_{out,t}-T_{in,t})\\ +I_t{F}_{win}SC+Q_{in,t}-Q_{AC,t}-\mathrm{\&rho;}CV(T_{in,t+1}-T_{in,t})=0\end{array}---\left(19\right)$

4-2-4) constraint and the power distribution network power purchase of microgrid structure self retrains, including:

Accumulator and the power of miniature gas turbine and power distribution network power purchase constraint satisfaction bound retrain:

$\left\{\begin{array}{c}\underset{\&OverBar;}{P_{ex}}<P_{ex}<\stackrel{\&OverBar;}{P_{ex}}\\ \underset{\&OverBar;}{P_{MT}}<P_{MT,t}<\stackrel{\&OverBar;}{P_{MT}}\\ \underset{\&OverBar;}{P_{bt}}<P_{bt}<\stackrel{\&OverBar;}{P_{bt}}\end{array}\right.---\left(20\right)$

The constraint of battery power storage amount is identical with battery power storage amount constraint in electricity refrigeration type building microgrid: such as formula (13) and (14) Shown in, and electricity energy storage at a whole story dispatching cycle Constraints of Equilibrium, as shown in formula (15)；

4-2-5) building indoor temperature bound constraint:

$\underset{\&OverBar;}{T_{in}}<T_{in,t}<\stackrel{\&OverBar;}{T_{in}}---\left(21\right)$

Step 5, Optimized Operation solve, and obtain scheduling scheme, instruct building microgrid to run

The optimized mathematical model that above-mentioned steps three and step 4 are collectively formed by CPLEX is called under MATLAB software environment Solve, respectively obtain electricity refrigeration type building microgrid and combined cooling and power type building microgrid merges Demand-side virtual energy storage After Optimized Operation scheme；Based on the scheduling scheme obtained, arrange electricity refrigeration type building microgrid and combined cooling and power type respectively Building microgrid runs, thus reaches the purpose of optimized operation.

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

The present invention merges the building microgrid Optimization Scheduling of Demand-side virtual energy storage system, is primarily based on building thermal storage effect, Construct a kind of virtual energy storage system model；And then, by the virtual energy storage system integration to building microgrid Optimal Operation Model, By building room temperature being optimized regulation in the range of temperature pleasant degree, it is achieved the charge and discharge fulgurite to building virtual energy storage system Reason；Last as a example by cooling in summer scene, two kinds of typical building microgrid examples are carried out economic optimization lexical analysis.The present invention The feature of the building microgrid Optimization Scheduling merging Demand-side virtual energy storage system is as follows:

1) equation of heat balances based on building, construct indoor temperature and refrigeration work consumption and external environment from the angle of preservation of energy Quantitative mathematical relation between situation, and then construct virtual energy storage model based on building；

2) the virtual energy storage system integration of building has been arrived in microgrid Optimized Operation mathematical model, temperature pleasant degree has been added simultaneously To optimizing in constraint, it is achieved the discharge and recharge optimum management of virtual energy storage, thus the operation that can reduce microgrid to a certain extent becomes This；

3) introduce user's sensitivity coefficient, and in economic load dispatching target, consider the punishment added because affecting user's comfortableness , the different user sensitivity coefficient of relative analysis simultaneously is to virtual energy storage charge-discharge electric power and the shadow of microgrid economic operation cost Ring；

4) virtual energy storage system is compared with actual energy storage device charge-discharge characteristic, and it is poor to analyze its charge-discharge characteristic Different Producing reason；The relation of relative analysis two types building microgrid virtual energy storage characteristic and Spot Price, and explain The two is charge and discharge process difference Producing reason under Spot Price guides.

To sum up, the present invention merge Demand-side virtual energy storage system building microgrid Optimization Scheduling can ensure temperature pleasant Fully excavate building on the premise of degree and participate in the virtual energy storage potentiality that microgrid economic optimization runs, can reduce micro-to a certain extent Network operation cost.

Accompanying drawing explanation

Fig. 1 (a) is electricity refrigeration type building microgrid structure chart；

Fig. 1 (b) is supply of cooling, heating and electrical powers type building microgrid structure chart；

Fig. 2 is embodiment intensity of illumination and outdoor temperature curve in the present invention；

Fig. 3 is that in the present invention, embodiment microgrid daily load and distributed power source are exerted oneself prediction curve；

Fig. 4 is that the electricity price with New York, United States typical case's day summer is to guide the Spot Price with energy behavior of building；

Fig. 5 is the electric refrigeration type microgrid Optimized Operation result not introducing virtual energy storage；

Fig. 6 is introduced into the electric refrigeration type microgrid Optimized Operation result of virtual energy storage；

Fig. 7 is electricity refrigeration type microgrid virtual energy storage Optimized Operation result；

Fig. 8 is electricity refrigeration type microgrid virtual energy storage discharge and recharge and electricity price relation；

Fig. 9 is the user indoor temperature situation of change under different user sensitivity coefficient γ value；

Figure 10 is the building virtual energy storage system charge-discharge electric power under different user sensitivity coefficient γ value；

Figure 11 is the supply of cooling, heating and electrical powers type microgrid Optimized Operation result not introducing virtual energy storage；

Figure 12 is introduced into the supply of cooling, heating and electrical powers type microgrid Optimized Operation result of virtual energy storage；

Figure 13 is supply of cooling, heating and electrical powers type microgrid virtual energy storage Optimized Operation result；

Figure 14 is supply of cooling, heating and electrical powers type microgrid virtual energy storage discharge and recharge and electricity price relation.

Detailed description of the invention

A kind of present invention that the present invention proposes as a example by summer cooling load, utilizes the thermal storage effect of building, structure in building microgrid Build the virtual energy storage model of building.Then, a kind of building microgrid Optimized Operation merging Demand-side virtual energy storage system is proposed Method, by building room temperature being adjusted in the range of temperature pleasant degree, it is achieved the management of charging and discharging to virtual energy storage, fall The operating cost of low microgrid.The present invention, on the basis of existing microgrid Optimized Operation research work, excavates Demand-side building further Virtual energy storage potentiality, service hoisting microgrid comprehensive energy utilization ratio.

Being described in further detail technical solution of the present invention with specific embodiment below in conjunction with the accompanying drawings, described is embodied as The present invention is only explained by example, not in order to limit the present invention.

The present invention is directed to Fig. 1 (a) and Fig. 1 (b) and show two kinds of typical building micro-grid systems, wherein, Fig. 1 (a) is electricity refrigeration Type building microgrid structure chart, the equipment of described electricity refrigeration type building microgrid includes photovoltaic, blower fan, accumulator and electricity refrigeration Machine；Fig. 1 (b) is supply of cooling, heating and electrical powers type building microgrid structure chart, and the equipment of described combined cooling and power type building microgrid includes light Volt, blower fan, accumulator, miniature gas turbine and Absorption Refrigerator.Utilizing the thermal storage effect of building, constructing fusion needs Seek the building microgrid Optimization Scheduling of side virtual energy storage system, comprise the following steps:

For Fig. 1 (a) and Fig. 1 (b), step one, first, shows that two kinds of typical building micro-grid systems carry out system model and build Vertical, constructing system model is as follows:

1-1) miniature gas turbine

Shown in miniature gas turbine output such as formula (1):

P_MT,t=P_gas×η_MT (1)

In formula (1): P_MT,tFor the output of miniature gas turbine, unit is kW；P_gasConsume for miniature gas turbine Natural gas power, unit is kW；η_MTGenerating efficiency for miniature gas turbine；

1-2) Absorption Refrigerator

Absorption Refrigerator is driven by the waste heat of miniature gas turbine, shown in its refrigeration work consumption such as formula (2):

Q_AC,t=η_HE×γ_MT×P_MT,t×COP_AC (2)

In formula (2): Q_AC,tRefrigeration work consumption for Absorption Refrigerator exports, and unit is kW；γ_MTFor miniature gas turbine Hotspot stress；η_HEEfficiency for heat-exchanger rig；COP_ACEnergy Efficiency Ratio for Absorption Refrigerator；

1-3) electric refrigerating machine

Electric refrigerating machine freezes by consuming electric energy, shown in its refrigeration work consumption such as formula (3):

Q_EC,t=P_EC,t×COP_EC (3)

In formula (3): Q_EC,tRefrigeration work consumption for electric refrigerating machine exports, and unit is kW；P_EC,tThe electric work consumed for electric refrigerating machine Rate, unit is kW；COP_ECEnergy Efficiency Ratio for electric refrigerating machine.

Step 2, building virtual energy storage system modelling

Show that the building virtual energy storage system in two kinds of typical building micro-grid systems is built for Fig. 1 (a) and Fig. 1 (b) Mould.

Present invention thermal storage effect based on building, obtains the equation of heat balance of building according to preservation of energy^[1][2], such as formula (4):

$\mathrm{\&Delta;}Q=\mathrm{\&rho;}\&times;C\&times;V\&times;\frac{{\mathrm{dT}}_{in}}{d\mathrm{\&tau;}}---\left(4\right)$

In formula (4): 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 empty 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 and is multiplied by its specific heat capacity again, etc. Variable quantity in indoor heat；V is room air volume, and unit is m³；

The principal element affecting interior of building heat has: the cold heat that indoor/outdoor temperature-difference causes dissipates, sun heat radiation, building The cooling/heating power output of interior human body and equipment heating and cooling/heating equipment.As a example by cooling in summer, formula (4) can be expressed For formula (5), i.e. based on building equation of heat balances build the virtual energy storage system model of building, expression formula such as formula (5):

$\begin{array}{c}{k}_{wall}\&times;F_{wall}\&times;(T_{out}-T_{in})+k_{win}\&times;F_{win}\&times;(T_{out}-T_{in})\\ +I\&times;F_{win}\&times;SC+Q_{in}-Q_{cl}=\mathrm{\&rho;}\&times;C\&times;V\&times;\frac{{\mathrm{dT}}_{in}}{d\mathrm{\&tau;}}\end{array}---\left(5\right)$

The equal sign left side in formula (5):

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

Section 2 (k_win×F_win×(T_out-T_in)) representing external window of building and the heat of outdoor transmission, unit is kW: wherein k_winFor building Building the heat transfer coefficient of exterior window, 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 that sun heat radiation transmits, and unit is kW, and wherein I is solar radiation power, Unit is kW/m², represent and the heat of every square metre of acceptance per second during illumination vertical irradiation；

SC is shading coefficient: its value is 0-1, concrete numerical value with whether have sunshading board and glass material etc. relevant^[3]；

Q_inFor the heating power of indoor airflow, unit is kW: include the heating of human body and electrical equipment；

Q_clFor the refrigeration work consumption of refrigeration plant, unit is kW；

Equation of heat balances based on building construct the virtual energy storage system model of building.Building indoor temperature is obtained according to formula (5) With the mathematical relationship of refrigerating device refrigeration power, accordingly, it is considered to arrive the thermal storage effect of building, the refrigeration demand of building is (with refrigeration The refrigeration work consumption of equipment is equal) or indoor temperature can be adjusted within the specific limits according to the requirement of temperature pleasant degree, from And externally show the energy storage charge-discharge characteristic being similar to energy-storage system, participate in the economic optimization scheduling of building microgrid.Base In shown in the charge-discharge electric power such as formula (6) of the virtual energy storage system of building:

Q_VSS,t=Q '_{cl,building,t}-Q_{cl,building,t} (6)

In formula (6): Q_VSS,tFor the charge-discharge electric power of virtual energy storage system, unit is kW, discharges for just, is charged as bearing；Q′_{cl,building,t} For not regulating the building refrigeration electrical power requirements of indoor temperature, unit is kW；Q_{cl,building,t}For considering in temperature pleasant degree scope The building refrigeration electrical power requirements of interior regulation indoor temperature, unit is kW.

Step 3, Optimized Operation object function build

The building virtual energy storage system optimization scheduling in two kinds of typical building micro-grid systems is shown for Fig. 1 (a) and Fig. 1 (b) Mathematical model build.Building virtual energy storage system model is integrated in the Optimum Regulation model of building microgrid, considers simultaneously The acceptable temperature regulating range of building user, builds the economic optimization scheduling model of building microgrid.Building microgrid economic optimization The main target of scheduling is that run minimized cost on the basis of ensureing user's temperature pleasant degree.Therefore its object function has Two parts form, and one is Financial cost, and two is the punishment that user brings because Thermal comfort is not satisfied, wherein economic one-tenth This includes again the working service cost of each equipment in purchases strategies and microgrid.

Electricity refrigeration type building microgrid shown in Fig. 1 (a) merges the object function of the economic optimization scheduling model after virtual energy storage system For:

$\begin{array}{c}\min \underset{t=1}{\overset{N}{\&Sigma;}}\{(\frac{C_{ph,t}+C_{se,t}}{2}{P}_{ex,t}+\frac{C_{ph,t}-C_{se,t}}{2}|P_{\mathrm{ex},t}\left|\right)\\ +(P_{WT,t}{C}_{WT\_om}+P_{PV,t}{C}_{PV\_om}\\ +\left|P_{bt,t}\right|C_{bt\_om}+P_{EC,t}{C}_{EC\_om})+\mathrm{\&gamma;}|T_{in,t}-T_{set}\left|\right\}\end{array}---\left(7\right)$

In formula (7): Section 1 is this microgrid cost from power distribution network power purchase.P_ex,tThe electrical power exchanged with power distribution network for microgrid, Unit is kW, and power purchase is just, sale of electricity is negative.Section 2 is the working service cost of all devices in this microgrid.P_WT,t、 P_PV,t、P_bt,tAnd P_EC,tIt is respectively that t blower fan is exerted oneself, photovoltaic is exerted oneself, accumulator cell charging and discharging power and electric refrigerating machine electric work Rate, unit is kW；Wherein, P_bt,tFor battery discharging just, P_bt,tIt is accumulator charging for bearing；C_{WT_om}、C_{PV_om}、 C_{bt_om}And C_{EC_om}Represent blower fan, photovoltaic, accumulator and the working service of electric refrigerating machine unit interval section unit power respectively Cost, unit is unit/kWh.Section 3 is to affect the penalty function item that user's temperature pleasant degree sets^[4], γ is penalty factor, single Position be first/DEG C, the present invention can be considered user's sensitivity to temperature pleasant degree, and this penalty factor is defined as user sensitivity system Number γ.Penalty function item of the present invention is set as that γ is multiplied by t indoor actual temperature T_in,tDeviation design temperature T_setDifference；With Family sensitivity coefficient γ selects according to different user's sensitivity, and the value of γ is 0-+ ∞；Can be seen that γ is the biggest, virtual The punishment that energy storage brings will be the biggest；Otherwise the punishment that virtual energy storage brings is less.In N represents a complete dispatching cycle Scheduling slot sum.In order to study the impact that user is brought by different γ-value, the present invention have selected a series of different γ-value Carry out simulation comparison analysis.N represents the scheduling slot sum in the complete dispatching cycle.

Compared to electricity refrigeration type building microgrid shown in Fig. 1 (a), the building microgrid of combined cooling and power type shown in Fig. 1 (b) eliminates electricity This electricity refrigeration link of refrigeration machine, in the flue gas that refrigeration duty mainly utilizes miniature gas turbine to discharge by Absorption Refrigerator Utilizing waste heat for refrigeration meets；Meanwhile, goddess of lightning's line too increases the P that exerts oneself of miniature gas turbine_MT.Compared to electricity shown in Fig. 1 (a) Refrigeration type building microgrid merges the object function of the economic optimization scheduling model after virtual energy storage system, cold electricity shown in Fig. 1 (b) In alliance type building microgrid economic optimization scheduling model, object function adds the combustion gas cost of miniature gas turbine (C_gasP_gas), miniature gas turbine use and maintenance cost (P_MT,tC_{MT_om}) and Absorption Refrigerator use and maintenance cost (γ_MTP_MT,tC_{AC_om}), eliminate the use and maintenance cost of electricity refrigeration simultaneously.Combined cooling and power type building microgrid economic optimization is adjusted Degree modeling process is similar to electricity refrigeration type microgrid, repeat no more, therefore, combined cooling and power type building microgrid merges virtual The object function of the economic optimization scheduling model after energy-storage system is:

$\begin{array}{c}\min \underset{t=1}{\overset{N}{\&Sigma;}}\{(\frac{C_{ph,t}+C_{se,t}}{2}{P}_{ex,t}+\frac{C_{ph,t}-C_{se,t}}{2}|P_{ex,t}\left|\right)\\ +(P_{WT,t}{C}_{WT\_om}+P_{PV,t}{C}_{PV\_om}+|P_{bt,t}|C_{bt\_om}\\ +P_{MT,t}{C}_{MT\_om}+{\mathrm{\&gamma;}}_{MT}{P}_{MT,t}{C}_{AC\_om})\\ +C_{gas}{P}_{gas}+\mathrm{\&gamma;}|T_{in,t}-T_{set}|\}\end{array}---\left(8\right)$

In formula (8): Section 2 is the working service cost of all devices in this microgrid；P_WT,t、P_PV,t、P_bt,tAnd P_MT,tRespectively Exert oneself for t blower fan, photovoltaic is exerted oneself, accumulator cell charging and discharging power and miniature gas turbine, and unit is kW；C_{MC_om} Representing the working service cost of miniature gas turbine unit interval section unit power, unit is unit/kWh；Section 3 is that microgrid is purchased Buy the cost of natural gas, P_gas,tBuying natural gas power for microgrid, unit is kW；C_gasFor buying the price of natural gas, single Position is unit/kWh.

Step 4, Optimized Operation constraints are chosen

Electricity refrigeration type building microgrid shown in Fig. 1 (a) merges the constraints bag of the Optimal Operation Model after Demand-side virtual energy storage Include:

1) electrical power Constraints of Equilibrium:

P_ex+P_WT+P_PV+P_bt=P_el+P_EC (9)

P in formula (9)_elElectric load for t；

2) refrigeration duty Constraints of Equilibrium:

Q_EC=Q_cl,building (10)

3) building thermal balance constraint:

Optimal load flow containing dynamic constrained is the differential equation and the optimization mathematical problem of algebraic equation mixing^[6].This type of generation Han differential The mathematical optimization problem of number equation (differential algebraic equations, DAE) can ask for time domain according to functional optimum theory Analytic solutions, it is also possible to the algebraically carrying out discretization processes, to ask for the algebraic solution along time domain discrete^[7].In view of in the present invention Building heat dissipates and the slow dynamic process of variations in temperature, the building equation of heat balance that can will be expressed by the differential equation in formula (5) Carry out differencing process, form building thermal balance constraint equation (11) expressed by difference equation, to realize building microgrid warp The simple of Ji optimization problem effectively solves.

$\begin{array}{c}\mathrm{\&Delta;}t\&lsqb;k_{wall}{F}_{wall}(T_{out,t}-T_{in,t})+k_{win}{F}_{win}(T_{out,t}-T_{in,t})\\ +I_t{F}_{win}SC+Q_{in,t}-Q_{EC,t}\&rsqb;-\mathrm{\&rho;}CV(T_{in,t+1}-T_{in,t})=0\end{array}---\left(11\right)$

Except the electrical power of microgrid balances and in addition to building thermal balance, also need to consider the constraint of various kinds of equipment self, including respectively setting The bound constraint of standby power, the charge-discharge electric power of energy storage device and energy storage capacity constraint.Each device constraints is as follows:

4) in microgrid structure, accumulator and the constraint of electric refrigerating machine self and power distribution network power purchase retrain, including:

Accumulator and the power of electric refrigerating machine and power distribution network power purchase constraint satisfaction bound retrain:

$\left\{\begin{array}{c}\underset{\&OverBar;}{P_{ex}}<P_{ex}<\stackrel{\&OverBar;}{P_{ex}}\\ \underset{\&OverBar;}{P_{bt}}<P_{bt}<\stackrel{\&OverBar;}{P_{bt}}\\ \underset{\&OverBar;}{P_{EC}}<P_{EC}<\stackrel{\&OverBar;}{P_{EC}}\end{array}\right.---\left(12\right)$

Additionally, accumulator is in the course of the work in addition to needing to consider the constraint of its maximum charge-discharge electric power, in addition it is also necessary to consider to store The constraint (as shown in formula (13) and (14)) of battery energy storage, and electricity energy storage at a whole story dispatching cycle Constraints of Equilibrium^[8][9](such as formula (15) shown in):

$\underset{\&OverBar;}{W_{bt}}<W_{bt,t}=W_{bt\left(0\right)}-\underset{i=1}{\overset{t}{\&Sigma;}}{P}_{bt,i}{\mathrm{\&eta;}}_{bt}\mathrm{\&Delta;}t<\stackrel{\&OverBar;}{W_{bt}}---\left(13\right)$

${\mathrm{\&eta;}}_{bt}=\left\{\begin{array}{cc}{\mathrm{\&eta;}}_{ch}& P_{bt,i}\&le;0\\ 1/{\mathrm{\&eta;}}_{dis}& P_{bt,i}>0\end{array}\right.---\left(14\right)$

W in formula_bt,tRepresenting the electricity of accumulator t, unit is kW；W_bt(0)For the initial quantity of electricity of accumulator, unit is kW；η_ch, η_disEfficiency for charge-discharge for accumulator.The general lead-acid accumulator moon, self-discharge rate was about 3%, complete at microgrid In it scheduling, the energy loss of accumulator can be ignored substantially^[5].Calculating therefore to simplify, the present invention have ignored accumulator and exists The energy loss produced because of self discharge in microgrid whole day Optimized Operation.

$\underset{t=1}{\overset{N}{\&Sigma;}}{P}_{bt,t}=0---\left(15\right)$

5) building indoor temperature bound constraint:

$\underset{\&OverBar;}{T_{in}}<T_{in,t}<\stackrel{\&OverBar;}{T_{in}}---\left(16\right)$

Indoor temperature upper lower limit value choose the effect that can directly affect building virtual energy storage.According to building virtual energy storage mathematical modulo Type understands, and indoor temperature range of accommodation is the biggest, and the effect of virtual energy storage should be the best, but the temperature pleasant degree of user is subject to simultaneously The impact arrived is the biggest.

Compared to electricity refrigeration type building microgrid shown in Fig. 1 (a), the building microgrid of combined cooling and power type shown in Fig. 1 (b) merges demand In the constraints of the Optimal Operation Model after the virtual energy storage of side, electrical power balance adds exerting oneself of miniature gas turbine, goes Fall the electrical power that electric refrigerating machine consumes.Electric refrigerating machine refrigeration work consumption (Q original in the constraint of building thermal balance_EC) become absorbing Refrigeration work consumption (the Q of formula refrigeration machine_AC).Equipment run constraint in add miniature gas turbine exert oneself bound constraint.Constraint Condition is made up of formula (17)～formula (20) and formula (12)～formula (15).Including:

1) electrical power Constraints of Equilibrium:

P_ex,t+P_WT,t+P_PV,t+P_MT,t+P_bt,t-P_el,t=0 (17)

2) refrigeration duty Constraints of Equilibrium:

Q_AC,t=Q_{cl,building,t} (18)

3) building thermal balance constraint:

The building virtual energy storage system model expressed by the differential equation in formula (5) is carried out differencing process, is formed by difference equation Building thermal balance constraint equation (19) expressed

$\begin{array}{c}{k}_{wall}{F}_{wall}(T_{out,t}-T_{in,t})+k_{win}{F}_{win}(T_{out,t}-T_{in,t})\\ +I_t{F}_{win}SC+Q_{in,t}-Q_{AC,t}-\mathrm{\&rho;}CV(T_{in,t+1}-T_{in,t})=0\end{array}---\left(19\right)$

Except the electrical power of microgrid balances and in addition to building thermal balance, also need to consider the constraint of various kinds of equipment self, including respectively setting The bound constraint of standby power, the charge-discharge electric power of energy storage device and energy storage capacity constraint.

4) constraint and the power distribution network power purchase of microgrid structure self retrains, including:

Accumulator and the power of miniature gas turbine and power distribution network power purchase constraint satisfaction bound retrain:

$\left\{\begin{array}{c}\underset{\&OverBar;}{P_{ex}}<P_{ex}<\stackrel{\&OverBar;}{P_{ex}}\\ \underset{\&OverBar;}{P_{MT}}<P_{MT,t}<\stackrel{\&OverBar;}{P_{MT}}\\ \underset{\&OverBar;}{P_{bt}}<P_{bt}<\stackrel{\&OverBar;}{P_{bt}}\end{array}\right.---\left(20\right)$

The constraint of battery power storage amount is identical with accumulator constraint in electricity refrigeration type building microgrid: as shown in formula (13) and (14), with And electricity energy storage at a whole story dispatching cycle Constraints of Equilibrium, as shown in formula (15).

5) building indoor temperature bound constraint:

$\underset{\&OverBar;}{T_{in}}<T_{in,t}<\stackrel{\&OverBar;}{T_{in}}---\left(21\right)$

Step 5, Optimized Operation solve, and obtain scheduling scheme, instruct building microgrid to run

The optimized mathematical model that above-mentioned steps three and step 4 are collectively formed by CPLEX is called under MATLAB software environment Solve, respectively obtain electricity refrigeration type building microgrid and combined cooling and power type building microgrid merges Demand-side virtual energy storage After Optimized Operation scheme；Based on the scheduling scheme obtained, arrange electricity refrigeration type building microgrid and combined cooling and power type respectively Building microgrid runs, thus reaches the purpose of optimized operation.

Embodiment: merge the scheduling knot that the building microgrid Optimization Scheduling of Demand-side virtual energy storage system is formed for the present invention Fruit is analyzed.

1, basic data

Respectively Fig. 1 (a) and Fig. 1 (b) is shown that two kinds of typical building microgrids carry out economic optimization lexical analysis.Consideration is carried out The economic optimization scheduling of one day, discontinuity surface when 15min takes.In two types building microgrid of the present invention, building sets For only office building, long 30m, wide 20m, floor height 3m, totally three layers.External wall uses 190mm single row of holes to lay bricks, Inside and outside 25mm thermal insulation mortar；Window is PVC material plastic window, and glass is ordinary insulating glass.Building relevant parameter is shown in Table 1^[10].Example chooses northern China a certain typical case's day in summer, and intensity of solar radiation curve and outdoor temperature are shown in Fig. 2.

Table 1 architectural modulus information table

Shading coefficient in view of sun direct projection direction and the angular relationship of external window of building, part exterior window back of the body sun and glass etc. because of Element, approximation takes I_tF_winSC is 0.45I_tF_win.Atmospheric density ρ and air specific heat capacity C take 1.2kg/m respectively³With 1000J/ (kg DEG C). If user's office hours is 8:00 to 20:00, the heating of building endogenous pyrogen is mainly made up of equipment and the human body two parts that generate heat.Certain One typical case's day wind-powered electricity generation prediction curve, photovoltaic prediction curve, day routine electricity consumption (without refrigeration electricity consumption) curve and building interior-heat Source curve is as shown in Figure 3.

Spot Price is a kind of important electricity price type demand response project^[11], its electricity price update cycle is shorter compared with tou power price, can Effectively to pass on electricity price signal, user is guided to change electricity consumption behavior, response microgrid running status change.Therefore, the present invention adopts Electricity price with New York, United States typical case's day summer^[12]Guide the use energy behavior of building, as shown in Figure 4.In figure electricity price be from The price of electrical network power purchase, is multiplied by a certain coefficient for sale of electricity price with this price during sale of electricity, and it is 0.8 that the present invention takes this coefficient.This Invention Gas Prices takes 1.58 yuan/m³, be converted into unit calorific value price be 0.16 yuan/(kWh) (heating value of natural gas GHV takes 35.56MJ/m³).Microgrid is respectively ± 400kW with the bound of power distribution network electrical network exchange power.Equipment relevant parameter in microgrid It is shown in Table 2.

2, for electricity refrigeration type building microgrid Optimized Operation interpretation of result as shown in Fig. 1 (a)

1) building virtual energy storage is not introduced

In the case of assuming not introduce virtual energy storage, the building temperature that sets of office hours (8:00 to 20:00) interior user as 22.5 DEG C, the non-working time is to temperature no requirement (NR).Optimized Operation result is as shown in Figure 5.

From Fig. 5 result it can be seen that in the case of not introducing virtual energy storage, electric refrigerating machine the most operationally between exert oneself, with Time quickly increase at 8:00 previous moment point consumption of electric power, to meet the refrigeration needs of working time at hand, with After office hours in, its electric power consumption follows the change of intensity of solar radiation and outdoor temperature substantially, makes indoor temperature protect Hold at user's set point.Charge status of battery follows electricity price change substantially, big and electric at user's power consumption in the daytime on the whole The moment that valency is high works in discharge condition, night electricity price low, user power utilization amount few period charging.Do not introduce virtual energy storage In the case of building microgrid day total operating cost be 949.8 yuan.

2) building virtual energy storage is introduced

Introduce virtual energy storage, if user operationally between can accept temperature design temperature ± 2.5 DEG C in the range of fluctuate, The design temperature of user is 22.5 DEG C.The sensitivity coefficient of user is set as γ=0.1.Optimized Operation result is as shown in Figure 6.

Table 2 building microgrid device parameter

From Fig. 6 result it can be seen that compare the Optimized Operation result not introducing virtual energy storage, after introducing virtual energy storage, microgrid Significant change is not had with the Power Exchange of power distribution network and the working condition of accumulator.And the electricity of (8:00 to 20:00) between operationally Refrigeration machine consumption of electric power and indoor temperature have significantly different, occur in that substantially fluctuation.In the case of Gai, building microgrid be always transported Row cost is 912.9 yuan, compares the Optimized Operation operating cost decline 3.89% not introducing virtual energy storage.Visible in introducing building In the case of space virtual energy storage, indoor temperature can be adjusted in the range of user's temperature pleasant degree, the day operation cost of microgrid Reduce the most to a certain extent.Can be seen that virtual energy storage system based on building can ensure that user is comfortable from optimum results The economic optimization scheduling of microgrid is participated in, it is possible to dynamically adjust electricity consumption behavior according to Spot Price, to a certain degree on the premise of degree Upper reduction microgrid operating cost.

3) virtual energy storage charge-discharge characteristic is analyzed

Fig. 7 gives the building refrigeration demand introducing virtual energy storage successively.After can be seen that introducing virtual energy storage, the system of building Cold demand load is by without fluctuating up and down on the basis of refrigeration demand load curve during virtual energy storage.The part exceeding benchmark is cold-storage, I.e. " charge "；Less than the part of benchmark for letting cool, i.e. " discharge ".In the case of two kinds, the difference of building refrigeration demand load is Virtual energy storage system charge-discharge electric power (formula (6)) based on building, as shown in Fig. 7 block diagram.

Owing to general lead-acid accumulator moon self-discharge rate is about 3%, the therefore energy loss of accumulator in the whole day scheduling of microgrid Substantially can ignore.Virtual energy storage system and the Optimized Operation result of actual energy-storage system (accumulator) in Fig. 6 in comparison diagram 7, Although the two all demonstrates the energy storage characteristic of charge and discharge, but still there is relatively big difference.First can be seen that virtual energy storage equipment not Energy trickle charge or electric discharge, its discharge and recharge frequency is far above accumulator.And the change that accumulator can follow electricity price is carried out continuously Discharge and recharge.Main cause is using common building as cold-storage device, and its energy dissipation dissipates very fast compared to battery, namely The self-discharge rate of virtual energy storage system is far above actual energy-storage system.And the building accumulation of heat obtained according to formula (5) equation of heat balance Amount, is affected very big by indoor/outdoor temperature-difference, illumination etc., and each moment is occurring considerable energy dissipation and temperature change. Therefore, in building virtual energy storage system, stored energy demand discharges to reach higher utilization ratio as early as possible, and if virtual storage Energy system is as routine electricity energy storage device, and continuously if " charging ", energy stored earlier above has also had not enough time to refrigeration and made With, dissipate the most voluntarily.

As it was previously stated, virtual energy storages based on building mainly utilize thermal storage effect and the electricity price gap the most in the same time of building, Freeze in advance during low electricity price, reduce refrigeration electricity consumption when high electricity price, thus save operating cost.Virtual energy storage discharge and recharge and electricity Valency relation is as shown in Figure 8.As can be seen from the figure virtual energy storage charge power is followed the change of electricity price and is changed: at electricity price point Moment before peak, i.e. the electricity price slope of curve become suddenly big moment, the usually moment of virtual energy storage charge power maximum, Freeze in advance in the moment that electricity price is relatively low, reduce electric cost；And the moment of virtual energy storage discharge power maximum is generally present in Than the electricity price spike moment a little later.

4) user's sensitivity impact analysis to virtual energy storage effect

Owing to user is different to the requirement of comfortableness, therefore invention introduces user sensitivity coefficient γ, and adjust at economic optimization Degree target considers the penalty term added because affecting user's comfortableness so that Optimized Operation can be to the different sensitivities of user Coefficient makes corresponding adjustment.

Fig. 9 illustrates the user indoor temperature situation of change under several different γ value.Virtual energy storage effect during γ=0.1 is obvious, Indoor temperature change generated in case is violent, and most of the time temperature all deviates 22.5 DEG C of user's setting farther out；During γ=0.3, indoor temperature Change relatively γ=0.1 time the most many, the most of the time is near design temperature 22.5 DEG C；During γ=0.5, temperature is only at electricity Valency amplitude of variation king-sized several time be carved with a little fluctuating.It addition, Figure 10 gives the virtual storage of building under different γ value Can system charge-discharge electric power.Therefrom it will be seen that γ-value is the biggest, the charge-discharge electric power of virtual energy storage system is the least, virtual energy storage Effect the most inconspicuous；Vice versa.

Building microgrid 24 hour operation cost is as shown in table 3 with the relation of γ-value.It will be seen that user's temperature pleasant degree can be to micro- Network operation cost brings impact.γ-value is the least, and virtual energy storage effect is the most obvious, and building microgrid 24 hour operation cost is the lowest；And γ Being worth the biggest, temperature pleasant degree is the highest, but the effect of virtual energy storage is the most inconspicuous, and building microgrid 24 hour operation cost is of a relatively high. When γ is the biggest, even if indoor temperature deviate from user, design temperature is the least, also can produce the biggest punishment in object function, Now in building Optimized Operation, virtual energy storage effect is relatively weak.

Table 3 building microgrid operating cost and γ-value relation

3, for combined cooling and power type building microgrid Optimized Operation interpretation of result as shown in Fig. 1 (b)

From electricity refrigeration type building microgrid different, combined cooling and power microgrid, its refrigeration duty all by CCHP with electricity determining by heat The mode of (following the thermal load, FTL) provides, and i.e. CCHP is premised on meeting cooling, consumes natural gas and enters Row generating, its generated energy is first supplied to microgrid load, sells to electrical network beyond part, and insufficient section is bought from electrical network.Due to The price of natural gas is constant, and therefore, electricity price is the highest, and combined cooling and power unit sale of electricity profit is the biggest.Therefore with miniature gas The virtual energy storage charge-discharge characteristic of the combined cooling and power microgrid that turbine is exerted oneself embodied, has the most very much not with the microgrid relying on electricity refrigeration With.

For combined cooling and power type building microgrid, the temperature that building office hours (8:00 to 20:00) interior user sets as 22.5 DEG C, Non-working time is to temperature no requirement (NR).Introduce virtual energy storage, if user operationally between can accept temperature at design temperature Fluctuating in the range of positive and negative 2.5 DEG C, the sensitivity coefficient of user is set as γ=0.3.Do not introduce virtual energy storage and introduce virtual energy storage Optimized Operation result respectively the most as is illustrated by figs. 11 and 12.

Combined cooling and power type microgrid Optimum Regulation result under the conditions of introducing and do not introduce virtual energy storage is micro-with electricity refrigeration type Net similar: charge status of battery and building microgrid are substantially followed electricity price to power distribution network purchase of electricity and changed, and operationally Between the miniature gas turbine output of (8:00 to 20:00) and indoor temperature have significantly different, occur in that substantially fluctuation.With Electricity refrigeration type microgrid unlike, owing to Gas Prices is fixed, combined cooling and power type microgrid when electricity price is higher, Reducing purchase of electricity by increasing exerting oneself of miniature gas turbine, miniature gas turbine produces that unnecessary electricity is the most counter sells to distribution Net, thus reduce the operating cost of microgrid.

Not introducing building microgrid total operating cost in the case of virtual energy storage is 964.9 yuan.In the case of introducing virtual energy storage, building are micro- Net total operating cost is 911.8 yuan.Visible, make virtual storage by regulating indoor temperature in the range of user's temperature pleasant degree System can participate in the scheduling of microgrid economic optimization, microgrid operating cost can be reduced to a certain extent.Figure 13 gives introducing void Intend energy storage successively, the refrigeration demand of combined cooling and power type building and virtual energy storage system optimization scheduling result.

Equally, Figure 14 gives virtual energy storage discharge and recharge and electricity price relation.As can be seen from the figure combined cooling and power type microgrid The work characteristics of virtual energy storage reveals contrary feature with the worksheet of electricity refrigeration type microgrid virtual energy storage.Electricity refrigeration microgrid is empty The charging peak intending energy storage generally corresponds to electricity price low ebb, and its electric discharge peak is normally at the position near electricity price peak.And cold In CCHP microgrid, electricity price peak is often to inductive charging peak, electric discharge peak correspondence electricity price low ebb.

Its reason is when electricity price is higher, and the electric refrigerating machine in electricity refrigeration type building microgrid can reduce refrigeration work consumption, table It is now building refrigeration demand load reduction and virtual energy storage electric discharge, thus reduces electric cost；And combined cooling and power type microgrid When electricity price is higher, purchase of electricity, meanwhile, miniature gas turbine can be reduced by increasing exerting oneself of miniature gas turbine Produce that unnecessary electricity is the most counter sells to power distribution network, show as building refrigeration demand load and raise and virtual energy storage charging, thus Reduce the operating cost of microgrid.

By above relative analysis, electricity refrigeration type building microgrid meets building refrigeration demand with electricity refrigeration plant, thus realizes Virtual energy storages based on building, are by reducing operating cost at peak of power consumption reduction plans；Combined cooling and power type microgrid with CCHP meets building refrigeration demand, thus realizes virtual energy storages based on building, is by increasing miniature in peak of power consumption Gas Turbine Output reduces operating cost.Both ultimate principles are identical, for no other reason than that electricity refrigeration plant consumes electricity when refrigeration Can, and combined cooling and power equipment can produce electric energy when refrigeration, thus cause virtual energy storage difference on charge-discharge characteristic.

Although above in conjunction with accompanying drawing, invention has been described, but the invention is not limited in above-mentioned specific embodiment party Formula, above-mentioned detailed description of the invention is only schematic rather than restrictive, and those of ordinary skill in the art is at this Under the enlightenment of invention, without deviating from the spirit of the invention, it is also possible to make many variations, these belong to the present invention Protection within.

Claims (1)

1. the building microgrid Optimization Scheduling merging Demand-side virtual energy storage system, it is characterised in that include following Step:

Step one, micro-grid system model, including

1-1) miniature gas turbine

Shown in miniature gas turbine output such as formula (1):

P_MT,t=P_gas×η_MT (1)

In formula (1): P_MT,tFor the output of miniature gas turbine, unit is kW；P_gasConsume for miniature gas turbine Natural gas power, unit is kW；η_MTGenerating efficiency for miniature gas turbine；

1-2) Absorption Refrigerator

Absorption Refrigerator is driven by the waste heat of miniature gas turbine, shown in its refrigeration work consumption such as formula (2):

Q_AC,t=η_HE×γ_MT×P_MT,t×COP_AC (2)

In formula (2): Q_AC,tRefrigeration work consumption for Absorption Refrigerator exports, and unit is kW；γ_MTFor miniature gas turbine Hotspot stress；η_HEEfficiency for heat-exchanger rig；COP_ACEnergy Efficiency Ratio for Absorption Refrigerator；

1-3) electric refrigerating machine

Electric refrigerating machine freezes by consuming electric energy, shown in its refrigeration work consumption such as formula (3):

Q_EC,t=P_EC,t×COP_EC (3)

In formula (3): Q_EC,tRefrigeration work consumption for electric refrigerating machine exports, and unit is kW；P_EC,tThe electric work consumed for electric refrigerating machine Rate, unit is kW；COP_ECEnergy Efficiency Ratio for electric refrigerating machine；

Step 2, building virtual energy storage system modelling

Thermal storage effects based on building, obtain the equation of heat balance of building, such as formula (4) according to preservation of energy:

$\mathrm{\&Delta;}Q=\mathrm{\&rho;}\&times;C\&times;V\&times;\frac{{\mathrm{dT}}_{in}}{d\mathrm{\&tau;}}---\left(4\right)$

In formula (4): 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 empty 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 and is multiplied by its specific heat capacity again, etc. Variable quantity in indoor heat；V is room air volume, and unit is m³；

During cooling in summer, equation of heat balances based on building build the virtual energy storage system model of building, expression formula such as formula (5):

$\begin{array}{c}{k}_{wall}\&times;F_{wall}\&times;(T_{out}-T_{in})+k_{win}\&times;F_{win}\&times;(T_{out}-T_{in})\\ +I\&times;F_{win}\&times;SC+Q_{in}-Q_{cl}=\mathrm{\&rho;}\&times;C\&times;V\&times;\frac{{\mathrm{dT}}_{in}}{d\mathrm{\&tau;}}\end{array}---\left(5\right)$

The equal sign left side in formula (5):

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

Section 2 (k_win×F_win×(T_out-T_in)) representing external window of building and the heat of outdoor transmission, unit is kW: wherein k_winFor building Building the heat transfer coefficient of exterior window, 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 that sun heat radiation transmits, and unit is kW, and wherein I is solar radiation power, Unit is kW/m², represent and the heat of every square metre of acceptance per second during illumination vertical irradiation；

SC is shading coefficient: its value is 0-1；

Q_inFor the heating power of indoor airflow, unit is kW: include the heating of human body and electrical equipment；

Q_clFor the refrigeration work consumption of refrigeration plant, unit is kW；

Obtain the mathematical relationship of building indoor temperature and refrigerating device refrigeration power according to formula (5), and relax according to user indoor temperature Building refrigeration demand is adjusted by the scope of appropriateness；

Shown in the charge-discharge electric power such as formula (6) of virtual energy storage systems based on building:

Q_VSS,t=Q '_{cl,building,t}-Q_{cl,building,t} (6)

In formula (6): Q_VSS,tFor the charge-discharge electric power of virtual energy storage system, unit is kW, discharges for just, is charged as bearing；Q′_{cl,building,t} For not regulating the building refrigeration electrical power requirements of indoor temperature, unit is kW；Q_{cl,building,t}For considering in temperature pleasant degree scope The building refrigeration electrical power requirements of interior regulation indoor temperature, unit is kW；

Step 3, Optimized Operation object function build

Building virtual energy storage system model is integrated in the Optimum Regulation model of building microgrid, considers that building user can connect simultaneously The temperature regulating range being subject to, builds the economic optimization scheduling model of building microgrid；Wherein, the type of building microgrid includes electricity system Cold type building microgrid and combined cooling and power type building microgrid, the equipment of described electricity refrigeration type building microgrid includes photovoltaic, wind Machine, accumulator and electric refrigerating machine, the equipment of described combined cooling and power type building microgrid includes photovoltaic, blower fan, accumulator, micro- Type gas turbine and Absorption Refrigerator；

The object function of the economic optimization scheduling model after 3-1) electricity refrigeration type building microgrid merges virtual energy storage system is:

$\begin{array}{c}\min \underset{t=1}{\overset{N}{\&Sigma;}}\left\{\left(\frac{C_{ph,t}+C_{se,t}}{2}{P}_{ex,t}+\frac{C_{ph,t}-C_{se,t}}{2}\left|P_{ex,t}\right|\right)\right\}\\ +(P_{WT,t}{C}_{WT\_om}+P_{PV,t}{C}_{PV\_om}\\ +\left|P_{bt,t}\right|C_{bt\_om}+P_{EC,t}{C}_{EC\_om})+\mathrm{\&gamma;}|T_{in,t}-T_{set}\left|\right\}\end{array}---\left(7\right)$

In formula (7):

Section 1 is this microgrid cost from power distribution network power purchase, P_ex,tFor the electrical power of microgrid with power distribution network exchange, unit is kW, Power purchase is just, sale of electricity is negative；

Section 2 is the working service cost of all devices in this microgrid, P_WT,t、P_PV,t、P_bt,tAnd P_EC,tIt is respectively t wind Machine is exerted oneself, photovoltaic is exerted oneself, accumulator cell charging and discharging power and electric refrigerating machine electrical power, and unit is kW；Wherein, P_bt,t For battery discharging just, P_bt,tIt is accumulator charging for bearing；C_{WT_om}、C_{PV_om}、C_{bt_om}And C_{EC_om}Represent wind respectively Machine, photovoltaic, accumulator and the working service cost of electric refrigerating machine unit interval section unit power, unit is unit/kWh；

Section 3 is to affect the penalty function item that user's temperature pleasant degree sets, and γ is penalty factor, unit be unit/DEG C, this penalty factor It is considered as user's sensitivity to temperature pleasant degree, this penalty factor is defined as user sensitivity coefficient γ；Penalty function item sets It is multiplied by t indoor actual temperature T for γ_in,tDeviation design temperature T_setDifference；User sensitivity coefficient γ is according to different User's sensitivity selects, and the value of γ is 0-+ ∞；

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

The object function of the economic optimization scheduling model after 3-2) combined cooling and power type building microgrid merges virtual energy storage system is:

$\begin{array}{c}\min \underset{t=1}{\overset{N}{\&Sigma;}}\{\left(\frac{C_{ph,t}+C_{se,t}}{2}{P}_{ex,t}+\frac{C_{ph,t}-C_{se,t}}{2}\left|P_{ex,t}\right|\right)\\ +(P_{WT,t}{C}_{WT\_om}+P_{PV,t}{C}_{PV\_om}+|P_{bt,t}|C_{bt\_om}\\ +P_{MT,t}{C}_{MT\_om}+{\mathrm{\&gamma;}}_{MT}{P}_{MT,t}{C}_{AC\_om})\\ +C_{gas}{P}_{gas}+\mathrm{\&gamma;}|T_{in,t}-T_{set}|\}\end{array}---\left(8\right)$

In formula (8):

Section 2 is the working service cost of all devices in this microgrid；P_WT,t、P_PV,t、P_bt,tAnd P_MT,tIt is respectively t Blower fan is exerted oneself, photovoltaic is exerted oneself, accumulator cell charging and discharging power and miniature gas turbine, and unit is kW；C_{MC_om}Represent micro- The working service cost of type gas turbine unit interval section unit power, unit is unit/kWh；

Section 3 is the cost that microgrid buys natural gas, P_gas,tBuying natural gas power for microgrid, unit is kW；C_gasFor purchasing Buying the price of natural gas, unit is unit/kWh；

Step 4, Optimized Operation constraints are chosen

The constraints of the Optimal Operation Model after 4-1) electricity refrigeration type building microgrid merges Demand-side virtual energy storage includes:

4-1-1) electrical power Constraints of Equilibrium:

P_ex+P_WT+P_PV+P_bt=P_el+P_EC (9)

P in formula (9)_elElectric load for t；

4-1-2) refrigeration duty Constraints of Equilibrium:

Q_EC=Q_cl,building (10)

4-1-3) building thermal balance constraint:

The building virtual energy storage system model expressed by the differential equation in formula (5) is carried out differencing process, is formed by difference equation Building thermal balance constraint equation (11) expressed

$\begin{array}{c}\mathrm{\&Delta;}t\&lsqb;k_{wall}{F}_{wall}(T_{out,t}-T_{in,t})+k_{win}{F}_{\sin }(T_{out,t}-T_{in,t})\\ +I_t{F}_{win}SC+Q_{in,t}-Q_{EC,t}\&rsqb;-\mathrm{\&rho;}CV(T_{in,t+1}-T_{in,t})=0\end{array}---\left(11\right)$

4-1-4) in microgrid structure, accumulator and the constraint of electric refrigerating machine self and power distribution network power purchase retrain, including:

Accumulator and the power of electric refrigerating machine and power distribution network power purchase constraint satisfaction bound retrain:

$\left\{\begin{array}{c}\underset{\&OverBar;}{P_{ex}}<P_{ex}<\stackrel{\&OverBar;}{P_{ex}}\\ \underset{\&OverBar;}{P_{bt}}<P_{bt}<\stackrel{\&OverBar;}{P_{bt}}\\ \underset{\&OverBar;}{P_{EC}}<P_{EC}<\stackrel{\&OverBar;}{P_{EC}}\end{array}\right.---\left(12\right)$

Battery power storage amount retrains: as shown in formula (13) and (14), and electricity energy storage at a whole story dispatching cycle Constraints of Equilibrium, as Shown in formula (15):

$\underset{\&OverBar;}{W_{bt}}<W_{bt,t}=W_{bt\left(0\right)}-\underset{i=1}{\overset{t}{\&Sigma;}}{P}_{bt,i}{\mathrm{\&eta;}}_{bt}\mathrm{\&Delta;}t<\stackrel{\&OverBar;}{W_{bt}}---\left(13\right)$

${\mathrm{\&eta;}}_{bt}=\left\{\begin{array}{cc}{\mathrm{\&eta;}}_{ch}& P_{bt,i}\&le;0\\ 1/{\mathrm{\&eta;}}_{dis}& P_{bt,i}>0\end{array}\right.---\left(14\right)$

In formula (13) and formula (14), W_bt,tRepresenting the electricity of accumulator t, unit is kW；W_bt(0)Initial for accumulator Electricity, unit is kW；η_ch, η_disEfficiency for charge-discharge for accumulator；In the whole day of microgrid is dispatched, accumulator is because of self discharge And the energy loss produced is ignored；

$\underset{t=1}{\overset{N}{\&Sigma;}}{P}_{bt,t}=0---\left(15\right)$

4-1-5) building indoor temperature bound constraint:

$\underset{\&OverBar;}{T_{in}}<T_{in,t}<\stackrel{\&OverBar;}{T_{in}}---\left(16\right)$

The constraints of the Optimal Operation Model after 4-2) combined cooling and power type building microgrid merges Demand-side virtual energy storage includes:

4-2-1) electrical power Constraints of Equilibrium:

P_ex,t+P_WT,t+P_PV,t+P_MT,t+P_bt,t-P_el,t=0 (17)

4-2-2) refrigeration duty Constraints of Equilibrium:

Q_AC,t=Q_{cl,building,t} (18)

4-2-3) building thermal balance constraint:

The building virtual energy storage system model expressed by the differential equation in formula (5) is carried out differencing process, is formed by difference equation Building thermal balance constraint equation (19) expressed

$\begin{array}{c}{k}_{wall}{F}_{wall}(T_{out,t}-T_{in,t})+k_{win}{F}_{win}(T_{out,t}-T_{in,t})\\ +I_t{F}_{win}SC+Q_{in,t}-Q_{AC,t}-\mathrm{\&rho;}CV(T_{in,t+1}-T_{in,t})=0\end{array}---\left(19\right)$

4-2-4) constraint and the power distribution network power purchase of microgrid structure self retrains, including:

Accumulator and the power of miniature gas turbine and power distribution network power purchase constraint satisfaction bound retrain:

$\left\{\begin{array}{c}\underset{\&OverBar;}{P_{ex}}<P_{ex}<\stackrel{\&OverBar;}{P_{ex}}\\ \underset{\&OverBar;}{P_{MT}}<P_{MT,t}<\stackrel{\&OverBar;}{P_{MT}}\\ \underset{\&OverBar;}{P_{bt}}<P_{bt}<\stackrel{\&OverBar;}{P_{bt}}\end{array}\right.---\left(20\right)$

The constraint of battery power storage amount is identical with battery power storage amount constraint in electricity refrigeration type building microgrid: such as formula (13) and (14) Shown in, and electricity energy storage at a whole story dispatching cycle Constraints of Equilibrium, as shown in formula (15)；

4-2-5) building indoor temperature bound constraint:

$\underset{\&OverBar;}{T_{in}}<T_{in,t}<\stackrel{\&OverBar;}{T_{in}}---\left(21\right)$

Step 5, Optimized Operation solve, and obtain scheduling scheme, instruct building microgrid to run

The optimized mathematical model that above-mentioned steps three and step 4 are collectively formed by CPLEX is called under MATLAB software environment Solve, respectively obtain electricity refrigeration type building microgrid and combined cooling and power type building microgrid merges Demand-side virtual energy storage After Optimized Operation scheme；Based on the scheduling scheme obtained, arrange electricity refrigeration type building microgrid and combined cooling and power type respectively Building microgrid runs, thus reaches the purpose of optimized operation.