CN109995027A - A kind of two stages zone user energy management method and system - Google Patents
A kind of two stages zone user energy management method and system Download PDFInfo
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- CN109995027A CN109995027A CN201910220294.1A CN201910220294A CN109995027A CN 109995027 A CN109995027 A CN 109995027A CN 201910220294 A CN201910220294 A CN 201910220294A CN 109995027 A CN109995027 A CN 109995027A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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Abstract
The present invention relates to a kind of two stages zone user energy management method and systems, which comprises the electricity consumption plan of day zone user is predicted using zone user day-ahead power purchase cost minimization as Target Acquisition；The electricity consumption plan of the prediction day zone user is adjusted using zone user comprehensive adjustment cost minimization as target；The electricity consumption plan of prediction day zone user after adjusting is issued to user.Technical solution provided by the invention is based on load and assembles quotient set team control making mechanism, establish the two stages Optimized model a few days ago with real-time power management, management scheme a few days ago is modified by real time phase, to optimize each user power utilization scheme under load aggregation quotient, photovoltaic utilization rate is maximumlly improved, the intelligence degree of user power utilization is greatly improved.
Description
Technical field
The present invention relates to customer side energy management technical fields, and in particular to a kind of two stages zone user energy management side
Method and system.
Background technique
With increasingly depleted, the growth of eco-environmental pressure increase and workload demand of traditional fossil energy, conventional electric power generation
Mode is difficult to adapt to human kind sustainable development.Wherein, distributed photovoltaic is as a kind of huge cleaning of current development potentiality, ring
It protects, be distributed relatively uniform renewable energy, be widely used in user.Meanwhile with the maturation of battery energy storage technology
With the decline of economic cost, electric car will gradually replace traditional using internal combustion engine as the automobile of power.It is estimated that 2020
Year, the quantity of Chinese electric car will reach 5,000,000~10,000,000.
However photovoltaic (photovoltaic, PV) power output has uncertainty, there are relatively large deviations for power output prediction.And it is electric
Electrical automobile is the addition of the novel uncertain load of representative, becomes more complicated the flowing of electric energy and management.High vacancy rate
Electric car and controllable temperature mode load make it possible to indoor economic load dispatching and photovoltaic consumption.Needle at present
Last stage day cooperative scheduling is mainly used to more resource energy managements research, but it has ignored in real time phase scheduling, user
Electricity consumption curve and photovoltaic power output and prediction deviation a few days ago, cause electricity consumption plan to deviate optimal.
More for zone user equipment, big status is born in communication, how the electricity consumption plan of rational different user with
The intelligent power for realizing user is a urgent problem to be solved.
Summary of the invention
In order to solve the problems, such as in garden that resource is energy-optimised under photovoltaic consumption and polynary user, the present invention provides a kind of base
Two stages zone user energy management method and system under clustered control, by a few days ago with two ranks of real-time power management
Section Optimized model, is modified management scheme a few days ago in real time phase, while mitigating system communication burden, improves
The economy of user power utilization.
A kind of two stages zone user energy management method provided by the invention, it is improved in that including:
The electricity consumption plan of day zone user is predicted using zone user day-ahead power purchase cost minimization as Target Acquisition；
The electricity consumption plan of the prediction day zone user is adjusted using zone user comprehensive adjustment cost minimization as target；
The electricity consumption plan of prediction day zone user after adjusting is issued to user；
Wherein, the electricity consumption plan include: temperature control load power, electric car charge volume and energy storage fill discharge capacity.
Preferably, described to predict that the electricity consumption of day zone user is counted using zone user day-ahead power purchase cost minimization as Target Acquisition
It draws, comprising:
By adaptive grey wolf optimization algorithm domain user's day-ahead power purchase cost objective function, optimum prediction day is obtained
The electricity consumption plan of zone user, wherein determine zone user day-ahead power purchase cost objective function as the following formula:
In above formula, F is zone user day-ahead power purchase cost, and m is tou power price, and T is dispatching cycle,For t moment area
Domain user is to the total active power of power grid power purchase；
Wherein, determine the t moment zone user to the total active power of power grid power purchase as the following formula
In above formula,For the basic load power of i-th of user of t moment, N is number of users in region,For t moment
The power of i-th of temperature control load, NACFor the temperature control load number loaded in region,For the charging of i-th of electric car of t moment
Power, NEVFor the electric car number being loaded in region,For the charge power of i-th of energy storage of t moment, NESSTo add in region
If energy storage number,For the active power of i-th of photovoltaic of t moment, NDGFor the photovoltaic number installed additional in region,For t moment
The discharge power of i-th of energy storage.
Preferably, the use that the prediction day zone user is adjusted using zone user comprehensive adjustment cost minimization as target
Electricity plan, comprising:
By adaptive grey wolf optimization algorithm domain user's comprehensive adjustment cost objective function, the prediction day is obtained
The electricity consumption of zone user the charge-discharge electric power regulated quantity of energy storage and temperature control load power regulated quantity in the works；
Being utilized respectively the electricity consumption for predicting day zone user, the charge-discharge electric power regulated quantity of energy storage and temperature control are negative in the works
Lotus power regulation adjusts the charge-discharge electric power and temperature control load function of the energy storage of the electricity consumption of the prediction day zone user in the works
Rate.
Further, the zone user comprehensive adjustment cost objective function is determined as the following formula:
In above formula, F2For zone user comprehensive adjustment cost, T1For real time phase dispatching cycle, N1For what is added in region
Energy storage number,For the adjustment cost of i-th of energy storage of t moment,It is mended for the comfort level of i-th of temperature control Load Regulation of t moment
Repay cost, N2For the temperature control load number loaded in region；
Wherein, the adjustment cost of i-th of energy storage of t moment is calculated as followsWith i-th of temperature control Load Regulation of t moment
Comfort level cost of compensation
In above formula, c1For energy storage adjustment cost coefficient,For it is described prediction day zone user electricity consumption in the works t when
Carve i-th of energy storage charge-discharge electric power regulated quantity, c2For temperature control Load Regulation penalty coefficient,For prediction day region use
The electricity consumption at family i-th of temperature control load power regulated quantity of t moment in the works.
Further, the charge-discharge electric power tune of the electricity consumption energy storage in the works for being utilized respectively the prediction day zone user
Section amount and temperature control load power regulated quantity adjust the charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works
With temperature control load power, comprising:
The charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
The temperature control load power of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
In above formula,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user
Correction value,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user,For institute
The charge-discharge electric power regulated quantity of electricity consumption i-th of energy storage of t moment in the works of prediction day zone user is stated,For the prediction
The discharge power correction value of the electricity consumption of day zone user i-th of energy storage of t moment in the works,For prediction day region use
The discharge power of the electricity consumption at family i-th of energy storage of t moment in the works,For the electricity consumption t in the works of the prediction day zone user
The power correction value of i-th of temperature control load of moment,For electricity consumption i-th of the t moment temperature in the works of the prediction day zone user
The power of load is controlled,For the power tune of electricity consumption i-th of temperature control load of t moment in the works of the prediction day zone user
Section amount.
A kind of two stages zone user Energy Management System provided by the invention, it is improved in that the system packet
It includes:
Module is obtained, for predicting the electricity consumption of day zone user using zone user day-ahead power purchase cost minimization as Target Acquisition
Plan；
Adjustment module, for adjusting the prediction day zone user by target of zone user comprehensive adjustment cost minimization
Electricity consumption plan；
Module is issued, for the electricity consumption plan of the prediction day zone user after adjusting to be issued to user；
Wherein, the electricity consumption plan include: temperature control load power, electric car charge volume and energy storage fill discharge capacity.
Preferably, the acquisition module, is used for:
By adaptive grey wolf optimization algorithm domain user's day-ahead power purchase cost objective function, optimum prediction day is obtained
The electricity consumption plan of zone user, wherein determine zone user day-ahead power purchase cost objective function as the following formula:
In above formula, F is zone user day-ahead power purchase cost, and m is tou power price, and T is dispatching cycle,For t moment area
Domain user is to the total active power of power grid power purchase；
Wherein, determine the t moment zone user to the total active power of power grid power purchase as the following formula
In above formula,For the basic load power of i-th of user of t moment, N is number of users in region,For t moment
The power of i-th of temperature control load, NACFor the temperature control load number loaded in region,For filling for i-th of electric car of t moment
Electrical power, NEVFor the electric car number being loaded in region,For the charge power of i-th of energy storage of t moment, NESSFor in region
The energy storage number added,For the active power of i-th of photovoltaic of t moment, NDGFor the photovoltaic number installed additional in region,When for t
Carve the discharge power of i-th of energy storage.
Preferably, the adjustment module, is used for:
By adaptive grey wolf optimization algorithm domain user's comprehensive adjustment cost objective function, the prediction day is obtained
The electricity consumption of zone user the charge-discharge electric power regulated quantity of energy storage and temperature control load power regulated quantity in the works；
Being utilized respectively the electricity consumption for predicting day zone user, the charge-discharge electric power regulated quantity of energy storage and temperature control are negative in the works
Lotus power regulation adjusts the charge-discharge electric power and temperature control load function of the energy storage of the electricity consumption of the prediction day zone user in the works
Rate.
Further, the zone user comprehensive adjustment cost objective function is determined as the following formula:
In above formula, F2For zone user comprehensive adjustment cost, T1For real time phase dispatching cycle, N1For what is added in region
Energy storage number,For the adjustment cost of i-th of energy storage of t moment,For the comfort level of i-th of temperature control Load Regulation of t moment
Cost of compensation, N2For the temperature control load number loaded in region；
Wherein, the adjustment cost of i-th of energy storage of t moment is calculated as followsWith i-th of temperature control Load Regulation of t moment
Comfort level cost of compensation
In above formula, c1For energy storage adjustment cost coefficient,For it is described prediction day zone user electricity consumption in the works t when
Carve i-th of energy storage charge-discharge electric power regulated quantity, c2For temperature control Load Regulation penalty coefficient,For prediction day region use
The electricity consumption at family i-th of temperature control load power regulated quantity of t moment in the works.
Further, the charge-discharge electric power tune of the electricity consumption energy storage in the works for being utilized respectively the prediction day zone user
Section amount and temperature control load power regulated quantity adjust the charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works
With temperature control load power, comprising:
The charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
The temperature control load power of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
In above formula,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user
Correction value,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user,For institute
The charge-discharge electric power regulated quantity of electricity consumption i-th of energy storage of t moment in the works of prediction day zone user is stated,For the prediction
The discharge power correction value of the electricity consumption of day zone user i-th of energy storage of t moment in the works,For prediction day region use
The discharge power of the electricity consumption at family i-th of energy storage of t moment in the works,For it is described prediction day zone user electricity consumption in the works t when
The power correction value of i-th of temperature control load is carved,For electricity consumption i-th of temperature control of t moment in the works of the prediction day zone user
The power of load,For the power regulation of electricity consumption i-th of temperature control load of t moment in the works of the prediction day zone user
Amount.
Compared with the latest prior art, technical solution provided by the invention has following excellent effect:
The present invention provides a kind of two stages zone user energy management method and systems, assemble quotient set team control based on load
Making mechanism establishes the two stages Optimized model a few days ago with real-time power management.In view of photovoltaic and user power utilization power prediction
Error exist, management scheme a few days ago is modified by real time phase, thus optimize load aggregation quotient under it is each
User power utilization scheme maximizes and improves photovoltaic utilization rate, greatly improves the intelligence degree of user power utilization.
Detailed description of the invention
Fig. 1 is the flow chart of two stages zone user energy management method provided by the invention；
Fig. 2 is that grey wolf optimization algorithm is improved in the two stages zone user energy management method provided in the embodiment of the present invention
Flow chart；
Fig. 3 is the structure chart of the two stages zone user Energy Management System provided in the embodiment of the present invention；
Fig. 4 is zone user optimization front and back in the two stages zone user energy management method provided in the embodiment of the present invention
Electricity consumption curve；
Fig. 5 is that region electric car fills in the two stages zone user energy management method provided in the embodiment of the present invention
Electrical power；
Fig. 6 is zone user temperature control load in the two stages zone user energy management method provided in the embodiment of the present invention
Electric power；
Fig. 7 is energy storage in zone user in the two stages zone user energy management method provided in the embodiment of the present invention
Charge-discharge electric power.
Specific embodiment
It elaborates with reference to the accompanying drawing to a specific embodiment of the invention.
Embodiment one
The embodiment of the present invention proposes that a kind of two stages zone user energy management method, flow chart are as shown in Figure 1, comprising:
The electricity consumption plan of day zone user is predicted using zone user day-ahead power purchase cost minimization as Target Acquisition；
The electricity consumption plan of the prediction day zone user is adjusted using zone user comprehensive adjustment cost minimization as target；
The electricity consumption plan of prediction day zone user after adjusting is issued to user；
Wherein, the electricity consumption plan include: temperature control load power, electric car charge volume and energy storage fill discharge capacity.
Specifically, may comprise steps of in optimum embodiment provided by the invention:
Step 1: load assemble quotient receiving area in respectively use the status information of indoor controllable resources, prediction photovoltaic power output with
Electricity consumption curve；
Step 2: in last stage day, load assembles quotient and establishes day using zone user day-ahead power purchase cost minimization as objective function
Preceding energy management Optimized model；
Step 3: scheduling model a few days ago being solved using adaptive grey wolf optimization algorithm；
Step 4: load assembles quotient and buys electricity to power grid in last stage day according to optimum results, and electricity consumption plan is issued to respectively
User；
Step 5: in real time phase, load assembles quotient every 4h more new information, to zone user comprehensive adjustment cost most
The small real-time power administrative model for objective function is solved using adaptive grey wolf optimization algorithm；
Step 6: updating each user power utilization according to optimum results and instruct.
Further, the electricity consumption that day zone user is predicted using zone user day-ahead power purchase cost minimization as Target Acquisition
Plan, comprising:
In last stage day, dispatching cycle is time interval 15min for 24 hours, solves area by adaptive grey wolf optimization algorithm
Domain user's day-ahead power purchase cost objective function obtains the electricity consumption plan of optimum prediction day zone user, wherein determines area as the following formula
Domain user's day-ahead power purchase cost objective function:
In above formula, F is zone user day-ahead power purchase cost, and m is tou power price, and T is dispatching cycle,For t moment area
Domain user is to the total active power of power grid power purchase；
Wherein, determine the t moment zone user to the total active power of power grid power purchase as the following formula
In above formula,For the basic load power of i-th of user of t moment, N is number of users in region,For t moment
The power of i-th of temperature control load, NACFor the temperature control load number loaded in region,For the charging of i-th of electric car of t moment
Power, NEVFor the electric car number being loaded in region,For the charge power of i-th of energy storage of t moment, NESSTo add in region
If energy storage number,For the active power of i-th of photovoltaic of t moment, NDGFor the photovoltaic number installed additional in region,For t moment
The discharge power of i-th of energy storage.
The adaptive grey wolf optimization algorithm, as shown in Figure 2, the specific steps are as follows:
Step a: initialization generates initial wolf pack X, maximum allowable the number of iterations G is arrangedmax；
Step b: fitness objective function is calculated；
Step c: first three optimal piece goods wolf position X is successively filtered out by ranking fitnessα(t), Xβ(t) and Xδ(t), t is
Current iteration number；
Step d: next-generation subgroup grey wolf position is updated；
Step d-1: adaptive convergence factor a is calculated
Step d-2: according to head wolf position Xα(t),Xβ(t) and Xδ(t) judge and need to surround at a distance from prey
D1=| C1Xα(t)-X(t)|
D2=| C2Xβ(t)-X(t)|
D3=| C3Xδ(t)-X(t)|
In above formula, C1, C2And C3For Discontinuous Factors, the disturbance to search for three piece goods wolves is respectively represented；
Step d-3: remaining wolf pack X is calculatedωThe direction of advance and distance
X1=Xα-A1D1
X2=Xβ-A2D2
X3=Xδ-A3D3
In above formula, X1Represent the position that wolf pack ω is updated according to the direction of search that head wolf α is instructed, X2Represent wolf pack ω according to
The position that the direction of search of head wolf β guidance updates, X3Represent the position that wolf pack ω is updated according to the direction of search that head wolf δ is instructed, A
To restrain variable, and A=2ar2- a, r2For the random number in [0,1]；
Step d-4: the dynamic learning weight w based on weight proportion is calculated1, w2, w3；
In formula, w1For the dynamic learning weight of wolf pack ω enemy wolf α, w2For the dynamic learning weight of wolf pack ω enemy wolf β,
w3For the dynamic learning weight of wolf pack ω enemy wolf δ；
Step d-5: the position X (t+1) of next-generation population grey wolf is updated
Step e: undated parameter adaptive convergence factor a, stochastic variable A, Discontinuous Factors C；
Step f: judging whether to meet termination condition, if conditions are not met, t=t+1 and going to step b, otherwise enters step
g；
Step g: the position of export head wolf α.
The electricity consumption plan that the prediction day zone user is adjusted using zone user comprehensive adjustment cost minimization as target,
Include:
By adaptive grey wolf optimization algorithm domain user's comprehensive adjustment cost objective function, the prediction day is obtained
The electricity consumption of zone user the charge-discharge electric power regulated quantity of energy storage and temperature control load power regulated quantity in the works；
Being utilized respectively the electricity consumption for predicting day zone user, the charge-discharge electric power regulated quantity of energy storage and temperature control are negative in the works
Lotus power regulation adjusts the charge-discharge electric power and temperature control load function of the energy storage of the electricity consumption of the prediction day zone user in the works
Rate.
Specifically, dispatching cycle be 4h, time interval 15min, determine as the following formula the zone user comprehensive adjustment at
This objective function:
In above formula, F2For zone user comprehensive adjustment cost, T1For real time phase dispatching cycle, N1For what is added in region
Energy storage number,For the adjustment cost of i-th of energy storage of t moment,It is mended for the comfort level of i-th of temperature control Load Regulation of t moment
Repay cost, N2For the temperature control load number loaded in region；
Wherein, the adjustment cost of i-th of energy storage of t moment is calculated as followsWith i-th of temperature control Load Regulation of t moment
Comfort level cost of compensation
In above formula, c1For energy storage adjustment cost coefficient,For it is described prediction day zone user electricity consumption in the works t when
Carve i-th of energy storage charge-discharge electric power regulated quantity, c2For temperature control Load Regulation penalty coefficient,For prediction day region use
The electricity consumption at family i-th of temperature control load power regulated quantity of t moment in the works.
The charge-discharge electric power regulated quantity and temperature of the electricity consumption energy storage in the works for being utilized respectively the prediction day zone user
Control load power regulated quantity adjusts the charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works and temperature control is born
Lotus power, comprising:
The charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
The temperature control load power of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
In above formula,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user
Correction value,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user,For institute
The charge-discharge electric power regulated quantity of electricity consumption i-th of energy storage of t moment in the works of prediction day zone user is stated,For the prediction
The discharge power correction value of the electricity consumption of day zone user i-th of energy storage of t moment in the works,For prediction day region use
The discharge power of the electricity consumption at family i-th of energy storage of t moment in the works,For the electricity consumption t in the works of the prediction day zone user
The power correction value of i-th of temperature control load of moment,For electricity consumption i-th of the t moment temperature in the works of the prediction day zone user
The power of load is controlled,For the power tune of electricity consumption i-th of temperature control load of t moment in the works of the prediction day zone user
Section amount.
Embodiment two
The embodiment of the present invention proposes that a kind of two stages zone user Energy Management System, structure are as shown in Figure 3, comprising:
Module is obtained, for predicting the electricity consumption of day zone user using zone user day-ahead power purchase cost minimization as Target Acquisition
Plan；
Adjustment module, for adjusting the prediction day zone user by target of zone user comprehensive adjustment cost minimization
Electricity consumption plan；
Module is issued, for the electricity consumption plan of the prediction day zone user after adjusting to be issued to user；
Wherein, the electricity consumption plan include: temperature control load power, electric car charge volume and energy storage fill discharge capacity.
Specifically, the acquisition module, is used for:
By adaptive grey wolf optimization algorithm domain user's day-ahead power purchase cost objective function, optimum prediction day is obtained
The electricity consumption plan of zone user, wherein determine zone user day-ahead power purchase cost objective function as the following formula:
In above formula, F is zone user day-ahead power purchase cost, and m is tou power price, and T is dispatching cycle,For t moment area
Domain user is to the total active power of power grid power purchase；
Wherein, determine the t moment zone user to the total active power of power grid power purchase as the following formula
In above formula,For the basic load power of i-th of user of t moment, N is number of users in region,For t moment
The power of i-th of temperature control load, NACFor the temperature control load number loaded in region,For the charging of i-th of electric car of t moment
Power, NEVFor the electric car number being loaded in region,For the charge power of i-th of energy storage of t moment, NESSTo add in region
If energy storage number,For the active power of i-th of photovoltaic of t moment, NDGFor the photovoltaic number installed additional in region,For t moment
The discharge power of i-th of energy storage.
Specifically, the adjustment module, is used for:
By adaptive grey wolf optimization algorithm domain user's comprehensive adjustment cost objective function, the prediction day is obtained
The electricity consumption of zone user the charge-discharge electric power regulated quantity of energy storage and temperature control load power regulated quantity in the works；
Being utilized respectively the electricity consumption for predicting day zone user, the charge-discharge electric power regulated quantity of energy storage and temperature control are negative in the works
Lotus power regulation adjusts the charge-discharge electric power and temperature control load function of the energy storage of the electricity consumption of the prediction day zone user in the works
Rate.
The zone user comprehensive adjustment cost objective function is determined as the following formula:
In above formula, F2For zone user comprehensive adjustment cost, T1For real time phase dispatching cycle, N1For what is added in region
Energy storage number,For the adjustment cost of i-th of energy storage of t moment,It is mended for the comfort level of i-th of temperature control Load Regulation of t moment
Repay cost, N2For the temperature control load number loaded in region；
Wherein, the adjustment cost of i-th of energy storage of t moment is calculated as followsWith i-th of temperature control Load Regulation of t moment
Comfort level cost of compensation
In above formula, c1For energy storage adjustment cost coefficient,For it is described prediction day zone user electricity consumption in the works t when
Carve i-th of energy storage charge-discharge electric power regulated quantity, c2For temperature control Load Regulation penalty coefficient,For prediction day region use
The electricity consumption at family i-th of temperature control load power regulated quantity of t moment in the works.
The charge-discharge electric power regulated quantity and temperature of the electricity consumption energy storage in the works for being utilized respectively the prediction day zone user
Control load power regulated quantity adjusts the charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works and temperature control is born
Lotus power, comprising:
The charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
The temperature control load power of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
In above formula,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user
Correction value,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user,For institute
The charge-discharge electric power regulated quantity of electricity consumption i-th of energy storage of t moment in the works of prediction day zone user is stated,For the prediction
The discharge power correction value of the electricity consumption of day zone user i-th of energy storage of t moment in the works,For prediction day region use
The discharge power of the electricity consumption at family i-th of energy storage of t moment in the works,For it is described prediction day zone user electricity consumption in the works t when
The power correction value of i-th of temperature control load is carved,For electricity consumption i-th of temperature control of t moment in the works of the prediction day zone user
The power of load,For the power regulation of electricity consumption i-th of temperature control load of t moment in the works of the prediction day zone user
Amount.
Embodiment three
A specific embodiment of the invention is done further by taking a large user in load aggregation quotient control area as an example
It is described in detail:
The distributed energy being equipped in large user includes photovoltaic cell and the lithium battery of 1000kW.Wherein, the temperature control of user
Load is air-conditioning, is set as 50, accounts for the 10% of total load；Schedulable load is electric car, is set as 20, accounts for total load 5%.
According to user demand, room temperature TaBound be respectively 22 DEG C and 26 DEG C；Electric car uses routine at a slow speed
Charging modes, battery capacity 70kWh, hundred kilometers of power consumption W100For 15kWh, unit time maximum charge power Pch,maxFor
7kW, the charging total amount of daily each car is by its daily travel diIt determines, electric car i starts to access charging moment ti,aIt arrives down
One stroke start time ti,sFor a charge cycle, electricity is full of during this period.Energy storage SOC state initial value is 0.5, storage
The SOC state of energy is limited to [0.2,1] up and down, efficiency for charge-discharge 82%, and energy content of battery multiplying power is 2.74, and the service life is 10 years.
In the region, load assemble quotient using sale of electricity price use tou power price, be divided into the peak period (8:00-12:00,17:
It 00-21:00) is 1.1002 yuan/kWh, when usually section (12:00-17:00,21:00-24:00) is 0.6601 yuan/kWh and paddy
Section (0:00-8:00) is 0.32 yuan/kWh.Photovoltaic subsidizes electricity price according to for 0.42 yuan/kWh, surplus rate for incorporation into the power network for 0.34 yuan/
kWh。
The dispatching cycle of system is that for 24 hours, simulation step length uses 15min, after energy management optimizes, the load that optimized
Curve as shown in figure 4, the charge power of optional one electric car and the power of air-conditioning respectively as it can be seen in figures 5 and 6, energy storage
Charge-discharge electric power is as shown with 7.
In example, the use time of electric car is adjusted to photovoltaic more abundance or electricity price lower period, air-conditioning and also leads to
It crosses optimization to shorten using the time, energy storage is charged in the case where electricity price is lower or photovoltaic is rich, in the higher Shi Fang electricity of electricity price.
In order to further illustrate raising of the electricity consumption plan generated by coordinated scheduling policy optimization to user's economy.
By the electricity consumption plan (strategy 5) after optimization, with original electricity consumption plan (strategy 1) and only, Optimized Operation demand response resource is (tactful
2), only Optimized Operation electric car (strategy 3), only the modes such as Optimized Operation energy storage (strategy 4) compare, then each scheduling resource
The electricity charge with one day are as shown in table 1.Wherein, for strategy 2 into strategy 4, the electricity consumption plan of other scheduling resources is constant.
The electricity charge compare in lower day of each scene of table 1
| Basic load/member | Air-conditioning/member | Electric car/member | Energy storage/member | Photovoltaic/member | Total electricity bill/member | |
| Strategy 1 | 33681 | 2080.3 | 166.6140 | -297.8973 | -4410.5 | 31219 |
| Strategy 2 | 33681 | 1002.7 | 166.6140 | -297.8973 | -4410.5 | 30142 |
| Strategy 3 | 33681 | 2080.3 | 103.6864 | -297.8973 | -4410.5 | 31156 |
| Strategy 4 | 33681 | 2080.3 | 166.6140 | -501.4185 | -4410.5 | 31016 |
| Strategy 5 | 33681 | 1002.7 | 103.6864 | -791.2185 | -4410.5 | 29056 |
As shown in Table 1, strategy 2 saves 3.4% electricity charge, effect；The electricity charge that strategy 3 is saved are less, and just 63 yuan, less than
1%, this is because electric car ownership is relatively low, the effect after optimization is less obvious.Strategy 4 saves 203 yuan, in strategy
Although 2 only scheduled a kind of resource into strategy 4, there has also been certain reductions for the electricity charge in zone user.Tactful 5 pairs of indoor institutes
There is resource to carry out coordinated scheduling, saves 2163 yuan (7%).Compared to only scheduling a kind of indoor resource, coordinated scheduling strategy
Under the daily alternating current network minimal of electricity consumption plan, effectively improve the economy of user.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Finally it should be noted that: the above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, to the greatest extent
Invention is explained in detail referring to above-described embodiment for pipe, it should be understood by those ordinary skilled in the art that: still
It can be with modifications or equivalent substitutions are made to specific embodiments of the invention, and without departing from any of spirit and scope of the invention
Modification or equivalent replacement, should all cover within the scope of the claims of the present invention.
Claims (10)
1. a kind of two stages zone user energy management method characterized by comprising
The electricity consumption plan of day zone user is predicted using zone user day-ahead power purchase cost minimization as Target Acquisition；
The electricity consumption plan of the prediction day zone user is adjusted using zone user comprehensive adjustment cost minimization as target；
The electricity consumption plan of prediction day zone user after adjusting is issued to user；
Wherein, the electricity consumption plan include: temperature control load power, electric car charge volume and energy storage fill discharge capacity.
2. the method as described in claim 1, which is characterized in that described to be obtained using zone user day-ahead power purchase cost minimization as target
Take the electricity consumption plan of prediction day zone user, comprising:
By adaptive grey wolf optimization algorithm domain user's day-ahead power purchase cost objective function, optimum prediction day region is obtained
The electricity consumption plan of user, wherein determine zone user day-ahead power purchase cost objective function as the following formula:
In above formula, F is zone user day-ahead power purchase cost, and m is tou power price, and T is dispatching cycle,For t moment zone user
To the total active power of power grid power purchase；
Wherein, determine the t moment zone user to the total active power of power grid power purchase as the following formula
In above formula,For the basic load power of i-th of user of t moment, N is number of users in region,It is i-th of t moment
The power of temperature control load, NACFor the temperature control load number loaded in region,For the charge power of i-th of electric car of t moment,
NEVFor the electric car number being loaded in region,For the charge power of i-th of energy storage of t moment, NESSFor what is added in region
Energy storage number,For the active power of i-th of photovoltaic of t moment, NDGFor the photovoltaic number installed additional in region,For t moment i-th
The discharge power of a energy storage.
3. the method as described in claim 1, which is characterized in that described using zone user comprehensive adjustment cost minimization as target tune
Save the electricity consumption plan of the prediction day zone user, comprising:
By adaptive grey wolf optimization algorithm domain user's comprehensive adjustment cost objective function, the prediction day region is obtained
The electricity consumption of user the charge-discharge electric power regulated quantity of energy storage and temperature control load power regulated quantity in the works；
It is utilized respectively the electricity consumption for predicting day zone user the charge-discharge electric power regulated quantity of energy storage and temperature control load function in the works
Rate regulated quantity adjusts the charge-discharge electric power and temperature control load power of the energy storage of the electricity consumption of the prediction day zone user in the works.
4. method as claimed in claim 3, which is characterized in that determine the zone user comprehensive adjustment cost objective as the following formula
Function:
In above formula, F2For zone user comprehensive adjustment cost, T1For real time phase dispatching cycle, N1For the energy storage added in region
Number,For the adjustment cost of i-th of energy storage of t moment,For i-th of temperature control Load Regulation of t moment comfort level compensation at
This, N2For the temperature control load number loaded in region；
Wherein, the adjustment cost of i-th of energy storage of t moment is calculated as followsIt is comfortable with i-th of temperature control Load Regulation of t moment
Spend cost of compensation
In above formula, c1For energy storage adjustment cost coefficient,For electricity consumption t moment i-th in the works of the prediction day zone user
A energy storage charge-discharge electric power regulated quantity, c2For temperature control Load Regulation penalty coefficient,For the use of the prediction day zone user
Electric i-th of temperature control load power regulated quantity of t moment in the works.
5. method as claimed in claim 3, which is characterized in that the electricity consumption meter for being utilized respectively the prediction day zone user
The charge-discharge electric power regulated quantity and temperature control load power regulated quantity of energy storage adjust the electricity consumption meter of the prediction day zone user in drawing
The charge-discharge electric power and temperature control load power of energy storage in drawing, comprising:
The charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
The temperature control load power of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
In above formula,For it is described prediction day zone user electricity consumption in the works i-th of energy storage of t moment charge power amendment
Value,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user,It is described pre-
The charge-discharge electric power regulated quantity of electricity consumption i-th of energy storage of t moment in the works of day zone user is surveyed,For the prediction day area
The discharge power correction value of the electricity consumption of domain user i-th of energy storage of t moment in the works,For the prediction day zone user
The discharge power of electricity consumption i-th of energy storage of t moment in the works,For the electricity consumption t moment in the works of the prediction day zone user
The power correction value of i-th of temperature control load,For the electricity consumption for predicting day zone user, i-th of temperature control of t moment is negative in the works
The power of lotus,For the power regulation of electricity consumption i-th of temperature control load of t moment in the works of the prediction day zone user.
6. a kind of two stages zone user Energy Management System characterized by comprising
Module is obtained, based on the electricity consumption by predicting day zone user using zone user day-ahead power purchase cost minimization as Target Acquisition
It draws；
Adjustment module, for adjusting the electricity consumption of the prediction day zone user using zone user comprehensive adjustment cost minimization as target
Plan；
Module is issued, for the electricity consumption plan of the prediction day zone user after adjusting to be issued to user；
Wherein, the electricity consumption plan include: temperature control load power, electric car charge volume and energy storage fill discharge capacity.
7. system as claimed in claim 6, which is characterized in that the acquisition module is used for:
By adaptive grey wolf optimization algorithm domain user's day-ahead power purchase cost objective function, optimum prediction day region is obtained
The electricity consumption plan of user, wherein determine zone user day-ahead power purchase cost objective function as the following formula:
In above formula, F is zone user day-ahead power purchase cost, and m is tou power price, and T is dispatching cycle,For t moment zone user
To the total active power of power grid power purchase；
Wherein, determine the t moment zone user to the total active power of power grid power purchase as the following formula
In above formula,For the basic load power of i-th of user of t moment, N is number of users in region,It is i-th of t moment
The power of temperature control load, NACFor the temperature control load number loaded in region,For the charge power of i-th of electric car of t moment,
NEVFor the electric car number being loaded in region,For the charge power of i-th of energy storage of t moment, NESSFor what is added in region
Energy storage number,For the active power of i-th of photovoltaic of t moment, NDGFor the photovoltaic number installed additional in region,For t moment i-th
The discharge power of a energy storage.
8. system as claimed in claim 6, which is characterized in that the adjustment module is used for:
By adaptive grey wolf optimization algorithm domain user's comprehensive adjustment cost objective function, the prediction day region is obtained
The electricity consumption of user the charge-discharge electric power regulated quantity of energy storage and temperature control load power regulated quantity in the works；
It is utilized respectively the electricity consumption for predicting day zone user the charge-discharge electric power regulated quantity of energy storage and temperature control load function in the works
Rate regulated quantity adjusts the charge-discharge electric power and temperature control load power of the energy storage of the electricity consumption of the prediction day zone user in the works.
9. system as claimed in claim 8, which is characterized in that determine the zone user comprehensive adjustment cost objective as the following formula
Function:
In above formula, F2For zone user comprehensive adjustment cost, T1For real time phase dispatching cycle, N1For the energy storage added in region
Number,For the adjustment cost of i-th of energy storage of t moment,For i-th of temperature control Load Regulation of t moment comfort level compensation at
This, N2For the temperature control load number loaded in region；
Wherein, the adjustment cost of i-th of energy storage of t moment is calculated as followsIt is comfortable with i-th of temperature control Load Regulation of t moment
Spend cost of compensation
In above formula, c1For energy storage adjustment cost coefficient,For electricity consumption t moment i-th in the works of the prediction day zone user
A energy storage charge-discharge electric power regulated quantity, c2For temperature control Load Regulation penalty coefficient,For the use of the prediction day zone user
Electric i-th of temperature control load power regulated quantity of t moment in the works.
10. system as claimed in claim 8, which is characterized in that the electricity consumption for being utilized respectively the prediction day zone user
The charge-discharge electric power regulated quantity of energy storage and temperature control load power regulated quantity adjust the electricity consumption of the prediction day zone user in the works
The charge-discharge electric power and temperature control load power of energy storage in the works, comprising:
The charge-discharge electric power of the energy storage of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
The temperature control load power of the electricity consumption of the prediction day zone user in the works is adjusted as the following formula:
In above formula,For it is described prediction day zone user electricity consumption in the works i-th of energy storage of t moment charge power amendment
Value,For the charge power of electricity consumption i-th of energy storage of t moment in the works of the prediction day zone user,It is described pre-
The charge-discharge electric power regulated quantity of electricity consumption i-th of energy storage of t moment in the works of day zone user is surveyed,For the prediction day area
The discharge power correction value of the electricity consumption of domain user i-th of energy storage of t moment in the works,For the prediction day zone user
The discharge power of electricity consumption i-th of energy storage of t moment in the works,For the electricity consumption t moment the in the works of the prediction day zone user
The power correction value of i temperature control load,For electricity consumption i-th of temperature control load of t moment in the works of the prediction day zone user
Power,For the power regulation of electricity consumption i-th of temperature control load of t moment in the works of the prediction day zone user.
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