CN105140939B - The multi-objective coordinated control method of active load based on energy-storage system - Google Patents
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Abstract
The invention discloses a kind of multi-objective coordinated control method of active load based on energy-storage system, the multiple target include regional power grid dominant eigenvalues and, user's economic benefit and Utilities Electric Co.'s operation benefits, adjust the weight of operational objective according to the actual requirements by user, by analyze Demand-side power supply output, energy-storage system state-of-charge, user with can demand, Spot Price plan the real-time output of energy-storage system automatically, realize that multiple target operation whole result is optimal.Rate-determining steps include：Data acquisition；Parameter setting；Data screening；Stepwise optimization；Instruction performs.Control method of the present invention can take into account the interests of user and power network, significantly improve the economic benefit and social benefit of intelligent Demand-side, the strategy can be used in the stored energy capacitance planning investment of intelligent Demand-side first stage of construction simultaneously, to obtain most preferably input/output ratio.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to an active load multi-target coordination control method based on an energy storage system.
Background
The intelligent demand side is an extension of the intelligent power grid on the power utilization side, and belongs to the key and hot point research field of the intelligent power grid. Different from the traditional demand side, the intelligent demand side has distributed renewable energy sources and energy storage devices, and the electric energy quality problem and the bidirectional circulation characteristic of the tide brought by the fluctuation of new energy power generation greatly challenge the original detection and control method; meanwhile, due to the high-speed development of the communication technology, the possibility of information interaction exists between the electric equipment and the power grid, so that the observability and controllability of the demand side are greatly enhanced, and a solid guarantee is provided for the realization of the intelligent demand side.
The intelligent demand side combines the communication technology and the power control technology, and a control object is converted from a traditional passive load into a distributed power supply with activity, energy storage and a controllable load. The randomness, intermittency and fluctuation of the output of the distributed renewable energy sources provide challenges for the quality of electric energy, the stability of a system and the dispatching of a power grid, and the energy storage device is required to be used for improving the quality of the electric energy, inhibiting power fluctuation and improving the utilization efficiency of the electric energy. In addition, the energy storage system can also provide voltage support and Uninterruptible Power Supply (UPS) for the intelligent demand side, relieve Power grid peak blockage, time-of-use Power rate management, and the like.
Therefore, by combining the characteristic of the energy storage system participating in response, an active load coordination control method for the energy storage system participating in response, which gives consideration to benefits of a user side and a power grid side simultaneously based on multi-objective optimization, is researched, on the premise of ensuring the safety of the user and the power grid, the collection and arrangement of the electricity price information, the meteorological information and the user energy demand are realized, and the output of the energy storage system is planned and controlled. On the premise of not changing the willingness of users, the power feeding and utilization behaviors are optimized, and the economic benefit is improved.
At present, the coordination control research of the related documents on the intelligent demand side energy storage system is limited to a theoretical stage, and the main defects of the existing control strategy are as follows: on one hand, the control characteristics and power supply information of the load on the comprehensive demand side do not exist, and a reasonable control scheme cannot be formulated on the premise of meeting the user energy demand to the maximum extent; on the other hand, the existing optimization strategies cannot give consideration to the benefits of power grid operators and users at the same time, and cannot realize the improvement of economic benefits and social benefits at the same time.
Disclosure of Invention
The invention aims to overcome the defects of the existing intelligent demand side control strategy, and provides an active load multi-target coordination control method based on an energy storage system from the viewpoints of avoiding overlarge power of a connecting line and improving the economic benefits of users and power companies.
In order to solve the technical problem, the invention provides an active load multi-target coordination control method based on an energy storage system, which comprises the following steps:
setting parameters, wherein the parameters comprise: control accuracy T, control weight coefficientAndmaximum charge-discharge conversion times N of energy storage systemcdmaxMinimum charging/discharging duration T of the energy storage systemminSOC of energy storage systemmaxDischarge cutoff SOC of energy storage systemmin(ii) a Wherein the control accuracy T is 1440/N, which means that 1440 minutes of the day is divided into N time periods with the length of T,representing the tie line power PpccThe weight coefficient of (a) is,represents the economic benefit B of the userueThe weight coefficient of (a) is,represents the operating benefit B of the electric power companycoA weight coefficient of (a), and
obtaining data including a demand side power contribution P for an nth time period of the day based on meteorological predictionspv(n), the state of charge SOC (n) of the energy storage system, the electricity demand L (n) of the user, and the peak time t of the power gridpAnd the off-peak time period t of the power gridvPeak electricity price u of power grid11And the off-peak electricity price u of the power grid12(ii) a Wherein N is 1,2,3 … N;
screening out an effective control curve combination C (n) ═ C meeting constraint conditions from output control curves of the energy storage system1(n)，C2(n)，…，Ci(n)，…，Cm(n), wherein m is the number of active control curves;
calculating to obtain the tie line power P according to the effective control curve combination and the collected datapccEconomic benefits of the users BueAnd utility company operating benefit Bco；
Will tie line power PpccEconomic benefits of the users BueAnd utility company operating benefit BcoAfter normalization processing, an optimized objective function F is obtained, wherein,
in the formula,represents the normalized tie-line power,the normalized user economic benefit is represented,the normalized utility operation benefit is represented,andrespectively representing the tie line power PpccEconomic benefits of the users BueAnd utility company operating benefit BcoThe normalization coefficient of (a);
sequentially combining the effective control curves into an optimized target function F, gradually calculating and obtaining the effective control curve when the optimized target function F is the minimum value, and taking the effective control curve as an optimal output curve;
and the energy storage system performs rated power charging/discharging according to the control instruction of the optimal output curve.
Further, the tie line power P is calculated and obtained according to the effective control curve combination and the collected datapccEconomic benefits of the users BueAnd utility company operating benefit BcoThe method specifically comprises the following steps:
calculating to obtain the tie line power P according to the effective control curve combination and the collected datapccWherein
in the formula, Ppcc(n)＝Ppv(n)+C(n)·Pes-Pfix(n)-(Pac(n)-Pacr(n))，Ppcc(n) represents the tie line power for the nth time period, PesIndicating rated charge/discharge power, P, of the energy storage systemac(n) total power of load capable of transferring power consumption time in nth time period, Pacr(n) active load power sum, P, for the nth time period participating in the responsefix(n) the total power of the load with fixed electricity utilization time in the nth time period;
calculating to obtain the economic benefit B of the user according to the effective control curve and the collected dataueWherein
in the formula, Bue(n)＝Brc(n)+Bss(n)-Cbe(n)，
Bue(n) represents the economic benefit, P, of the user for the nth time periodn(n) the surplus power of the nth time slot, Cbe(n) the electricity purchase fee paid by the user in the nth time zone, Brc(n) benefit of user's surplus electricity network subsidy in nth time slot, Bss(n) the spontaneous self-use subsidy income of the user in the nth time period, u2For the user's surplus electricity, the price of electricity for accessing the Internet3Self-powered electricity price is automatically provided for the user;
calculating to obtain the operation benefit B of the power company according to the collected dataco，
Wherein,in the formula,
Bco(n)＝Cbt(n)-C′bt(n)+Cal(n)-C′al(n)+B′se(n)-Bse(n)+B′id(n)-Bid(n)，
Bco(n) represents the utility operating benefit for the nth time period, Cbt(n) represents the power purchase cost and the transmission cost from the electric power company to the power plant in the nth time period before the active load response, Cbt' (n) represents the power purchase cost and the transmission cost from the power company to the power plant in the nth time period after the active load response, Cal(n) represents the cost of the utility performing active load compensation during the nth time period prior to the active load response, Cal' (n) represents the cost of the utility to implement active load compensation at the nth time period after the active load response, Bse(n) shows the electric power company's revenue of selling electricity in the nth time period before the active load response, Bse'(n) indicates the electric power company's income from selling electricity in the nth time period after the active load response, Bid(n) represents the indirect revenue of the utility company for the nth time period before the active load response, Bid' (n) indicates utility indirect revenue for the nth time period after the active load response; u. of01And u02Purchase price of electricity, u, for the active and reactive power, respectively, of the electric power company10Compensating the electricity price for active load, kuFor unit apparent power yield, P (n) is total energy consumption requirement of each time interval, and is kept constant, Δ P (n) is active load response power of nth time interval, S (n) and Pl(n)+jQl(n) purchasing power and line loss power for the nth time period of power utility prior to active load response, S' (n) and Pl'(n)+jQl' (n) power and line loss power are purchased by the utility company for the nth time period after the active load response.
Further, the constraint conditions are specifically:
td0-tc≥Tmin，tc0-td≥Tmin，Ncd≤Ncdmax，L(n)＝-(1-k(n))·Pl，0≤Pacr(n)≤Pac，-Pes-Ppv(n)＜ΔP(n)≤P(n)+Pes，Pacr(n)＝k(n)·Pl＝ΔP(n)-C(n)·Pes-Ppv(n)，0≤k(n)≤1，C(n)∈ΩC(n)
Ncand NdNumber of continuous charging and discharging periods, NcdIs the total number of charging and discharging times in one day, td0For the point in time at which the energy storage system changes from a charging state to a discharging or hot standby state, tc0For the point in time at which the energy storage system changes from the discharged state to the charged or hot standby state, tdFor the point in time at which the energy storage system changes from the charging or hot stand-by state to the discharging state, tcFor the point in time, P, at which the energy storage system changes from the discharged or hot standby state to the charged stateacTotal power of load, omega, for transferable electricity timeC(n)Is the value constraint of C (n).
The implementation of the invention has the following beneficial effects:
1. the concept of an output control curve of the energy storage system is introduced, the energy storage system can be used as a bipolar active load, not only can be used as a load, but also can be used as a power supply, the control of the energy storage system is mainly based on the power stabilization of a power grid, and meanwhile, the cost benefit of the energy storage system is considered. Making a power generation power curve and a load power curve corresponding to the demand side of each time period based on meteorological prediction and a load amount before the day; after the parameters are obtained, calculating multi-target functions corresponding to different output control curves of the energy storage system in sequence, obtaining an output control curve corresponding to the F minimum by using a bubbling method, namely a target control curve to be planned, and finally taking the output control curve as an output control instruction of the energy storage system on the same day;
2. on the premise of ensuring the safety of a power grid and not changing the willingness of users, the method optimizes feeding and power utilization behaviors, establishes an optimization model which simultaneously realizes three targets of regional power grid tie line power, user economic benefit and electric power company operation benefit, and can obviously improve the economic benefit and social benefit of an intelligent demand side by the strategy of the model;
3. the multi-target active load coordination control technology provided by the invention can also be applied to the energy storage capacity planning investment in the initial stage of intelligent demand side construction so as to obtain the optimal input/output ratio.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of an active load multi-target coordination control method based on an energy storage system according to an embodiment of the present invention;
FIG. 2 is a block diagram of a system implementing the method of FIG. 1;
FIG. 3 is a schematic flow chart of step S106 in FIG. 1;
FIG. 4 is a graph of line transmission power before an active load response;
fig. 5 is a graph of line transmission power after an active load response.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides an active load multi-target coordination control method based on an energy storage system, as shown in fig. 1, and a system structure for realizing the method is shown in fig. 2.
The embodiment of the invention comprises the following steps:
and S101, setting parameters.
The parameters include: control accuracy T, control weight coefficientAndmaximum charge-discharge conversion times N of energy storage systemcdmaxMinimum charging/discharging duration T of the energy storage systemminSOC of energy storage systemmaxDischarge cutoff SOC of energy storage systemmin(ii) a Wherein the control accuracy T is 1440/N, which means that 1440 minutes of the day is divided into N time periods with the length of T,representing the tie line power PpccThe weight coefficient of (a) is,represents the economic benefit B of the userueThe weight coefficient of (a) is,represents the operating benefit B of the electric power companycoA weight coefficient of (a), and
and S102, acquiring data.
The data includes a demand-side power contribution P for the nth time period of the day based on meteorological predictionspv(n), the state of charge SOC (n) of the energy storage system, the electricity demand L (n) of the user, and the peak time t of the power gridpAnd the off-peak time period t of the power gridvPeak electricity price u of power grid11And the off-peak electricity price u of the power grid12(ii) a Wherein N is 1,2,3 … N.
PpvAnd (n) is the output of all power sources on the demand side based on meteorological prediction, SOC (n) is the SOC state based on real-time detection of the energy storage system, L (n) is the load of the user at the corresponding moment 1 day before planning, and the real-time electricity price and the peak-valley period of the power grid are set by a local power company.
S103, screening out an effective control curve combination C (n) meeting the constraint condition from the output control curves of the energy storage system.
In the whole process, the SOC of the energy storage system is assumed to be always in a charge cut-off state of charge (SOC)maxAnd discharge cutoff state of charge SOCminIn the meantime, an effective control curve combination C (n) { { C) meeting constraint conditions is screened from output control curves of the energy storage system1(n)，C2(n)，…，Ci(n)，…，Cm(n) }. Where m is the number of effective control curves, theoretically the maximum value being 3NBecause the value of C (n) is limited by the constraint condition, the actual effective combination number is far less than 3N。
S104, calculating according to the effective control curve combination and the collected data to obtain the tie line power PpccEconomic benefits of the users BueAnd utility company operating benefit Bco。
Step S104 includes the steps of:
s1041, combining and collecting the data meter according to the effective control curveCalculating to obtain the power P of the tie linepccWherein
in the formula, Ppcc(n)＝Ppv(n)+C(n)·Pes-Pfix(n)-(Pac(n)-Pacr(n))
Ppcc(n) represents the tie line power for the nth time period, PesIndicating the rated charge/discharge power of the energy storage system, read from the energy storage device specification, Pac(n) total power of load capable of transferring power consumption time in nth time period, Pacr(n) active load power sum, P, for the nth time period participating in the responsefix(n) the power utilization time of the nth time period is fixed, and the total power of the loads is obtained. Pac(n)、Pacr(n)、PfixThe (n) parameter is the actual electricity consumption data of the previous day.
S1042, calculating to obtain user economic benefit B according to the effective control curve combination and the collected dataueWherein
in the formula, Bue(n)＝Brc(n)+Bss(n)-Cbe(n)，
Bue(n) represents the economic benefit, P, of the user for the nth time periodn(n) the surplus power of the nth time slot, Cbe(n) the electricity purchase fee paid by the user in the nth time zone, Brc(n) benefit of user's surplus electricity network subsidy in nth time slot, Bss(n) is the user's voluntary self-use complement of the nth time periodPost benefit u2For the user's surplus electricity, the price of electricity for accessing the Internet3Self-powered electricity price is automatically provided for the user;
s1043, calculating and obtaining operation benefit B of the electric power company according to the collected dataco。
Wherein,
in the formula, Bco(n)＝Cbt(n)-C′bt(n)+Cal(n)-C′al(n)+B′se(n)-Bse(n)+B′id(n)-Bid(n)，
Bco(n) represents the utility operating benefit for the nth time period, Cbt(n) represents the power purchase cost and the transmission cost from the electric power company to the power plant in the nth time period before the active load response, Cbt' (n) represents the power purchase cost and the transmission cost from the power company to the power plant in the nth time period after the active load response, Cal(n) represents the cost of the utility performing active load compensation during the nth time period prior to the active load response, Cal' (n) represents the cost of the utility to implement active load compensation at the nth time period after the active load response, Bse(n) shows the electric power company's revenue of selling electricity in the nth time period before the active load response, Bse'(n) indicates the electric power company's income from selling electricity in the nth time period after the active load response, Bid(n) represents the indirect revenue of the utility company for the nth time period before the active load response, Bid' (n) indicates utility indirect revenue for the nth time period after the active load response; u. of01And u02Purchase price of electricity, u, for the active and reactive power, respectively, of the electric power company10Compensating the electricity price for active load, kuFor unit apparent power yield, P (n) is the total energy demand per time interval, and Δ P (n) is the nthTime period active load response power, S (n) and Pl(n)+jQl(n) purchasing power and line loss power for the nth time period of power utility prior to active load response, S' (n) and Pl'(n)+jQl' (n) power purchased by the utility company and power consumed by the line for the nth time period after the active load response, refer to fig. 4 and 5. Cal(n)、Bid(n)、u01、u02、u10、kuGiven by the electric company, the other power parameters are actual electricity consumption data of the previous day.
S105, connecting line power PpccEconomic benefits of the users BueAnd utility company operating benefit BcoAnd after normalization processing, obtaining an optimized objective function F.
Specifically, the intelligent demand side power supply grid connection changes the traditional power grid-user power supply mode, and meanwhile peak load pressure of a power distribution network is effectively relieved. However, when the power transmitted by the bidirectional power flow is too large, the power grid tie line is adversely affected. Therefore, the tie line power PpccMinimum, user economic benefit BueMaximum and utility company operating benefit BcoTaking the maximum as an optimization target to obtain an optimization target function F, wherein,in the formula,represents the normalized tie-line power,the normalized user economic benefit is represented,the normalized utility operation benefit is represented,andrespectively representing the tie line power PpccEconomic benefits of the users BueAnd utility company operating benefit BcoThe normalized coefficient of (2).
And S106, sequentially bringing the effective control curves in the effective control curve combination into an optimized objective function F, gradually calculating and obtaining the effective control curve when the optimized objective function F is the minimum value, and taking the effective control curve as a target control curve.
Specifically, the processing of step S106 is as shown in fig. 3.
And S107, the reserve system carries out rated power charging/discharging according to the control of the target control curve.
When the SOC of the energy storage system does not meet the charging/discharging condition, execution is suspended, and the energy storage system is protected mainly.
In step S103, the constraint condition is specifically:
td0-tc≥Tmin，tc0-td≥Tmin，Ncd≤Ncdmax，L(n)＝-(1-k(n))·Pl，0≤Pacr(n)≤Pac，-Pes-Ppv(n)＜ΔP(n)≤P(n)+Pes，Pacr(n)＝k(n)·Pl＝ΔP(n)-C(n)·Pes-Ppv(n)，0≤k(n)≤1，C(n)∈ΩC(n)；
Ncand NdNumber of continuous charging and discharging periods, NcdIs the total number of charging and discharging times in one day, td0For the point in time at which the energy storage system changes from a charging state to a discharging or hot standby state, tc0For the point in time at which the energy storage system changes from the discharged state to the charged or hot standby state, tdFor the point in time at which the energy storage system changes from the charging or hot stand-by state to the discharging state, tcFor the point in time, P, at which the energy storage system changes from the discharged or hot standby state to the charged stateacTotal power of load, omega, for transferable electricity timeC(n)Is the value constraint of C (n).
The implementation of the invention has the following beneficial effects:
1. the concept of an output control curve of the energy storage system is introduced, the energy storage system can be used as a bipolar active load, not only can be used as a load, but also can be used as a power supply, the control of the energy storage system is mainly based on the power stabilization of a power grid, and meanwhile, the cost benefit of the energy storage system is considered. Making a power generation power curve and a load power curve corresponding to the demand side of each time period based on meteorological prediction and a load amount before the day; after the parameters are obtained, calculating multi-target functions corresponding to different output control curves of the energy storage system in sequence, obtaining an output control curve corresponding to the F minimum by using a bubbling method, namely a target control curve to be planned, and finally taking the output control curve as an output control instruction of the energy storage system on the same day;
2. on the premise of ensuring the safety of a power grid and not changing the willingness of users, the method optimizes feeding and power utilization behaviors, establishes an optimization model which simultaneously realizes three targets of regional power grid tie line power, user economic benefit and electric power company operation benefit, and can obviously improve the economic benefit and social benefit of an intelligent demand side by the strategy of the model;
3. the multi-target active load coordination control technology provided by the invention can also be applied to the energy storage capacity planning investment in the initial stage of intelligent demand side construction so as to obtain the optimal input/output ratio.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (3)
1. An active load multi-target coordination control method based on an energy storage system is characterized by comprising the following steps:
setting parameters, wherein the parameters comprise: control accuracy T, control weight coefficientAndmaximum charge-discharge conversion times N of energy storage systemcdmaxMinimum charging/discharging duration T of the energy storage systemminSOC of energy storage systemmaxDischarge cutoff SOC of energy storage systemmin(ii) a Wherein the control accuracy T is 1440/N, which means that 1440 minutes of the day is divided into N time periods with the length of T,representing the tie line power PpccThe weight coefficient of (a) is,represents the economic benefit B of the userueThe weight coefficient of (a) is,represents the operating benefit B of the electric power companycoA weight coefficient of (a), and
obtaining data including a demand side power contribution P for an nth time period of the day based on meteorological predictionspv(n), the state of charge SOC (n) of the energy storage system, the electricity demand L (n) of the user, and the peak time t of the power gridpAnd the off-peak time period t of the power gridvPeak electricity price u of power grid11And the off-peak electricity price u of the power grid12(ii) a Wherein N is 1,2,3 … N;
screening out an effective control curve combination C (n) ═ C meeting constraint conditions from output control curves of the energy storage system1(n)，C2(n)，…，Ci(n)，…，Cm(n), wherein m is the number of active control curves;
calculating to obtain the tie line power P according to the effective control curve combination and the collected datapccEconomic benefits of the users BueAnd utility company operating benefit Bco；
Will tie line power PpccEconomic benefits of the users BueAnd utility company operating benefit BcoNormalization is carried outAfter the treatment, an optimized objective function F is obtained, wherein,
<mrow> <mi>F</mi> <mo>=</mo> <munder> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> <mi>u</mi> </munder> <mo>&Sigma;</mo> <mrow> <mo>(</mo> <msub> <mi>&omega;</mi> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>c</mi> <mi>c</mi> </mrow> </msub> </msub> <mo>&CenterDot;</mo> <msub> <mi>I</mi> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>c</mi> <mi>c</mi> </mrow> </msub> </msub> <mo>+</mo> <msub> <mi>&omega;</mi> <msub> <mi>B</mi> <mrow> <mi>u</mi> <mi>e</mi> </mrow> </msub> </msub> <mo>&CenterDot;</mo> <msub> <mi>I</mi> <msub> <mi>B</mi> <mrow> <mi>u</mi> <mi>e</mi> </mrow> </msub> </msub> <mo>+</mo> <msub> <mi>&omega;</mi> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> </mrow> </msub> </msub> <mo>&CenterDot;</mo> <msub> <mi>I</mi> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> </mrow> </msub> </msub> <mo>)</mo> </mrow> </mrow>
in the formula,represents the normalized tie-line power,the normalized user economic benefit is represented,the normalized utility operation benefit is represented,andrespectively representing the tie line power PpccEconomic benefits of the users BueAnd utility company operating benefit BcoThe normalization coefficient of (a);
sequentially combining the effective control curves into an optimized target function F, gradually calculating and obtaining the effective control curve when the optimized target function F is the minimum value, and taking the effective control curve as an optimal output curve;
and the energy storage system performs rated power charging/discharging according to the control instruction of the optimal output curve.
2. The active load multi-target coordination control method based on energy storage system as claimed in claim 1, wherein the tie line power P is obtained through calculation according to the effective control curve combination and the collected datapccEconomic benefits of the users BueAnd utility company operating benefit BcoThe method specifically comprises the following steps:
calculating to obtain the tie line power P according to the effective control curve combination and the collected datapccWherein
in the formula, Ppcc(n)＝Ppv(n)+C(n)·Pes-Pfix(n)-(Pac(n)-Pacr(n))，Ppcc(n) represents the tie line power for the nth time period, PesIndicating rated charge/discharge power, P, of the energy storage systemac(n) the transferable electricity utilization in the nth time periodTotal power of load in time, Pacr(n) active load power sum, P, for the nth time period participating in the responsefix(n) the total power of the load with fixed electricity utilization time in the nth time period;
calculating to obtain the economic benefit B of the user according to the effective control curve and the collected dataueWhereinin the formula, Bue(n)＝Brc(n)+Bss(n)-Cbe(n)，
<mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>c</mi> <mi>c</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>v</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>+</mo> <mi>C</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>&CenterDot;</mo> <msub> <mi>P</mi> <mrow> <mi>e</mi> <mi>s</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>P</mi> <mrow> <mi>f</mi> <mi>i</mi> <mi>x</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>-</mo> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mrow> <mi>a</mi> <mi>c</mi> </mrow> </msub> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>-</mo> <msub> <mi>P</mi> <mrow> <mi>a</mi> <mi>c</mi> <mi>r</mi> </mrow> </msub> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mtable> <mtr> <mtd> <mrow> <msub> <mi>C</mi> <mrow> <mi>b</mi> <mi>e</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <mo>-</mo> <mrow> <mo>(</mo> <msub> <mi>u</mi> <mn>11</mn> </msub> <mo>+</mo> <msub> <mi>u</mi> <mn>12</mn> </msub> <mo>)</mo> </mrow> <mo>&CenterDot;</mo> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>c</mi> <mi>c</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>c</mi> <mi>c</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo><</mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>B</mi> <mrow> <mi>r</mi> <mi>c</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>u</mi> <mn>2</mn> </msub> <mo>&CenterDot;</mo> <msub> <mi>P</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mn>0</mn> <mo><</mo> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>c</mi> <mi>c</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>B</mi> <mrow> <mi>s</mi> <mi>s</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <msub> <mi>u</mi> <mn>3</mn> </msub> <mo>&CenterDot;</mo> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>v</mi> </mrow> </msub> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>+</mo> <msub> <mi>P</mi> <mrow> <mi>e</mi> <mi>s</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>c</mi> <mi>c</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo><</mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>B</mi> <mrow> <mi>s</mi> <mi>s</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>u</mi> <mn>3</mn> </msub> <mo>&CenterDot;</mo> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mrow> <mi>f</mi> <mi>i</mi> <mi>x</mi> </mrow> </msub> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>+</mo> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mrow> <mi>a</mi> <mi>c</mi> </mrow> </msub> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>-</mo> <msub> <mi>P</mi> <mrow> <mi>a</mi> <mi>c</mi> <mi>r</mi> </mrow> </msub> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mn>0</mn> <mo><</mo> <msub> <mi>P</mi> <mrow> <mi>p</mi> <mi>c</mi> <mi>c</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> </mtable> </mtd> </mtr> </mtable> </mfenced> <mo>,</mo> </mrow>
Bue(n) represents the economic benefit, P, of the user for the nth time periodn(n) the surplus power of the nth time slot, Cbe(n) the electricity purchase fee paid by the user in the nth time zone, Brc(n) benefit of user's surplus electricity network subsidy in nth time slot, Bss(n) the spontaneous self-use subsidy income of the user in the nth time period, u2For the user's surplus electricity, the price of electricity for accessing the Internet3Self-powered electricity price is automatically provided for the user;
calculating to obtain the operation benefit B of the power company according to the collected datacoWhereinin the formula, Bco(n)＝Cbt(n)-Cb′t(n)+Cal(n)-Ca′l(n)+Bs′e(n)-Bse(n)+Bi′d(n)-Bid(n)，
<mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>C</mi> <mrow> <mi>b</mi> <mi>t</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>u</mi> <mn>01</mn> </msub> <mo>&CenterDot;</mo> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mi>l</mi> </msub> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>+</mo> <mi>P</mi> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>u</mi> <mn>02</mn> </msub> <mo>&CenterDot;</mo> <msub> <mi>Q</mi> <mi>l</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msubsup> <mi>C</mi> <mrow> <mi>b</mi> <mi>t</mi> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>u</mi> <mn>01</mn> </msub> <mo>&CenterDot;</mo> <mrow> <mo>(</mo> <msubsup> <mi>P</mi> <mi>l</mi> <mo>&prime;</mo> </msubsup> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>+</mo> <mi>P</mi> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>-</mo> <mi>&Delta;</mi> <mi>P</mi> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>u</mi> <mn>02</mn> </msub> <mo>&CenterDot;</mo> <msubsup> <mi>Q</mi> <mi>l</mi> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>C</mi> <mrow> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msubsup> <mi>C</mi> <mrow> <mi>a</mi> <mi>l</mi> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>u</mi> <mn>10</mn> </msub> <mo>&CenterDot;</mo> <mi>&Delta;</mi> <mi>P</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>B</mi> <mrow> <mi>s</mi> <mi>e</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <msub> <mi>u</mi> <mn>11</mn> </msub> <mo>+</mo> <msub> <mi>u</mi> <mn>12</mn> </msub> <mo>)</mo> </mrow> <mo>&CenterDot;</mo> <mi>P</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msubsup> <mi>B</mi> <mrow> <mi>s</mi> <mi>e</mi> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <msub> <mi>u</mi> <mn>11</mn> </msub> <mo>+</mo> <msub> <mi>u</mi> <mn>12</mn> </msub> <mo>)</mo> </mrow> <mo>&CenterDot;</mo> <mrow> <mo>(</mo> <mi>P</mi> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>-</mo> <mi>&Delta;</mi> <mi>P</mi> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>B</mi> <mrow> <mi>i</mi> <mi>d</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msubsup> <mi>B</mi> <mrow> <mi>i</mi> <mi>d</mi> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>k</mi> <mi>u</mi> </msub> <mrow> <mo>(</mo> <mi>S</mi> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>-</mo> <msup> <mi>S</mi> <mo>&prime;</mo> </msup> <mo>(</mo> <mi>n</mi> <mo>)</mo> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>,</mo> </mrow>
Bco(n) represents the utility operating benefit for the nth time period, Cbt(n) represents the power purchase cost and the transmission cost from the electric power company to the power plant in the nth time period before the active load response, Cbt' (n) represents the power purchase cost and the transmission cost from the power company to the power plant in the nth time period after the active load response, Cal(n) represents the cost of the utility performing active load compensation during the nth time period prior to the active load response, Cal' (n) represents the cost of the utility to implement active load compensation at the nth time period after the active load response, Bse(n) shows the electric power company's revenue of selling electricity in the nth time period before the active load response, Bse'(n) indicates the electric power company's income from selling electricity in the nth time period after the active load response, Bid(n) represents the indirect revenue of the utility company for the nth time period before the active load response, Bid' (n) indicates utility indirect revenue for the nth time period after the active load response; u. of01And u02Purchase price of electricity, u, for the active and reactive power, respectively, of the electric power company10Compensating the electricity price for active load, kuFor unit apparent power yield, P (n) is total energy consumption requirement of each time interval, and is kept constant, Δ P (n) is active load response power of nth time interval, S (n) and Pl(n)+jQl(n) purchasing power and line loss power for the nth time period of power utility prior to active load response, S' (n) and Pl'(n)+jQl' (n) power and line loss power are purchased by the utility company for the nth time period after the active load response.
3. The active load multi-target coordination control method based on the energy storage system as claimed in claim 2, wherein the constraint condition is specifically:
<mrow> <mi>C</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mo>-</mo> <mn>1</mn> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mi>t</mi> <mo>&Element;</mo> <msub> <mi>t</mi> <mi>v</mi> </msub> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mi>S</mi> <mi>O</mi> <mi>C</mi> <mo>&le;</mo> <msub> <mi>SOC</mi> <mi>max</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mn>0</mn> <mo>,</mo> </mrow> </mtd> <mtd> <mrow></mrow> </mtd> <mtd> <mrow></mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mn>1</mn> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mi>t</mi> <mo>&Element;</mo> <msub> <mi>t</mi> <mi>p</mi> </msub> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <msub> <mi>SOC</mi> <mi>min</mi> </msub> <mo>&le;</mo> <mi>S</mi> <mi>O</mi> <mi>C</mi> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>,</mo> </mrow>
<mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>u</mi> <mn>12</mn> </msub> <mo>=</mo> <mn>0</mn> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mi>t</mi> <mo>&Element;</mo> <msub> <mi>t</mi> <mi>p</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>u</mi> <mn>11</mn> </msub> <mo>=</mo> <mn>0</mn> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mi>t</mi> <mo>&Element;</mo> <msub> <mi>t</mi> <mi>v</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>,</mo> </mrow>
td0-tc≥Tmin，tc0-td≥Tmin，Ncd≤Ncdmax，L(n)＝-(1-k(n))·Pl，0≤Pacr(n)≤Pac，-Pes-Ppv(n)＜ΔP(n)≤P(n)+Pes，Pacr(n)＝k(n)·Pl＝ΔP(n)-C(n)·Pes-Ppv(n)，0≤k(n)≤1，C(n)∈ΩC(n)
Ncand NdNumber of continuous charging and discharging periods, NcdIs the total number of charging and discharging times in one day, td0For the point in time at which the energy storage system changes from a charging state to a discharging or hot standby state, tc0For the point in time at which the energy storage system changes from the discharged state to the charged or hot standby state, tdFor the point in time at which the energy storage system changes from the charging or hot stand-by state to the discharging state, tcFor the point in time, P, at which the energy storage system changes from the discharged or hot standby state to the charged stateacTotal power of load, omega, for transferable electricity timeC(n)Is the value constraint of C (n).
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