AU2022353321A1

AU2022353321A1 - Multi-stage multi-energy distributed resource aggregation method and apparatus of virtual power plant, and storage medium

Info

Publication number: AU2022353321A1
Application number: AU2022353321A
Authority: AU
Inventors: Yueshuang BAO; Xueting CHENG; Jie Hao; Fan HU; Yulong Jin; Rui Li; Xinyuan Liu; Yaohui Lu; Jun PI; Ying QU; Xincong SHI; Changwen SUN; Jinhao WANG; Tan WANG; Weiru Wang; Gang Yang; Huiping ZHENG; Ying Zhong
Original assignee: State Grid Shanxi Electric Power Res Institute; Electric Power Research Institute of State Grid Shanxi Electric Power Co Ltd
Current assignee: Electric Power Research Institute of State Grid Shanxi Electric Power Co Ltd
Priority date: 2021-12-08
Filing date: 2022-12-01
Publication date: 2023-06-22
Also published as: WO2023103862A1; CN114154910A

Abstract

The present disclosure provides a multi-stage multi-energy distributed resource aggregation method and apparatus of a virtual power plant, and a storage medium. The multi-stage multi-energy distributed resource aggregation method includes: obtaining prices and energy that are reported in real time by various distributed resources; sorting and grading the distributed resources based on the prices and the energy, formulating an aggregation scheme for distributed resources of a same grade based on a preset admission rule, and performing aggregation; participating in scheduling of a virtual power plant based on an aggregation result, obtaining a unit fee of a scheduling volume, and calculating a scheduling fee based on the aggregation result; calculating an operation earning of the virtual power plant based on an energy selling income, an energy purchasing cost, the aggregation cost, and the scheduling fee; and constructing an objective function by taking a maximum earning of the virtual power plant as a goal, and obtaining a final aggregation scheme by the objective function. The present disclosure can improve market participation rates and participation grades of the distributed resources, integrate and utilize the distributed resources to participate in a market, and maximize an economic benefit of the virtual power plant.

Description

MULTI-STAGE MULTI-ENERGY DISTRIBUTED RESOURCE AGGREGATION METHOD AND APPARATUS OF VIRTUAL POWER PLANT, AND STORAGE MEDIUM TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of virtual power plants, and provides a multi-stage multi-energy distributed resource aggregation method and apparatus of a virtual power plant, and a storage medium.

BACKGROUND

[0002] Energy resource is the basis for human survival and development. Sustainable and low-carbon energy resource supply is a common concern of all countries in the world today. To this end, all sectors of society have carried out a lot of research on improving energy resource utilization and reducing a proportion of fossil energy resources. With the development of renewable energy resources, energy resource interconnection, and energy resource marketization in the world, a user-side resource is more willing to participate in a market transaction. How to aggregate and make full use of user-side electricity-gas-heat multi-energy distributed resources to participate in a transaction of a virtual power plant, and how to construct a business model used by the multi-energy distributed resources to participate in a market transaction of the virtual power plant are urgent problems to be resolved at present.

[0003] Market players of a distributed resource are mainly the multi-energy distributed resource and the virtual power plant, and their users are scattered. The quantity of single users is small and it is difficult to manage them uniformly. Many distributed resources that do not meet a transaction admission requirement are difficult to participate in a transaction, resulting in waste. The virtual power plant is configured to perform aggregation and coordinated optimization on a distributed generator (DG), an energy storage system, a controllable load, and other distributed energy resources (DERs), so as to participate in the operation of an electricity market and a power grid as a special power plant. The virtual power plant can improve the utilization of a new energy resource when a proportion of new energy power generation continues to increase. In addition, as a typical management mode of a DER, the virtual power plant can improve the overall management and control capability of the DER through optimization and aggregation, thereby improving the overall economical efficiency and competitiveness of the DER in the electricity market. The virtual power plant is a new generation of a business model that aggregates the distributed resource to achieve coordinated development of "source-network-load-storage". It can effectively aggregate the distributed resource to participate in the transaction operation and optimization of a system. In this business model, the virtual power plant may be operated by a power grid company to enter into a leasing model with an operator, participate in a day-ahead market and a real-time market, and collect a platform leasing fee and a grid-crossing fee in transaction and operation processes. This is a mutually beneficial business model for the power grid company, the operator, and the distributed resource.

[0004] At present, some research has been carried out to establish a stochastic model for a load aggregator to optimize a one-day bidding strategy, such that small and medium-sized loads can participate in a transaction in the electricity market. In addition, from a perspective of overall aggregation, an aggregation method based on user demand in a regional electricity transaction scenario is proposed, and an aggregation profit increases with an increase in the quantity of aggregated resources. Considering a new market mode of a load aggregation resource participating in the market transaction, it is found that participation of a load-side resource in the market can bring flexibility, which is more flexible than market regulation under a vertical management mode of the electricity market. Most existing researche consider the participation of the load-side resource in the market, and most researches on the aggregation of the DER and participation of the DER in the market transaction is carried out from a perspective of a power system. A user side is often a controlled unit, and less involves a multi-level admission threshold problem of the user-side resource participating in a multi-energy transaction. Researches on participation in purchasing and selling decision-making and scheduling of the virtual power plant through graded user aggregation are not comprehensive.

SUMMARY

[0005] In order to overcome the disadvantages in the prior art, the present disclosure provides a multi-stage multi-energy distributed resource aggregation method and apparatus of a virtual power plant, and a storage medium, so as to improve market participation rates and participation grades of distributed resources, integrate and utilize the distributed resources to participate in a market, and maximize an economic benefit of a virtual power plant.

[0006] In order to achieve the above objective, the present disclosure adopts the following technical solutions:

[0007] According to a first aspect, the present disclosure provides a multi-stage multi-energy distributed resource aggregation method of a virtual power plant, including:

[0008] obtaining prices and energy that are reported in real time by various distributed resources;

[0009] sorting and grading the distributed resources based on the prices and the energy, formulating an aggregation scheme for distributed resources of a same grade based on a preset admission rule, and performing aggregation;

[0010] participating in scheduling of a virtual power plant based on an aggregation result, obtaining a unit fee of a scheduling volume, and calculating a scheduling fee based on the aggregation result;

[0011] obtaining transaction prices and transaction volumes of a real-time market and a day-ahead market, and calculating an energy selling income and an energy purchasing cost of the virtual power plant;

[0012] obtaining a unit compensation fee of the scheduling volume, and calculating an aggregation cost of the virtual power plant based on the aggregation result;

[0013] constructing an objective function based on the energy selling income, the energy purchasing cost, the aggregation cost, and the scheduling fee to calculate an operation earning of the virtual power plant; and

[0014] taking a maximum earning of the virtual power plant as a goal, and obtaining a final aggregation scheme by the objective function, so as to regulate the distributed resources based on the aggregation scheme.

[0015] Optionally, the distributed resources are DERs or controllable dummy loads (DLs), the DERs include a controllable DG and an uncontrollable DG, and the controllable DLs include an interruptible load (IL) and a translatable load (TL).

[0016] Optionally, the admission rule includes a first-level indicator and a second-level indicator that are set based on adjustable load capacities and supply capacities of electricity, gas, and heat of the distributed resources.

[0017] Optionally, priorities of aggregating the distributed resources of the same grade based on the preset admission rule in descending order are as follows: a distributed resource whose indicator is less than or equal to the first-level indicator, a distributed resource whose indicator is greater than the first-level indicator and less than the second-level indicator, and a distributed resource whose indicator is greater than or equal to the second-level indicator.

[0018] Optionally, the performing aggregation includes aggregating the distributed resources into a power supply resource (PSR), an interruptible load resource (ILR), and a translatable load resource (TLR).

[0019] Optionally, the scheduling fee is:

[ /1 EILR K L I M CR -- CR=)T pa~SR 'sP Ne SR PeDs R h,sR NERp ks 'k,s~t

+I L G TLRN RP +TLI~

S 1 9

[0020] where CR represents a calling fee after the aggregation; AT represents duration of a calling time period; D, H, and L represent quantities of PSRs, ILRs, and TLRs respectively; and E, K, and G represent quantities of DERs, ILs, and TLs respectively;

[0021] pZSR represents a unit fee of a calling volume of an sth type of energy resource of a dth

PSR, p represents a unit fee of a calling volume of an sth type of energy resource of an hth

ILR, and pR represents a unit fee of a calling volume of an sth type of energy resource of an

1 th TLR;

[0022] NPR, N R, and NTR represent variables set to 0 or 1, where when the variable is set to

1, it indicates participating in the aggregation, and when the variable is set to 0, it indicates not participating in the aggregation;

[0023] PDER represents a power output of an sth type of energy resource of an eth DER in a

time period, represents a quantity of interrupted loads of an th typeof energyresource

of a kth IL in the time period t, and represents a quantity of translated loads of an sth

type of energy resource of a gth TL in the time period t; and

[0024] s = 1, 2, 3, which respectively represent electricity, gas, and heat energy resources.

[0025] Optionally, the objective function is: T N K G M

max G ATZ {psell [Y Pt -Y(1 - NI)Pr,t- (1 - N R)pg ,t p 7 ,s,t t=1 s i=1 k=1 g=1 m=1 E K

- pPs-pt'sPt's - pe(1 - N Rpes Y s(1 - N Pks,t e=1 k=1 G

-Y ps(1-N TR pTL} - CR g=1

[0026] where max G represents a maximum profit of the virtual power plant in one scheduling cycle, AT represents duration of the scheduling cycle, and T represents a total quantity of time periods in the scheduling cycle;

[0027] p sl represents a price at which the sth type of energy resource is sold to a user in the

time period t, Pst represents a multi-energy load of an ith user in the time period t, P ,,

represents an aggregated calling volume of an mth sorted grade in the time period t, and N and M represent a quantity of users and a quantity of sorted grades respectively;

[0028] Pd, and P respectively represent the transaction price and the transaction volume of the day-ahead market, and p,s and P[, respectively represent the transaction price and the transaction volume of the virtual power plant in the real-time market;

[0029] when p,s > 0, thesth typeof energyresource is purchased from the real-time market; or when p,s < 0, the sth typeof energyresource is soldto the real-time market; and

[0030] pDER represents a unit payment fee of the sth type of energy resource of the eth DER, IL th Pks represents a unit compensation fee of load interruption of the st type of energy resource of

the kth IL, and pL represents a unit compensation fee of load translation of the Sth type of

energy resource of the gth TL.

[0031] According to a second aspect, the present disclosure provides a multi-stage multi-energy distributed resource aggregation apparatus of a virtual power plant, including:

[0032] a data obtaining module configured to obtain prices and energy that are reported in real time by various distributed resources;

[0033] a resource aggregation module configured to sort and grade the distributed resources based on the prices and the energy, formulate an aggregation scheme for distributed resources of a same grade based on a preset admission rule, and perform aggregation;

[0034] a scheduling fee module configured to participate in scheduling of a virtual power plant based on an aggregation result, obtain a unit fee of a scheduling volume, and calculate a scheduling fee based on the aggregation result;

[0035] an energy purchasing and selling module configured to obtain transaction prices and transaction volumes of a real-time market and a day-ahead market, and calculate an energy selling income and an energy purchasing cost of the virtual power plant;

[0036] an aggregation cost module configured to obtain a unit compensation fee of the scheduling volume, and calculate an aggregation cost of the virtual power plant based on the aggregation result;

[0037] an earning calculation module configured to construct an objective function based on the energy selling income, the energy purchasing cost, the aggregation cost, and the scheduling fee to calculate an operation earning of the virtual power plant; and

[0038] a scheme obtaining module configured to take a maximum earning of the virtual power plant as a goal, and obtain a final aggregation scheme by the objective function, so as to regulate the distributed resources based on the aggregation scheme.

[0039] According to a third aspect, the present disclosure provides a multi-stage multi-energy distributed resource aggregation apparatus of a virtual power plant, including a processor and a storage medium, where

[0040] the storage medium is configured to store instructions; and

[0041] the processor is configured to perform operations according to the instructions to perform the steps of the method described in the first aspect.

[0042] According to a fourth aspect, the present disclosure provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the method described in the first aspect.

[0043] Compared with the prior art, the present disclosure achieves the following beneficial effects:

[0044] The multi-stage multi-energy distributed resource aggregation method and apparatus of a virtual power plant, and the storage medium that are provided in the present disclosure clarify a linkage relation between the virtual power plant and the distributed resource and between the virtual power plant and an external market, such that the distributed resource can participate in market dealing and operation, and a user-side resource can be fully utilized; perform dynamic resource grading, so as to enable a distributed, irregular, and small-capacity resource that is difficult to be admitted to reach a lowest admission rule, and enable a distributed resource that only meets a low admission rule to reach a higher-level admission rule through dynamic aggregation, thereby improving a market participation rate and a participation grade of the distributed resource; calculate the calling fee, so as to help call the distributed resource and make full use of the user-side resource; and construct the objective function by taking the maximum earning of the virtual power plant as the goal, such that the virtual power plant integrates and utilizes the distributed resource to participate in the market while ensuring safe and stable operation of an energy system in a region within the jurisdiction of the virtual power plant, so as to maximize an economic benefit of the virtual power plant.

BRIEF DESCRIPTION OF THE DRAWINGS

[0045] FIG. 1 is a flowchart of a multi-stage multi-energy distributed resource aggregation method of a virtual power plant according to an embodiment of the present disclosure;

[0046] FIG. 2 is a first schematic diagram of resource calling according to an embodiment of the present disclosure;

[0047] FIG. 3 is a second schematic diagram of resource calling according to an embodiment of the present disclosure;

[0048] FIG. 4 is a third schematic diagram of resource calling according to an embodiment of the present disclosure;

[0049] FIG. 5 is a fourth schematic diagram of resource calling according to an embodiment of the present disclosure;

[0050] FIG. 6 is a schematic diagram of an operation strategy of an energy storage resource of a virtual power plant according to an embodiment of the present disclosure;

[0051] FIG. 7 is a schematic diagram of a transaction volume of a virtual power plant in a real-time market according to an embodiment of the present disclosure; and

[0052] FIG. 8 is a schematic diagram of a retail price of a virtual power plant according to an embodiment of the present disclosure.

DETAILED DESCRIPTION

[0053] The present disclosure is further described in combination with the following examples are only used for describing the technical solutions of the present disclosure more clearly, and are not intended to limit the protection scope of the present disclosure.

[0054] Embodiment 1

[0055] As shown in FIG. 1, the present disclosure provides a multi-stage multi-energy distributed resource aggregation method of a virtual power plant, including the following steps.

[0056] 1. Obtain prices and energy that are reported in real time by distributed resources.

[0057] The distributed resources are DERs or controllable DLs, the DERs include a controllable DG and an uncontrollable DG, and the controllable DLs include an IL and a TL.

[0058] 2. Sort and grade the distributed resources based on the prices and the energy, formulate an aggregation scheme for distributed resources of a same grade based on a preset admission rule, and perform aggregation.

[0059] The admission rule includes a first-level indicator and a second-level indicator that are set based on adjustable load capacities and supply capacities of electricity, gas, and heat of the distributed resources.

[0060] Priorities of aggregating the distributed resources of the same grade based on the preset admission rule in descending order are as follows: a distributed resource whose indicator is less than or equal to the first-level indicator, a distributed resource whose indicator is greater than the first-level indicator and less than the second-level indicator, and a distributed resource whose indicator is greater than or equal to the second-level indicator.

[0061] The performing aggregation includes aggregating the distributed resources into a PSR, an ILR, and a TLR.

[0062] 3. Participate in scheduling of a virtual power plant based on an aggregation result, obtain a unit fee of a scheduling volume, and calculate a scheduling fee based on the aggregation result.

[0063] The scheduling fee is:

T I D P E + H PLR KE IRI CR- ATR N= R + p N Ps,t

+ t=1 S d e s h k L G

+ I s p( I' R N IR NT s9 pg ,t s S 1

[0064] where CR represents a calling fee after the aggregation; AT represents a duration of a calling time period; D, H, and L represent quantities of PSRs, ILRs, and TLRs respectively; and E, K, and G represent quantities of DERs, ILs, and TLs respectively;

[0065] paSR represents a unit fee of a calling volume of an sth type of energy resource of a dth

PSR, p I represents a unit fee of a calling volume of an sth type of energy resource of an hth

ILR, and p4R represents a unit fee of a calling volume of an sth type of energy resource of an

1 th TLR;

[0066] NeR, NkIR, and Ng R Tepresent variables set to 0 or 1, where when the variable is set to

[0067] PeDE represents a power output of an sth type of energy resource of an eth DER in a

time period t, Pk,, represents a quantity of interrupted loads of ansth typeof energyresource

of a kth IL in the time period t, and P represents a quantity of translated loads of an sth

type of energy resource of a gth TL in the time period t; and

[0068] s = 1, 2, 3, which respectively represent electricity, gas, and heat energy resources.

[0069] 4. Obtain transaction prices and transaction volumes of a real-time market and a day-ahead market, and calculate an energy selling income and an energy purchasing cost of the

virtual power plant.

[0070] 5. Obtain a unit compensation fee of the scheduling volume, and calculate an aggregation cost of the virtual power plant based on the aggregation result.

[0071] 6. Calculate an operation earning of the virtual power plant based on the energy selling

income, the energy purchasing cost, the aggregation cost, and the scheduling fee.

[0072] An objective function is:

T N K G M

max G =AT {pes [Y Pits, - (1 - NIRLsPt - - NSRAp ,tm t=1 s i=1 k=1 g=1 m=1 E K

-- psPt- pP, -- peR(1- NSR)pe -Nt Is(1 e=1 k=1 G

-ZpI~(1 - NR } CR g=1

[0073] where max G represents a maximum profit of the virtual power plant in one scheduling cycle, AT represents duration of the scheduling cycle, and T represents a total quantity of time periods in the scheduling cycle;

[0074] p sl represents a price at which the sth type of energy resource is sold to a user in the

time period t, P,, represents a multi-energy load of an ith user in the time period t,Pmi,s,t

[0075]tps andP respectively represent the transaction price and the transaction volume of

the day-ahead market, and pr,s and Ptr,, respectively represent the transaction price and the transaction volume of the virtual power plant in the real-time market;

[0076] when pr,s > 0, thesth typeof energyresource is purchased from the real-time market; or when pr,s < 0, the sth typeof energyresource is soldto the real-time market; and

[0077] pDER represents a unit payment fee of the sth type of energy resource of the eth DER, IL th Pks represents a unit compensation fee of load interruption of the st type of energy resource of

the kth IL, and ps represents a unit compensation fee of load translation of the Sth type of

energy resource of the gth TL.

[0078] 7. Construct the objective function by taking a maximum earning of the virtual power plant as a goal, and obtain a final aggregation scheme by the objective function.

[0079] Specifically, the objective function can also set following constraints:

[0080] (1) Electricity-specific power flow constraint

Pijt = k,t + ijj,t Pj,t kEj

ij,t k EQjk,t + xijIjt+

Pi't = P + TL +Pch - PiEB kpIL TL,- pDER t gEt P-,t it it-it-E ~ ~ gEi g EL mEi pmR,t

QNt L TL,+ T ?,L,- VnIL - V QDER Q't+ g~ Qg~ Yg~,t - k~ Le1k,t e MEi 'mt

V2 V - 2(r P + x Q ;) +(riz jt ijj jtt i t

Vi'min Vi't ! Vi'max Iij,t Iij,max

IQ,tI Qo,max

[0081] where Pij,t and Q ij ,t respectively represent an active power and a reactive power of a

power grid branch ij in the time period t; k represents base load of a tail-end node with a node j as a first node; rij and xij respectively represent resistance and reactance of the power grid branch ij; Iij,t represents a line current amplitude of the power grid branch ij; Pi,t and

Qi,t respectively represent net injection values of an active power and a reactive power of a node

i;P andPO' respectively represent charging and discharging powers of an electricity energy

storage (EES) system; PP represents a power of an electric boiler (EB); QQg, Qt' , Q T',

t, QetR, and Qt respectively represent a reactive power of a load of the node i in the

time period t, a load into which a reactive power of a gth TL resource is transferred in the time

period t, a load from which the reactive power of the gth TL resource is transferred in the time period t, a load on which a reactive power of a kth IL resource is interrupted in the time period t, a reactive power of the eth DER in the time period t, and a hierarchically and a reactive power of an mth resource after graded dynamic combination in the time period t; Vi,t and Vj,t

respectively represent voltage amplitudes of the nodes i andj; Vimax and Vimin respectively represent upper and lower limits of the voltage amplitude of the node i; Iij,max represents an

upper limit of a current amplitude of the power grid branch ij; Po, and QOt respectively represent active and reactive powers flowing in/out of a tie line of a main power grid between a

superior power grid and the virtual power plant in the time period t, where a positive value

indicates that the power flows from the superior power grid to the virtual power plant, and a negative value indicates that the power flows from the virtual power plant to the superior power grid; and Po,max and Qo,max respectively represent upper limits of the active and reactive

powers flowing in/out of the tie line of the main power grid.

[0082] (2) Gas-specific power flow constraint

O-W - P~t)

Qjt 2 -'(Q t + Q9P

Qn,min - n- n,max

0 Q + Qij, + QG + S,out FGS,in _ QCHP

iEnj

Pj,t -comPi,t

Lij,= Mi;pi j,t

'i j,t = 2-1pi,t + pj,t)

Lij,t = Lij,t-1+Q - Q9Pt

mtax pnin

[0083] where Q o1 represents an average flow rate on a pipe at a time point t; Q! and Q9,

respectively represent an injection flow rate of natural gas at a first segment of the pipe ij and an output flow rate of the natural gas at a tail end of the pipe ij at the time point t; Cij represents a constant related to efficiency, a temperature, a length, an inner diameter, a compressibility factor, and the like of the pipe ij; pi,t and p,t respectively represent pressure values of a first node i

and a last node j at the time point t; Qn,max, Qn,min,and QN, respectively represent upper and

lower limits of a supply flow rate of the natural gas at a gas source point n and a power output of

agas source at the time point t; QNt represents a gas supply flow rate of the gas source on the

node i at the time point t; Q PG represents a gas supply flow rate of a power-to-gas (P2G)

device on the node i at the time point t; FiGS1in and Fi,out respectively represent injection and

extraction flow rates of a gas storage facility of the node i in the time period t; Q represents a

natural gas load on the node i at the time point t; QC 4P represents a natural gas flow rate

consumed by a combined heat and power (CHP) unit on the node i at the time point t; #3 com represents a compression coefficient of a compressor; pi,t and pj,t respectively represent the pressure values of the nodes i andj; Lij, represents a stock of the pipe ij at the time point t; Mij represents a constant related to the length, a radius, the temperature, a gas density, the

compressibility factor, and the like of the pipe ij; and Pij,t represents average pressure of the pipeijatthetimepointt.pnax andpl" respectively represent upper and lower limit values of the pressure value of the node i.

[0084] (3) Heat-specific power flow constraint Zjeppe+Q - j k'tpe ~/ Q 9 T 1 ': YkS p-Qg -

jEipe+ kESPpe JES

he cQ T(I T~

Tg. < T<Tma mm- ,t - max Twhin Th Tha

Te =(Ta- Ts)x(Rcpf)-1+T,

[0085] where S and respectively represent a set of pipes connected to the node i

and starting from the node i and a set of pipes connected to the node i and ending with the node i;

' represents a mass flow rate of hot water in a pipe j in the time period t; ' represents a

temperature at an outlet of the hot water in the pipe j in the time period t; ' represents a

temperature at an inlet of the hot water in a pipe k in the time period t; hh represents a heat

consumption of the load node i in the time period t, ' represents a temperature of supplied

water flowing through the load node i, and ' represents a temperature of return water flowing

through the load node; C represents a specific heat capacity of the hot water, which is set to 4.2 kJ/(kg-°C); x represents a distance between a point on a pipe segment and a head end of the pipe segment; R represents thermal resistance per unit length of the pipe segment; T,, Te, and Ta respectively represent a temperature at the head end of the pipe segment, a temperature at x of the pipe segment, and an external temperature; and f represents a flow rate of the hot water.

[0086] (4) Electricity-gas-heat coupling constraint

e,l g,17T17CHP 1 Lg = le,27IP2G Ag,2 p Lh le,317EBg A1g,1HEOCHPTCHP(1]

[0087] where Le, Lg, and Lh respectively represent load consumptions of the electricity, the gas, and the heat; qCHP, qHE, qT, P2G, and respectively /EB represent the efficiency of the CHP unit, a heat exchanger (HE), a power transformer T, the P2G device, and the EB; CHP CHP represents a heat-to-electric ratio of the CHP unit; le,1, e,2, andLe,3 represent distribution proportions of input electricity; Lg,1 and g,2 represent distribution proportions of input natural gas; Pg represents a consumption of the natural gas; and Pe represents a consumption of the electricity.

[0088] (5) IL contract constraint

ks,min ks,t - ks,max

IL pIL

[0089] where k,s,max and k,s,min respectively represent the upper and lower limits of an

independent IL contract that is of the sth type of energy resource and is declared by the kthIL resource.

[0090] (6) TL contract constraint pTL .< PIL < PIL gs,min - g,,t - gsmax

TL, _ TL,+ g,s,t- g,s,t~x P P TL TL

[0091] where g max and smin respectively represent the upper and lower limits of an

independent TL contract that is of the sth type of energy resource and is declared by the gth TL resource.

[0092] (7) Power output constraint of a DER

pDER UNDER < pDER < pDER UNDER e,s,min e,s,t - e,s,t - e,s,max e,s,t

[0093] where "mx and 'sMn respectively represent upper and lower limits of an active

power output of an independent contract that is of an sth type of energy resource and is declared UNDER by the DER; and N, ,t represents an enabling/disabling state of the sth type of energy resource

of the eth DER in the time period t, which is a variable set to 0 or 1.

[0094] (8) Constraint on resource grading, aggregation, and calling

pR .< PR < PR ,min - m,t - m,max

pILR .N k,s,min ILR < k,s - N k,s ILRpIL < pILR k,s,t - N ILR k,s,max k,s

<NTLRpTL < pTLR NTLR g,s,mtn NTLR pTLR g,s - g,s g,s,t - g,s,max g,s

<NPSRpDER < pPSR NDERNPSR e,s,min NDERNPSR pPSR e,s,t e,s - e,s e,s,t - e,s,max e,s,t e,s

PR pR

[0095] where 'nmx and 'Imin respectively represent upper and lower limits of calling a

pILR rILR real-time dynamic aggregation contract of the mth resource; ks'max and k,s,min Tespectively represent upper and lower limits of calling an sth type of energy resource of ato-be-aggregated TLR TLR ILR of the IL resource; %"''a and "minrespectively represent upper and lower limits of pPR calling an sth type of energy resource of a to-be-aggregated TLR of a TL resource; and emu ax pPR The mn respectively represent upper and lower limits of calling an sth type of energy resource of a to-be-aggregated PSR of the DER.

[0096] (9) Operation constraint of the energy storage system

[0097] In a region within the jurisdiction of the virtual power plant, three types of energy storage systems, namely, an electricity storage system, a gas storage system, and a heat storage system, are connected, and their categories are represented by s.

FF, + dis t,s,t + i" t<1

0o sP is,max

E+S PS,tS,tCschAT - F P -AT = ESSi,s,t+1

pdis o2 0 st di ! Pi,,max

[0098] where ESSi,s,t represents total energy of an sth type of energy storage system connected to Fht Fdis the node i in the time period t; eC and lI' respectively represent charging and discharging

states of the sth type of energy storage system connected to the node i, which are variables set to

or 1; 1nch and 7sdis respectively represent charging and discharging efficiency of the sthtype

of energy storage system; and Anmax The d"Sax respectively represent upper charging and

discharging limits of the sth type of energy storage system connected to the node i. ESSi,s,max X 20% ESSi,s, 5 ESSi,s,max X 90%

[0099] ESSi,-ax represents an upper limit of a capacity of the sth type of energy storage system

connected to node i. In order to ensure the normal use of the energy storage system, ensure the working efficiency of the energy storage system, and prolong the service life of the energy

storage system, it is necessary to limit charging and discharging ranges. Actual charging and

discharging ranges of the energy storage system are set to 20%90%. ESSiST P Tsch T TsdislAT = ESSi,s, = ESSi,s,max>x50%

[0100] In addition, in order to ensure that the energy storage system can be charged and

discharged at the beginning of scheduling and has the same regulation characteristic in a new

scheduling cycle, an initial electricity quantity of the energy storage system is set to 50% of a capacity limit, which is equal to an initial capacity of a next cycle.

[0101] (10) Transaction constraint of the real-time market

[0102] Within a given load range, a spot price has a linear relationship with a load level. Therefore, the present disclosure assumes that a relationship between an energy resource price in the real-time market and a load follows the following formula: PSt = ap.L+b pr,t a,~ ,t + bs

[0103] where as and bs represent coefficients of the relationship between the energy resource price in the real-time market and the load.

[0104] In addition, in order to ensure the reliable and orderly operation of a real-time transaction, it is assumed that the transaction volume of the virtual power plant in the real-time market follows the following formula:

Psr,I srmax

[0105] where Prmax represents an upper limit of an electricity quantity traded by the virtual power plant for the sth type of energy resource in the real-time market.

[0106] (11) Constraint on an energy selling price

[0107] The energy selling price is an important factor affecting the earning of the virtual power plant, and a retail energy price is formulated based on the following constraints: sell < sell < sell Psmin- Pi' - Ps',rax

E'T sell sl T -1 Sp! = P',average sell l

[0108] where Pax andP min respectively represent upper and lower limits of the energy

selling price; and Ose"ae represents an average energy selling price, which is determined

through negotiation by the virtual power plant and a user in the region within the jurisdiction of the virtual power plant.

[0109] According to the method in the present disclosure, it is assumed that there are 6 types of

distributed resources coexisting in the local region, where RI, R2, and R3 are electricity-gas-heat multi-energy distributed resources, R4 is an electricity-gas multi-energy distributed resource, R5

is a natural gas resource, and R6 is a heat resource. Detailed data is shown in Table 1. Table 1 Maximum capacity Resource Type (W (MW)

PS 150 RI TL 30 TL 30

PS 100 R2 TL 30 TL 30 IL 200 R3 TL 100 IL 30 PS 200 R4 IL 100 R5 TL 40 R6 IL 40

[0110] Each subsystem is equipped with the electricity energy storage (EES) system, a gas energy storage (GES) system, and a heat energy storage (HES) system, with capacities of 120 MW, 100 MW and 100 MW, respectively. The charging efficiency and discharging efficiency of the energy storage system are 95% and 90%, respectively. For the TL, a translation interval is set to 4 h. The first-level indicator and the second-level indicator are respectively set to 110 MW and 220 MW for an electricity resource, 40 MW and 60 MW for a gas resource, and 18 MW and 35 MW for a heat resource, and calling levels of the electricity resource, the gas resource, and the heat resource is set to a first level, a second level, and a third level respectively. Calorific value conversion is performed to convert energy supplied by the natural gas and the hot water flow into MW. It is assumed that 80% of an energy capacity of the virtual power plant has been purchased from the day-ahead market, and an energy price in the real-time market and the retail energy price are determined at an interval of 1 h.

[0111] Based on a multi-energy load curve, 24 h in a day is divided into three time periods that each have a total length of 8 h, namely, a period time from 8:00 to 11:00 and from 18:00 to 21:00, a time period from 12:00 to 17:00 and from 22:00 to 23:00, and a time period from 1:00 to 7:00 and 24:00, which are respectively recorded as a time period a, a time period b, and a time period c. In the time period a, the R, the R2, and the R4 experience graded dynamic resource aggregation 1, and the R3, the R5, and the R6 experience graded dynamic resource aggregation 2. In the time period b, the R3 and the R5 experience graded dynamic resource aggregation 3. In the time period c, the R3 and the R6 experience graded dynamic resource aggregation 4. Corresponding resource calling is shown in Table 2. Table 2

T Graded dynamic resource R Electricity Gas calling Heat calling aggregation calling (MW-h) (MW-h) (MW-h)

Graded dynamic resource R1 1159 120 40 aggregation 1 R2 759 97 40

R4 1526 68

/ R3 1309 302 82 Graded dynamic resource R5/ 124

/ aggregation 2 R6 / / 52

R3 653 763 174 b Graded dynamic resource aggregation 3 R5 / 304

/ Graded dynamic resource R3 0 326 232 c aggregation 4 R6 / / 315

[0112] Resource calling by the virtual power plant within 24 h is shown in FIG. 2 to FIG. 5. The dotted lines in the figures show graded admission levels of the electricity, the gas and the heat. It can be seen from FIG. 2 to FIG. 5 that most resources are called in a peak load period to reduce a high energy purchasing cost in the real-time market. The energy purchasing cost in the real-time market is low in an off-peak load period, and a resource will not be called even if the resource meets an admission requirement. As shown in FIG. 2 to FIG. 5, the heat resources of the RI and the R2 cannot meet an admission requirement of Gh,1 (the first-level indicator). However, after the graded dynamic resource aggregation 1, the heat resources of the RI and the R2 meet the admission requirement of Gh,1 (the first-level indicator), and are called, thereby successfully participating in a heat transaction. Similarly, natural gas resources of the RI, the R2 and the R4 also meet an admission requirement of Gg,1 (the first-level indicator) after the graded dynamic resource aggregation 1. Respective heat resources of the R3 and the R6 meet an admission requirement of Gh,1 (the first-level indicator), but the market they participate is limited. Limited by maximum capacities, the heat resources of the R3 and the R6 cannot meet an admission requirement of Gh,2 (the second-level indicator), and are difficult to participate in a higher-level transaction. However, after the graded dynamic resource aggregation 4, the heat resources of the R3 and the R6 meet the admission requirement of Gh,2 (the second-level indicator), and successfully participate in a higher-level heat transaction. Similarly, electricity resources of the RI, the R2 and the R4 meet an admission requirement of Ge,1, and participate in a higher-level electricity transaction after meeting an admission requirement of Ge,2 (the second-level indicator) through the dynamic resource aggregation 1.

[0113] An operation strategy of electricity storage, gas storage, and heat storage of the virtual power plant is shown in FIG. 6. Energy is charged in the off-peak load period and discharged in the peak load period to supply load for the virtual power plant. This reduces the energy purchasing cost in the real-time market, and even can sell an energy resource to the real-time market, thereby improving the economic benefit of the virtual power plant.

[0114] A transaction state of the virtual power plant in the real-time market is shown in FIG. 7.

In FIG. 7, a part greater than 0 represents energy purchased by the virtual power plant from the real-time market, and a part less than 0 represents energy sold. It can be seen that through reasonable resource scheduling such as graded dynamic resource aggregation, the virtual power plant reduces energy purchasing in the case of a high electricity price in the real-time market, and sell excess energy to the real-time market, so as to increase an energy selling earning while reducing the energy purchasing cost, thereby greatly improving the profitability of the virtual power plant.

[0115] A retail price of an energy resource sold by the virtual power plant to the user is shown in FIG. 8. The retail price basically changes with a price change in the real-time market. The retail price provided for the user is increased when the price in the real-time market is high, to avoid a loss caused by a high energy purchasing cost. The virtual power plant has made a large number of calls for the graded dynamic resource aggregation during peak hours and off-peak hours, achieving a certain peak clipping effect. The virtual power plant reduces energy purchasing when the real-time price is high, reducing the energy purchasing cost. Therefore, a peak retail price in FIG. 8 has a certain tolerance rate compared with a peak real-time price.

[0116] Different scenarios are set to compare energy purchasing and selling earnings of the virtual power plant when resource aggregation is performed and energy purchasing and selling earnings of the virtual power plant when no aggregation is performed.

[0117] Scenario 1: A graded dynamic resource aggregation strategy is not considered.

[0118] Scenario 2: The graded dynamic resource aggregation strategy is considered.

[0119] In the different scenarios, energy purchasing and selling benefits of the virtual power plant are shown in Table 3, which proves that using the graded dynamic resource aggregation strategy to aggregate different types of distributed resources is conducive to improving resource utilization and increasing the energy purchasing and selling earnings. Table 3 Scenario Earning($) Scenario 1 31427.48 Scenario 2 45116.64

[0120] Embodiment 2

[0121] This embodiment of the present disclosure provides a multi-stage multi-energy distributed resource aggregation apparatus of a virtual power plant, including:

[0122] a data obtaining module configured to obtain prices and energy that are reported in real time by distributed resources;

[0123] a resource aggregation module configured to perform sorting and grading based on the prices and the energy, formulate an aggregation scheme for distributed resources of a same grade based on a preset admission rule, and perform aggregation;

[0124] a scheduling fee module configured to participate in scheduling of a virtual power plant based on an aggregation result, obtain a unit fee of a scheduling volume, and calculate a scheduling fee based on the aggregation result;

[0125] an energy purchasing and selling module configured to obtain transaction prices and transaction volumes of a real-time market and a day-ahead market, and calculate an energy selling income and an energy purchasing cost of the virtual power plant;

[0126] an aggregation cost module configured to obtain a unit compensation fee of the scheduling volume, and calculate an aggregation cost of the virtual power plant based on the aggregation result;

[0127] an earning calculation module configured to calculate an operation earning of the virtual power plant based on the energy selling income, the energy purchasing cost, the aggregation cost, and the scheduling fee; and

[0128] a scheme obtaining module configured to construct an objective function by taking the maximum earning of the virtual power plant as a goal, and obtain a final aggregation scheme by the objective function.

[0129] Embodiment 3

[0130] Based on Embodiment 1, the present disclosure provides a multi-stage multi-energy distributed resource aggregation apparatus of a virtual power plant, including a processor and a storage medium, where

[0131] the storage medium is configured to store instructions; and

[0132] the processor is configured to perform operations according to instructions to perform the steps of the method described above.

[0133] Embodiment 4

[0134] Based on Embodiment 1, the present disclosure provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the method described above.

[0135] Those skilled in the art should understand that the embodiments of the present disclosure may be provided as a method, a system, or a computer program product. Therefore, the present disclosure may use a form of hardware-only embodiments, software-only embodiments, or embodiments with a combination of software and hardware. Moreover, the present disclosure may be in a form of a computer program product that is implemented on one or more computer-usable storage media (including but not limited to a magnetic disk memory, a CD-ROM, optical memory, and the like) that include computer-usable program code.

[0136] The present disclosure is described with reference to the flowcharts and/or block diagrams of the method, the device (system), and the computer program product according to the embodiments of the present disclosure. It should be understood that computer program instructions may be used to implement each process and/or each block in the flowcharts and/or the block diagrams and a combination of a process and/or a block in the flowcharts and/or the block diagrams. These computer program instructions may be provided for a general-purpose computer, a dedicated computer, an embedded processor, or a processor of another programmable data processing device to generate a machine, such that the instructions executed by a computer or a processor of another programmable data processing device generate an apparatus for implementing a specific function in one or more processes in the flowcharts and/or in one or more blocks in the block diagrams.

[0137] These computer program instructions may be stored in a computer-readable memory that can instruct a computer or another programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate an artifact that includes an instruction apparatus. The instruction apparatus implements a specific function in one or more processes in the flowcharts and/or in one or more blocks in the block diagrams.

[0138] These computer program instructions may be loaded onto a computer or another programmable data processing device, such that a series of operations and steps are performed on the computer or another programmable device, thereby generating computer-implemented processing. Therefore, the instructions executed on the computer or another programmable device provide steps for implementing a specific function in one or more processes in the flowcharts and/or in one or more blocks in the block diagrams.

[0139] The above described are preferred implementations of the present disclosure, and it should be noted that for those of ordinary skill in the art, various improvements and modifications may be made without departing from the principles of the present disclosure. These improvements and modifications should be regarded as falling within the protection scope of the present disclosure.

Claims

CLAIMS: 1. A multi-stage multi-energy distributed resource aggregation method of a virtual power plant, comprising: obtaining prices and energy that are reported in real time by various distributed resources; sorting and grading the distributed resources based on the prices and the energy, formulating an aggregation scheme for distributed resources of a same grade based on a preset admission rule, and performing aggregation; participating in scheduling of a virtual power plant based on an aggregation result, obtaining a unit fee of a scheduling volume, and calculating a scheduling fee based on the aggregation result; obtaining transaction prices and transaction volumes of a real-time market and a day-ahead market, and calculating an energy selling income and an energy purchasing cost of the virtual power plant; obtaining a unit compensation fee of the scheduling volume, and calculating an aggregation cost of the virtual power plant based on the aggregation result; constructing an objective function based on the energy selling income, the energy purchasing cost, the aggregation cost, and the scheduling fee to calculate an operation earning of the virtual power plant; and taking a maximum earning of the virtual power plant as a goal, and obtaining a final aggregation scheme by the objective function, so as to regulate the distributed resources based on the aggregation scheme.
2. The multi-stage multi-energy distributed resource aggregation method of a virtual power plant according to claim 1, wherein the distributed resources are distributed energy resources, DERs, or controllable dummy loads, DLs, the DERs comprise a controllable distributed generator, DG, and an uncontrollable DG, and the controllable DLs comprise an interruptible load, IL, and a translatable load, TL.
3. The multi-stage multi-energy distributed resource aggregation method of a virtual power plant according to claim 1, wherein the admission rule comprises a first-level indicator and a second-level indicator that are set based on adjustable load capacities and supply capacities of electricity, gas, and heat of the distributed resources.
4. The multi-stage multi-energy distributed resource aggregation method of a virtual power plant according to claim 3, wherein priorities of aggregating the distributed resources of the same grade based on the preset admission rule in descending order are as follows: a distributed resource whose indicator is less than or equal to the first-level indicator, a distributed resource whose indicator is greater than the first-level indicator and less than the second-level indicator, and a distributed resource whose indicator is greater than or equal to the second-level indicator.
5. The multi-stage multi-energy distributed resource aggregation method of a virtual power plant according to claim 2, wherein the performing aggregation comprises aggregating the distributed resources into a power supply resource, PSR, an interruptible load resource, ILR, and a translatable load resource, TLR.
6. The multi-stage multi-energy distributed resource aggregation method of a virtual power plant according to claim 5, wherein the scheduling fee is:

CR = AT CR -- [z M p!SR N's R Pe Ne Ph~ ++p DEPR~ kNs

+ t=1 S d e s h k L G

+ ( T[R R gT g' g ~ S 1 s, 9)

wherein CR represents a calling fee after the aggregation; AT represents duration of a calling time period; D, H, and L represent quantities of PSRs, ILRs, and TLRs respectively; and E, K, and G represent quantities of DERs, ILs, and TLs respectively; PSR Pds represents a unit fee of a calling volume of an sth type of energy resource of a dth

PSR, p I represents a unit fee of a calling volume of an sth type of energy resource of an hth

ILR, and p TR represents a unit fee of a calling volume of an sth type of energy resource of an

1 th TLR;

NeSR, N R, and N R represent variables set to 0 Or 1, wherein when the variable is set to 1,

it indicates participating in the aggregation, and when the variable is set to 0, it indicates not participating in the aggregation;

Pe,,t represents a power output of an sth type of energy resource of an eth DER in a time

periodt,Ps, represents a quantity of interrupted loads of an sth type of energy resource of a

kth IL in the time period t, andP , represents a quantity of translated loads of an sth type of

energy resource of a gth TL in the time period t; and s = 1, 2, 3, which respectively represent electricity, gas, and heat energy resources.
7. The multi-stage multi-energy distributed resource aggregation method of a virtual power plant according to claim 6, wherein the objective function is: T N K G M max G = AT {pt's[ZPt- (1- N R st - (1 - NTR pg ,t m t=1 s i=1 k=1 g=1 m=1 E K

- psP-ptP, - pR(1- N Rpe s Ps(1-N s,t e=1 k=1 G

- pg s(P~1 s s - g-NgTPJt s,tZ CR g=1

wherein max G represents a maximum profit of the virtual power plant in one scheduling cycle, AT represents duration of the scheduling cycle, and T represents a total quantity of time periods in the scheduling cycle; sell Pts represents a price at which the sth type of energy resource is sold to a user in the time

period t, Pst represents a multi-energy load of an ith user in the time period t, pR,

represents an aggregated calling volume of an mth sorted grade in the time period t, and N and M represent a quantity of users and a quantity of sorted grades respectively;

Ps and P respectively represent the transaction price and the transaction volume of the

day-ahead market, and pr,s and Ptr,, respectively represent the transaction price and the

transaction volume of the virtual power plant in the real-time market; when p,s > 0, the sth typeof energyresource is purchased from the real-time market; or

when pr,s < 0, the sth typeof energyresource is soldto the real-time market; and DER Pe,s represents a unit payment fee of the sth type of energy resource of the eth DER, pIks

represents a unit compensation fee of load interruption of the sth type of energy resource of the

kth IL, and pg represents a unit compensation fee of load translation of the sth type of energy

resource of the gth TL.
8. A multi-stage multi-energy distributed resource aggregation apparatus of a virtual power plant, comprising:

a data obtaining module configured to obtain prices and energy that are reported in real time

by various distributed resources; a resource aggregation module configured to sort and grade the distributed resources based

on the prices and the energy, formulate an aggregation scheme for distributed resources of a same grade based on a preset admission rule, and perform aggregation; a scheduling fee module configured to participate in scheduling of a virtual power plant based on an aggregation result, obtain a unit fee of a scheduling volume, and calculate a scheduling fee based on the aggregation result; an energy purchasing and selling module configured to obtain transaction prices and transaction volumes of a real-time market and a day-ahead market, and calculate an energy selling income and an energy purchasing cost of the virtual power plant; an aggregation cost module configured to obtain a unit compensation fee of the scheduling volume, and calculate an aggregation cost of the virtual power plant based on the aggregation result; an earning calculation module configured to construct an objective function based on the energy selling income, the energy purchasing cost, the aggregation cost, and the scheduling fee to calculate an operation earning of the virtual power plant; and a scheme obtaining module configured to take a maximum earning of the virtual power plant as a goal, and obtain a final aggregation scheme by the objective function, so as to regulate the distributed resources based on the aggregation scheme.
9. A multi-stage multi-energy distributed resource aggregation apparatus of a virtual power plant, comprising a processor and a storage medium, wherein the storage medium is configured to store instructions; and the processor is configured to perform operations according to the instructions to perform the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the method according to any one of claims 1 to 7.