CN107563676A - Consider the source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response - Google Patents

Consider the source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response Download PDF

Info

Publication number
CN107563676A
CN107563676A CN201710938157.2A CN201710938157A CN107563676A CN 107563676 A CN107563676 A CN 107563676A CN 201710938157 A CN201710938157 A CN 201710938157A CN 107563676 A CN107563676 A CN 107563676A
Authority
CN
China
Prior art keywords
load
few days
idr
pdr
power
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201710938157.2A
Other languages
Chinese (zh)
Inventor
孙丹丹
苗世洪
李力行
尹斌鑫
刘子文
晁凯云
涂青宇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Huazhong University of Science and Technology
Original Assignee
Huazhong University of Science and Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Huazhong University of Science and Technology filed Critical Huazhong University of Science and Technology
Priority to CN201710938157.2A priority Critical patent/CN107563676A/en
Publication of CN107563676A publication Critical patent/CN107563676A/en
Pending legal-status Critical Current

Links

Abstract

PDR electricity prices and corresponding load amount, A classes IDR size are determined the invention discloses a kind of source lotus coordinated operation dispatching method for considering Multiple Time Scales polymorphic type demand response, including according to operation plan model a few days ago.The Unit Combination of rapid starting/stopping unit, B classes IDR size are determined according in a few days operation plan model, PDR electricity prices, PDR electricity price corresponding load amounts and A classes IDR size.Rapid starting/stopping unit output is determined according to Real-Time Scheduling planning model, PDR electricity prices, PDR electricity price corresponding loads amount, A classes IDR size, the Unit Combination of rapid starting/stopping unit and B classes IDR size, abandons regenerative resource amount and the Power Exchange amount of higher level's power network and C classes IDR size.The present invention considers three levels and is directed to Multiple Time Scales demand response resource, effectively different types of demand response resource can be caused to play an active part in electric power system dispatching, realize the scheduling that becomes more meticulous.

Description

Consider the source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response
Technical field
The invention belongs to distributed power source and flexible load coordinated operation Research on Scheduling field, more particularly, to A kind of source lotus coordinated operation dispatching method for considering Multiple Time Scales polymorphic type demand response.
Background technology
In recent years, with renewable energy power generation equipment update and regenerative resource interconnection technology increasingly into Ripe, the regenerative resource using wind-powered electricity generation, photovoltaic as representative is quickly grown in the world.But compared with conventional power source, due to Wind-powered electricity generation, photovoltaic unit output are influenceed by the randomness of natural cause (wind speed, light intensity etc.), and stronger intermittence, randomness is presented And the features such as fluctuation.When wind-powered electricity generation, grid-connected permeability reach to a certain degree, wind-powered electricity generation, the online capacity of photovoltaic are for hair Electricity plan work out, active Real-Time Scheduling and FREQUENCY CONTROL and spare capacity arrangement etc. will all produce extreme influence.If no Effectively scheduling can be realized, will necessarily occur it is unnecessary abandon wind, abandon light, influence the economy of operation of power networks, can also shadow when serious Ring power network safety operation.Demand response (Demand Response, DR) participates in electric network active scheduling, for consumption wind-powered electricity generation, light The uncertainty of volt provides a kind of new method.By calling Demand-side resource, user is set to be carried out with Utilities Electric Co. interactive, can To make Demand-side resource participate in the scheduling of power system as calling Generation Side resource.Therefore, power distribution network is studied Lotus coordinated operation strategy in source turns into one of study hotspot of current generation power industry development.
Scheduling of the current scheduling strategy for demand response resource focuses mostly on dispatches a few days ago, more time chis of demand response Degree characteristic does not obtain enough attention always.It is various to participate in the load species of demand response, for classification above, it is negative both to have included industry Lotus, include resident load again.Not only motor type load had been included but also including the temperature control load such as refrigerator, water heater.These loads participate in adjusting The potentiality of degree and the pattern of response are all otherwise varied.In summary, on the one hand the precision of scene prediction is relevant with time scale, when Between yardstick it is shorter and nearer apart from current time, then precision of prediction is higher；On the other hand, the various resources for participating in scheduling are deposited in itself In the characteristic of Multiple Time Scales, individually it is difficult to make full use of the Multiple Time Scales of demand response resource special using scheduling model a few days ago Property, all kinds of resources are carried out with economic scheduling.Therefore, it is necessary to a kind of new in terms of the lotus coordinated operation strategy study of power distribution network source Method improve existing scheduling strategy.Based on above-mentioned consideration, the present invention proposes one kind based on " multilevel coordination, refining step by step " The source lotus coordinated operation strategy of Multiple Time Scales polymorphic type demand response, it can effectively cause different types of demand response resource Electric power system dispatching is played an active part in, realizes the scheduling that becomes more meticulous, improves power distribution network economic benefit and environmental benefit.
The content of the invention
For the disadvantages described above or Improvement requirement of prior art, the invention provides one kind to consider Multiple Time Scales polymorphic type The source lotus coordinated operation dispatching method of demand response, its object is to solve existing traffic control method due to technical problem.
To achieve the above object, the invention provides a kind of source lotus for considering Multiple Time Scales polymorphic type demand response to coordinate Traffic control method, comprises the following steps：
Step 1：Operating cost object function a few days ago and a few days ago operation plan model constraint set are established, a few days ago operating cost mesh Scalar functions include rapid starting/stopping Unit Commitment machine cost, power cost are exchanged with higher level's power network, scheduling A classes and scheduling B classes IDR are born The cost of lotus, PDR sales of electricity income and regenerative resource cost is abandoned, operation plan model constraint set includes power a few days ago and put down a few days ago Weighing apparatus constraint, a few days ago system reserve constraint, balance nodes ability to transmit electricity constrain, abandon the constraint of regenerative resource amount, rapid starting/stopping unit Constraint, the constraint of A class IDR and B class IDR schedulable resource constraint, PDR user satisfaction, obtain operation plan model a few days ago；According to Operation plan model obtains optimal PDR electricity prices, optimal PDR load, optimal A classes IDR load a few days ago；
Step 2：Judge whether the time reaches the in a few days operation plan cycle, if so, then establishing in a few days operating cost target letter Number and in a few days operation plan model constraint set, in a few days operating cost object function include rapid starting/stopping Unit Commitment machine cost, with Higher level's power network exchanges power cost, the cost of scheduling B class IDR loads and C class IDR loads and abandoned regenerative resource cost, day Interior operation plan model constraint set include in a few days power-balance constraint, in a few days system reserve constraint, balance nodes ability to transmit electricity about Beam, the constraint of regenerative resource amount, rapid starting/stopping Unit commitment and B class IDR and C class IDR schedulable resource constraints are abandoned, obtained In a few days operation plan model；According in a few days operation plan model, optimal PDR electricity prices, optimal PDR load and optimal A classes IDR Load determines the Unit Combination of optimal rapid starting/stopping unit, optimal B classes IDR load；Otherwise, into step 3；
Step 3：Judge whether the time reaches Real-Time Scheduling planning cycle, if so, establishing real time execution cost objective function With Real-Time Scheduling planning model constraint set, real time execution cost objective function includes exchanging power cost, scheduling C with higher level's power network The cost of class IDR loads and regenerative resource cost is abandoned, Real-Time Scheduling planning model constraint set includes realtime power and balanced about Beam, real-time system Reserve Constraint, balance nodes ability to transmit electricity constraint, abandon the constraint of regenerative resource amount, rapid starting/stopping Unit commitment, C class IDR schedulable resource constraints, establish Real-Time Scheduling planning model；According to Real-Time Scheduling planning model, optimal PDR electricity prices, most Excellent PDR load, optimal A classes IDR power consumptions, the Unit Combination of optimal rapid starting/stopping unit, optimal B classes IDR power consumptions obtain Optimal rapid starting/stopping unit output, optimal C classes IDR load, optimal abandon regenerative resource amount and optimal with higher level's power network Power Exchange amount；By optimal PDR electricity prices, optimal PDR load, optimal A classes IDR load, optimal rapid starting/stopping unit machine Group combination, optimal B classes IDR load, optimal rapid starting/stopping unit output, optimal C classes IDR load, optimal abandon renewable energy Source is measured and the optimal and Power Exchange amount of higher level's power network is as management and running result；Otherwise, into step 4；
Step 4：Renewal time, and judge whether the time meets the operation plan time a few days ago, if so, then enter step 1, it is no Then enter step 2.
Preferably, in the model constraint set of operation plan a few days ago：
Allow regenerative resource predict a few days ago output, rapid starting/stopping unit provide power, regenerative resource abandon power with And higher level's power network purchase power sum and superior power network electricity sales amount, a few days ago reference load premeasuring, PDR load, A classes IDR Power consumption and the equal realization power-balance constraint a few days ago of B class IDR power consumption sums；
Work of electric power system total output when EIAJ state is allowed to be more than maximum Alternative load amount and power system a few days ago Total output is less than minimum Alternative load amount realization system reserve constraint a few days ago a few days ago when working in minimum load state；
Allow balance nodes to exchange power with higher level's power network and realize balance nodes ability to transmit electricity about less than power maximum is exchanged Beam；
Allow abandon regenerative resource amount be less than abandon regenerative resource amount maximum obtain abandon regenerative resource amount constraint；
Allow rapid starting/stopping unit output in the range of rapid starting/stopping unit allows to contribute, reservoir water yield allows in reservoir In the range of water, reservoir capacity reservoir allow storage capacity in the range of realize to rapid starting/stopping Unit commitment；
Electricity price is within PDR load electricity price allowed bands corresponding to the transference PDR loads variable, and A class IDR loads are in A classes In IDR loads allowed band and B class IDR loads obtain a few days ago that DR schedulable resource is about in B class IDR load allowed bands Beam；
The PDR load of all load buses is allowed less than the PDR prediction load of corresponding load bus, while is allowed all negative The PDR prediction electric costs that the PDR electric costs of lotus node are less than all load buses realize that PDR user satisfaction constrains.
Preferably, according to formulaObtain day Preceding operating cost object function；
In formula, TdHop count when expression dispatches total a few days ago, NHGRepresent rapid starting/stopping unit number, 1≤t≤Td, 1≤i≤NHG,Rapid starting/stopping unit i is represented in t period on-off states,Start costs of the start and stop unit i in period t is represented,Represent start and stop unit i in period t shutdown cost, dP respectivelybalance,tRepresent t balance nodes from higher level's power network power purchase Amount, uPbalance,tT balance nodes superior power network electricity sales amount is represented,Represent t balance nodes from higher level's electricity Net purchase electricity price,Represent t balance nodes superior power network sale of electricity electricity price, NIDRRepresent to provide the poly- of IDR loads Close quotient amount, 1≤n≤NIDR；WithN-th of Load aggregation is represented respectively Business is in period t A classes IDR increases electricity, reduction electricity, unit increases energy cost and unit subtracts energy cost；WithRepresent that n-th of Load aggregation business increases in period t B classes IDR respectively Power-up amount, reduction electricity, unit increases energy cost and unit subtracts energy cost；NPDRExpression PDR load bus numbers, 1≤m≤ NPDR；qPDR,t,mRepresent PDR load buses m in period t knots modification, λPDR,tExpression and t corresponding to PDR changing load amounts Electricity price, NreRepresent regenerative resource access node number, CreRepresent that system unit abandons regenerative resource cost, Δ qre,k,tRepresent the K renewable energy source node abandons regenerative resource amount, 1≤k≤N in t a few days agore。
Preferably, according to formula in the step 1
Obtain power-balance constraint a few days ago；
According to formula
It is a few days ago System Reserve Constraint；
According to formulaObtain the constraint of balance nodes ability to transmit electricity；
According to 0≤Δ of formula qre,k,t≤Δq(re,k,t)maxThe constraint of regenerative resource amount is abandoned in acquisition；
According to formulaObtain rapid starting/stopping Unit commitment；
According to formulaObtain DR schedulable resource constraint a few days ago；
According to formulaObtaining PDR user expires Meaning degree constrains；
In formula,Represent that the prediction of regenerative resource a few days ago that period t is linked on node k is contributed,Represent Node l is in period t reference load a few days ago, 1≤l≤NL, NLRepresent reference load number of nodes, uP(balance,t)max、 dP(balance,t)maxRespectively balance nodes exchange power, exchange power maximum downwards upwards；Point Not Biao Shi t period rapid starting/stopping unit i maximums can use contribute, minimum can use contribute, Δ q(re,k,t)maxRepresent that period t is linked into section Maximum on point k can abandon honourable electricity, PL,tRepresent t-th of moment total load, κ1,1Positive reserve factor, κ are dispatched in expression a few days ago1,2 Represent to dispatch negative reserve factor a few days ago,Represent that t period rapid starting/stopping units i is actual to contribute；η is that water potential energy is converted into electric energy Efficiency；Qout,tFor reservoir t period Water discharge flow speed；HtRepresent reservoir t period head heights；Q(out,t)max、Q(out,t)minPoint Not Biao Shi reservoir water outlet current Peak Flow Rate, minimum flow velocity；VtRepresent the storage capacity of t reservoir, Qin,tRepresent that t flows into The flow rate of water flow of reservoir；Vmax、VminRepresent that reservoir maximum can bear storage capacity and minimum storage capacity limit value, λ respectivelyPDR,max、λPDR,minTable Show the maxima and minima of PDR load electricity prices；qPDR,t0,mIt is PDR load buses m under benchmark electricity price a few days ago at the beginning of PDR load Initial value, δPDR,tFor the load responding rate of PDR after dispatch a few days ago；mswhFor PDR loads user power utilization mode satisfaction lower limit a few days ago, λPDR,t0To dispatch the original electricity prices of preceding PDR a few days ago；mschSatisfaction lower limit is paid for PDR loads demand charge.
Preferably, allowed in the step 2 regenerative resource in a few days predict output, rapid starting/stopping unit provide power, can The renewable sources of energy abandon power and higher level's power network purchase power sum and superior power network electricity sales amount, in a few days load prediction amount, PDR Load, A class IDR power consumptions, B class IDR power consumptions and the equal realization in a few days power-balance constraint of C class IDR power consumption sums；
Work of electric power system total output when EIAJ state is allowed to be more than in a few days maximum Alternative load amount and power system Total output is less than in a few days minimum Alternative load amount realization in a few days system reserve constraint when working in minimum load state；
Allow balance nodes to exchange power with higher level's power network and realize balance nodes ability to transmit electricity about less than power maximum is exchanged Beam；
Allow abandon regenerative resource amount be less than abandon regenerative resource amount maximum obtain abandon regenerative resource amount constraint；
Allow rapid starting/stopping unit output in the range of rapid starting/stopping unit allows to contribute, reservoir water yield allows in reservoir In the range of water, reservoir capacity reservoir allow storage capacity in the range of realize to rapid starting/stopping Unit commitment；
Allow C class IDR loads in C class IDR load ranges and B class IDR loads obtain in a few days in B class IDR load ranges DR schedulable resource constraints.
Preferably, according to formula in the step 2
Obtain in a few days operating cost target Function；
In formula, TmHop count when expression in a few days dispatches total,WithRespectively Represent that n-th of Load aggregation business is powered down in period t C classes IDR increases electricity, reduction electricity, unit increasing energy cost and unit Measure cost.
Preferably, according to formula in the step 2
Obtain in a few days power-balance constraint；
According to formula
It is in a few days System Reserve Constraint；
According to formulaObtain the constraint of balance nodes ability to transmit electricity；
According to 0≤Δ of formula qre,k,t≤Δq(re,k,t)maxThe constraint of regenerative resource amount is abandoned in acquisition；
According to formulaObtain rapid starting/stopping Unit commitment；
According to formulaObtain DR schedulable resource constraints；
In formula,Represent that the in a few days regenerative resource prediction that period t is linked on node k is contributed,Represent Node l is in period t in a few days reference load, κ2,1Positive reserve factor, κ are in a few days dispatched in expression2,2Represent in a few days to dispatch and bear standby system Number,WithRepresent that Load aggregation business n scheduling C classes IDR unit interval most increases load respectively With unit interval maximum load shedding amount.
Preferably, allowed in the step 3 regenerative resource real-time estimate contribute, rapid starting/stopping unit provide power, can The renewable sources of energy abandon power and higher level's power network purchase power sum and superior power network electricity sales amount, Real-time Load premeasuring, PDR Load, A class IDR power consumptions, B class IDR power consumptions and C class IDR power consumption sums are equal realizes realtime power Constraints of Equilibrium；
Work of electric power system total output when EIAJ state is allowed to be more than real-time maximum Alternative load amount and power system Total output realizes real-time system Reserve Constraint less than real-time minimum Alternative load amount when working in minimum load state；
Allow balance nodes to exchange power with higher level's power network and realize balance nodes ability to transmit electricity about less than power maximum is exchanged Beam；
Allow abandon regenerative resource amount be less than abandon regenerative resource amount maximum obtain abandon regenerative resource amount constraint；
Allow rapid starting/stopping unit output in the range of rapid starting/stopping unit allows to contribute, reservoir water yield allows in reservoir In the range of water, reservoir capacity reservoir allow storage capacity in the range of realize to rapid starting/stopping Unit commitment；
C class IDR loads are allowed to allow to obtain DR schedulable resource constraints in excursion in C class IDR loads.
Preferably, according to formula in the step 3
Obtain real time execution cost objective Function.
Preferably, according to formula in the step 3
Obtain realtime power Constraints of Equilibrium；
According to formula Obtain real-time system Reserve Constraint；
According to formulaObtain balance nodes conveying electric energy constraint；
According to 0≤Δ of formula qre,k,t≤Δq(re,k,t)maxThe constraint of regenerative resource amount is abandoned in acquisition；
According to formulaObtain rapid starting/stopping Unit commitment；
According to formulaObtain DR schedulable resource constraints；
In formula,Represent that the real-time regenerative resource prediction that period t is linked on node k is contributed,Represent Real-time reference load κs of the node l in period t3,1Represent the positive reserve factor κ of Real-Time Scheduling3,2Reserve factor is born for Real-Time Scheduling.
In general, by the contemplated above technical scheme of the present invention compared with prior art, have below beneficial to effect Fruit：
1st, Generation Side has been taken into full account in system modelling for power distribution network source lotus coordinated operation scheduling problem, the present invention Resource and Demand-side resource.In order that the resource of different time scales carries out rational management, it is proposed that one includes three levels , a few days ago-in a few days-Multiple Time Scales scheduling strategy in real time for Multiple Time Scales demand response resource.Can effectively it cause Different types of demand response resource plays an active part in electric power system dispatching, realizes the scheduling that becomes more meticulous.
2nd, in conventional scheduling method, the Multiple Time Scales characteristic of scheduling resource is never paid attention to.And the present invention is A few days ago-in a few days-Multiple Time Scales scheduling model in real time of polymorphic type demand response resource, the demand of different time scales can be made Resource response is participated in electric power system dispatching, makes the slower demand response resource of a part of response speed (PDR and A class IDR) Participate in the peak load shifting of electric load and the consumption of regenerative resource, utilize some faster DR resources (B classes) of response The fluctuation of the regenerative resource under short period yardstick is stabilized, makes some direct loads control resource (C class IDR) to be revolved as system Turn a standby part, participate in the scheduling of system.
3rd, using the source lotus coordinated operation strategy of consideration Multiple Time Scales polymorphic type demand response proposed by the present invention, to carrying High power distribution network economic benefit and environmental benefit have directive significance.
Brief description of the drawings
Fig. 1 is the source lotus coordinated operation dispatching method of consideration Multiple Time Scales polymorphic type demand response provided by the invention Flow chart；
Fig. 2 is the source lotus coordinated operation dispatching method of consideration Multiple Time Scales polymorphic type demand response provided by the invention Time-scale scheme；
Fig. 3 is that the prediction of different time scales regenerative resource is contributed in embodiment provided by the invention；
Fig. 4 is that different time scales load prediction is contributed in embodiment provided by the invention；
Fig. 5 is the demand response scheduling of resource result of embodiment Scene one provided by the invention；
Fig. 6 is the demand response scheduling of resource result of embodiment Scene two provided by the invention.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples The present invention is further elaborated.It should be appreciated that specific embodiment described herein is only to explain the present invention, not For limiting the present invention.As long as in addition, technical characteristic involved in each embodiment of invention described below that Conflict can is not formed between this to be mutually combined.
In source lotus traffic control method provided by the invention, not only different time scales demand response resource is coordinated Scheduling, and considered the Generation Side resource and Demand-side of the Multiple Time Scales such as the complementation of wind-powered electricity generation photovoltaic, rapid starting/stopping unit The interaction of resource, consider following schedulable resource：
1) generating set resource.All it is to be directly accessed big electricity in view of the conventional Large-scale machine set such as actual conditions, fired power generating unit Net, small-sized rapid starting/stopping machine is can access in power distribution network.The rapid starting/stopping Unit Commitment time is shorter, and its Unit Combination can be in day Determined in interior scheduling.
2) demand response side resource.DR (demand response, demand response) resource can generally speaking be divided into electricity price Type (price-based demand response, PDR) and stimulable type (incentive-based demand response, IDR) two kinds.Electricity price uses a kind of pattern of dynamic price (day-ahead pricing, DAP) a few days ago in model, therefore PDR needs to determine in dispatch a few days ago, needs to consider the electric cost expenditure satisfaction of user and power mode satisfaction when dispatching PDR Degree.And IDR is broadly divided into following 3 kinds according to the difference of its advance notification times：
I. the IDR, hereinafter referred to as A classes IDR that the previous day informs user are carried；
II. the IDR, hereinafter referred to as B classes IDR that 15min~2h informs user are shifted to an earlier date；
III. shift to an earlier date 5~15min to inform the IDR of user or can respond in real time, similar to direct load control IDR, hereinafter referred to as C classes IDR.
Therefore, source lotus traffic control method provided by the invention can realize the Unit Combination of rapid starting/stopping unit, quick machine Group output, PDR electricity prices, PDR load, A class IDR load, B class IDR load, C class IDR load, abandon regenerative resource Amount and the scheduling with the Power Exchange amount of higher level's power network.
Fig. 1 is a kind of source lotus coordinated operation dispatching party for considering Multiple Time Scales polymorphic type demand response provided by the invention The flow chart of method, the source lotus coordinated operation dispatching method comprise the following steps：
Step 1：Unit Combination, the rapid starting/stopping unit that rapid starting/stopping unit is obtained according to operation plan model a few days ago go out Power, PDR electricity prices, PDR load, A class IDR load, B class IDR load, C class IDR load, abandon regenerative resource amount with And the Power Exchange amount with higher level's power network, and using PDR electricity prices, PDR load, A class IDR load successively as optimal PDR electricity Valency, optimal PDR load, optimal A classes IDR load.Operation plan model is with the minimum mesh of system call operating cost a few days ago Scalar functions, object function includes rapid starting/stopping Unit Commitment machine cost, balance nodes exchange power cost with higher level's power network, scheduling Cost, cost, the system of scheduling B class IDR loads of A class IDR loads to PDR loads user's sale of electricity income and abandon renewable energy Source cost.Operation plan model includes power-balance constraint a few days ago, system reserve is constrained, balance nodes ability to transmit electricity is constrained, abandoned The constraint of regenerative resource amount, rapid starting/stopping Unit commitment, IDRA and IDRB schedulable resource constraint, the constraint of PDR user satisfaction.
Operation plan model specific implementation is known to different time scales regenerative resource prediction output a few days ago Under the premise of, regenerative resource prediction is contributed and includes wind-powered electricity generation, photovoltaic generation prediction curve a few days ago, the load based on different time scales Prediction data, in the case where meeting the various constraintss of system, with the minimum target of system call operating cost.
Operation plan a few days ago
A few days ago shown in operation plan model objective function such as formula (1)：
In formula, F represents to dispatch totle drilling cost a few days ago；TdHop count when expression dispatches total a few days ago, 1≤t≤Td, in dispatch a few days ago Td=24；NHGRepresent rapid starting/stopping unit number, 1≤i≤NHG,Represent rapid starting/stopping unit i in t period switching on and shutting down shapes State, value are 0 or 1, whenWhen be off-mode,When be open state. Start and stop is represented respectively Start cost, shutdown costs of the group i in period t, Section 1 expression formula are used to represent rapid starting/stopping Unit Commitment machine cost. dPbalance,t、uPbalance,tRepresent t balance nodes from higher level's power network purchase of electricity and t balance nodes superior electricity respectively Net electricity sales amount；Represent t balance nodes from higher level's power network purchase electricity price and t balance nodes respectively Superior power network sale of electricity electricity price；Section 2 expression formula and Section 3 expression formula represent that balance nodes exchange work(with higher level's power network jointly Rate cost；NIDRThe polymerization quotient amount of offer IDR loads is provided；WithPoint Do not represent that A class IDR increase electricity, reduction electricity, unit increasing energy cost and unit of n-th of Load aggregation business in period t subtract Energy cost； WithRepresent n-th of Load aggregation business period t's respectively B classes IDR increases electricity, reduction electricity, unit increases energy cost and unit subtracts energy cost；Section 4 expression formula and Section 5 table Represent the cost of scheduling A class IDR, B class IDR loads respectively up to formula；NPDRRepresent PDR load bus numbers；qPDR,t,mRepresent that PDR is born Lotus node m is in period t changing load amount, 1≤m≤NPDR, λPDR,t,mRepresent in PDR load buses m and PDR changing load amounts Corresponding t electricity price, PDR load=PDR initial load amount+PDR changing load amounts, PDR initial load amounts refer to without Electricity when crossing PDR scheduling, after PDR scheduling is carried out, electrovalence policy changes, and PDR load changes, and this part changes Amount is referred to as PDR changing load amounts.Section 6 represents system to PDR load user's sale of electricity incomes (therefore previous symbol is negative).Nre、 Cre、Δqre,k,tRegenerative resource access node number is represented respectively, system unit abandons regenerative resource cost and k-th renewable Energy source node abandons regenerative resource amount, 1≤k≤N in t a few days agore, Section 7 expression formula abandons renewable energy for expression Source cost.
The constraint set of operation plan model includes following constraint a few days ago：
1) power-balance constraint a few days ago
The production and consumption of electric energy is all instantaneously completed, and the top priority of Operation of Electric Systems is ensuring that any moment Power network is supplied to power demand of the active power of load all with load to balance each other, and frequency departure, voltage pulsation otherwise occurs, System crash is resulted even in when situation is serious, it is therefore necessary to have power-balance constraint：
In formula, Section 1 expression formula is used to represent superior power network purchase of electricity；NHGRapid starting/stopping unit number is represented,Table Show power outputs of the rapid starting/stopping unit i in period t, Section 2 expression formula is used to represent rapid starting/stopping unit power output；Represent that the prediction of regenerative resource a few days ago that period t is linked on node k is contributed, Section 3 expression formula can be again for expression The raw energy predicts output electricity a few days ago；Δqre,k,tRepresent that period t is linked on node k regenerative resource amount of abandoning a few days ago, the 4th table It is used to represent the regenerative resource amount abandoned up to formula；qPDR,t,mRepresent power consumptions of the PDR load buses m in period t；Section 5 table It is used to represent superior power network electricity sales amount, N up to formulaLReference load nodes are represented,Represent days of the node l in period t Preceding reference load, 1≤l≤NL, Section 6 is for representing reference load amount；Section 7 is used to represent that PRD power consumptions, A classes IDR are used Electricity and B class IDR power consumptions.
Formula (2) left side is used to represent that power network to be supplied to the active power of load a few days ago, and power network provides the wattful power of load Rate includes regenerative resource prediction output, the power that rapid starting/stopping unit provides, regenerative resource and abandons power and higher level's electricity Power is bought in net purchase.Represent the power demand of load on the right of formula (2), the power demand of load include superior power network electricity sales amount, Reference load premeasuring, PDR load, A class IDR power consumptions and B class IDR power consumptions.
2) system reserve constrains
In order to ensure power network safety operation, power system optimal dispatch must leave enough spare capacities to tackle Various abnormal conditions.After particularly introducing the intermittent power supply such as wind-powered electricity generation and photovoltaic generation, the uncertain increasing of system generated output Add, for reply wind-powered electricity generation, photoelectricity and load actual size and the inconsistent situation of predicted value, introduce the positive and negative standby of system：
In formula, uP(balance,t)max、dP(balance,t)maxRespectively balance nodes exchange power, exchange power downwards upwards Maximum, adjust to obtain according to multiple factors such as line transmission power limit, higher level's grid stability demands by higher level's power network；Represent that t period rapid starting/stopping unit i maximums can use output, minimum to use and contribute respectively, rapid starting/stopping Unit output is most worth to be limited by specific reservoir,Represent that the regenerative resource a few days ago that period t is linked on node k predicts Power；Δq(re,k,t)maxRepresent that the maximum that period t is linked on node k can abandon honourable electricity, it is basis to abandon wind and abandon light quantity maximum New energy online regulation obtains, PL,tRepresent t-th of moment total load, total load include reference load premeasuring, PDR load, The sum of A class IDR power consumptions and B class IDR power consumptions, κ1,1、κ1,2Positive and negative reserve factor is respectively dispatched a few days ago, wherein, κ1,1Greatly In 1, κ1,2Between 0~1.
First inequality represents that total output is more than a few days ago maximum standby when work of electric power system is in EIAJ state Load capacity.Wherein, EIAJ state refers to that superior power network purchase of electricity is maximum, unit output is maximum, abandoned in regenerative resource With the state that scene amount is maximum.Second inequality represents that total output is less than day when work of electric power system is in minimum treat state Preceding minimum Alternative load amount, minimum load state are the state that unit processing is minimum and superior electricity sales amount is maximum.
3) balance nodes ability to transmit electricity constrains
Balance nodes exchange the outpost of the tax office of power as power distribution network with higher level's power network, it is contemplated that security constraint and line transmission energy Power, it conveys electric energy and should be less than limit value：
In formula, (uPbalance,t)max、(dPbalance,t)maxRespectively balance nodes exchange power, exchange power downwards upwards Maximum.
4) constraint of regenerative resource amount is abandoned
0≤Δqre,k,t≤Δq(re,k,t)max (5)
In formula, Δ q(re,k,t)maxRepresent that the maximum that period t is linked on node k can abandon honourable amount.
5) rapid starting/stopping Unit commitment
In formula,Represent that t period rapid starting/stopping unit i maximums can be used respectively contribute, be minimum available Contribute；Represent that t period rapid starting/stopping units i is actual to contribute；η is the efficiency that water potential energy is converted into electric energy, is had according to reservoir Running body situation determines；Qout,tFor reservoir t period Water discharge flow speed；HtRepresent reservoir t period head heights；Q(out,t)max、 Q(out,t)minPeak Flow Rate, the minimum flow velocity of reservoir water outlet current are represented respectively, are determined according to reservoir carrying out practically situation；VtTable Show the storage capacity of t reservoir, Qin,tRepresent that t flows into the flow rate of water flow of reservoir；Vmax、VminRepresent that reservoir maximum can be held respectively By storage capacity and minimum storage capacity limit value, determined according to reservoir carrying out practically situation.Rapid starting/stopping unit is small-sized water power in the present invention Unit, inequality represent quick unit output constraint, traffic constraints and storage capacity constraint respectively from top to bottom.Because quick unit opens Stop associated with quick unit output, therefore the constraint of traffic constraints and storage capacity is also contained in rapid starting/stopping Unit commitment.
6) DR schedulable resource constraint
In formula, λPDR,tExpression and t electricity price corresponding to PDR changing load amounts；λPDR,max、λPDR,minRepresent PDR loads The maxima and minima of electricity price；WithLoad aggregation business n scheduling A class IDR units are represented respectively Time most increases load and unit interval maximum load shedding amount, is determined according to A class IDR loads satisfaction, cuts down or add Load is no more than the 10% of former A classes IDR load；Represent that Load aggregation business n is adjusted respectively The degree B class IDR unit interval most increases load and unit interval maximum load shedding amount, is determined according to B class IDR loads satisfaction , cut down or add load is no more than former B classes IDR load 10%.PDR electricity tariff constraints a few days ago, A, B are distinguished from top to bottom Class IDR peak responses amount constrains.
7) PDR user satisfaction constrains
Wherein,
In formula, NPDRRepresent PDR load bus numbers；qPDR,t,mPower consumptions of the PDR load buses m in period t is represented, qPDR,t0,mFor PDR load buses m before dispatch a few days ago PDR load initial values under original electricity price, according to historical data, economy, The factors such as politics are predicted accordingly, δPDR,tFor the load responding rate of PDR after dispatch a few days ago；mswhFor PDR loads user a few days ago Power mode satisfaction lower limit, generally less than equal to 1, concrete numerical value is usually that power network voluntarily determines according to interaction effect, λPDR,t0To dispatch the original electricity prices of preceding PDR, λ a few days agoPDR,tExpression and t electricity price corresponding to PDR changing load amounts；mschFor PDR Load demand charge pays satisfaction lower limit, and generally less than equal to 1, concrete numerical value is usually that power network is voluntarily true according to interaction effect Fixed；εPDR,tIt is PDR in t period self-elasticity coefficients, coefficient of elasticity is determined according to price elasticity of electricity demand matrix model. Generally, self-elasticity coefficient is negative that mutual coefficient of elasticity is just.PDR loads user power utilization mode a few days ago is distinguished from top to bottom Satisfaction constraint, demand charge expenditure satisfaction constraint.
Step 2：Judge whether the time reaches the in a few days operation plan cycle, if then, according in a few days operation plan model, most Excellent PDR electricity prices, optimal PDR load and optimal A classes IDR load determine the Unit Combination of rapid starting/stopping unit, quickly opened Stop unit output, B class IDR load, C class IDR load, abandon regenerative resource amount and the Power Exchange with higher level's power network Amount.The Unit Combination of rapid starting/stopping unit, B class IDR load are designated as to the Unit Combination, most of optimal rapid starting/stopping unit successively Excellent B classes IDR load.Otherwise, into step 3.
In a few days operation plan model includes rapid starting/stopping with the minimum object function of system call operating cost, object function Unit Commitment machine cost, balance nodes exchange power cost, the cost for dispatching B class IDR loads, scheduling C classes IDR with higher level's power network The cost of load and abandon regenerative resource cost.In a few days it is standby to include power-balance constraint, system for operation plan model constraint set With constraint, balance nodes constrain, abandon the constraint of regenerative resource amount, rapid starting/stopping Unit commitment, IDRB schedulable resource constraint and IDRC schedulable resource constraints.
In a few days operation plan model by the use of PDR electricity prices, PDR load and A class IDR load obtained by step (2) as Known quantity, make total operating cost minimum.Total operating cost considers rapid starting/stopping Unit Commitment cost, scheduling B classes, C class IDR loads Cost, abandon regenerative resource cost, balance nodes exchange power cost with higher level's power network.I.e.：
In formula, TmHop count when expression in a few days dispatches total, the T in a few days dispatchingm=4, Section 1 represents that rapid starting/stopping unit opens Represent to shut down cost, Section 2 represents that the scheduling cost of B class IDR loads, Section 3 represent the cost of scheduling C class IDR loads, the Four represent to abandon regenerative resource cost balance node, and Section 5 represents that higher level's power network exchanges power cost, due to PDR electricity prices, PDR load has been known quantity, therefore is not included in system in object function to PDR load user's sale of electricity incomes.
In a few days the constraint set of operation plan model includes following constraint：
1) power-balance constraint in day
In formula,Represent that the in a few days regenerative resource prediction that period t is linked on node k is contributed,Represent Node l period t in a few days reference load, the formula left side be used for represent that power network is supplied to the in a few days active power of load, power network There is provided load in a few days active power include regenerative resource in a few days predict outputs, rapid starting/stopping unit offer power, can be again The raw energy abandons power and higher level's power network purchase power.The in a few days power demand of load, the electricity consumption of load are represented on the right of formula Demand includes superior power network electricity sales amount, reference load in a few days premeasuring, PDR load, A class IDR power consumptions and B classes IDR Power consumption.
2) system reserve constrains
In formula, uP(balance,t)max、dP(balance,t)maxRespectively balance nodes exchange power, exchange power downwards upwards Maximum；Represent that t period unit i maximums can use output, minimum to use and contribute respectively, Δ q(re,k,t)maxRepresent that the maximum that period t is linked on node k can abandon honourable amount, κ2,1、κ2,2Respectively in a few days dispatch positive and negative standby Coefficient, wherein, κ2,1More than 1, κ2,2Between 0~1.First inequality is represented when work of electric power system is in EIAJ state When total output be more than in a few days maximum Alternative load amount.Second inequality is represented when work of electric power system is in minimum treat state Total output is less than in a few days minimum Alternative load amount.
3) balance nodes conveying electric energy constraint
Balance nodes exchange the outpost of the tax office of power as power distribution network with higher level's power network, it is contemplated that security constraint and line transmission energy Power, it conveys electric energy and should be less than limit value：
4) constraint of regenerative resource amount is abandoned
0≤Δqre,k,t≤Δq(re,k,t)max (14)
In formula, Δ q(re,k,t)maxRepresent that the maximum that period t is linked on node k can abandon honourable amount.
5) rapid starting/stopping Unit commitment
In formula, the constraint of rapid starting/stopping unit output, traffic constraints and storage capacity constraint are represented respectively.
6) DR schedulable resource constraint in day
In formula,WithLoad aggregation business n scheduling B, C classes IDR unit interval is represented respectively The load that most increases and unit interval maximum load shedding amount.Determined according to C class IDR loads satisfaction, cut down or add load 10% of amount no more than former C classes IDR load.In a few days DR schedulable resource constraint and operation plan a few days ago in operation plan model In model DR schedulable resource constraint difference be, in a few days in planned dispatching model DR schedulable resource constraint to B class IDR dosages Enter row constraint with C class IDR power consumptions.
Step 3:Judge whether the time reaches Real-Time Scheduling planning cycle, if so, then according to Real-Time Scheduling planning model, PDR electricity prices, PDR load, A class IDR power consumptions, the Unit Combination of rapid starting/stopping unit, B class IDR power consumptions obtain optimal fast Fast start and stop unit output, optimal C classes IDR load, optimal abandon regenerative resource amount and optimal hand over the power of higher level's power network The amount of changing.By optimal PDR electricity prices, PDR load, the Unit Combination of A class IDR load/optimal rapid starting/stopping unit, optimal B classes IDR load, optimal rapid starting/stopping unit output, optimal C classes IDR load, it is optimal abandon regenerative resource amount and it is optimal with The Power Exchange amount of higher level's power network is as management and running result.Otherwise, into step 4.
By Real-Time Scheduling planning model with the minimum object function of system call operating cost, object function includes balance and saved Point exchanges the cost of power cost dispatch C class IDR loads with higher level's power network and abandons regenerative resource cost.Real-Time Scheduling plan Model constraint set includes power-balance constraint, system reserve constrains, balance nodes constrain, abandons the constraint of regenerative resource amount, be quick Start and stop Unit commitment, IDRC schedulable resource constraints.
Real-Time Scheduling planning model utilizes PDR electricity prices, PDR load, A class IDR electricity consumptions obtained by step (2) and step (3) Amount, the Unit Combination of rapid starting/stopping unit, B class IDR power consumptions make total operating cost minimum as known quantity.Acquisition is quickly opened Stop unit output, C class IDR load, abandon regenerative resource amount and the Power Exchange amount with higher level's power network.Total operating cost is examined Consider and consider that cost, the balance nodes of scheduling C class IDR loads exchange power cost with higher level's power network, abandon eolian.That is,
Wherein, TsRepresent hop count when Real-Time Scheduling is total, the T in Real-Time Schedulings=3, Section 1 represents scheduling C class IDR loads Cost, Section 2 represent abandon regenerative resource cost, Section 3 represent balance nodes exchange power cost with higher level's power network.
(4.2) step (4.1) bound for objective function is as follows：
1) realtime power Constraints of Equilibrium
Represent that the real-time regenerative resource prediction that period t is linked on node k is contributed,Represent node l In period t real-time reference load.
2) system reserve constrains
In formula, uP(balance,t)max、dP(balance,t)maxRespectively balance nodes exchange power, exchange power downwards upwards Maximum；Represent that t period unit i maximums can use output, minimum to use and contribute respectively, Δ q(re,k,t)maxRepresent that the maximum that period t is linked on node k can abandon honourable amount, κ3,1、κ3,2Respectively Real-Time Scheduling is positive and negative standby Coefficient, wherein, κ3,1More than 1, κ3,2Between 0~1.
First inequality represents that total output is more than maximum in real time standby when work of electric power system is in EIAJ state Load capacity.Second inequality represents that total output is less than minimum in real time standby negative when work of electric power system is in minimum treat state Carrying capacity.
3) balance nodes constrain
Balance nodes exchange the outpost of the tax office of power as power distribution network with higher level's power network, it is contemplated that security constraint and line transmission energy Power, it conveys electric energy and should be less than limit value：
In formula, uP(balance,t)max、dP(balance,t)maxRespectively balance nodes exchange power, exchange power downwards upwards Maximum.
4) constraint of regenerative resource amount is abandoned
0≤Δqre,k,t≤Δq(re,k,t)max (21)
In formula, Δ q(re,k,t)maxRepresent that the maximum that period t is linked on node k can abandon honourable amount.
5) rapid starting/stopping Unit commitment
In formula, the constraint of rapid starting/stopping unit output, traffic constraints and storage capacity constraint are represented respectively.
6) DR schedulable resource constraint
In formula,WithLoad aggregation business n scheduling C classes IDR unit interval is represented respectively most The load that increases and unit interval maximum load shedding amount.
Step 4：Renewal time, and judge whether the time meets the operation plan time a few days ago, if so, then enter step 1, it is no Then enter step 2.
The source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response provided by the invention, foundation are adjusted a few days ago Planning model is spent, operation plan performs once for one day a few days ago, and the same day determines scheduling quantum one day after.The task bag dispatched a few days ago Include：Determine PDR electricity prices and corresponding load amount, A classes IDR size.Dispatch a few days ago to consider power-balance constraint, system reserve Constraint, the constraint of system security constraint, balance nodes, abandon the constraint of regenerative resource amount, rapid starting/stopping Unit commitment, IDRA and IDRB Schedulable resource constraint, the constraint of PDR user satisfaction.
Establish in a few days operation plan model.In a few days operation plan performs once per 15min, and in a few days dispatching for task includes： Determine Unit Combination, the B classes IDR size of rapid starting/stopping unit.In a few days scheduling model is minimum with system call operating cost Object function, consider that power-balance constraint, system reserve constraint, system security constraint, balance nodes constrain, abandon regenerative resource Measure constraint, rapid starting/stopping Unit commitment, IDRB and IDRC schedulable resource constraints.
Establish Real-Time Scheduling planning model.Real-Time Scheduling plan performs once per 5min, and the task of Real-Time Scheduling includes：Really Determine rapid starting/stopping unit output, abandon regenerative resource amount, Power Exchange amount, C classes IDR size with higher level's power network.Adjust in real time Spend model with the minimum object function of total operating cost, consider power-balance constraint, system reserve constraint, system security constraint, Balance nodes constraint, abandon the constraint of regenerative resource amount, rapid starting/stopping Unit commitment, IDRC schedulable resource constraints.It is final to obtain Management and running result.
Scheduling a few days ago, in a few days relation such as Fig. 2 of scheduling and Real-Time Scheduling.Operation plan is daily 24 a few days ago:00 formulates one It is secondary, at the same time rolled per 15min and formulate once in a few days operation plan, rolled per 5min and formulate a Real-Time Scheduling plan.With The passage of time, in a few days, the period corresponding to Real-Time Scheduling plan constantly elapses forward.Scheduling a few days ago, in a few days scheduling, adjust in real time The scheduling scope (Period Length) dispatched each time of degree is respectively set as 24h, 1h and 15min.
In order to verify that a kind of source lotus coordinated operation for considering Multiple Time Scales polymorphic type demand response proposed by the present invention is adjusted Strategy validity is spent, using Suizhou real system gathered data as embodiment, i.e. the regenerative resource of different time scales is pre- Measure force curve and see Fig. 3, the load prediction curve of different time scales is shown in Fig. 4, and solution is write using CPLEX solvers.Introduce Two scenes：
Scene one：Scheduling scenario a few days ago.24 hours one day all kinds of resources are configured only with scheduling model a few days ago, i.e., Not only determine A, B class IDR in dispatch a few days ago, and determine C class IDR, and the generated output of each rapid starting/stopping unit and with The Power Exchange amount of bulk power grid.
Scene two：Carried out using the source lotus coordinated operation scheduling strategy of the Multiple Time Scales polymorphic type demand response of the present invention Scheduling.
Embodiment result：The demand response scheduling of resource result of scene one is as shown in figure 5, the demand response resource of scene two is adjusted It is as shown in Figure 6 to spend result.Compared to seeing, scene one is not due to using Multiple Time Scales to dispatch, and the degree that becomes more meticulous of scheduling is low, B Class and C classes IDR scheduling quantum are less than scene two, it is difficult to the advantages of playing its flexible scheduling, fast response time.And scene two, need Ask the scheduling scope of PDR and A classes IDR in resource response wider, it is main to be responsible for being adjusted on a large scale a few days ago.B classes and C classes IDR scheduling scope is small, but calls flexibly, is had outstanding performance in the fast dispatch of short-term time scale.
In addition, the scheduling economic benefit of scene one and scene two is as shown in table 1, rung by Multiple Time Scales polymorphic type demand The source lotus coordinated operation scheduling strategy answered, realizes the complete consumption of wind-powered electricity generation, adds the overall income of power network.As can be seen here, A kind of source lotus coordinated operation scheduling strategy of consideration Multiple Time Scales polymorphic type demand response proposed by the invention not only improves The scheduling of traditional scheduler becomes more meticulous the defects of low, also improves the economy of operation of power networks.Simulation result has absolutely proved this Invention strategy validity.
1 liang of Scene dispatch economic benefit (unit of table：Member)
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to The limitation present invention, all any modification, equivalent and improvement made within the spirit and principles of the invention etc., all should be included Within protection scope of the present invention.

Claims (10)

  1. A kind of 1. source lotus coordinated operation dispatching method for considering Multiple Time Scales polymorphic type demand response, it is characterised in that including Following steps：
    Step 1：Operating cost object function a few days ago and a few days ago operation plan model constraint set are established, a few days ago operating cost target letter Number includes rapid starting/stopping Unit Commitment machine cost, power cost is exchanged with higher level's power network, dispatching A classes and dispatch B class IDR loads Cost, PDR sales of electricity income and regenerative resource cost is abandoned, operation plan model constraint set includes a few days ago that power-balance is about a few days ago Beam, a few days ago system reserve constraint, balance nodes ability to transmit electricity constraint, abandon the constraint of regenerative resource amount, rapid starting/stopping Unit commitment, A class IDR and B class IDR schedulable resource constraint, the constraint of PDR user satisfaction, obtain operation plan model a few days ago；According to a few days ago Operation plan model obtains optimal PDR electricity prices, optimal PDR load, optimal A classes IDR load；
    Step 2：Judge whether the time reaches the in a few days operation plan cycle, if so, then establish in a few days operating cost object function and In a few days operation plan model constraint set, in a few days operating cost object function include rapid starting/stopping Unit Commitment machine cost and higher level Power network exchanges power cost, the cost of scheduling B class IDR loads and C class IDR loads and abandons regenerative resource cost, in a few days adjusts Degree planning model constraint set includes in a few days power-balance constraint, in a few days system reserve constraint, balance nodes ability to transmit electricity and constrains, abandons The constraint of regenerative resource amount, rapid starting/stopping Unit commitment and B class IDR and C class IDR schedulable resource constraints, are in a few days adjusted Spend planning model；According in a few days operation plan model, optimal PDR electricity prices, optimal PDR load and optimal A classes IDR load Determine the Unit Combination of optimal rapid starting/stopping unit, optimal B classes IDR load；Otherwise, into step 3；
    Step 3：Judge whether the time reaches Real-Time Scheduling planning cycle, if so, establishing real time execution cost objective function and reality When operation plan model constraint set, real time execution cost objective function include is exchanged with higher level's power network power cost, dispatch C classes The cost of IDR loads and abandon regenerative resource cost, Real-Time Scheduling planning model constraint set include realtime power Constraints of Equilibrium, Real-time system Reserve Constraint, the constraint of balance nodes ability to transmit electricity, abandon the constraint of regenerative resource amount, rapid starting/stopping Unit commitment, C classes IDR schedulable resource constraints, establish Real-Time Scheduling planning model；According to Real-Time Scheduling planning model, optimal PDR electricity prices, optimal PDR load, optimal A classes IDR power consumptions, the Unit Combination of optimal rapid starting/stopping unit, optimal B classes IDR power consumptions obtain most Excellent rapid starting/stopping unit output, optimal C classes IDR load, optimal abandon regenerative resource amount and optimal with higher level's power network work( Rate exchange capacity；By optimal PDR electricity prices, optimal PDR load, optimal A classes IDR load, optimal rapid starting/stopping unit unit Combination, optimal B classes IDR load, optimal rapid starting/stopping unit output, optimal C classes IDR load, optimal abandon regenerative resource Amount and the optimal and Power Exchange amount of higher level's power network are as management and running result；Otherwise, into step 4；
    Step 4：Renewal time, and judge whether the time meets the operation plan time a few days ago, if so, then entering step 1, otherwise enter Enter step 2.
  2. 2. source lotus coordinated operation dispatching method as claimed in claim 1, it is characterised in that the model of operation plan a few days ago is about In constriction：
    Allow regenerative resource predict a few days ago output, rapid starting/stopping unit provide power, regenerative resource abandon power and on Level power network purchase power sum and superior power network electricity sales amount, a few days ago reference load premeasuring, PDR load, A class IDR electricity consumptions Amount and the equal realization power-balance constraint a few days ago of B class IDR power consumption sums；
    Work of electric power system total output when EIAJ state is allowed to be more than maximum Alternative load amount and work of electric power system a few days ago Total output is less than minimum Alternative load amount realization system reserve constraint a few days ago a few days ago when minimum load state；
    Allow balance nodes to exchange power with higher level's power network and realize that balance nodes ability to transmit electricity constrains less than power maximum is exchanged；
    Allow abandon regenerative resource amount be less than abandon regenerative resource amount maximum obtain abandon regenerative resource amount constraint；
    Allow rapid starting/stopping unit output rapid starting/stopping unit allow contribute in the range of, reservoir water yield reservoir allow water outlet model Enclose interior, reservoir capacity allows to realize to rapid starting/stopping Unit commitment in the range of storage capacity in reservoir；
    Electricity price corresponding to the transference PDR loads variable within PDR load electricity price allowed bands, in A classes IDR bear by A class IDR loads In lotus allowed band and B class IDR loads obtain DR schedulable resource constraint a few days ago in B class IDR load allowed bands；
    The PDR load of all load buses is allowed less than the PDR prediction load of corresponding load bus, while allows all load sections The PDR prediction electric costs that the PDR electric costs of point are less than all load buses realize that PDR user satisfaction constrains.
  3. 3. source lotus coordinated operation dispatching method as claimed in claim 1 or 2, it is characterised in that according to formulaObtain operating cost object function a few days ago；
    In formula, TdHop count when expression dispatches total a few days ago, NHGRepresent rapid starting/stopping unit number, 1≤t≤Td, 1≤i≤NHG,Table Show rapid starting/stopping unit i in t period on-off states,Start costs of the start and stop unit i in period t is represented,Respectively Represent start and stop unit i in period t shutdown cost, dPbalance,tT balance nodes are represented from higher level's power network purchase of electricity, uPbalance,tT balance nodes superior power network electricity sales amount is represented,Represent t balance nodes from higher level's power network Purchase electricity price,Represent t balance nodes superior power network sale of electricity electricity price, NIDRThe polymerization of offer IDR loads is provided Quotient amount, 1≤n≤NIDR；WithN-th of Load aggregation business is represented respectively In period t A classes IDR increases electricity, reduction electricity, unit increases energy cost and unit subtracts energy cost；WithRepresent that n-th of Load aggregation business increases in period t B classes IDR respectively Power-up amount, reduction electricity, unit increases energy cost and unit subtracts energy cost；NPDRExpression PDR load bus numbers, 1≤m≤ NPDR；qPDR,t,mRepresent PDR load buses m in period t knots modification, λPDR,tExpression and t corresponding to PDR changing load amounts Electricity price, NreRepresent regenerative resource access node number, CreRepresent that system unit abandons regenerative resource cost, Δ qre,k,tRepresent the K renewable energy source node abandons regenerative resource amount, 1≤k≤N in t a few days agore。
  4. 4. the source lotus coordinated operation dispatching method as described in any one of claims 1 to 3, it is characterised in that root in the step 1 According to formulaObtain work(a few days ago Rate Constraints of Equilibrium；
    According to formulaObtain System reserve a few days ago is obtained to constrain；
    According to formulaObtain the constraint of balance nodes ability to transmit electricity；
    According to 0≤Δ of formula qre,k,t≤Δq(re,k,t)maxThe constraint of regenerative resource amount is abandoned in acquisition；
    According to formulaObtain rapid starting/stopping unit Constraint；
    According to formulaObtain DR schedulable resource constraint a few days ago；
    According to formulaObtain PDR user satisfaction about Beam；
    In formula,Represent that the prediction of regenerative resource a few days ago that period t is linked on node k is contributed,Represent node l In period t reference load a few days ago, 1≤l≤NL, NLRepresent reference load number of nodes, uP(balance,t)max、dP(balance,t)max Respectively balance nodes exchange power, exchange power maximum downwards upwards；The t periods are represented respectively Rapid starting/stopping unit i maximums can use output, minimum to use and contribute, Δ q(re,k,t)maxRepresent that period t is linked into the maximum on node k Honourable electricity, P can be abandonedL,tRepresent t-th of moment total load, κ1,1Positive reserve factor, κ are dispatched in expression a few days ago1,2Expression is dispatched a few days ago Negative reserve factor,Represent that t period rapid starting/stopping units i is actual to contribute；η is the efficiency that water potential energy is converted into electric energy；Qout,t For reservoir t period Water discharge flow speed；HtRepresent reservoir t period head heights；Q(out,t)max、Q(out,t)minReservoir is represented respectively Peak Flow Rate, the minimum flow velocity of water outlet current；VtRepresent the storage capacity of t reservoir, Qin,tRepresent that t flows into the current of reservoir Flow velocity；Vmax、VminRepresent that reservoir maximum can bear storage capacity and minimum storage capacity limit value, λ respectivelyPDR,max、λPDR,minRepresent PDR loads The maxima and minima of electricity price；qPDR,t0,mFor PDR load buses m under benchmark electricity price a few days ago PDR load initial value, δPDR,tFor the load responding rate of PDR after dispatch a few days ago；mswhFor PDR loads user power utilization mode satisfaction lower limit a few days ago, λPDR,t0 To dispatch the original electricity prices of preceding PDR a few days ago；mschSatisfaction lower limit is paid for PDR loads demand charge.
  5. 5. the source lotus coordinated operation dispatching method as described in any one of Claims 1-4, it is characterised in that allowed in the step 2 Regenerative resource in a few days predicts power, regenerative resource discarding power and the higher level's power network that output, rapid starting/stopping unit provide Buy power sum and superior power network electricity sales amount, in a few days load prediction amount, PDR load, A class IDR power consumptions, B classes IDR are used Electricity and the equal realization in a few days power-balance constraint of C class IDR power consumption sums；
    Work of electric power system total output when EIAJ state is allowed to be more than in a few days maximum Alternative load amount and work of electric power system Total output is less than in a few days minimum Alternative load amount realization in a few days system reserve constraint when minimum load state；
    Allow balance nodes to exchange power with higher level's power network and realize that balance nodes ability to transmit electricity constrains less than power maximum is exchanged；
    Allow abandon regenerative resource amount be less than abandon regenerative resource amount maximum obtain abandon regenerative resource amount constraint；
    Allow rapid starting/stopping unit output rapid starting/stopping unit allow contribute in the range of, reservoir water yield reservoir allow water outlet model Enclose interior, reservoir capacity allows to realize to rapid starting/stopping Unit commitment in the range of storage capacity in reservoir；
    Allowing C class IDR loads to obtain in a few days DR in B class IDR load ranges with B class IDR loads in C class IDR load ranges can Scheduling resource constrains.
  6. 6. the source lotus coordinated operation dispatching method as described in any one of claim 1 to 5, it is characterised in that root in the step 2 According to formulaObtain in a few days operating cost mesh Scalar functions；
    In formula, TmHop count when expression in a few days dispatches total,WithRepresent respectively N-th of Load aggregation business period t C classes IDR increases electricity, reduce electricity, unit increase energy cost and the powered down amount of unit into This.
  7. 7. the source lotus coordinated operation dispatching method as described in any one of claim 1 to 6, it is characterised in that root in the step 2 According to formulaObtain in a few days power-balance constraint；
    According to formulaObtain In a few days system reserve is obtained to constrain；
    According to formulaObtain the constraint of balance nodes ability to transmit electricity；
    According to 0≤Δ of formula qre,k,t≤Δq(re,k,t)maxThe constraint of regenerative resource amount is abandoned in acquisition；
    According to formulaObtain rapid starting/stopping unit Constraint；
    According to formulaObtain DR schedulable resource constraints；
    In formula,Represent that the in a few days regenerative resource prediction that period t is linked on node k is contributed,Represent node l In period t in a few days reference load, κ2,1Positive reserve factor, κ are in a few days dispatched in expression2,2Represent in a few days to dispatch negative reserve factor,WithRepresent that Load aggregation business n scheduling C classes IDR unit interval most increases load and list respectively Position time maximum load shedding amount.
  8. 8. the source lotus coordinated operation dispatching method as described in any one of claim 1 to 7, it is characterised in that allowed in the step 3 Power, regenerative resource discarding power and the higher level's power network that regenerative resource real-time estimate is contributed, rapid starting/stopping unit provides Power sum is bought to use with superior power network electricity sales amount, Real-time Load premeasuring, PDR load, A class IDR power consumptions, B classes IDR Electricity and C class IDR power consumption sums are equal realizes realtime power Constraints of Equilibrium；
    Work of electric power system total output when EIAJ state is allowed to be more than real-time maximum Alternative load amount and work of electric power system Total output realizes real-time system Reserve Constraint less than real-time minimum Alternative load amount when minimum load state；
    Allow balance nodes to exchange power with higher level's power network and realize that balance nodes ability to transmit electricity constrains less than power maximum is exchanged；
    Allow abandon regenerative resource amount be less than abandon regenerative resource amount maximum obtain abandon regenerative resource amount constraint；
    Allow rapid starting/stopping unit output rapid starting/stopping unit allow contribute in the range of, reservoir water yield reservoir allow water outlet model Enclose interior, reservoir capacity allows to realize to rapid starting/stopping Unit commitment in the range of storage capacity in reservoir；
    C class IDR loads are allowed to allow to obtain DR schedulable resource constraints in excursion in C class IDR loads.
  9. 9. the source lotus coordinated operation dispatching method as described in any one of claim 1 to 8, it is characterised in that root in the step 3 According to formulaObtain real time execution cost mesh Scalar functions.
  10. 10. the source lotus coordinated operation dispatching method as described in any one of claim 1 to 9, it is characterised in that in the step 3 According to formulaObtain realtime power balance about Beam；
    According to formulaObtain real When system reserve constrain；
    According to formulaObtain balance nodes conveying electric energy constraint；
    According to 0≤Δ of formula qre,k,t≤Δq(re,k,t)maxThe constraint of regenerative resource amount is abandoned in acquisition；
    According to formulaObtain rapid starting/stopping unit Constraint；
    According to formulaObtain DR schedulable resource constraints；
    In formula,Represent that the real-time regenerative resource prediction that period t is linked on node k is contributed,Represent node l In period t real-time reference load κ3,1Represent the positive reserve factor κ of Real-Time Scheduling3,2Reserve factor is born for Real-Time Scheduling.
CN201710938157.2A 2017-10-11 2017-10-11 Consider the source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response Pending CN107563676A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710938157.2A CN107563676A (en) 2017-10-11 2017-10-11 Consider the source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710938157.2A CN107563676A (en) 2017-10-11 2017-10-11 Consider the source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response

Publications (1)

Publication Number Publication Date
CN107563676A true CN107563676A (en) 2018-01-09

Family

ID=60984512

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710938157.2A Pending CN107563676A (en) 2017-10-11 2017-10-11 Consider the source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response

Country Status (1)

Country Link
CN (1) CN107563676A (en)

Cited By (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108416536A (en) * 2018-04-10 2018-08-17 国网江苏省电力有限公司电力科学研究院 A kind of demand response resource Multiple Time Scales rolling scheduling method of consumption new energy
CN109412142A (en) * 2018-10-11 2019-03-01 南京南瑞继保电气有限公司 A kind of dynamic virtual partition method and its system for flexible load regulation
CN109472469A (en) * 2018-10-23 2019-03-15 国网福建省电力有限公司 A kind of the multiagent interaction coordination approach and system of the consumption of promotion garden clean energy resource
CN109524958A (en) * 2018-11-08 2019-03-26 国网浙江省电力有限公司经济技术研究院 Consider the electric system flexibility Optimization Scheduling of depth peak regulation and demand response
CN109861204A (en) * 2018-12-18 2019-06-07 青岛理工大学 Active distribution network cooperative control system and method based on Model Predictive Control
CN110137942A (en) * 2019-04-23 2019-08-16 河海大学 Multiple Time Scales flexible load rolling scheduling method and system based on Model Predictive Control
CN111049192A (en) * 2019-12-11 2020-04-21 云南电网有限责任公司 Power generation control method considering renewable energy resource bidding on same station
CN111277005A (en) * 2020-02-19 2020-06-12 东北电力大学 Multi-source power system multi-time scale scheduling method considering source-load coordination optimization
CN111509716A (en) * 2020-05-22 2020-08-07 广东电网有限责任公司 Power grid flexible load control method and device, computer equipment and storage medium
CN111541272A (en) * 2020-05-22 2020-08-14 国网山西省电力公司电力科学研究院 Multi-time scale scheduling method and system for carbon capture power plant
CN111738622A (en) * 2020-07-17 2020-10-02 深圳华工能源技术有限公司 Electric power demand response variety pricing method considering different time scales
CN111738621A (en) * 2020-07-17 2020-10-02 深圳华工能源技术有限公司 Method for demand side to adjust resource time-scale aggregation participation demand response
CN111950807A (en) * 2020-08-26 2020-11-17 华北电力大学（保定） Comprehensive energy system optimization operation method considering uncertainty and demand response
CN112260321A (en) * 2020-09-17 2021-01-22 国网浙江省电力有限公司宁波供电公司 New energy power grid dispatching method combined with energy storage power station
CN112270433A (en) * 2020-10-14 2021-01-26 中国石油大学(华东) Micro-grid optimization method considering renewable energy uncertainty and user satisfaction
CN112583021A (en) * 2020-11-23 2021-03-30 国家电网有限公司 Comprehensive energy system optimal scheduling method and device considering comprehensive demand response
CN112927095A (en) * 2021-01-11 2021-06-08 东北电力大学 Multi-time scale coordinated scheduling method for electric heating combined system
CN113610339A (en) * 2021-06-24 2021-11-05 华北电力大学 Demand response system based on multi-time scale coordination
CN113746089A (en) * 2021-08-31 2021-12-03 河海大学 Multi-user-oriented multi-time-scale power package and family energy optimization method
CN114243692A (en) * 2021-12-15 2022-03-25 深圳供电局有限公司 Source-network-load coordinated optimization scheduling method
CN114612021A (en) * 2022-05-12 2022-06-10 四川大学 Multi-granularity-attribute-considered thermal load cooperative regulation and control method
CN116845871A (en) * 2023-06-30 2023-10-03 国家电网有限公司华东分部 Power and electricity quantity balancing method and device, storage medium and computer equipment

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102810186A (en) * 2012-08-01 2012-12-05 江苏省电力设计院 Multi-time scale microgrid energy optimizing management system structure and method
CN105470987A (en) * 2015-12-23 2016-04-06 华北电力大学 Load-source coordination control based renewable energy day-ahead plan correction method
CN107017630A (en) * 2017-05-18 2017-08-04 南京师范大学 A kind of electric power demand side response method of Multiple Time Scales
CN107194514A (en) * 2017-05-27 2017-09-22 重庆大学 A kind of demand response Multiple Time Scales dispatching method for wind power prediction error

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102810186A (en) * 2012-08-01 2012-12-05 江苏省电力设计院 Multi-time scale microgrid energy optimizing management system structure and method
CN105470987A (en) * 2015-12-23 2016-04-06 华北电力大学 Load-source coordination control based renewable energy day-ahead plan correction method
CN107017630A (en) * 2017-05-18 2017-08-04 南京师范大学 A kind of electric power demand side response method of Multiple Time Scales
CN107194514A (en) * 2017-05-27 2017-09-22 重庆大学 A kind of demand response Multiple Time Scales dispatching method for wind power prediction error

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
ZHAO C Y ET AL.: "Multi-stage robust unit commitment considering wind and demand response uncertainties", 《IEEE TRANSACTIONS ON POWER SYSTEMS》 *
包宇庆 等: "考虑大规模风电接入并计及多时间尺度需求响应资源协调优化的滚动调度模型", 《中国电机工程学报》 *

Cited By (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108416536A (en) * 2018-04-10 2018-08-17 国网江苏省电力有限公司电力科学研究院 A kind of demand response resource Multiple Time Scales rolling scheduling method of consumption new energy
CN109412142A (en) * 2018-10-11 2019-03-01 南京南瑞继保电气有限公司 A kind of dynamic virtual partition method and its system for flexible load regulation
CN109472469A (en) * 2018-10-23 2019-03-15 国网福建省电力有限公司 A kind of the multiagent interaction coordination approach and system of the consumption of promotion garden clean energy resource
CN109472469B (en) * 2018-10-23 2021-12-24 国网福建省电力有限公司 Multi-subject interactive coordination method and system for promoting consumption of park clean energy
CN109524958A (en) * 2018-11-08 2019-03-26 国网浙江省电力有限公司经济技术研究院 Consider the electric system flexibility Optimization Scheduling of depth peak regulation and demand response
CN109524958B (en) * 2018-11-08 2020-06-30 国网浙江省电力有限公司经济技术研究院 Power system flexibility optimization scheduling method considering deep peak shaving and demand response
CN109861204A (en) * 2018-12-18 2019-06-07 青岛理工大学 Active distribution network cooperative control system and method based on Model Predictive Control
CN110137942A (en) * 2019-04-23 2019-08-16 河海大学 Multiple Time Scales flexible load rolling scheduling method and system based on Model Predictive Control
CN110137942B (en) * 2019-04-23 2022-09-16 河海大学 Multi-time scale flexible load rolling scheduling method and system based on model predictive control
CN111049192A (en) * 2019-12-11 2020-04-21 云南电网有限责任公司 Power generation control method considering renewable energy resource bidding on same station
CN111049192B (en) * 2019-12-11 2023-04-11 云南电网有限责任公司 Power generation control method considering renewable energy source bidding on same station
CN111277005A (en) * 2020-02-19 2020-06-12 东北电力大学 Multi-source power system multi-time scale scheduling method considering source-load coordination optimization
CN111541272A (en) * 2020-05-22 2020-08-14 国网山西省电力公司电力科学研究院 Multi-time scale scheduling method and system for carbon capture power plant
CN111509716A (en) * 2020-05-22 2020-08-07 广东电网有限责任公司 Power grid flexible load control method and device, computer equipment and storage medium
CN111541272B (en) * 2020-05-22 2021-07-30 国网山西省电力公司电力科学研究院 Multi-time scale scheduling method and system for carbon capture power plant
CN111738621B (en) * 2020-07-17 2020-11-24 深圳华工能源技术有限公司 Method for demand side to adjust resource time-scale aggregation participation demand response
CN111738622B (en) * 2020-07-17 2020-11-24 深圳华工能源技术有限公司 Electric power demand response variety pricing method considering different time scales
CN111738621A (en) * 2020-07-17 2020-10-02 深圳华工能源技术有限公司 Method for demand side to adjust resource time-scale aggregation participation demand response
CN111738622A (en) * 2020-07-17 2020-10-02 深圳华工能源技术有限公司 Electric power demand response variety pricing method considering different time scales
CN111950807A (en) * 2020-08-26 2020-11-17 华北电力大学（保定） Comprehensive energy system optimization operation method considering uncertainty and demand response
CN111950807B (en) * 2020-08-26 2022-03-25 华北电力大学（保定） Comprehensive energy system optimization operation method considering uncertainty and demand response
CN112260321A (en) * 2020-09-17 2021-01-22 国网浙江省电力有限公司宁波供电公司 New energy power grid dispatching method combined with energy storage power station
CN112270433A (en) * 2020-10-14 2021-01-26 中国石油大学(华东) Micro-grid optimization method considering renewable energy uncertainty and user satisfaction
CN112270433B (en) * 2020-10-14 2023-05-30 中国石油大学(华东) Micro-grid optimization method considering renewable energy uncertainty and user satisfaction
CN112583021A (en) * 2020-11-23 2021-03-30 国家电网有限公司 Comprehensive energy system optimal scheduling method and device considering comprehensive demand response
CN112927095A (en) * 2021-01-11 2021-06-08 东北电力大学 Multi-time scale coordinated scheduling method for electric heating combined system
CN113610339A (en) * 2021-06-24 2021-11-05 华北电力大学 Demand response system based on multi-time scale coordination
CN113746089A (en) * 2021-08-31 2021-12-03 河海大学 Multi-user-oriented multi-time-scale power package and family energy optimization method
CN114243692A (en) * 2021-12-15 2022-03-25 深圳供电局有限公司 Source-network-load coordinated optimization scheduling method
CN114612021A (en) * 2022-05-12 2022-06-10 四川大学 Multi-granularity-attribute-considered thermal load cooperative regulation and control method
CN116845871A (en) * 2023-06-30 2023-10-03 国家电网有限公司华东分部 Power and electricity quantity balancing method and device, storage medium and computer equipment
CN116845871B (en) * 2023-06-30 2024-03-22 国家电网有限公司华东分部 Power and electricity quantity balancing method and device, storage medium and computer equipment

Similar Documents

Publication Publication Date Title
CN107563676A (en) Consider the source lotus coordinated operation dispatching method of Multiple Time Scales polymorphic type demand response
Sarker et al. Progress on the demand side management in smart grid and optimization approaches
Nguyen et al. Dynamic pricing design for demand response integration in power distribution networks
Zamani et al. Day-ahead resource scheduling of a renewable energy based virtual power plant
Samadi et al. Load scheduling and power trading in systems with high penetration of renewable energy resources
CN109727158A (en) A kind of electric heating integrated energy system dispatching method based on the weak robust optimization of improvement
Salmani et al. Virtual power plant: New solution for managing distributed generations in decentralized power systems
CN106981888A (en) The multiple target dynamic dispatching method of Thermal and Hydroelectric Power Systems is stored based on the complementary wind of multi-source
CN108304961A (en) A kind of coordination approach and system in wind storage access net source
CN104537428B (en) One kind meter and the probabilistic economical operation appraisal procedure of wind power integration
CN106844916A (en) A kind of generating and electricity consumption method for organizing and device based on peak regulation assisted hatching
CN106548291A (en) A kind of micro-capacitance sensor on-road efficiency distribution method based on Shapley values
CN110175727A (en) A kind of major-minor coordination optimizing method of peak load regulation network assisted hatching
Mashhour et al. A review on operation of micro grids and virtual power plants in the power markets
CN109286208A (en) A kind of integrated energy system dispatching method and system
CN107341601A (en) Based on a few days ago, the electric power resource dispatching method of time of day yardstick and system
Peikherfeh et al. Optimal dispatch of distributed energy resources included in a virtual power plant for participating in a day-ahead market
Huang et al. Dynamic pricing for distributed generation in smart grid
Lv et al. Review on power generation and bidding optimization of virtual power plant
Ali Development and Improvement of Renewable Energy Integrated with Energy Trading Schemes based on Advanced Optimization Approaches
Pilz et al. Selfish energy sharing in prosumer communities: A demand-side management concept
Jin et al. An overview of virtual power plant development from the perspective of market participation
CN109726894A (en) Ensure the new energy active command calculation method of spot exchange and medium-term and long-term electricity
CN105226649B (en) One kind predicting improved provincial power network power generation dispatching optimization method based on bus load
CN110247392A (en) More standby resources robust Optimal methods of meter and wind-powered electricity generation marginal capacity and Demand Side Response

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20180109