CN104052069B - The idle work optimization method in distributing wind power integration area - Google Patents

Abstract

The invention discloses the idle work optimization method in a kind of distributing wind power integration area in intelligent grid design field.Comprise idle work optimization target function and the constraints of the opening-closing capacitor bank determining distributing wind power integration area, and determine power distribution network real-time reactive power optimization target function and the constraints in described area; According to idle work optimization target function and the constraints of opening-closing capacitor bank, ask for the switching time of Capacitor banks; According to the capacitor group switching time, drop into and excision container group; According to power distribution network real-time reactive power optimization target function and power distribution network constraints, that asks for static passive compensation device idlely to exert oneself and the idle of Wind turbines is exerted oneself; To exert oneself according to static passive compensation device idle and the idle of Wind turbines is exerted oneself, regulate static passive compensation device and Wind turbines.The present invention has good adaptability and can promote the receiving ability of electrical network to dispersion wind-powered electricity generation.

Description

The idle work optimization method in distributing wind power integration area

Technical field

The invention belongs to intelligent grid design field, particularly relate to a kind of idle work optimization method of distributing wind power integration area.

Background technology

The central role of electric power system is under the prerequisite ensureing power grid security economical operation, for the economical production of modern society and people's lives provide sufficient and high-quality electric energy.In system, whether reactive power flow distribution rationally directly determines the quality of system voltage quality, and this is not only related to electric power system provides quality from the quality of power supply to power consumer, also directly has influence on fail safe and the economy of electrical network self-operating.If voltage deviation is excessive or fluctuate excessive, not only directly can affect runnability and the useful life of electric equipment, but also can power system security be given, stable operation brings difficulty, system voltage even can be caused to collapse, cause large area blackout.

In the power system operation stage, by idle work optimization, configuration is optimized to idle resource existing in system, its measure comprises regulator generator set end voltage, adjustment on-load transformer tap changer position, change reactive power compensator switching capacity etc., thus reach the reactive power flow distribution optimizing electrical network, reduce electric network active loss, improve system voltage level, improve fail safe and the economy of entire system, and the object such as electric equipment and customer charge can be run safely and reliably, very important practical engineering value is had to electric power system, significant economic benefit can be brought to electric power enterprise.

The Mathematical Modeling of reactive power optimization of power system is more complicated; target function and constraints are all containing nonlinear equation; its control variables often mixes discrete variable and continuous variable; also often need to consider multiple optimization aim simultaneously, and there is the features such as solution space complexity, multiple constraint, multipole value, many uncertainties.This problem itself belongs to NP-hard problem, is the sizable work of computation complexity to solving of problems.Along with the continuous expansion of electric power system scale, also more and more higher to the requirement solving Reactive Power Optimazation Problem, as optimal solution reliably can be asked for, the Reactive power control etc. that can converge to optimal solution as soon as possible, problem that in solution space, feasible subspace and infeasible subspace interlock can be solved, large scale electric network can be carried out real-time dynamicly, the difficulty that solves of Reactive Power Optimazation Problem increases further thus.Therefore, it is very necessary for carrying out deep research to Reactive Power Optimazation Problem, not only has important practical significance, also has very important theoretical significance.

Summary of the invention

The object of the invention is to, for the weak point mentioning the existence of distributing wind power integration in above-mentioned background technology, a kind of idle work optimization method of distributing wind power integration area is provided, there is provided theories integration for promoting the receiving ability of electrical network to dispersion wind-powered electricity generation, the large-scale development for distributing wind-powered electricity generation provides strong technical guarantee.

To achieve these goals, the technical scheme that the present invention proposes is that a kind of idle work optimization method of distributing wind power integration area, is characterized in that described method comprises:

Step 1: idle work optimization target function and the constraints of determining the opening-closing capacitor bank in distributing wind power integration area, and the power distribution network real-time reactive power optimization target function in described area and constraints;

Step 2: according to idle work optimization target function and the constraints of opening-closing capacitor bank, ask for the switching time of Capacitor banks;

Step 3: according to the capacitor group switching time, drops into and excision Capacitor banks;

Step 4: according to power distribution network real-time reactive power optimization target function and power distribution network constraints, that asks for static passive compensation device idlely to exert oneself and the idle of Wind turbines is exerted oneself;

Step 5: regulate static passive compensation device, make it according to the idle output reactive power of exerting oneself of the static passive compensation device asked for; Regulating wind power unit, makes it according to the idle output reactive power of exerting oneself of the Wind turbines asked for.

The idle work optimization target function of described opening-closing capacitor bank is

F ₁for described regional whole day 24 hours total idle network loss;

for the idle network loss sum of described regional i-th hour;

The constraints of described opening-closing capacitor bank is for comprising:

$\mathrm{\Σ}{P}_G^i+\mathrm{\Σ}{P}_0^i=\mathrm{\Σ}{P}_{\mathrm{Loss}}^i+\mathrm{\Σ}{P}_L^i;$

$\mathrm{\Σ}{Q}_G^i+\mathrm{\Σ}{Q}_0^i=\mathrm{\Σ}{Q}_{\mathrm{Loss}}^i+\mathrm{\Σ}{Q}_L^i;$

0.93≤U _k≤1.07；

1≤T ₁≤T ₂≤24；

for the active power sum that described regional i-th hour Wind turbines sends;

for the active power sum of described regional i-th h for equilibration node;

for the active power loss sum of described regional i-th hour;

for the active power sum of load bus absorption in described regional i-th hour;

for the reactive power sum that described regional i-th hour Wind turbines sends;

for the reactive power sum of described regional i-th h for equilibration node;

for the idle network loss sum of described regional i-th hour;

for the reactive power sum of load bus absorption in described regional i-th hour;

U _kfor the voltage perunit value of a described regional kth node;

T ₁for Capacitor banks drops into the moment;

T ₂for the Capacitor banks excision moment.

Described power distribution network real-time reactive power optimization target function is

∑ Q _lossfor the total reactive power network loss of power distribution network;

Described power distribution network constraints comprises:

∑P _G+∑P ₀＝∑P _Loss+∑P _L；

∑Q _G+∑Q ₀＝∑Q _Loss+∑Q _L；

0.93≤U _k≤1.07；

Q _Smin≤Q _S≤Q _Smax；

-0.45P≤Q _G≤0.45P；

∑ P _gfor the real-time active power sum that power distribution network Wind turbines sends;

∑ P ₀for the real-time active power sum of power distribution network balance node;

∑ P _lossfor the real-time active power loss sum of power distribution network;

∑ P _lfor the real-time active power sum that distribution network load node absorbs;

∑ Q _gfor the reactive power power sum that power distribution network Wind turbines sends;

∑ Q ₀for the reactive power power sum of power distribution network balance node;

∑ Q _lossfor the reactive power network loss sum of power distribution network;

∑ Q _lfor the reactive power power sum that distribution network load node absorbs;

Q _sfor the reactive power of static passive compensation device is exerted oneself;

Q _smaxfor the idle upper limit of exerting oneself of static passive compensation device;

Q _sminfor the idle lower limit of exerting oneself of static passive compensation device;

Q _gfor the reactive power power that power distribution network Wind turbines sends;

P is the specified meritorious capacity of Wind turbines.

The optimization method that the present invention proposes pushes back before adopting according to the feature of actual electric network and calculates electric network swim for Load flow calculation algorithm, uses the reactive-load compensation equipment of interior point method to electrical network to be optimized, to the idle work optimization of actual electric network, has good adaptability; Meanwhile, the present invention can promote the receiving ability of electrical network to dispersion wind-powered electricity generation, and the large-scale development for distributing wind-powered electricity generation provides strong technical guarantee.

Accompanying drawing explanation

Fig. 1 is the idle work optimization method flow chart in distributing wind power integration area;

Fig. 2 is that double-fed fan motor unit reactive power is exerted oneself scope schematic diagram;

Fig. 3 is the capacitor group switching time data table of idle work optimization;

Fig. 4 be real-time reactive power optimization carries out to power distribution network reactive power compensation before and after each node voltage of system and SVC and the idle schematic diagram of exerting oneself of double-fed fan motor unit; Wherein, a () is each node voltage of system and SVC and the idle schematic diagram of exerting oneself of double-fed fan motor unit before power distribution network carries out the reactive power compensation of real-time reactive power optimization, (b) is each node voltage of system and SVC and the idle schematic diagram of exerting oneself of double-fed fan motor unit after power distribution network carries out the reactive power compensation of real-time reactive power optimization;

Fig. 5 be real-time reactive power optimization carries out to power distribution network reactive power compensation before and after each node voltage of system and SVC and the idle tables of data of exerting oneself of double-fed fan motor unit.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.It is emphasized that following explanation is only exemplary, instead of in order to limit the scope of the invention and apply.

Fig. 1 is the idle work optimization method flow chart in distributing wind power integration area, and as shown in Figure 1, the idle work optimization method in distributing wind power integration area provided by the invention comprises:

Step 1: determine the idle work optimization target function of the opening-closing capacitor bank in distributing wind power integration area and the power distribution network real-time reactive power optimization target function in constraints and described area and constraints respectively.

Of the present inventionly exert oneself so that the double-fed fan motor unit shown in Fig. 2 is idle, double-fed fan motor unit reactive power is exerted oneself should be dynamically adjustable in the scope of Fig. 2 defined.

Determine that the idle work optimization target function of the opening-closing capacitor bank in distributing wind power integration area is:

$\min f_1=\underset{i=1}{\overset{24}{\mathrm{\Σ}}}\mathrm{\Σ}{Q}_{\mathrm{Loss}}^i---\left(1\right)$

Wherein, f1 is distributing wind-powered electricity generation ^connectenter regional whole day 24 hours total idle network loss, for this area's idle network loss sum of i-th hour.

The constraints of opening-closing capacitor bank is for comprising:

$\mathrm{\Σ}{P}_G^i+\mathrm{\Σ}{P}_0^i=\mathrm{\Σ}{P}_{\mathrm{Loss}}^i+\mathrm{\Σ}{P}_L^i---\left(2\right)$

$\mathrm{\Σ}{Q}_G^i+\mathrm{\Σ}{Q}_0^i=\mathrm{\Σ}{Q}_{\mathrm{Loss}}^i+\mathrm{\Σ}{Q}_L^i---\left(3\right)$

0.93≤U _k≤1.07(4)

1≤T ₁≤T ₂≤24(5)

Wherein, for the active power sum that described regional i-th hour Wind turbines sends, for the active power sum of described regional i-th h for equilibration node, for the active power loss sum of described regional i-th hour, for the active power sum of load bus absorption in described regional i-th hour, for the reactive power sum that described regional i-th hour Wind turbines sends, for the reactive power sum of described regional i-th h for equilibration node, for the idle network loss sum of described regional i-th hour, for the reactive power sum of load bus absorption in described regional i-th hour.U _kfor the voltage perunit value of a described regional kth node, T ₁for Capacitor banks drops into the moment, T ₂for the Capacitor banks excision moment, i=1,2 ..., 24.

Power distribution network real-time reactive power optimization target function is:

minf ₂＝∑Q _Loss(6)

Wherein, ∑ Q _lossfor the total reactive power network loss of power distribution network.

Power distribution network constraints comprises:

∑P _G+∑P ₀＝∑P _Loss+∑P _L(7)

∑Q _G+∑Q ₀＝∑Q _Loss+∑Q _L(8)

0.93≤U _k≤1.07(9)

Q _Smin≤Q _S≤Q _Smax(10)

-0.45P≤Q _G≤0.45P(11)

Wherein, ∑ P _gfor the real-time active power sum that power distribution network Wind turbines sends, ∑ P ₀for the real-time active power sum of power distribution network balance node, ∑ P _lossfor the real-time active power loss sum of power distribution network, ∑ P _lfor the real-time active power sum that distribution network load node absorbs, ∑ Q _gfor the reactive power power sum that power distribution network Wind turbines sends, ∑ Q ₀for the reactive power power sum of power distribution network balance node, ∑ Q _lossfor the reactive power network loss sum of power distribution network, ∑ Q _lfor the reactive power power sum that distribution network load node absorbs.Q _sfor the reactive power of static passive compensation device is exerted oneself, Q _smaxfor the idle upper limit of exerting oneself of static passive compensation device, Q _sminfor the idle lower limit of exerting oneself of static passive compensation device, Q _gfor the reactive power power that power distribution network Wind turbines sends, P is the specified meritorious capacity of Wind turbines.

Step 2: according to idle work optimization target function and the constraints of opening-closing capacitor bank, ask for the switching time of Capacitor banks.

After the idle work optimization target function of opening-closing capacitor bank and constraints are determined, existing derivation algorithm can be selected to resolve, obtain the input moment T of Capacitor banks ₁with excision moment T ₂.

Step 3: according to making time and the mute time of Capacitor banks, drops into and excision Capacitor banks.

Step 4: according to power distribution network real-time reactive power optimization target function and power distribution network constraints, that asks for static passive compensation device idlely to exert oneself and the idle of Wind turbines is exerted oneself.

Select existing derivation algorithm to resolve, what obtain static passive compensation device idlely to exert oneself and the idle of Wind turbines is exerted oneself.

Step 5: regulate static passive compensation device, make it according to the idle output reactive power of exerting oneself of the static passive compensation device asked for; Regulating wind power unit, makes it according to the idle output reactive power of exerting oneself of the Wind turbines asked for.The present invention adopts interior point method to carry out the real-time reactive power optimization of distributing wind power integration local distribution network, real time data be collection per hour once.

As shown in Figure 3, it is the capacitor group switching time of a routine opening-closing capacitor bank idle work optimization, its feature shows as: before carrying out reactive power compensation, electrical network is 1.95084175371926MWh the total idle network loss of a day 24 hours, after carrying out reactive power compensation, the total idle network loss of system in one day is 1.6782730768404MWh, after can finding out that compensation condenser group carries out idle work optimization input electrical network, has very large effect to the reduction of the idle network loss of electrical network.

As shown in Figure 4, to be an example to power distribution network to carry out before and after the reactive power compensation of real-time reactive power optimization each node voltage of system and SVC (static passive compensation device) and double-fed fan motor unit is idle exerts oneself, and its data result as shown in Figure 5.Fig. 5 shows: idle the exerting oneself optimizing SVC and Wind turbines can well improve system voltage level; The reactive power using interior point method to calculate SVC and double-fed unit is exerted oneself, and can meet the requirement of system to real-time reactive power optimization algorithm very well.

Reactive Power Optimazation Problem is an extremely complicated nonlinear programming problem, and its target function generally all mixes with discrete type with the continuity that is non-linear, control variables of constraints mutually, up to the present, does not still have a kind of quick and perfect idle work optimization computational methods.The key issue that reactive power optimization of power system faces is process to nonlinear function, convergence and the discrete variable how in optimization problem.The present invention pushes back before adopting according to the feature of actual electric network and calculates electric network swim for Load flow calculation algorithm, uses the reactive-load compensation equipment of interior point method to electrical network to be optimized.To the idle work optimization of actual electric network, there is good adaptability.

The present invention is applicable to the area of distributing wind power integration, to be idlely optimized it.The idle work optimization strategy clear physical concept in the distributing wind power integration area that the present invention proposes, clear thinking, calculates easy, achieves the idle optimization in arbitrary distributing wind power integration area.

The above; be only the present invention's preferably embodiment, but protection scope of the present invention is not limited thereto, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; the change that can expect easily or replacement, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.

Claims (2)

1. the idle work optimization method in distributing wind power integration area, is characterized in that described method comprises:

Step 1: idle work optimization target function and the constraints of determining the opening-closing capacitor bank in distributing wind power integration area, and the power distribution network real-time reactive power optimization target function in described area and constraints;

Step 2: according to idle work optimization target function and the constraints of opening-closing capacitor bank, ask for the switching time of Capacitor banks;

Step 3: according to the capacitor group switching time, drops into and excision Capacitor banks;

Step 4: according to power distribution network real-time reactive power optimization target function and power distribution network constraints, that asks for static passive compensation device idlely to exert oneself and the idle of double-fed fan motor unit is exerted oneself;

Step 5: regulate static passive compensation device, make it according to the idle output reactive power of exerting oneself of the static passive compensation device asked for; Regulate double-fed fan motor unit, make it according to the idle output reactive power of exerting oneself of the double-fed fan motor unit asked for;

The idle work optimization target function of described opening-closing capacitor bank is

F ₁for described regional whole day 24 hours total idle network loss;

for the idle network loss sum of described regional i-th hour;

The constraints of described opening-closing capacitor bank is for comprising:

${\mathrm{\ΣP}}_G^i+{\mathrm{\ΣP}}_0^i={\mathrm{\ΣP}}_{Loss}^i+{\mathrm{\ΣP}}_L^i;$

${\mathrm{\ΣQ}}_G^i+{\mathrm{\ΣQ}}_0^i={\mathrm{\ΣQ}}_{Loss}^i+{\mathrm{\ΣQ}}_L^i;$

0.93≤U _k≤1.07；

1≤T ₁≤T ₂≤24；

for the active power sum that described regional i-th hour Wind turbines sends;

for the active power sum of described regional i-th h for equilibration node;

for the active power loss sum of described regional i-th hour;

for the active power sum of load bus absorption in described regional i-th hour;

for the reactive power sum that described regional i-th hour Wind turbines sends;

for the reactive power sum of described regional i-th h for equilibration node;

for the idle network loss sum of described regional i-th hour;

for the reactive power sum of load bus absorption in described regional i-th hour;

U _kfor the voltage perunit value of a described regional kth node;

T ₁for Capacitor banks drops into the moment;

T ₂for the Capacitor banks excision moment.

2. idle work optimization method according to claim 1, is characterized in that described power distribution network real-time reactive power optimization target function is minf ₂=∑ Q _loss;

∑ Q _lossfor the total reactive power network loss of power distribution network;

Described power distribution network constraints comprises:

∑P _G+∑P ₀＝∑P _Loss+∑P _L；

∑Q _G+∑Q ₀＝∑Q _Loss+∑Q _L；

0.93≤U _k≤1.07；

Q _Smin≤Q _S≤Q _Smax；

-0.45P≤Q _G≤0.45P；

∑ P _gfor the real-time active power sum that power distribution network Wind turbines sends;

∑ P ₀for the real-time active power sum of power distribution network balance node;

∑ P _lossfor the real-time active power loss sum of power distribution network;

∑ P _lfor the real-time active power sum that distribution network load node absorbs;

∑ Q _gfor the reactive power power sum that power distribution network Wind turbines sends;

∑ Q ₀for the reactive power power sum of power distribution network balance node;

∑ Q _lossfor the reactive power network loss sum of power distribution network;

∑ Q _lfor the reactive power power sum that distribution network load node absorbs;

Q _sfor the reactive power of static passive compensation device is exerted oneself;

Q _smaxfor the idle upper limit of exerting oneself of static passive compensation device;

Q _sminfor the idle lower limit of exerting oneself of static passive compensation device;

Q _gfor the reactive power power that power distribution network Wind turbines sends;

P is the specified meritorious capacity of Wind turbines.