CN104036337A - Photovoltaic generating optimization scheduling method based on prediction of uncertainty and clearance output - Google Patents

Abstract

The invention provides a photovoltaic generating optimization scheduling method based on prediction of uncertainty and clearance output. The method comprises the following steps: (1), according to a photovoltaic generating clearance model, obtaining a clearance output P clearance; (2), calculating a photovoltaic generating admission capability; (3), determining whether photovoltaic generating is in a limiting period; (4), performing optimization distribution on the power of a photovoltaic power station in a limiting period; and (5), outputting a generating scheduling plan of the photovoltaic power station. The photovoltaic generating optimization scheduling method provided by the invention is used for guiding scheduling of the photovoltaic generating, improves the system safe stable operation level and the system photovoltaic generating adsorptive capacity, reduces limited electric power of the photovoltaic generating, and improves the utilization rate of the photovoltaic generating.

Description

Based on the photovoltaic generation Optimization Scheduling of predicting that uncertainty and headroom are exerted oneself

Technical field

The invention belongs to generation of electricity by new energy field, be specifically related to a kind of photovoltaic generation Optimization Scheduling based on predicting that uncertainty and headroom are exerted oneself.

Background technology

Electric system is a complicated dynamic system, and its safe and stable operation requires must the moment keep balance between generating and workload demand in essence.There is imbalance of supply and demand if electric system can not control effectively, the reliable electricity consumption of impact load even may be caused to the large-scale accident of system.

Photovoltaic generation has the feature of intermittent and randomness, large-scale photovoltaic electricity generation grid-connecting has brought very large impact to the safe and stable operation of electric system, in system, other stabilized power sources must be as follow load, follows the going out fluctuation of photovoltaic generation and fluctuates.When photovoltaic generation in system penetrates power hour, it exerts oneself smaller on the impact of system.But when photovoltaic generation penetrates power when larger, its wide fluctuations of exerting oneself produces very large impact to security of system Plan for Economical Operation, traditional safety and economic operation scheme must adjust and just can maintain system stability.

In the system that there is no photovoltaic power generation grid-connecting, dispatching of power netwoks department, according to load prediction curve, makes rational planning for and arranges each generating plant generating task, proposes the day generation schedule of each generating plant.After large-scale photovoltaic electricity generation grid-connecting, arrange generation schedule if still only press load prediction curve, can not meet the wide fluctuations characteristic that photovoltaic generation is exerted oneself.The management and running problem of large-scale photovoltaic electricity generation grid-connecting is the difficult problem that the electrical network of photovoltaic generation installation large percentage all faces.For tackle photovoltaic generation randomness, intermittence and can not be arbitrarily controlled, electric system is in operation and must considers to leave enough standby power supplies and peak, can be normally to customer power supply during with guarantee photovoltaic generation undercapacity, this will cause system reserve capacity to increase; And it is large and when underload to exert oneself at photovoltaic generation, must take again to reduce the mode that fired power generating unit exerts oneself and ensure the equilibrium of supply and demand, this has not only increased the operating cost of system, bring hidden danger also can to the safe and stable operation of system simultaneously.Therefore, along with the increase of photovoltaic generation installed capacity, management and running after it is grid-connected become the problem that solves of needing too impatient to wait, safe and stable operation, the raising system of management and running guarantee electric system of only having photovoltaic generation to participate in system the dissolve ability of photovoltaic generation, the economy of raising system operation.

The management and running of photovoltaic generation depend on photovoltaic generation power prediction, because photovoltaic generation power prediction mainly depends on numerical weather forecast, are subject to the impact of numerical weather forecast, and photovoltaic generation power prediction result precision is on the low side.Be subject to the impact of precision of prediction, photovoltaic generation power also fails accurately to include in system call operation, causes that system is in service can not pay the utmost attention to photovoltaic generation, causes in actual motion photovoltaic generation power limited comparision of quantity of electricity many, is unfavorable for the utilization of clean energy resource.

Summary of the invention

For overcoming above-mentioned defect, the invention provides a kind of photovoltaic generation Optimization Scheduling based on predicting that uncertainty and headroom are exerted oneself, be used in reference to the scheduling of guided photovoltaic generating, thereby the ability that provides the safe and stable operation level of system and system to dissolve photovoltaic generation, to reduce the limited electric weight of photovoltaic generation, improve photovoltaic generation utilization factor.

For achieving the above object, the invention provides a kind of photovoltaic generation Optimization Scheduling of exerting oneself based on prediction uncertainty and headroom, its improvements are, described method comprises the steps:

(1). according to photovoltaic generation headroom model, obtain the headroom P that exerts oneself _headroom;

(2). the whole network photovoltaic generation is received capacity calculation;

(3). judge that whether photovoltaic generation is in the limited period;

(4). limited power is optimized to distribution;

(5). output photovoltaic power station power generation operation plan.

In optimal technical scheme provided by the invention, in described step 1, headroom is exerted oneself and is referred to the maximum output limit value that the headroom model of photovoltaic plant obtains.

In the second optimal technical scheme provided by the invention, described headroom model, is at fine day, block without cloud layer in the situation that, calculates and set up the relational expression model between instantaneous intensity of solar radiation near the ground and the instantaneous intensity of solar radiation in section, exoatmosphere.

In the 3rd optimal technical scheme provided by the invention, in described step 2, in order to obtain photovoltaic generation Plan Curve P _{planned value}, need be to the maximum receiving ability of the photovoltaic generation P under peak load regulation network and the restriction of various security constraint _{the maximum receiving ability of photovoltaic generation}judge.

In the 4th optimal technical scheme provided by the invention, P _{the maximum receiving ability of photovoltaic generation}obtained by the peak regulation constraint maximum receiving ability of lower photovoltaic generation and the lower maximum ability integration of receiving of various security constraint restriction; The maximum receiving ability of photovoltaic generation and load prediction value, interconnection plan, Unit Combination mode, Region control deviation and margin capacity associated under peak load regulation network constraint, computing formula is:

P _{the maximum receiving ability of the limited lower photovoltaic generation of peak regulation}=P _{total load prediction}+ P _{interconnection plan}-P _{conventional unit minimum load}-ACE-P _{margin capacity}(1)

In formula (1), the Region control deviation that ACE is electrical network.

In the 5th optimal technical scheme provided by the invention, in described step 3, according to the maximum receiving ability of the electrical network photovoltaic generation obtaining P _{the maximum receiving ability of photovoltaic generation}, and and photovoltaic generation power prediction value P _predictionrelatively, if P _{light the maximum receiving ability of volt generating}> P _prediction, photovoltaic generation scheduling enters non-rationing the power supply the period, and photovoltaic generation Plan Curve is the interval band of considering that predicted value error and headroom are exerted oneself, i.e. P _{planned value}=(P _prediction-σ) MW～min ((P _prediction+ σ), P _headroom) MW; If P _{the maximum receiving ability of photovoltaic generation}< P _prediction, photovoltaic generation scheduling enters the period of rationing the power supply, and photovoltaic generation Plan Curve is that maximal value is P _{the maximum receiving ability of photovoltaic generation}, minimum value be zero interval band, i.e. P _{planned value}=0～P _{the maximum receiving ability of photovoltaic generation}.

In the 6th optimal technical scheme provided by the invention, in described step 4, stablize limited scheduling slot in security of system, by limited power limit value P _{the maximum receiving ability of photovoltaic generation}, each photovoltaic plant power prediction value P _{prediction, i}, prediction uncertainty σ _iwith the headroom P that exerts oneself _{headroom, i}as the input of power allocation scheme, taking the limited photovoltaic generation electric weight of system minimum in the power limited period as target, be constraint according to each photovoltaic plant predicted power and general power limit value, optimize and distribute the exportable power P of each photovoltaic plant _i(t); Optimize partition function as shown in the formula described:

$\min f=\underset{i}{\overset{n}{\mathrm{\&Sigma;}}}{Q}_i\left(P_i\left(t\right)\right)---\left(2\right)$

s.t.

P _i(t)≤P _{prediction, i}(3)

In formula, P _i(t) be the output power of i photovoltaic plant, Q _i(P _i(t)) be the electric weight of rationing the power supply of i photovoltaic plant.

Compared with the prior art, a kind of photovoltaic generation Optimization Scheduling based on predicting that uncertainty and headroom are exerted oneself provided by the invention, allow photovoltaic plant to participate in system in service, by coordinating the scheduling of photovoltaic generation and normal power supplies, make to improve the photovoltaic generation ability of dissolving on the basis of safeguards system safe and stable operation; Allow photovoltaic plant can participate in electric power system dispatching operation, comprise and allow the photovoltaic plant that power swing is larger to participate in operation of power networks; Set up the communication system of photovoltaic plant and dispatching center, the expectation generated output that photovoltaic plant is reported descends photovoltaic plant to carry out after arranging by the coordination of dispatching center again, to coordinate the power scheduling between each photovoltaic plant and between photovoltaic plant and normal power supplies; To make full use of photovoltaic generation institute generated energy as principle, photovoltaic generation scheduling is divided into limited period of safety and stability and non-limited period of safety and stability, in two periods, adopt respectively diverse ways scheduling photovoltaic power station power generation; Allow the photovoltaic plant operation of fluctuating within the specific limits, can adapt to photovoltaic generation and rely on the demand that solar energy resources fluctuates, and regulation fluctuation range is conducive to improve power prediction precision; Priority scheduling photovoltaic generation under the prerequisite of considering electricity net safety stable constraint, is conducive to improve electric network security; Limited power optimization in the limited safety and stability period is assigned to each photovoltaic plant, has reduced the limited electric weight of photovoltaic generation, be conducive to improve the dissolve ability of photovoltaic generation of electrical network; Taking the multiple electricity of photovoltaic plant as principle, economy and the feature of environmental protection of the operation of increase system.

Brief description of the drawings

Fig. 1 is the schematic flow sheet based on predicting the photovoltaic generation Optimization Scheduling that uncertainty and headroom are exerted oneself.

Fig. 2 is the interval form of photovoltaic plant operation plan.

Fig. 3 judges the whether schematic diagram in the limited period of photovoltaic generation in step 3 in method.

Fig. 4 is the schematic diagram that in method, step 4 is optimized distribution to limited power.

Embodiment

As shown in Figure 1, a kind of photovoltaic generation Optimization Scheduling based on predicting that uncertainty and headroom are exerted oneself, comprises the steps:

(1). according to photovoltaic generation headroom model, obtain the headroom P that exerts oneself _headroom;

(2). the whole network photovoltaic generation is received capacity calculation;

(3). judge that whether photovoltaic generation is in the limited period;

(4). limited power is optimized to distribution;

(5). output photovoltaic power station power generation operation plan.

In described step 1, headroom is exerted oneself and is referred to the maximum output limit value that the headroom model of photovoltaic plant obtains.

Described headroom model, is at fine day, block without cloud layer in the situation that, calculates and set up the relational expression model between instantaneous intensity of solar radiation near the ground and the instantaneous intensity of solar radiation in section, exoatmosphere.

In described step 2, in order to obtain photovoltaic generation Plan Curve P _{planned value}, need be to the maximum receiving ability of the photovoltaic generation P under peak load regulation network and the restriction of various security constraint _{the maximum receiving ability of photovoltaic generation}judge.

P _{the maximum receiving ability of photovoltaic generation}obtained by the peak regulation constraint maximum receiving ability of lower photovoltaic generation and the lower maximum ability integration of receiving of various security constraint restriction; The maximum receiving ability of photovoltaic generation and load prediction value, interconnection plan, Unit Combination mode, Region control deviation and margin capacity associated under peak load regulation network constraint, computing formula is:

P _{the maximum receiving ability of the limited lower photovoltaic generation of peak regulation}=P _{total load prediction}+ P _{interconnection plan}-P _{conventional unit minimum load}-ACE-P _{margin capacity}(1)

In formula (1), the Region control deviation that ACE is electrical network.

In described step 3, according to the maximum receiving ability of the electrical network photovoltaic generation obtaining P _{the maximum receiving ability of photovoltaic generation}, and and photovoltaic generation power prediction value P _predictionrelatively, if P _{the maximum receiving ability of photovoltaic generation}> P _prediction, photovoltaic generation scheduling enters non-rationing the power supply the period, and photovoltaic generation Plan Curve is the interval band of considering that predicted value error and headroom are exerted oneself, i.e. P _{planned value}=(P _prediction-σ) MW～min ((P _prediction+ σ), P _headroom) MW; If P _{the maximum receiving ability of photovoltaic generation}< P _prediction, photovoltaic generation scheduling enters the period of rationing the power supply, and photovoltaic generation Plan Curve is that maximal value is P _{the maximum receiving ability of photovoltaic generation}, minimum value be zero interval band, i.e. P _{planned value}=0～P _{the maximum receiving ability of photovoltaic generation}.

In described step 4, stablize limited scheduling slot in security of system, by limited power limit value P _{photovoltaic generation large receiving ability}, each photovoltaic plant power prediction value P _{prediction, i}, prediction uncertainty σ _iwith the headroom P that exerts oneself _{headroom, i}as the input of power allocation scheme, taking the limited photovoltaic generation electric weight of system minimum in the power limited period as target, be constraint according to each photovoltaic plant predicted power and general power limit value, optimize and distribute the exportable power P of each photovoltaic plant _i(t); Optimize partition function as shown in the formula described:

$\min f=\underset{i}{\overset{n}{\mathrm{\&Sigma;}}}{Q}_i\left(P_i\left(t\right)\right)---\left(2\right)$

s.t.

P _i(t)≤P _{prediction, i}(3)

In formula, P _i(t) be the output power of i photovoltaic plant, Q _i(P _i(t)) be the electric weight of rationing the power supply of i photovoltaic plant.

Need statement, content of the present invention and embodiment are intended to prove the practical application of technical scheme provided by the present invention, should not be construed as limiting the scope of the present invention.Those skilled in the art inspired by the spirit and principles of the present invention, can do various amendments, be equal to and replace or improve.But in the protection domain that these changes or amendment are all awaited the reply in application.

Claims (7)

1. the photovoltaic generation Optimization Scheduling based on predicting that uncertainty and headroom are exerted oneself, is characterized in that, described method comprises the steps:

(1). according to photovoltaic generation headroom model, obtain the headroom P that exerts oneself _headroom;

(2). the whole network photovoltaic generation is received capacity calculation;

(3). judge that whether photovoltaic generation is in the limited period;

(4). the photovoltaic plant power to the limited period is optimized distribution;

(5). output photovoltaic power station power generation operation plan.

2. method according to claim 1, is characterized in that, in described step 1, headroom is exerted oneself and referred to the maximum output limit value that the headroom model of photovoltaic plant obtains.

3. method according to claim 2, it is characterized in that, described photovoltaic generation headroom model, is at fine day, block without cloud layer in the situation that, calculates and set up the relational expression model between instantaneous intensity of solar radiation near the ground and the instantaneous intensity of solar radiation in section, exoatmosphere.

4. method according to claim 1, is characterized in that, in described step 2, in order to obtain photovoltaic generation Plan Curve P _{planned value}, need be to the maximum receiving ability of the photovoltaic generation P under peak load regulation network and the restriction of various security constraint _{the maximum receiving ability of photovoltaic generation}judge.

5. method according to claim 4, is characterized in that, P _{the maximum receiving ability of photovoltaic generation}obtained by the peak regulation constraint maximum receiving ability of lower photovoltaic generation and the lower maximum ability integration of receiving of various security constraint restriction; The maximum receiving ability of photovoltaic generation and load prediction value, interconnection plan, Unit Combination mode, Region control deviation and margin capacity associated under peak load regulation network constraint, computing formula is:

P _{the maximum receiving ability of the limited lower photovoltaic generation of peak regulation}=P _{total load prediction}+ P _{interconnection plan}-P _{conventional unit minimum load}-ACE-P _{margin capacity}(1)

In formula (1), the Region control deviation that ACE is electrical network.

6. method according to claim 1, is characterized in that, in described step 3, according to the maximum receiving ability of the electrical network photovoltaic generation obtaining P _{the maximum receiving ability of photovoltaic generation}, and and photovoltaic generation power prediction value P _predictionrelatively, if P _{the maximum receiving ability of photovoltaic generation}> P _prediction, photovoltaic generation scheduling enters non-rationing the power supply the period, and photovoltaic generation Plan Curve is the interval band of considering that predicted value uncertainty and headroom are exerted oneself, i.e. P _{planned value}=(P _prediction-σ) MW～min ((P _prediction+ σ), P _headroom) MW; If P _{the maximum receiving ability of photovoltaic generation}< P _prediction, photovoltaic generation scheduling enters the period of rationing the power supply, and photovoltaic generation Plan Curve is that maximal value is P _{the maximum receiving ability of photovoltaic generation}, minimum value be zero interval band, i.e. P _{planned value}=0～P _{the maximum receiving ability of photovoltaic generation}.

7. method according to claim 1, is characterized in that, in described step 4, stablizes limited scheduling slot in security of system, by limited power limit value P _{the maximum receiving ability of photovoltaic generation}, each photovoltaic plant power prediction value P _{prediction, i}, prediction uncertainty σ _iwith the headroom P that exerts oneself _{headroom, i}as the input of power allocation scheme, taking the limited photovoltaic generation electric weight of system minimum in the power limited period as target, be constraint according to each photovoltaic plant predicted power and general power limit value, optimize and distribute the exportable power P of each photovoltaic plant _i(t); Optimize partition function as shown in the formula described:

$\min f=\underset{i}{\overset{n}{\mathrm{\&Sigma;}}}{Q}_i\left(P_i\left(t\right)\right)---\left(2\right)$

s.t.

P _i(t)≤P _{prediction, i}(3)

In formula, P _i(t) be the output power of i photovoltaic plant, Q _i(P _i(t)) be the electric weight of rationing the power supply of i photovoltaic plant.