Weather Data and Probability

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1814 H.X. Yang et al. / Renewable Energy 28 (2003) 1813–1824

Nomenclature

Pw(v) The power generated by the wind turbine when the wind velocityis v, W

Pr The rated power generated by the wind turbine, W

vr The rated wind velocity of the wind turbine, m / svc The cut-in wind speed of the wind turbine, m / s

v Wind speed, m / s

v f The cut-off wind speed of the wind turbine, m / s

G The total solar radiation absorbed by the PV panels, W/m2

V Voltage generated by the PV module, V

I Current generated by the PV module, A

P Power output by the PV module, W

C 1,C 2,C 3 Parameters that can be identified by tests [12]

C 4,C 5,C 6 Parameters that can be identified by tests [12]

C 7 Parameter that can be identified by tests [12]

T ce Operating temperature of solar cells, K , determined by ambient airtemperature, the characteristics of the module, insulation on the

module, and other variables such as wind velocity.

SOC (t ) Battery state of charge of the battery bank at hour t , Ah

s Self-discharge rate of the battery bank, percentage

h( I bat (t )) Charging efficiency of the battery bank with the charging currentat hour t , assumed 1 during discharge, and 0.65 to 0.85 duringcharge

I bat (t ) Charging current at hour t , A

t Time interval, 1.0 h in this study

I bat ,max(t ) Possible maximum battery current rate at h t , A

I max The maximum battery current rate of the battery bank, A

C Constant, zero during discharge and 1 during charge

SOC max The maximum state of charge of the battery bank, Ah

SOC min The minimum state of charge of the battery bank, Ah

C (t ) Power input to the storage system at hour t , W P(t ) Power generated by the wind turbine and PV modules at hour t , W

L(t ) Electricity load needed by the demand system at hour t , W

PW (t ) Power generated by the wind turbine at hour t , W

PPV (t ) Power generated by PV modules at hour t , W

V L The nominal voltage need by the system, V

I needed (t ) Current needed for the load at hour t , A

I sup ply(t ) Current supplied by both PV modules and wind turbine at hour t , A

LPSP Loss of power supply probability

SOC The nominal capacity of the battery bank, equaling SOC max, Ah



1815 H.X. Yang et al. / Renewable Energy 28 (2003) 1813 – 1824

1. Introduction

For different districts and locations, climatic conditions, including solar irradiance,

variations in wind speed, temperature, and so forth, are always changing. In orderto ef ficiently utilize renewable energy using wind power and solar energy, an analysis

of the characteristics of solar irradiance and wind conditions at a potential site should

be made at the stage of inception.

There are a number of methods used to design a hybrid photovoltaic wind system

and to calculate the probability or reliability of its power generating capacity. Themost popular method, LPSP (loss of power supply probability) method has been

used to design a hybrid system using linear programming, goal programming and

probabilistic techniques [1–3]. LPSP is the probability that an insuf ficient power

supply results when the hybrid system (PV, wind power and energy storage) is not

able to satisfy the load demand. The LPSP is considered to be the implemented

criteria for a hybrid PV–wind system employing a battery bank. For one location,

long-term data on wind speed and irradiance records for every hour of the day are

deduced to produce the probability density function of the combined generation. For

a given load distribution, the probability density function of the storage is obtained

and the battery size calculated to give the relevant level of the system’s reliability

using the LPSP technique. Additionally, the trade-off/risk method is a recent theoreti-

cal advance to solve problems with multiple conflicting objectives and uncertainty

in system planning [4].

In this study, a simulation model of a hybrid system is established, and itsreliability or probability for a telecommunication system is analyzed using the LPSP

technique. For a given loss probability, different combinations of PV modules, wind

turbines and battery banks are determined.

2. Weather data analysis

For the Hong Kong Special Administrative region, the climate data for 1989 are

taken as the typical weather year, as shown in Ref. [5]. It is seen from Fig. 1 that

Fig. 1. Monthly accumulated solar radiation and wind power distribution in 1989.




Fig. 2. Daily accumulated solar radiation and wind power distribution in January.

solar and wind sources are complementary over that year. The summer provides

good solar irradiance but poor wind conditions, whilst a relatively good wind source

but poor solar radiation occurs in the winter. For the daily distribution the results

are shown in Fig. 2. On most days with high solar radiation, the wind energy is

poor. Such periods usually last for 3–5 days, thus such complementary characteristicsmake the hybrid application more reliable. The above shows that the combination of

the two energy sources can provide a better utilization factor for the available energy.

For a typical day of sunshine, the radiation peaks at around 13:00, as shown inFig. 3. The available solar power is able to meet the load profile and peak load

during the daytime. For the wind distribution in Hong Kong, September to March

provides the highest wind speeds, which occur early in the morning, with the lowestin the afternoons. In other months, the wind speed in good wind exposure areas

changes daily and continuously [6]. Thus, solar energy and wind energy resources

can compensate for each other not only for a few days but also for the whole year.

Fig. 3. Typical diurnal solar radiation distribution in a sunny day.




3. Probability analysis of hybrid photovoltaic–wind power generation systems

3.1. Methodology

In order to calculate the performance of an existing system, or to predict energy

consumption or energy generated from a system in the design stage, appropriate

weather data is required. The development of methodologies for generating the so-

called typical meteorological year (TMY) provides a standard for hourly data for

solar radiation and other meteorological parameters for a period of 1 year, rep-resenting climatic conditions considered to be typical over a longer time period.

Previous studies are mostly for solar energy systems and building energy studies [7–

10], but no appropriate TMY study is available for wind and hybrid solar–wind

application. In earlier studies, the weighting criteria for wind have been very small-

scale, so a TMY for a hybrid solar–wind system was required.

A suitable TMY for hybrid solar-wind systems should be studied and achieved

for Hong Kong and other areas to calculate the performance of the renewable energy

application [11]. Here, the typical weather year of 1989 is applied for the probability

study on an hourly basis instead of one appropriate TMY for Hong Kong. The results

achieved in this study are for the typical weather year of 1989 only. Thus, more

reliable results and fewer errors can be achieved if the appropriate TMY were

applied.

3.2. The simulation models

The system is shown in Fig. 4. The wind energy conversion system (WECS) and

photovoltaic system are paralleled in order to supply electrical power to the load,

and the excess energy generated is supplied to the batteries. Once the energy is

deficit, the batteries discharge to supply the shortfall in demand. The following simul-

ation determines the performance of a hybrid system.For the output power of the wind energy conversion system (WECS), the wind

Fig. 4. Schematic diagram of a hybrid solar–wind system.




speed distribution for selected sites and chosen wind turbine type are the main factors

considered. The following simplified model is used to assess power generation prob-

ability as a function of wind velocity:

Pw(v) Pr

(vr vc)(vvc)······vcvvr

Pr ························vr vv f

0··························otherwise

(1)

For most PV modules, the power generation characteristic can be described by

[12]:

I C 1 C 2·GC 3 EXP V

C 4T ce1C 5· EXP V

C 6T ce1 V

C 7T ce(2)

P VI (3)

A maximum power point tracker (MPPT) is used to extract the maximum available

power at every isolation level. Here, the monocrystalline silicon PV modules are

used. The specifications are shown in Section 3.4. More details about the photovoltaic

modules are introduced in the literature [12]. The maximum power points are

found from:

∂P

∂V 0 (4)

Small-sized lead-acid batteries are used for energy storage. The selection of a

proper battery for these types of applications requires a complete analysis of the

battery’s charge and discharge requirements, including load, output and pattern of the solar or alternative energy source, the operating temperature, and the ef ficiency

of the charger and other system components.

Energy losses occur when charging a battery. The battery ef ficiency drops further

when as the battery ages or if it is not maintained correctly. The battery’s state of

charge (SOC) is computed using:

SOC (t 1) SOC (t )·s I bat (t )·t ·h( I bat (t )) (5)

The maximum possible battery current rate I bat,max at time t, is determined by:

I bat .max(t ) max{0,min[ I max,(C ·(SOC maxSOC (t )) (SOC (t ) (6)

SOC min)·(1C )) / t ]}

I bat,max depends on the battery’s state at each time instant. The battery’s state is

described by the amount of the battery’s state of charge, by the sign of the batterycurrent, as well as by the history of the battery. I max is given by manufactures as

around 20% of the value of nominal capacity.




In this study, the electrical energy is supplied to a telecommunication system. The

main consumer is the telecommunication equipment, as well as four buoys of 40 W

each during the nighttime. The operation mode is about 30% in emission and 70%

in reception. The power consumption is 70 W from 7:00 to 19:00, and 230 W from19:00 to 7:00.

3.3. Loss of power supply probability (LPSP)

The power input to the storage system is controlled by the equation C (t ) =

P(t ) L(t ) in which P(t ) = PW (t ) + PPV (t ). It is evident that the power generated by

the hybrid system and the amount of energy stored are time dependent. For the

charging process of the battery, [PW (t ) + PPV (t )] L(t ), the objective function is:

SOC (t 1) SOC (t )·s PW (t ) PPV (t ) L(t )V L

·t ·h( I bat (t )) (7)

The charging ef ficiency is considered to be 0.75, and the self-discharge rate is

assumed to be zero since it is only 0.007% for 1 h. There are some constraints

restricting the range of the decision variables during the charging process:

PW (t ) PPV (t ) L(t )0.2SOC ·V L

t (8)

0.2SOC SOC (t )SOC (9)

For the discharging process, PW (t ) + PPV (t ) L(t ), the related equations are as fol-

lows:

I needed (t ) L(t )PW (t )PPV (t )

V L·h( I bat (t )) (10)

I sup ply(t ) min I max 0.2SOC

t ,

SOC (t )·s SOC min

t (11)

LPSP

n

i 1

hours( I sup ply(t ) I needed (t ))

n (12)

The discharging ef ficiency is considered to be 1. For longevity of battery, themaximum charging rate, SOC /5, is given as the upper limit. To avoid deep discharg-

ing, the battery cannot be discharged to 20% or less, so that SOC min is 20% of the

nominal capacity of the chosen battery.

3.4. Sizing selection of wind generator, PV module and battery

Using the LPSP technique, the size of the equipment is optimized and can beselected when economical constraints are not considered. The assumptions of this

study are as follows:




Table 1

Characteristics of PV modules

Height Width Frame PV area (m2

) Electrical performance(mm) (mm)

Dep.(mm) Wid.(mm) Isc Voc Pmax

1280 357 29 27 0.457 2.5 A 22 V 50 W

1. For the PV alone system, the optimization starts from 30 × 50 W PV moduleswith an interval of one 50 W PV module. The modules are placed horizontal, and

their characteristics are given in Table 1.

2. To assess the wind turbine alone system, a 0.3 kW wind generator is chosen asthe starting point, and 0.1 kW is considered as the interval. The characteristics

of wind turbines are, as follows: Start-up wind speed, 2.7 m/s; rated wind speed,

12.5 m/s; cut-off wind speed, 20.3 m/s; tower height, 22 m.

3. To assess the hybrid PV–wind power generation system, the capacity of wind

generators ranges from 0.2–2 kW with an interval of 0.1 kW, while two PV

modules is the starting point with one PV module as interval. Here, the wind

turbine power rate is considered as the lead power generator because of the coinci-

dent variation trend between daily load and wind speed distribution curve.

4. For the PV alone and wind alone power systems, considering their randomness

and discontinuity, 3 or 5 days’ worth of battery storage capacity is chosen, i.e.about 450 and 750 Ah (24 V voltage). For the hybrid system, three different

battery storage capacities are used for comparison, i.e. 150, 450 and 750 Ah.

3.5. Results and discussion

3.5.1. Results for the PV system operating alone

For the PV system alone, the PV capacity required is quite large, as shown in

Fig. 5. If the desired LPSP is 1%, the PV module number is more than 82 for 3

Fig. 5. The number of PV modules required for the desired LPSP.




days’ battery storage capacity, and 64 for 5 days’ battery storage capacity. If the

desired LPSP is 0%, the PV system alone with 3 days’ battery storage cannot meet

the requirement, but the one with 5 days’ battery storage can meet the requirement

when the PV modules number 76. This is because heavy cloudy/rain weather maycontinue for more than 3 days, but less than 5 days.

Results also show that the LPSP reduction ratio declines with the increase in the

PV module numbers. Higher ratios exist when the number of the PV modules is less

than 40, while ratios become lower when the PV module number is more than 70.

Thus, for this system, it is not appropriate to increase the number of PV modulesfor satisfying reliability.

3.5.2. Results for wind power system operating alone

The wind power system usually meets demand very well due to good wind speed

distribution in Hong Kong and because the load profile coincides with power density

distribution, that is, a higher load during night-time with good wind speed. For such

a load profile, the wind power system is more suitable. If the desired LPSP is 1%,

a 900 W or larger wind turbine is needed with 3 days’ battery storage, and 700 W

with 5 days’ battery storage. If the desired LPSP is 0%, the system with 3 days’

battery storage cannot meet the requirement, but for the 5-day battery storage systemthe rated power needed is 1400 W. For PV or wind power systems, a 5-day storage

battery is more suitable. This is because, in Hong Kong, both bad solar radiation

and bad wind speed occurs continually for more than 3 days, but for less than 5 days.

The curves also show that the LPSP reduction ratio has the same trend of the PVsystem alone curves, as shown in Fig. 6. Changes to the ratio are very small when

the rated power of the wind turbine exceeds 700 or 800 W.

3.5.3. Results for hybrid PV – wind systems

Hybrid PV–wind power systems usually meet load demands well because of the

good complementary effect of solar radiation and wind speed. For 150 or 450 Ah

battery storage capacities, the wind turbines with 200, 800, 1400 and 2000 W for

Fig. 6. The wind turbine capacity required for the desired LPSP.




different numbers of PV modules are chosen for comparison, as shown in Fig. 7.

For the 750 Ah storage, the trend is very similar to the 450 Ah case. The combi-

nations have very high reliability with very small LPSP, except for the 200 W wind

turbine system. Comparing the hybrid system with the PV system alone or the windsystem alone shows that the hybrid system can reduce both photovoltaic capacity

and wind turbine capacity.

For different desired LPSPs, the calculation results are shown in Fig. 8 and Fig.

9. The areas above the curves are areas that can ensure the required probability. For

a desired LPSP of 1% it shows that the hybrid system with a 1-day storage batterycan also provide high reliability and good probability, but the system needs an

excessive number of PV modules. The combinations for the system with 3-day stor-

age and the ones with 5-day storage are very similar. The 3-day storage hybrid

system is very suitable for the needed LPSP of 1%. For the desired LPSP of 0%,

only the systems with 3 or 5-day storage can meet the need. The changing ratio is

also very gradual when the rated power of the wind turbine exceeds 500 W. The

number of PV modules needed is also very large, at least 15 for the 3-day storage

system, while the hybrid system with 5-day storage has good performance to meet

the no-loss operating hours.

Fig. 7. (a) Combinations of PV and wind power capacities for the desired LPSP (150 Ah battery); (b)

Combinations of PV and wind power capacities for the desired LPSP (450 Ah battery).




Fig. 8. Combinations of PV and wind capacities for the desired LPSP of 1% with different storage

capacities.

Fig. 9. Combinations of PV and wind capacities for the desired LPSP of 0% with different storage

capacities.

4. Conclusions

As the first step in developing solar–wind hybrid energy in Hong Kong, the 1989

weather data as the typical weather year was used to analyze the complementary

characteristics of solar radiation and wind power. Simulation models for hybrid pho-

tovoltaic–wind systems with a storage battery are set up for LPSP calculation. Theoptimized combinations of photovoltaic modules, wind turbine and battery bank are

obtained for different desired LPSPs.

For the load demand system in this study, the priority sequence for choosing

renewable systems in Hong Kong should be the hybrid PV–wind power generation

system, the wind power system alone, then the PV system alone. The priority

sequence is affected not only by the load profile but also by wind speed and by solar

radiation conditions. The results show that the hybrid system with a 3-day power

storage battery is suitable for ensuring an LPSP of 1%, while the hybrid system with

a 5-day power storage battery is suitable for ensuring an LPSP of 0%. The weather

conditions, the types of photovoltaic modules and wind turbine, and the profile of the demand load also influence the priority sequence. Detailed simulation should be

undertaken before designing a hybrid renewable power generation system.




The weather data used in this study is the data of the typical weather year of

1989. Suitable weather data of TMY (for renewable energy use) can provide more

correct calculation or analysis results with fewer errors.

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