Small-scale Solar Plants coupled with Smart Public Transport System and its Coordination
3.2 The ONB determination and failure analysis in SPTS
The capa-bus (supercapacitor based buses) based public transportation system is presented in [113]. This system appears to be vulnerable for the increased number of passengers per hour (NP) at EBSs. Capa-bus limited capacity and the lack of communication among EBSs may lead to the complete system failure. The present work conquers these issues and provides the fail-proof performance of SPTS. The increased NP may trouble the functioning of both, the grid and SPTS. Therefore, ONB is required to manage the NP demand. ONB determination is a challenging task due to the dynamic behaviour of the load, passengers, SP and ESD. ONB should not affect the performance of both, the grid and SPTS. Algorithm of ONB has insight of all such issues while deciding ONB [135], and it shows the following benefits:
• Decides ONB based on four dynamic profiles.
• Achieves the smooth functionality of SPTS using energy form both, the grid and SP.
• Avoids stress on the grid, which may occur due to the increased number of e-buses (NBs).
• Utilize the solar energy in proportion to the increased NBs.
The e-buses halt on their way if the consecutive EBSs failed to charge the e-buses. Such kinds of situations are restricted with the smart communication among the EBSs. The salient features of failure analysis in SPTS are, therefore:
• Optimal power utilization from both, the grid and SP.
• Fail proof.
• Smart communication.
• Intelligent energy management within EBS and among EBSs.
The major issues investigated in the failure analysis are:
• Different types of failures that exist in SPTS.
• The solution for each type of failure to ensure smooth functioning of SPTS.
• The solution for each type of failure to ensure grid support.
• Support from SP to SPTS in failure situations.
The real time data of the load, solar and passengers have been collected from the following departments.
• Load data from the state electricity board, Assam, India [121, 122].
• Solar data from the India meteorological department [124].
• Commuter’s data from the central transportation authority.
The details about ONB determination, failure analysis and FLC are given in the following sub-sections.
3.2.1 The ONB determination
Grid
SP
ND Bus stop
NP
Load
SD
B (SD1)h
H (SD2)o
D (SD3)u
D (SD4)i
Day type ND/SD
N -Number of passengersP
Grid condition off-peak/peak period
Vpu
peak period
NBs w.r.t ND/SD
NBs w.r.t EESD NBs w.r.t ESP
NB1 NB2 NB3
off-peak period
NBs w.r.t ND/SD
NBs w.r.t EESD NBs w.r.t ESP
NB2 NB3
NB1
w.r.t - with respect to ONB
ND SD SD
NB1
NB1
PP ND
Fig. 3.3ONB determination for ND and SDs in SPTS
The algorithm for ONB determination is explained through Fig. 3.3. Two types of days have been considered based on NP. One is the normal day (ND) and the other as a special day (SD). NP varies from minimum to medium for NDs (considered the passengers travel for office and other purposes) and varies from medium to maximum for SDs (considered the devotees travel to the temples). Four types of festival days have been considered under SD:
has been given for the smooth functionality of SPTS, so that the NB is considered as an objective function. The maximum NBs are proportional to NP. Off-peak period is considered when Vpu is greater than 1pu otherwise peak period.
The proposed algorithm decides ONB in the following manner: first, it checks the grid condition, whether it is in off-peak/peak period. Then it decides the day type, whether it is ND/SD. After that it decides: the NBs with respect to ND/SD, the NBs with respect to EESD
and the NBs with respect to ESP during off-peak and peak period separately as shown in Fig.
3.3. ONB is the average of NB1 (NBs with respect to NP), NB2 (NBs with respect to EESD) and NB3 (NBs with respect to ESP) for ND/SD during off-peak/peak period (3.5). Therefore, ONB during off-peak period (ONBOPP) and in peak period (ONBPP) can be expressed as
OPP
1 2 3
PP
ONB = f(NB , NB , NB ) ONB
(3.1) If the grid stays under off-peak period, then ONB is determined in the following manner.
ONBOPP: NBs according to NP is given by
1
(0 ) ( )
N B =
0 = 0
≤
C
C P
P P ND P ND P P SD
P SD
P
N < N N / N < N < N
R
N otherwise R
N
(3.2)
RC is the e-bus carrying capacity (limited to 30 passengers), NP ND is the maximum passenger limit for ND (180 passengers/ h) and NP SD is the maximum passenger limit for SD (360 passengers/ h). NBs with respect to EESD (ESD total capacity (EESDT) is considered as 300 kWh) [133] is expressed as
1
2
NB 20%
NB =
0 = 0
≥
ESD ESD
ESD min
ESD
E
E otherwise
E
E
(3.3)
Minimum energy always remain in the ESD (EESD min) is considered as 20%. ESD is able to support the maximum NBs when EESD is greater than 20%. The supporting formulas such as:
ESD sizing and SP sizing can be observed from Chapter-2, Section 2.1.2 to 2.1.4 [133]. NBs with respect to ESP (SP capacity is considered as 50 kW) [133] is therefore
3 1
( 15.75% for N D ) / ( 31.5% for S D ) N B = N B ( 15.75% for N D ) / ( 31.5% for S D )
0
≤ ≤
> >
SP
SP SP
BT m in
SP SP
E E E
E
E E
otherw ise
(3.4)
ESP varies from 0 to 50 kWh with respect to solar irradiance availability during sunshine hours (ref. Fig. 3.4), 31.5% of SP energy is required to support the maximum NBs in SDs (the maximum NBs for SD are 12 and EBT min is 1.31 kWh [133], which is 15.72 kWh. A 31.5% of ESP is 15.75 kWh). The maximum NBs for ND are 6. Therefore, ESP limit is 15.75%. The resultant ONB in off-peak period is therefore
1 2 3
OPP
1 2 3
(NB + NB + NB )
ONB =
( + + )
T T T (3.5) where T1, T2 and T3 are the temporary variables as a function of NB1, NB2, and NB3. Individually, T1, T2 and T3 become ‘0’, if NB1, NB2 and NB3 are ‘0’, otherwise ‘1’. If the grid stays under peak period, then ONB is determined in the following manner.
ONBPP: NBs according to NP is same as that of (3.2). NBs according to EESD is given by
2
NB 1 30%
NB =
0 = 0
≥
ESD ESD
ESD min
ESD
E
E otherwise
E
E
(3.6)
NBs according to ESP are same as that of (3.4). The resultant ONB with respect to NB1, NB2
and NB3 in peak period is same as that of (3.5). Table 3.1 shows the total use of NBs in 24 h for both, ND and SD.
Table 3.1: SP specification and the number of e-buses for ND and SD
Variable Rating
The number of e-buses for ND (in 24 h) 112 The number of e-buses for SD (in 24 h) 180
SP capacity 50 kW
Fig. 3.4 shows the solar irradiance availability and its seasonal variation. The solar irradiance availability is calculated based on the real time solar data collected from the India meteorological department (IMD). The solar irradiance availability is low in winter, moderate in rainy and high in the summer season. SDs cover all the seasons of a year, which can be seen in Fig. 3.4. The load profiles used for SPTS simulations are shown in Fig. 3.5.
Fig. 3.4Solar irradiance availability for ND and SDs
Fig. 3.5Load profiles of the grid for ND and SDs
3.2.2 Failure Analysis in SPTS
Failures in SPTS are divided into two categories. First category explains the failures from hardware side, and the second category explains the failures from software side.
1. Failures from hardware side: Four types of failures have been considered under this