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IOT Based Energy Management System for Standalone PV Systems

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Abstract

An energy management system (EMS) is a system of computer-aided tools used by operators of electric utility grids to monitor, control, and optimize the performance of the generation and/or transmission system. In this paper, an IOT based power management system is proposed for standalone photovoltaic (SAPV) system, which involves loads that are categorized based on priorities as emergency, critical, essential and convenient. The Internet of Things (IOT) based EMS is realized to provide proper and convenient load shedding, source management, data acquisition and control of the SAPV networks. The load prediction in SAPV networks is handled using LabVIEW. The EMS is designed to diagnose the normal and overcurrent conditions in the network. During overcurrent faults, the loads are automatically disconnected and the load status at any instant is sent to the registered email. The user is able to access the remote SAPV networks, control the loads and restore the network operation using mobile app. The proposed system is validated and tested on 2-bus and 3-bus SAPV networks.

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Abbreviations

p:

Priority index

l:

Number of priorities

i:

Load index

mp :

Count of loads of priority p

B:

Battery index

Spi :

Return value of load i with priority p

Sb :

Return value associated with operating the battery

Wpi :

Count of units for load operation i of priority p

Wb :

Maximum number of units of time to operate battery b

Api :

Average power demand of load i of priority p for the time interval

Apb :

Average power required by battery b in specific time period

rpi :

Unit return value of load i with priority p

T:

Total time consumed for energy and load management control strategy

Tt :

Count of time increments

Epi :

Energy demand of load i of priority p

Ea :

Output energy of array

Eb :

Battery capacity

η:

Battery efficiency

SOCb :

Battery SOC

SOCb,min :

Minimum SOC of battery

smax :

Unit return of highest priority load

Ab :

Average power demand of battery b in time interval t

Epi,t :

Optimized actual energy

SFACT :

Supply factor

K:

Total count of loads including batteries

y:

Dependent variable

Et :

Cumulative energy from array and the battery

a:

Parameterized integer of Et

b:

Stage number in forward dynamic formulation

f(b,a):

Maximum total return

x:

Independent variable

β0, β1 :

Intercept coefficient

ε:

Error term

L1, L2, L3, L4:

Loads

S1,S2,S3:

Sources

RL1, RL2, RL3, RL4:

Relays connected across loads

RS1, RS2:

Relays connected across sources

CS1, CS2, CS3, CS4:

Current sensors across loads

Iout :

Actual output current

Vout :

Actual output voltage

DS:

Distributed storage

DSM:

Demand side management

IOT:

Internet of things

SOC:

State of charge

SAPV:

Stand alone photovoltaic

EMS:

Energy management system

ESS:

Energy storage system

BSS:

Battery storage system

t:

Instant of time

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Acknowledgements

The authors gratefully acknowledge the support provided by the Senate Research Council, University of Moratuwa (SRC/LT/2017/06).

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Authors and Affiliations

  1. School of Electrical Engineering, VIT University Chennai, Chennai, India

    O. V. Gnana Swathika

  2. Department of Electrical Engineering, University of Moratuwa, Colombo, Sri Lanka

    K. T.M. U. Hemapala

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  1. O. V. Gnana Swathika
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Correspondence to O. V. Gnana Swathika.

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Swathika, O.V.G., Hemapala, K.T.U. IOT Based Energy Management System for Standalone PV Systems. J. Electr. Eng. Technol. 14, 1811–1821 (2019). https://doi.org/10.1007/s42835-019-00193-y

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