TY - JOUR
T1 - Power loss minimisation of off-grid solar DC nano-grids - part II
T2 - a quasi-consensus-based distributed control algorithm
AU - Samende, Cephas
AU - Bhagavathy, Sivapriya M.
AU - McCulloch, Malcolm
N1 - © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - This paper investigates the power loss minimization problem of solar DC nanogrids that are designed to provide energy access to households in off-grid areas. We consider nano-grids with distributed battery storage energy systems and that are enabled by multi-port DC-DC converters. As the nano-grids are not connected to the national grid and have batteries and converters distributed in each household, addressing the power loss problem while ensuring supply-demand balance is a challenge. To address the challenge, we propose a novel quasi-consensus based distributed control approach. The proposed approach consists of two algorithms namely, incremental loss consensus algorithm and voltage consensus algorithm. The incremental loss consensus algorithm is proposed to optimally schedule the battery charge/discharge operation while ensuring that supply-demand balance and the battery constraints are satisfied. The voltage consensus algorithm is proposed to determine optimal distribution voltage set points which act as optimal control signals. Both algorithms are implemented in a distributed manner, where minimal information exchange between households is required to obtain the optimal control actions. Simulation results of a solar DC nano-grid with five interconnected households verify the effectiveness of the proposed approach at addressing the nano-grid power loss problem.
AB - This paper investigates the power loss minimization problem of solar DC nanogrids that are designed to provide energy access to households in off-grid areas. We consider nano-grids with distributed battery storage energy systems and that are enabled by multi-port DC-DC converters. As the nano-grids are not connected to the national grid and have batteries and converters distributed in each household, addressing the power loss problem while ensuring supply-demand balance is a challenge. To address the challenge, we propose a novel quasi-consensus based distributed control approach. The proposed approach consists of two algorithms namely, incremental loss consensus algorithm and voltage consensus algorithm. The incremental loss consensus algorithm is proposed to optimally schedule the battery charge/discharge operation while ensuring that supply-demand balance and the battery constraints are satisfied. The voltage consensus algorithm is proposed to determine optimal distribution voltage set points which act as optimal control signals. Both algorithms are implemented in a distributed manner, where minimal information exchange between households is required to obtain the optimal control actions. Simulation results of a solar DC nano-grid with five interconnected households verify the effectiveness of the proposed approach at addressing the nano-grid power loss problem.
KW - battery storage energy system%
KW - distributed control
KW - energy access
KW - multi-port converter
KW - power losses
KW - solar DC nano-grid
UR - https://ora.ox.ac.uk/objects/uuid:aef81036-fee6-4be7-9e4a-53aa62fff5bb
U2 - 10.1109/TSG.2021.3111779
DO - 10.1109/TSG.2021.3111779
M3 - Article
AN - SCOPUS:85114713776
SN - 1949-3053
VL - 13
SP - 38
EP - 46
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
IS - 1
ER -
