Chukwuka Monyei

Mr. Chukwuka Monyei

orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2019 in Advanced Engineering Informatics
Verified
Journal Article
Open access
XLX.J. Luo
X.J. Luo
LOLukumon O. Oyedele
Lukumon O. Oyedele
AAAnuoluwapo O. Ajayi
Anuoluwapo O. Ajayi
CMChukwuka Monyei
Chukwuka Monyei
OAOlugbenga O. Akinade
Olugbenga O. Akinade
LALukman A. Akanbi
Lukman A. Akanbi

1 August 2018 in Energy Policy
Verified
Journal Article
Open access
CMChukwuka Monyei
Chukwuka Monyei
KJK. Jenkins
K. Jenkins
Serestina ViririSerestina Viriri
Serestina Viriri
AAA.O. Adewumi
A.O. Adewumi

1 January 2018 in Renewable and Sustainable Energy Reviews
Verified
Journal Article
Open access
CMChukwuka Monyei
Chukwuka Monyei
AAAderemi O. Adewumi
Aderemi O. Adewumi
MOMichael O. Obolo
Michael O. Obolo
BSBarka Sajou
Barka Sajou

1 December 2017 in Energy Policy
Verified
Journal Article
Open access
CMChukwuka Monyei
Chukwuka Monyei
AAA.O. Adewumi
A.O. Adewumi

1 September 2015 in Sustainable Cities and Society
Verified
Journal Article
Closed access
AOA.S.O. Ogunjuyigbe
A.S.O. Ogunjuyigbe
CMChukwuka Monyei
Chukwuka Monyei
TAT.R. Ayodele
T.R. Ayodele

1 May 2018 in Electric Power Systems Research
Verified
Journal Article
Open access
CMChukwuka Monyei
Chukwuka Monyei
AAA.O. Adewumi
A.O. Adewumi
The energy crisis of 2008 in South Africa, due to electricity demand surpassing supply and a depleted electricity reserve margin has exposed the need for more synergy between home energy management systems (HEMS) and supply side energy management systems (SSEMS). Demand side management (DSM) techniques have been investigated and proven to be viable means of regulating electricity demand from the consumer side. However, the viability of DSM is dependent on the participation of willing consumers. In this paper, a combined energy management system (CEMS) is proposed to provide a platform for incorporating the demands and constraints of consumers (time of dispatch, reduction of electricity costs, etc.) and suppliers (reduced operations cost, reduced emissions, etc.). The proposed CEMS utilizes dynamic pricing (DP) and a standard deviation biased genetic algorithm (SDBGA) in minimizing the DSM window to be allocated to the DSM loads of consumers based on the multi-objective constraints. The Medupi power plant which has been modelled to utilize carbon capture and sequestration (CCS) technology is used in carrying out the dispatch of the participating DSM loads (cloth washers, cloth dryers and dish washers) for 100,000 random residential customers. Results show that in dispatch option 1 (in which the user is in control of the start time), a lower cost of electricity of ZAR 373,218.40 is obtained compared to ZAR 416,280.20 by dispatch option 2 (in which the utility selects dispatch time for participating DSM loads) for the consumers. However, dispatch option 2 achieves a better minimized DSM window (14.94 MW), lower operating cost (about 1.6% lower than dispatch option 1), higher plant capacity utilization (87.92% efficiency) and a more evenly distributed profile.