TY - GEN
T1 - A Utility Maximized Demand-Side Management for Autonomous Microgrid
AU - Pasha, Aisha M.
AU - Ibrahim, Hebatallah M.
AU - Hasan, Syed Rafay
AU - Belkacemi, Rabie
AU - Awwad, Falah
AU - Hasan, Osman
N1 - Funding Information:
VI. ACKNOWLEDGMENT This work is supported by ICT Fund UAE, fund number 21N206 at UAE University, Al Ain, United Arab Emirates.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/31
Y1 - 2018/12/31
N2 - With the increase in renewable energy integration in the electrical power systems along with increase in the time-varying energy consumption by the users, it is imperative to regulate the load profile through pragmatic economical Demand-Side Management. Thus, the study carried out in this paper presents a real-time algorithm for cost optimization to achieve Demand-Side Management of a Renewable Energy Source integrated microgrid. The algorithm aims to achieve utility maximization and cost reduction for an optimal power scheduling in the presence of variable loads. The proposed approach mitigates the continuous changes in the variable loads that emulates the load profile found in residential, commercial and industrial users. The particular focus of this work is on developing a decentralized control scheme and a utility-oriented energy community, which provides user satisfaction based on energy management system, production units and load demand. Moreover, the paper presents utility maximization solutions on the combined energy profile of the microgrid targeting two main objectives, i.e., (1) minimizing the aggregate energy cost and (2) maximizing the provider's and user's satisfaction. Minimizing the aggregate energy cost aims to reduce the peak to average ratio of the aggregate energy profile of the microgrid using the cost function for energy cost minimization. The proposed technique is tested on microgrid which is coordinated in master-slave control topology. The implemented algorithm ensures a stable and efficient operation of the microgrid while minimizing the total cost of production.
AB - With the increase in renewable energy integration in the electrical power systems along with increase in the time-varying energy consumption by the users, it is imperative to regulate the load profile through pragmatic economical Demand-Side Management. Thus, the study carried out in this paper presents a real-time algorithm for cost optimization to achieve Demand-Side Management of a Renewable Energy Source integrated microgrid. The algorithm aims to achieve utility maximization and cost reduction for an optimal power scheduling in the presence of variable loads. The proposed approach mitigates the continuous changes in the variable loads that emulates the load profile found in residential, commercial and industrial users. The particular focus of this work is on developing a decentralized control scheme and a utility-oriented energy community, which provides user satisfaction based on energy management system, production units and load demand. Moreover, the paper presents utility maximization solutions on the combined energy profile of the microgrid targeting two main objectives, i.e., (1) minimizing the aggregate energy cost and (2) maximizing the provider's and user's satisfaction. Minimizing the aggregate energy cost aims to reduce the peak to average ratio of the aggregate energy profile of the microgrid using the cost function for energy cost minimization. The proposed technique is tested on microgrid which is coordinated in master-slave control topology. The implemented algorithm ensures a stable and efficient operation of the microgrid while minimizing the total cost of production.
KW - Demand-Side Management
KW - Distributed Generation (DG)
KW - Master-Slave Control
KW - Utility function
KW - cost optimization
KW - smart grid
UR - http://www.scopus.com/inward/record.url?scp=85061907758&partnerID=8YFLogxK
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U2 - 10.1109/EPEC.2018.8598451
DO - 10.1109/EPEC.2018.8598451
M3 - Conference contribution
AN - SCOPUS:85061907758
T3 - 2018 IEEE Electrical Power and Energy Conference, EPEC 2018
BT - 2018 IEEE Electrical Power and Energy Conference, EPEC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Electrical Power and Energy Conference, EPEC 2018
Y2 - 10 October 2018 through 11 October 2018
ER -