Enhancing demand-side flexibility to reduce grid stress and maximize off-peak pricing benefits

As energy demand and energy security increase rapidly, energy management has become a global issue and concern. The main objective of this study was to optimize hospital energy consumption by scheduling hospital consumption based on time-of-use (TOU) pricing. Removing load from the power system, changing load demand from peak hours to off-peak hours, and switching off-appliance are generally demand-side management strategies employed to lower energy costs at the expense of consumers’ comfort. To address the problems of appliances turned “off” during peak periods which are unacceptable by consumers, PV/battery systems are incorporated into the grid system to improve power balance and total energy costs. Most recent studies focused on optimizing energy consumption between the cost and value of micro-grid operation during a certain time period. This study proposed a fuzzy logic controller integrated energy management for commercial loads. The proposed method intelligently selects energy sources using the grid energy cost, remaining daily limit, load consumption and availability of the solar PV or battery at any time of the day. The control system operates the loads at a reduced cost without any shifting. MATLAB/Simulink was used to model the system. The controller can optimize and improve power consumption, power system stability and electricity cost. The simulation results showcase the capability of the proposed model to manage and control systems in a more intelligent manner compared to traditional control systems. Furthermore, after the introduction of the fuzzy logic controller system, a reduction of 20.8 % in total energy consumption and 18.64 % in electricity cost was achieved.

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Publication Details

Journal
Energy Reports
Published
2024-11-28
DOI
https://doi.org/10.1016/j.egyr.2024.11.053
Citations
2
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.42
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article

Enhancing demand-side flexibility to reduce grid stress and maximize off-peak pricing benefits

Guiqiang Li, Abraham Hizkiel Nebey
2 citations
Energy Reports
Smart Grid Energy Management
0.42
article

Enhancing demand-side flexibility to reduce grid stress and maximize off-peak pricing benefits

Guiqiang Li, Abraham Hizkiel Nebey
article en
2 citations

Abstract

As energy demand and energy security increase rapidly, energy management has become a global issue and concern. The main objective of this study was to optimize hospital energy consumption by scheduling hospital consumption based on time-of-use (TOU) pricing. Removing load from the power system, changing load demand from peak hours to off-peak hours, and switching off-appliance are generally demand-side management strategies employed to lower energy costs at the expense of consumers’ comfort. To address the problems of appliances turned “off” during peak periods which are unacceptable by consumers, PV/battery systems are incorporated into the grid system to improve power balance and total energy costs. Most recent studies focused on optimizing energy consumption between the cost and value of micro-grid operation during a certain time period. This study proposed a fuzzy logic controller integrated energy management for commercial loads. The proposed method intelligently selects energy sources using the grid energy cost, remaining daily limit, load consumption and availability of the solar PV or battery at any time of the day. The control system operates the loads at a reduced cost without any shifting. MATLAB/Simulink was used to model the system. The controller can optimize and improve power consumption, power system stability and electricity cost. The simulation results showcase the capability of the proposed model to manage and control systems in a more intelligent manner compared to traditional control systems. Furthermore, after the introduction of the fuzzy logic controller system, a reduction of 20.8 % in total energy consumption and 18.64 % in electricity cost was achieved.

Energy ReportsVol. 12
University of Science and Technology of China (CN)
Openalex Percentile: Top 36%
Smart Grid Energy Management
0.42
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