M
Mehdi Pazhoohesh
Researcher at De Montfort University
Publications - 20
Citations - 384
Mehdi Pazhoohesh is an academic researcher from De Montfort University. The author has contributed to research in topics: HVAC & Computer science. The author has an hindex of 5, co-authored 16 publications receiving 137 citations. Previous affiliations of Mehdi Pazhoohesh include Newcastle University & University of Newcastle.
Papers
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Journal ArticleDOI
Optimal scheduling of a renewable based microgrid considering photovoltaic system and battery energy storage under uncertainty
Liang Luo,Sarkew S. Abdulkareem,Alireza Rezvani,Mohammad Reza Miveh,Sarminah Samad,Nahla Aljojo,Mehdi Pazhoohesh +6 more
TL;DR: Simulation results demonstrate that the use of practical PV model in a real environment improve the accuracy of the energy management system and decreases the total operational cost of the grid-connected microgrid.
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Investigating Smart City Development Based on Green Buildings, Electrical Vehicles and Feasible Indicators
Armin Razmjoo,Meysam Majidi Nezhad,Lisa Gakenia Kaigutha,Mousa Marzband,Seyedali Mirjalili,Mehdi Pazhoohesh,Saim Memon,Mehdi Ali Ehyaei,Giuseppe Piras +8 more
TL;DR: In this article, the authors investigated different aspects of smart cities development and introduced new feasible indicators related to green buildings and EVs in designing smart cities, presenting existing barriers to smart city development, and solutions to overcome them.
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Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption - A systematic review
TL;DR: In this paper , the authors present state-of-the-art machine learning, deep learning and statistical analysis models that have been used in the area of forecasting building energy consumption.
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A satisfaction-range approach for achieving thermal comfort level in a shared office
Mehdi Pazhoohesh,Cheng Zhang +1 more
TL;DR: The result shows that the proposed approach has a significant potential of maintaining most of the occupants in a reasonable thermal comfort range and is based on the advantages of the comfort level modelling.
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Building as a Virtual Power Plant, Magnitude and Persistence of Deferrable Loads and Human Comfort Implications
TL;DR: In this paper, the authors used high resolution data from 130 electricity sub-meters to characterise a 12,500m2 commercial building as a virtual power plant by assessing magnitude and duration of electrical loads suitable for demand response (DR).