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Muhammad Muzaffar Iqbal

Researcher at National University of Computer and Emerging Sciences

Publications -  15
Citations -  193

Muhammad Muzaffar Iqbal is an academic researcher from National University of Computer and Emerging Sciences. The author has contributed to research in topics: Renewable energy & Photovoltaic system. The author has an hindex of 5, co-authored 15 publications receiving 85 citations. Previous affiliations of Muhammad Muzaffar Iqbal include University of Engineering and Technology & University of Engineering and Technology, Lahore.

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Journal ArticleDOI

Optimal Scheduling of Residential Home Appliances by Considering Energy Storage and Stochastically Modelled Photovoltaics in a Grid Exchange Environment Using Hybrid Grey Wolf Genetic Algorithm Optimizer

TL;DR: This paper presents an efficient home energy management system (HEMS) for consumer appliance scheduling in the presence of an energy storage system and photovoltaic generation with the intention to reduce the energy consumption cost determined by the service provider.
Proceedings ArticleDOI

Optimal Operation of Energy Storage System for a Prosumer Microgrid Considering Economical and Environmental Effects

TL;DR: A BESS operation strategy considering gas emissions as a key drive indicator to analyze five different energy management scenarios shows a significant reduction in energy cost and a remarkable decrease in greenhouse gas (GHG) emissions.
Proceedings ArticleDOI

IoT-Enabled Smart Home Energy Management Strategy for DR Actions in Smart Grid Paradigm

TL;DR: In this article, the authors investigated the electricity cost for residential end-users due to integration of distributed photovoltaic (PV) and electrical energy storage (EES) for IoT-enabled smart homes.
Proceedings ArticleDOI

Energy Management in Smart Homes with PV Generation, Energy Storage and Home to Grid Energy Exchange

TL;DR: Simulation results show that the proposed method can enhance the performance of the home electricity scheduling, decrease the effect of uncertainty on system and reduce the overall energy cost.