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Alahmad, Mahmoud

Publications and source records attributed to Alahmad, Mahmoud.

Time and Frequency Analysis of Load Profile Data

Technology advancements and integration of modern advanced metering systems can monitor, forecast, inform, control, and operate the building's mechanical, electrical, and plumbing (MEP) systems. They offer a higher level of information, which can contribute to making smart buildings more energy efficient and to making them closer to becoming grid-interactive energy efficient buildings (GEB). This paper builds on the ongoing research on variability analysis of a case study building with a 1-minute load profile and examines the Discrete Wavelet Transform (DWT) process in the frequency domain to quantify the signal's energy in each bandwidth, with respect to each end-use category. Moreover, the amount of variability in the total variability is not similar among the end-use categories. This information is needed to understand the behavior of the variability in the frequency domain for future applications, such as generating synthetic load profiles with a similar frequency spectrum as the measured signal.

decomposition↗

Comparison of time-frequency-analysis techniques applied in building energy data noise cancellation for building load forecasting: A real-building case study

Time-frequency analysis that disaggregates a signal in both time and frequency domain is an important supporting technique for building energy analysis such as noise cancellation in data-driven building load forecasting. There is a gap in the literature related to comparing various time–frequency-analysis techniques, especially discrete wavelet transform (DWT) and empirical mode decomposition (EMD), to guide the selection and tuning of time–frequency-analysis techniques in data-driven building load forecasting. This article provides a framework to conduct a comprehensive comparison among thirteen DWT/EMD techniques with various parameters in a load forecasting modeling task. A real campus building is used as a case study for illustration. The DWT and EMD techniques are also compared under various data-driven modeling algorithms for building load forecasting. The results in the case study show that the load forecasting models trained with noise-cancelled energy data have increased their accuracy to 9.6% on average tested under unseen data. This study also shows that the effectiveness of DWT/EMD techniques depends on the data-driven algorithms used for load forecasting modeling and the training data. Hence, DWT/EMD-based noise cancellation needs customized selection and tuning to optimize their performance for data-driven building load forecasting modeling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Electronic Switch Arrays for Managing Microbattery Arrays

Integrated circuits have been invented for managing the charging and discharging of such advanced miniature energy-storage devices as planar arrays of microscopic energy-storage elements [typically, microscopic electrochemical cells (microbatteries) or microcapacitors]. The architecture of these circuits enables implementation of the following energy-management options: dynamic configuration of the elements of an array into a series or parallel combination of banks (subarrarys), each array comprising a series of parallel combination of elements; direct addressing of individual banks for charging/or discharging; and, disconnection of defective elements and corresponding reconfiguration of the rest of the array to utilize the remaining functional elements to obtain the desited voltage and current performance. An integrated circuit according to the invention consists partly of a planar array of field-effect transistors that function as switches for routing electric power among the energy-storage elements, the power source, and the load. To connect the energy-storage elements to the power source for charging, a specific subset of switches is closed; to connect the energy-storage elements to the load for discharging, a different specific set of switches is closed. Also included in the integrated circuit is circuitry for monitoring and controlling charging and discharging. The control and monitoring circuitry, the switching transistors, and interconnecting metal lines are laid out on the integrated-circuit chip in a pattern that registers with the array of energy-storage elements. There is a design option to either (1) fabricate the energy-storage elements in the corresponding locations on, and as an integral part of, this integrated circuit; or (2) following a flip-chip approach, fabricate the array of energy-storage elements on a separate integrated-circuit chip and then align and bond the two chips together.

Mojarradi, Mohammad↗