In a practical distribution system, the power delivery lines are not transposed and loads are not balanced. Often, these unbalanced distribution systems are also multi-phase in nature, i.e., power delivery lines have a mix of single-phase, two-phase, three-phase and/or neutral lines. Additionally, the integration of single-phase Distributed Generation (DG) units like solar PV cells and small wind turbines into the distribution grid makes it even more unbalanced. Moreover, balanced approximation based positive-sequence modelling is known to have some practical problems highlighted in literature, including lack of accurate power loss calculation, no consideration of unbalanced loading effect, unequal spacing and mutual coupling among phases. Consequently, multi-phase modelling leads to more accurate analysis and result.
Relevant publications:
My research on distribution system basically focuses on the voltage management and energy efficiency:
Voltage Management (Volt/VAr Control):
Traditionally, distribution system deploys On-Load Tap Changing (OLTC) transformers and reactive power (VAr) compensation devices (e.g., capacitor banks) to regulate voltages within the required operating constraints using local sensor readings. Thanks to the widespread deployment of advanced metering infrastructure in a smart grid environment, it is now possible to design more accurate strategies for Volt/VAr control to manage voltage profile, reduce power loss and shave peak demand. Smart grid data arriving in near real-time from numerous distributed sensors must be analysed in timely manner to enable effective Volt/VAr optimization. Most of the existing works lack: (i) realistic unbalanced multi-phase distribution system modelling, (ii) scalability of the Volt/VAr algorithm for larger test system, (iii) ability to handle gross errors and noise in data processing.
In our research, we consider realistic distribution system models that include unbalanced loadings and multi-phased feeders and the presence of gross errors such as communication errors and device malfunction, as well as random noise. At the core of the optimization process is an intelligent optimization based technique that is parallelized using high performance computing technique to solve Volt/VAr based power loss minimization problem. Extensive experiments covering the different aspects of the proposed framework show significant improvement over existing Volt/VAr approaches in terms of both the accuracy and scalability on IEEE 123 node and a larger IEEE 8500 node benchmark test systems.
Fig: The framework of the parallel Volt/VAr approach
Fig: Voltage profile with and without Volt/VAr control
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Energy Efficiency:
An electric power distribution system, which is typically a low-voltage network, is a vital part of the energy supply chain and, as almost 70% of total energy losses occur in its area. It is expected that voltage drops and power losses will be as low as possible in the distribution area to enhance the system efficiency. Also, the importance of a distribution system’s efficiency evaluation has increased recently because of the focus of industries and regulatory bodies being on its environmental impacts, energy efficiency and smart-grid capabilities. To increase a network’s efficiency by managing loss reduction in its distribution system, it is necessary to use effective and efficient planning methodologies.
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