Power Management and Control to Balance Residential Microgrids with Individual Phase-wise Generation and Storage
Bibliographic record
Abstract
The past decade has seen a significant rise in proliferation of roof-top photovoltaic (PV) systems with storage units at residential sites. This has affected the way power system engineers and researchers have previously studied distribution systems as passive networks. With the introduction of these local distributed energy resources, a distribution system has become part of an active network. This modernization of the power distribution network, brings along with itself a number of key issues that need to be pro-actively tackled by the local utilities.\nIn North America, with family-owned roof-top PV systems, storage devices and electric vehicles, the concept of central generation has transformed to local distributed generation (DG). With this phenomenon reshaping the current perspective of distribution networks, the local generation and storage capacities, with their respective controllers, allow for these DG units to be grouped together to form single-phase microgrids most commonly referred to as residential microgrids. This thesis looks into the two key issues pertaining to residential microgrids i.e. accommodating multiple embedded generation and energy storage units while balancing the generation and loading in each phase to achieve overall three-phase system balance.\nA benchmark distribution system model is proposed in this thesis to study residential microgrids both in grid-connected and islanded modes. Limitations in existing distribution network models have been identified along with possible architectures for these residential microgrids. The configuration parameters of the benchmark model have been carefully selected after consultation with the London Hydro (local power utility in London, Ontario). Several case studies have been presented to show that the proposed benchmark model can be used to represent a particular architecture of the residential microgrids.\nMathematical foundations of balancing residential microgrids through back-to-back converters have been developed in this thesis, which lay the foundation stone of the subsequent contributions with regards to this thesis. An online toolkit is developed in LabVIEW from the derived mathematical formulations.\nTwo power management strategies for single-phase residential microgrids, namely intra-phase and inter-phase power management strategies have been proposed which cater for the coordinated control of these single-phase microgrids to balance generation and loading in all of the three-phases seen from a primary feeder.\nAn operational control strategy has been later studied for optimal selection of power surplus phase(s) to mitigate the deficit(s) in other phase(s). This allows the system to transfer power from the surplus phase(s) to power deficient ones to achieve an overall balance, despite diverse load demand profiles in each phase.\nAn experimental validation of the proposed control strategies has been carried out with laboratory-scale design and development of the back-to-back converter along side single-phase sources, loads and a control platform to mimic a typical residential microgrid. From the experimental results, it is concluded that phase imbalance can be mitigated by the transfer of surplus power from a phase to the power deficit phase.\nThis work on power balancing single-phase residential microgrids can potentially open up new areas of research in the field of microgrids, especially with an unprecedented growth of roof-top PV panels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".