Energy Control and Storage to Promote High PV Penetration in Weak Distribution Networks
Bibliographic record
Abstract
The integration of Photovoltaic Distributed Energy Resources (PVDER) and central energy storage in low voltage distribution networks has been rapidly increasing in popularity within the last decade. Such integration can offer many benefits but may also harm the grid if not managed properly. This research focuses on the technical challenges in weak distribution networks arising from high PVDER penetration. The work concentrates on the issues of feeder voltage regulation, network power factor, generation fair access of participation, system losses and battery energy storage performance in cold weather. The deployment of central battery storage can increase the PV hosting capacity of network. However, battery performance evaluation in Canadian climate is very limited. Practical cycle testing of a vanadium redox flow battery and Li-Ion battery are performed during the winter season in Alberta, Canada. The common methods of Volt/VAr and Volt/Watt used for PVDER local power injection control focus on voltage regulation. However, the side effects impacting the network power factor and generation fair equity are not widely investigated in the literature. This research evaluates the performance of those techniques under real life load demand and PV generation data from a rural distribution network in Alberta, Canada. It becomes evident that under high PV generation scenarios the techniques are inadequate in maintaining an acceptable voltage profiles and severely impact the network power factor and fair generation access. New local control algorithms are developed to mitigate the aforementioned issues. Local PVDER power injection control can be limited in achieving the desired operational outcome. Nonetheless, its use is sometimes the only viable alternative due to the lack or unreliability of communication capability in the distribution network. For when such capability exists, a coordinated algorithm with optimized fair access to generation is developed and evaluated under the same real life demand and PV generation data. The optimized fair access control is able to mitigate the voltage regulation and power factor issues while achieving a high degree of fair generation equity and low system losses.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".