Conservation Voltage Reduction Technique in Renewable-Rich Multi-Energy Systems
Notice bibliographique
Résumé
Conservation Voltage Reduction (CVR) is an advanced distribution system management technique implemented by utilities to achieve energy savings and peak shaving by controlling the voltage magnitudes for voltage-dependent loads. With increasing penetration of solar photovoltaics (PVs) in distribution grids, their interfacing inverters can significantly contribute to CVR. This thesis focuses on two aspects of CVR: 1) CVR implementation in renewable-rich multi-energy distribution networks; 2) optimal PV placement to enhance CVR in multi-energy distribution networks. A deterministic programming model is first developed for day-ahead scheduling of voltage regulation devices for CVR implementation, including on-load tap changers (OLTC), capacitor banks (CBs), and PV interfacing smart inverters to power grids. This model minimizes the daily load consumptions and network power losses to provide optimal settings for voltage regulation devices. Natural gas networks are integrated with electric distribution systems to improve reliability and resiliency through energy conversion devices, such as gas-fired DGs (GFDGs) and the power-to-gas (P2G) technology. To address uncertainties of the forecasted load and PV power generation, a two-stage stochastic programming model for CVR implementation in multi-energy distribution networks is then proposed. The first stage finds the optimal tap and switch positions of OLTCs and CBs, respectively, and the base reactive power injection or absorption of PV smart inverters. After the realization of uncertainties via numerous scenarios, the second stage finds the amount of readjustments in reactive power output of PV smart inverters based on their droop characteristics to reach optimal CVR results. A two-step relaxation-based technique is also developed, which is proven to improve the computation speed significantly. The proposed stochastic model is validated by the modified IEEE 33-bus 7-node integrated electricity and natural gas system (IEGS), and the model scalability is then tested on the modified IEEE 123-bus 20-node IEGS. The proposed CVR technique is also validated by comparing with existing methods. To evaluate the proposed technique in real-world applications, the model is extended to unbalanced distribution grids, and is assessed using a 404-bus unbalanced distribution system operated by Saskatoon Light and Power in Saskatoon, Saskatchewan, Canada. The second part of this thesis focuses on optimal placement of PVs along with the capacity of PV smart inverters in multi-energy distribution networks to enhance CVR implementation. A framework is developed through two steps to determine a suitable number of PVs. A mixed-integer quadratically constrained programming (MIQCP) model is solved at the first step, considering an initial optimal number of PVs to be installed, and the amount of reductions in load consumptions and network power losses are calculated; a day-ahead CVR implementation model proposed in the first part of this thesis is then solved for randomly placed PVs, at the second step. The stopping criterion is whether improvements in load consumptions and power losses reductions are considerable (roughly 60% reduction is desired). If the planners need more improvements, the number of installed PVs can be increased, and the whole process is repeated until the stopping criterion is met. The PV optimal placement technique is validated using the IEEE 33-bus 7-node test system. It is found that there is a limit on the number of PVs in load consumption reductions, but integrating more PVs in the system can reduce power losses significantly. The CVR implementation with optimal placed PVs can achieve better results than that using randomly placed PVs.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».