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Title: Strategic distribution network planning with smart grid technologies
Author: Mohtashami, Sara
ISNI:       0000 0004 5361 3628
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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Increased penetration of distributed generations in distribution networks are altering the technical characteristics of the grid, pushing them to operate closer to their limits of safe and reliable operation. New renewable generators connecting to the distribution network will be constrained due to the presence of thermal and voltage constraints during times of low demand and high generation output. The traditional reinforcement planning by means of increasing the capacity of network assets can be very costly and usually ends up in overinvested network with low utilization rates of the assets. In recent years, some smart technologies have been introduced to be used to increase the utilization of network assets and provide the adequate capacity for Distributed Generations (DGs). These smart solutions can help the Distributed Network Operators (DNOs) to provide cheaper and faster network connections for DGs. This thesis presents a multi epoch Optimal Power Flow (OPF) model for capacity and voltage management of a distribution network for integrating new DGs. The model uses the smart solutions including Dynamic Line Rating (DLR), Quad-Booster (QB), Static VAR Compensator (SVC) and Automatic Network Management (ANM) for DGs as well as the traditional reinforcement options. Also the model finds the optimal connection points for new DGs to reduce the cost of network investment and DG curtailment. The multi epoch model is solved with both incremental approach where the investment is carried out incrementally and with integrated approach where the planning is done strategically anticipating the future needs of the network. It compares the application of smart solutions in short and long term planning. The proposed model is applied to a generic UK distribution network and the results are discussed.
Supervisor: Strbac, Goran Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available