Designing Electricity Distribution Network Charges for an Efficient Integration of Distributed Energy Resources and Customer Response

Doctoral Thesis (2018)
Author(s)

I.I.A. Abdelmotteleb (TU Delft - Energy and Industry)

Research Group
Energy and Industry
Copyright
© 2018 I.I.A. Abdelmotteleb
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Publication Year
2018
Language
English
Copyright
© 2018 I.I.A. Abdelmotteleb
Research Group
Energy and Industry
ISBN (print)
978-84-09-04874-8
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Abstract

A significant transformation has been gradually taking place within the energy sector, mainly as a result of energy policies targeting environmental objectives. Consequently, the penetration of Distributed Energy Resources (DERs) has been escalating, including self-generation, demand side management, storage, and electrical vehicles. Although the integration of DERs may create technical challenges in the operation of distribution networks, it may also provide opportunities to more efficiently manage the network and defer network reinforcements. These opportunities and challenges impose the necessity of redesigning distribution network charges to incentivize efficient customer response. This PhD thesis focuses on the design of distribution network charges that send correct economic signals and trigger optimal responses within the context of active customers. First, a cost-reflective network charge is proposed that consists of a forward-looking locational component based on the network’s utilization level, which transmits the long-term incremental cost of network upgrades. Then, a residual cost component that recovers the remaining part of the regulated network revenues is proposed. The objective of the proposed network charge is to increase the system’s efficiency by incentivizing efficient short- and long-term customers’ reaction while ensuring network cost recovery. The Thesis presents an optimization model that simulates customers’ response to the proposed network charge in comparison to other traditional network charge designs. The model considers the operational and DER investment decisions that customers take rationally to minimize their total costs.

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