Journal article
Why do electricity policy and competitive markets fail to use advanced PV systems to improve distribution power quality
Journal of Solar Energy, Article ID 5187317
2016
Abstract
The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications are forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibit active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by; uncertainties of baseline local distribution network power quality, and; to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the network characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage, and explores effective mitigation measures for PV system variability. We discuss of useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.
Details
- Title
- Why do electricity policy and competitive markets fail to use advanced PV systems to improve distribution power quality
- Authors/Creators
- M.P. McHenry (Author/Creator)J. Johnson (Author/Creator)M. Hightower (Author/Creator)
- Publication Details
- Journal of Solar Energy, Article ID 5187317
- Publisher
- Hindawi Publishing Corporation
- Identifiers
- 991005540813907891
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Journal article
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