Deriving policies from connection codes to ensure ongoing voltage stability

• Published in: Energy Informatics 2019-09, Vol.2 (Suppl 1), p.1-14, Article 19
• Main Authors: Ryan, David, Ponce De Leon, Miguel, Grant, Niall, Butler, Bernard, Vogel, Steffen, Mirz, Markus, Lyons, Pádraig
• Format: Article
• Language: English
• Subjects: Algorithms; Computer Science; Computer simulation; Distributed generation; Electric power grids; Electrical engineering; Electricity distribution; Energy sources; Fault detection; Grid codes; Information Systems and Communication Service; Management; Networks; Optimization; Parameters; Policies; Policy based network management; Power flow; Smart grid; Text mining; Voltage stability
• ISSN: 2520-8942; 2520-8942
• DOI: 10.1186/s42162-019-0081-3

The management and transmission networks is becoming increasingly complex due to the proliferation of renewables-based distributed energy resources (DER). Existing control systems for DER are based on static specifications from interdependent network connection documents. Such systems are inflexible and their maintenance requires concerted effort between grid stakeholders. In this paper we present a new supplementary control approach to increase the agility of the electricity grid. The ICT system that underlies smart grids has the potential to offer, by analogy with ICT based network management, a control plane overlay for the modern smart grid. Policy-based Network Management (PBNM) is widely deployed in managed telecoms networks. We outline how PBNM can augment the management of power and energy networks and report on our initial work to validate the approach. To configure the PBNM system, we have used text mining to derive connection parameters at the LV level. In our simulations, PBNM was used in collaboration with a Volt-VAr optimisation (VVO) to tune the connection settings at each DER to manage the voltage across all the buses. We argue that the full benefits will be realised when stakeholders focus on agreeing relatively stable high-level connection policies, the policies being refined dynamically, and algorithms such as VVO that set connection parameters so they are consistent with those high-level policies. Thus faults, power quality issues and regulatory infringement can be identified sooner, and power flow can be optimised.