Learning-based load control to support resilient networked microgrid operations

• Published in: IET Smart Grid Vol. 3; no. 5; pp. 697 - 704
• Main Authors: Radhakrishnan, Nikitha, Schneider, Kevin P, Tuffner, Francis K, Du, Wei, Bhattarai, Bishnu P
• Format: Journal Article
• Language: English
• Published: Durham The Institution of Engineering and Technology 01.10.2020; John Wiley & Sons, Inc; Wiley
• Subjects: Adaptive algorithms; adaptive gradient descent-based algorithm; Algorithms; bulk transmission systems; changing grid dynamic characteristics; Consumers; Controllers; critical end-use; device-level algorithm; Distributed generation; distributed power generation; domestic appliances; Dynamic characteristics; Dynamic stability; effective option; end-use customers; end-use devices; ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; Frequency deviation; frequency set-points; GFA controllers; Grid Friendly Appliance; IEEE 123‐node test system; improved dynamic stability; individual GFA controller frequency setpoints; inverter-connected assets; invertors; isolated microgrids; larger frequency deviations; load control; load regulation; microgrid operators; operational characteristics; operational experience; Participation; power generation control; power grids; Research Article; Resilience; resilient networked microgrid operations; Switching; switching operations; switching transients; Systems stability; TM controllers; transient events; Washers & dryers; Water heaters; end-use customers; TM controllers; microgrid operators; power generation control; distributed power generation; switching operations; domestic appliances; operational experience; changing grid dynamic characteristics; switching transients; invertors; device-level algorithm; transient events; individual GFA controller frequency setpoints; power grids; inverter-connected assets; load regulation; improved dynamic stability; effective option; adaptive gradient descent-based algorithm; bulk transmission systems; load control; resilient networked microgrid operations; critical end-use; operational characteristics; larger frequency deviations; end-use devices; isolated microgrids; IEEE 123-node test system; Grid Friendly Appliance; frequency set-points; GFA controllers
• ISSN: 2515-2947; 2515-2947
• DOI: 10.1049/iet-stg.2019.0265

Networked and interconnected microgrids can improve resilience of critical end-use loads during extreme events. However, the frequency deviations in microgrids during transient events are significantly larger than those typically seen in bulk transmission systems. The larger frequency deviations can cause a loss of inverter-connected assets, resulting in a loss of power to critical end-use loads. Grid Friendly ApplianceTM (GFA) controllers can mitigate the transient event effects by engaging end-use loads. This paper presents a method to select set-points for end-use loads equipped with GFA controllers, while minimizing the interruptions to end-use customers. An online (i.e. real-time), device-level algorithm adjusts individual GFA controller frequency setpoints based on the operational characteristics of each end-use load and on the changing grid dynamic characteristics to selectively engage the load for mitigating the switching transients. The adaptive gradient-descent-based algorithm does not require control or coordination amongst end-use devices for adapting frequency set-points. The method is validated using dynamic simulations on a modified version of the IEEE 123-node test system with three microgrids using the GridLAB-DTM simulation environment. The improved dynamic stability achieved through the engagement of GFAs support the switching operations necessary for networked microgrid operations.