Loads Mismatch and Network Voltage Behavior for Future Planning of Demand Response With Customer Satisfaction

Abstract

Thermostatically controlled loads (TCLs) aggregated into a generalized virtual battery (VB) offer a systematic approach to optimally manage such devices. However, challenges arise when operational conditions are oversimplified or overlooked, leading to a mismatch between expected and actual outcomes. This paper delves into the demand response mismatch (DRM) challenge within the context of peak load management, exploring the implications of power reductions stemming from external management and aggregator control. A customer satisfaction index has been introduced to assess the impact of such reductions on customer comfort. A comprehensive VB model is employed to govern the aggregator, ensuring adherence to all operational constraints. The DRM percentage is evaluated under both standard operating conditions and peak shaving strategies. The study also investigates the different types of customer discomfort according to device operation and cost. A predictive analysis of the percentages of load DRM serves as a valuable tool for future peak shaving planning. This research further analyzes the impacts of voltage variation on a distribution network that ends with customer loads.

Keywords

• Demand response
• peak management
• mismatch
• thermostatically controlled loads
• virtual battery
• smart grid