Benchmarking Flexible Electric Loads Scheduling Algorithms

Because of increasing amounts intermittent and distributed generators in power systems, many demand response programs have been developed to schedule flexible energy consumption. However, proper benchmarks for comparing these methods are lacking, especially when decisions made based on information which is repeatedly updated. This paper presents a new benchmarking tool designed bridge this gap. Surveys that classify flexibility planning algorithms were an input define the standards. The framework can be used different objectives under diverse conditions faced by electricity stakeholders interested scheduling algorithms. It includes simulation environment captures evolution look--ahead information, enables online test seven measuring their performance uncertain market conditions. results show importance decision making, influence data quality algorithm performance, benefit using robust stochastic programming approaches, necessity trustworthy benchmarking.