A novel distributed approach for event-triggered economic dispatch of energy hubs under ramp-rate limits integrated with sustainable energy networks

Abstract

This paper investigates a new consensus-oriented distributed approach for the event-triggered (ET) economic dispatch problem (EDP) over a smart grid under ramp-rate limits (RRLs) integrated with green power sources (GPSs) such as solar and wind energy for demand response strategies over hybrid energy power systems. To address the RRL condition, the authors have transformed the RRLs as minimum and maximum bounds on the derivative of generation for a generator. Then, a Karush–Kuhn–Tucker (KKT) condition and a more practical approximate KKT condition are developed for determining the optimality conditions. A practical ET protocol is proposed over a topology between generators by application of the proposed approximate KKT condition. In contrast to existing distributed optimization methods, this paper provides both optimally condition and distributed optimization scheme for dealing with RRLs integrated with sustainable hybrid energy systems. In addition, a computationally efficient ET mechanism, eliminating Zeno behaviour, has been considered for dealing with the efficient utilization of communication resources. This study incorporates the real-time input data from thermal production plants and GPSs for experimental analysis. RETScreen software having data-set of over 6,700 local meteorological stations is applied to obtain input data for GPSs. Furthermore, Weibull and Beta distribution functions have been applied for dealing with uncertainty in wind and solar energy sources. Two case studies are examined (with and without GPSs), and simulation results demonstrated the suitable performance of the proposed distributed ET EDP approach.