Cloud Computing and Local Chip-Based Dynamic Economic Dispatch for Microgrids

Abstract

Dynamic economic dispatch in microgrids is usually realized in a centralized energy management system (EMS). However, centralized systems are subject to single-point failure problems. In rural areas and islands, a failed EMS cannot be recovered in a timely manner due to lack of technical support. In this paper, we propose a cloud and edge computing-based framework to realize dynamic economic dispatch, which is conducted on a local Digital Signal Processor (DSP) chip and a remote cloud computing platform (CCP). Based on the multi-parametric programming algorithm, the dispatch process is divided into two parts: offline calculation and real-time decision making. These calculation tasks can be conducted on the remote cloud computing platform and the DSP chip of the inverter in an arbitrary renewable generator, respectively. The tests are carried out on the Amazon Web Service (AWS) EC2 instance and an autonomous microgrid with DSP TMS320F28335 chip. The results show that the proposed method can obtain the same results as the conventional method, with significantly improved reliability.