English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Microgrids represent an emerging paradigm of future electric power systemsthat can utilize both distributed and centralized generations. Two recenttrends in microgrids are the integration of local renewable energy sources(such as wind farms) and the use of co-generation (i.e., to supply bothelectricity and heat). However, these trends also bring unprecedentedchallenges to the design of intelligent control strategies for microgrids.Traditional generation scheduling paradigms rely on perfect prediction offuture electricity supply and demand. They are no longer applicable tomicrogrids with unpredictable renewable energy supply and with co-generation(that needs to consider both electricity and heat demand). In this paper, westudy online algorithms for the microgrid generation scheduling problem withintermittent renewable energy sources and co-generation, with the goal ofmaximizing the cost-savings with local generation. Based on the insights fromthe structure of the offline optimal solution, we propose a class ofcompetitive online algorithms, called CHASE (Competitive Heuristic Algorithmfor Scheduling Energy-generation), that track the offline optimal in an onlinefashion. Under typical settings, we show that CHASE achieves the bestcompetitive ratio among all deterministic online algorithms, and the ratio isno larger than a small constant 3.

Online Energy Generation Scheduling for Microgrids with Intermittent Energy Sources and Co-Generation