M
Michael Angelo A. Pedrasa
Researcher at University of the Philippines Diliman
Publications - 42
Citations - 1328
Michael Angelo A. Pedrasa is an academic researcher from University of the Philippines Diliman. The author has contributed to research in topics: Distributed generation & Microgrid. The author has an hindex of 9, co-authored 42 publications receiving 1245 citations. Previous affiliations of Michael Angelo A. Pedrasa include University of the Philippines & University of New South Wales.
Papers
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Journal ArticleDOI
Coordinated Scheduling of Residential Distributed Energy Resources to Optimize Smart Home Energy Services
TL;DR: This work improves the basic formulation of cooperative PSO by introducing stochastic repulsion among the particles and simultaneously scheduling all DER schedules, to investigate the potential consumer value added by coordinated DER scheduling.
Journal ArticleDOI
Scheduling of Demand Side Resources Using Binary Particle Swarm Optimization
TL;DR: In this paper, the authors investigated the use of binary particle swarm optimization (BPSO) to schedule a significant number of varied interruptible loads over 16 hours and achieved near-optimal solutions in manageable computational time-frames for this relatively complex, nonlinear and noncontinuous problem.
Proceedings ArticleDOI
Improved energy services provision through the intelligent control of distributed energy resources
TL;DR: In this paper, an energy service modeling technique was proposed to capture temporal variations of its demand and value, and differentiate it from the electric energy consumed by the end-use equipment.
Proceedings ArticleDOI
Robust scheduling of residential distributed energy resources using a novel energy service decision-support tool
TL;DR: In this article, a methodology for making robust day-ahead operational schedules for controllable residential distributed energy resources (DER) using a novel energy service decision support tool is described, based on the consumers deriving benefit from energy services and not on electric energy.
Journal ArticleDOI
A novel energy service model and optimal scheduling algorithm for residential distributed energy resources
TL;DR: In this paper, a decision-support tool that aims to optimize the provision of residential energy services from the perspective of the end-user is proposed, which is composed of a novel energy service model and a novel distributed energy resources scheduling algorithm.