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Deep Reinforcement Learning For The Optimization Of Building Energy Control And Management, Jun Hao
Deep Reinforcement Learning For The Optimization Of Building Energy Control And Management, Jun Hao
Electronic Theses and Dissertations
Most of the current game-theoretic demand-side management methods focus primarily on the scheduling of home appliances, and the related numerical experiments are analyzed under various scenarios to achieve the corresponding Nash-equilibrium (NE) and optimal results. However, not much work is conducted for academic or commercial buildings. The methods for optimizing academic-buildings are distinct from the optimal methods for home appliances. In my study, we address a novel methodology to control the operation of heating, ventilation, and air conditioning system (HVAC).
We assume that each building in our campus is equipped with smart meter and communication system which is envisioned in …
Satellite Constellation Deployment And Management, Joseph Ryan Kopacz
Satellite Constellation Deployment And Management, Joseph Ryan Kopacz
Electronic Theses and Dissertations
This paper will review results and discuss a new method to address the deployment and management of a satellite constellation. The first two chapters will explorer the use of small satellites, and some of the advances in technology that have enabled small spacecraft to maintain modern performance requirements in incredibly small packages.
The third chapter will address the multiple-objective optimization problem for a global persistent coverage constellation of communications spacecraft in Low Earth Orbit. A genetic algorithm was implemented in MATLAB to explore the design space – 288 trillion possibilities – utilizing the Satellite Tool Kit (STK) software developers kit. …