Reinforcement-Learning Approach Guidelines for Energy Management
نویسندگان
چکیده
منابع مشابه
A Reinforcement-Learning Approach to Power Management
We describe an adaptive, mid-level approach to the wireless device power management problem. Our approach is based on reinforcement learning, a machine learning framework for autonomous agents. We describe how our framework can be applied to the power management problem in both infrastructure and ad hoc wireless networks. From this thesis we conclude that mid-level power management policies can...
متن کاملDeep Reinforcement Learning Solutions for Energy Microgrids Management
This paper addresses the problem of efficiently operating the storage devices in an electricity microgrid featuring photovoltaic (PV) panels with both shortand long-term storage capacities. The problem of optimally activating the storage devices is formulated as a sequential decision making problem under uncertainty where, at every time-step, the uncertainty comes from the lack of knowledge abo...
متن کاملBatch Reinforcement Learning for Smart Home Energy Management
Smart grids enhance power grids by integrating electronic equipment, communication systems and computational tools. In a smart grid, consumers can insert energy into the power grid. We propose a new energy management system (called RLbEMS) that autonomously defines a policy for selling or storing energy surplus in smart homes. This policy is achieved through Batch Reinforcement Learning with hi...
متن کاملA Reinforcement Learning Approach to Setting Multi-Objective Goals for Energy Demand Management
In order to cope with the unpredictability of the energy market and provide rapid response when supply is strained by demand, an emerging technology, called energy demand management, enables appliances to manage and defer their electricity consumption when price soars. Initial experiments with our multi-agent, power load management simulator, showed a marked reduction in energy consumption when...
متن کاملReinforcement Learning Based PID Control of Wind Energy Conversion Systems
In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. Theadaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinearcharacteristics of wind variations as plant input, wind turbine structure and generator operational behaviordemand for high quality adaptive controller to ensure both robust stability an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Low Power Electronics
سال: 2019
ISSN: 1546-1998
DOI: 10.1166/jolpe.2019.1618