Dynamic energy management of a microgrid using approximate dynamic programming and deep recurrent neural network learning
This paper focuses on economical operation of a microgrid (MG) in real-time. A novel
dynamic energy management system is developed to incorporate efficient management of …
dynamic energy management system is developed to incorporate efficient management of …
Stochastic optimization of economic dispatch for microgrid based on approximate dynamic programming
This paper proposes an approximate dynamic programming (ADP)-based approach for the
economic dispatch (ED) of microgrid with distributed generations. The time-variant …
economic dispatch (ED) of microgrid with distributed generations. The time-variant …
Co-optimizing battery storage for the frequency regulation and energy arbitrage using multi-scale dynamic programming
B Cheng, WB Powell - IEEE Transactions on Smart Grid, 2016 - ieeexplore.ieee.org
We are interested in optimizing the use of battery storage for multiple applications, in
particular energy arbitrage and frequency regulation. The nature of this problem requires the …
particular energy arbitrage and frequency regulation. The nature of this problem requires the …
Optimal operation of energy storage systems considering forecasts and battery degradation
Energy storage systems have the potential to deliver value in multiple ways, and these must
be traded off against one another. An operational strategy that aims to maximize the …
be traded off against one another. An operational strategy that aims to maximize the …
On the sample complexity of actor-critic method for reinforcement learning with function approximation
Reinforcement learning, mathematically described by Markov Decision Problems, may be
approached either through dynamic programming or policy search. Actor-critic algorithms …
approached either through dynamic programming or policy search. Actor-critic algorithms …
A fast technique for smart home management: ADP with temporal difference learning
This paper presents a computationally efficient smart home energy management system
(SHEMS) using an approximate dynamic programming (ADP) approach with temporal …
(SHEMS) using an approximate dynamic programming (ADP) approach with temporal …
Tutorial on stochastic optimization in energy—Part I: Modeling and policies
There is a wide range of problems in energy systems that require making decisions in the
presence of different forms of uncertainty. The fields that address sequential, stochastic …
presence of different forms of uncertainty. The fields that address sequential, stochastic …
From reinforcement learning to optimal control: A unified framework for sequential decisions
WB Powell - Handbook of Reinforcement Learning and Control, 2021 - Springer
There are over 15 distinct communities that work in the general area of sequential decisions
and information, often referred to as decisions under uncertainty or stochastic optimization …
and information, often referred to as decisions under uncertainty or stochastic optimization …
[HTML][HTML] Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming
Most modern energy markets trade electricity in advance for technical reasons. Thus, market
participants must commit to delivering or consuming a certain amount of energy before the …
participants must commit to delivering or consuming a certain amount of energy before the …
Identifying the strategic priorities of the technical factors for the sustainable low carbon industry based on macroeconomic conditions
This study aims to find out the strategic priorities of the technical factors to have sustainable
low carbon industry. For this purpose, a hybrid multi-criteria decision-making (MCDM) is …
low carbon industry. For this purpose, a hybrid multi-criteria decision-making (MCDM) is …