Wind-Farm Power Tracking Via Preview-Based Robust Reinforcement Learning

Abstract

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Data-Driven Wind Farm Control via Multiplayer Deep Reinforcement Learning

“…There are also several essential differences between the work in this paper and Ref. [4]. Firstly, these two studies consider different tasks.…”

“…Though single turbine's control strategies have been widely studied, directly employing these methods to control every turbine in a wind farm via a non-cooperative way can lead to significantly degraded operating efficiency. A lot of studies [2], [3], [4] have demonstrated that the greedy strategy (i.e. every turbine in the farm aims to maximize its own power outputs) is not the optimal control strategy for farm-level power generation maximization.…”

“…It is noteworthy that the method proposed in this paper is partially built upon [14], [15], [4], and substantial new contributions have been made. Specifically, though Refs.…”

A Multiagent Reinforcement Learning Approach for Wind Farm Frequency Control

“…In recent years, Deep Reinforcement Learning (DRL) has achieved great success in solving computationally challenging decision-making problems, such as Atari [16], Go [17], and StarCraft [18]. Due to its powerful model-free optimisation capabilities, DRL has recently been used for real-time control problems in wind farms, such as output power maximisation [19], [20] and power tracking [21]. However, these works do not take into account the fast frequency response of the wind farm, and they do not model the power grid or the mechanical structure of WTs.…”

Intelligent Wind Farm Control via Grouping-Based Reinforcement Learning

“…It has attracted worldwide research interest and been applied to many important fields [15], [16], [17]. Notably, several recent studies [18], [19], [20], [21] successfully applied DRL to address wind farm control tasks. They verified the feasibility of employing DRL to maximize wind farms' economic profitability.…”