Related papers: Distributed Voltage Regulation of Active Distribut…
Renewable energy resources (RERs) have been increasingly integrated into distribution networks (DNs) for decarbonization. However, the variable nature of RERs introduces uncertainties to DNs, frequently resulting in voltage fluctuations…
We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the…
Dynamic spectrum access (DSA) is regarded as an effective and efficient technology to share radio spectrum among different networks. As a secondary user (SU), a DSA device will face two critical problems: avoiding causing harmful…
The increased penetration of volatile renewable energy into distribution networks necessities more efficient distributed voltage control. In this paper, we design distributed feedback control algorithms where each bus can inject \emph{both…
Targets search and detection encompasses a variety of decision problems such as coverage, surveillance, search, observing and pursuit-evasion along with others. In this paper we develop a multi-agent deep reinforcement learning (MADRL)…
Inverter-based distributed energy resources facilitate the advanced voltage control algorithms in the online setting with the flexibility in both active and reactive power injections. A key challenge is to continuously track the…
Operational constraint violations may occur when deep reinforcement learning (DRL) agents interact with real-world active distribution systems to learn their optimal policies during training. This letter presents a universal…
This paper proposes a data-driven solution for Volt-VAR control problem in active distribution system. As distribution system models are always inaccurate and incomplete, it is quite difficult to solve the problem. To handle with this…
Deep reinforcement learning (DRL) is a machine learning-based method suited for complex and high-dimensional control problems. In this study, a real-time control system based on DRL is developed for long-term voltage stability events. The…
As a typical switching power supply, the DC-DC converter has been widely applied in DC microgrid. Due to the variation of renewable energy generation, research and design of DC-DC converter control algorithm with outstanding dynamic…
In this paper, we propose a network scenario where the baseband processes of the virtual small cells powered solely by energy harvesters and batteries can be opportunistically executed in a grid-connected edge computing server, co-located…
Network slicing enables the operator to configure virtual network instances for diverse services with specific requirements. To achieve the slice-aware radio resource scheduling, dynamic slicing resource partitioning is needed to…
Multicast communication technology is widely applied in wireless environments with a high device density. Traditional wireless network architectures have difficulty flexibly obtaining and maintaining global network state information and…
This paper proposes a data-driven affinely adjustable robust Volt/VAr control (AARVVC) scheme, which modulates the smart inverter reactive power in an affine function of its active power, based on the voltage sensitivities with respect to…
Increasing amounts of distributed generation in distribution networks can provide both challenges and opportunities for voltage regulation across the network. Intelligent control of smart inverters and other smart building energy management…
This paper presents a cooperative multi-agent deep reinforcement learning (MADRL) approach for unmmaned aerial vehicle (UAV)-aided mobile edge computing (MEC) networks. An UAV with computing capability can provide task offlaoding services…
The development of renewable energy generation empowers microgrids to generate electricity to supply itself and to trade the surplus on energy markets. To minimize the overall cost, a microgrid must determine how to schedule its energy…
The issue of voltage variations caused by integration of renewables has been addressed in this paper through distributed management of Microgrids (MGs). The distribution network (DN) takes the network losses and voltage quality as…
In this paper, we investigate the computational resource allocation problem in a distributed Ad-Hoc vehicular network with no centralized infrastructure support. To support the ever increasing computational needs in such a vehicular…
The increasing electricity use and reliance on intermittent renewable energy sources challenge power grid management during peak demand, making Demand Response programs and energy conservation measures essential. This research combines…