Related papers: Assisted Energy Management in Smart Microgrids
The smart grid vision entails advanced information technology and data analytics to enhance the efficiency, sustainability, and economics of the power grid infrastructure. Aligned to this end, modern statistical learning tools are leveraged…
The smart grid is envisioned to significantly enhance the efficiency of energy consumption, by utilizing two-way communication channels between consumers and operators. For example, operators can opportunistically leverage the delay…
An optimal scheduling model for a microgrid participating in the electricity distribution market in interaction with a Distribution Market Operator (DMO) is proposed in this paper. The DMO administers the established electricity market in…
With the phenomenal growth in renewable energy generation, the conventional synchronous generator-based power plants are gradually getting replaced by renewable energy sources-based microgrids. Such transition gives rise to the challenges…
Renewable sources are taking center stage in electricity generation. However, matching supply with demand in a renewable-rich system is a difficult task due to the intermittent nature of renewable resources (wind, solar, etc.). As a result,…
The vast integration of non-synchronous renewable energy sources compromises power system stability, increasing vulnerability to frequency deviations due to the lack of inertia. Current efforts to decarbonise electricity grids while…
In order to reduce the energy cost of data centers, recent studies suggest distributing computation workload among multiple geographically dispersed data centers, by exploiting the electricity price difference. However, the impact of data…
We propose and solve a stochastic dynamic programming (DP) problem addressing the optimal provision of regulation service reserves (RSR) by controlling dynamic demand preferences in smart buildings. A major contribution over past dynamic…
The electricity market is threatened by supply scarcity, which may lead to very sharp price spikes in the spot market. On the other hand, demand-side's activities could effectively mitigate the supply scarcity and absorb most of these…
In this paper, a flexibility-oriented microgrid optimal scheduling model is proposed to mitigate distribution network net load variability caused by large penetration distributed solar generation. The distributed solar generation…
Integrating volatile renewable energy resources into the bulk power grid is challenging, due to the reliability requirement that at each instant the load and generation in the system remain balanced. In this study, we tackle this challenge…
Electricity market mechanisms designed to steer sustainable generation of electricity play an important role for the energy transition intended to mitigate climate change. One of the major problems is to complement volatile renewable energy…
This paper introduces a demand-side distributed and secured energy commitment framework and operations for a Power Producer and Supplier (PPS) in deregulated environment. Due to the diversity of geographical location as well as customers'…
The increasing number of Electric Vehicles (EVs) have led to rising energy demands which aggregates the burden on grid supply. A few solutions have been proposed to reduce grid load, for example, using storage systems for storing surplus…
Large electricity customers (e.g., large data centers) can exhibit huge and variable electricity demands, which poses significant challenges for the electricity suppliers to plan for sufficient capacity. Thus, it is desirable to design…
The emerging interest in deployment of renewable energy resources (RESs) in smart system represents a great challenge to both system planners and owners of Microgrids (MGs) operators. In this regard, we propose a Tri-level power market…
An increasing concern in power systems is how to elicit flexibilities in demand, which leads to nontraditional electricity products for accommodating loads of different flexibility levels. We have proposed Multiple-Arrival Multiple-Deadline…
Mobile edge computing (MEC) has emerged as one of the key technical aspects of the fifth-generation (5G) networks. The integration of MEC with resource-constrained unmanned aerial vehicles (UAVs) could enable flexible resource provisioning…
We present a deep reinforcement learning-based framework for autonomous microgrid management. tailored for remote communities. Using deep reinforcement learning and time-series forecasting models, we optimize microgrid energy dispatch…
Renewable energy brings huge uncertainties to the power system, which challenges the traditional power system operation with limited flexible resources. One promising solution is to introduce dynamic pricing to more consumers, which, if…