Related papers: Unionized Data Governance in Virtual Power Plants
This paper addresses the problem of management and coordination of energy resources in a typical microgrid, including smart buildings as flexible loads, energy storages, and renewables. The overall goal is to provide a comprehensive and…
This paper presents a distributionally robust model predictive control (DRMPC) framework for the optimal Virtual Power Plant (VPP) operation under electricity price uncertainty. A unified VPP model is formulated that captures the…
Battery diagnosis, prognosis and health management models play a critical role in the integration of battery systems in energy and mobility fields. However, large-scale deployment of these models is hindered by a myriad of challenges…
The smart power grid aims at harnessing information and communication technologies to enhance reliability and enforce sensible use of energy. Its realization is geared by the fundamental goal of effective management of demand load. In this…
This paper examines how decentralized energy systems can be enhanced using collaborative Edge Artificial Intelligence. Decentralized grids use local renewable sources to reduce transmission losses and improve energy security. Edge AI…
As an essential measure to combat global warming, electric vehicles (EVs) have witnessed rapid growth. Flexible EVs can enhance power systems' ability to handle renewable generation uncertainties. How EV flexibility can be utilized in power…
Power grids are one of the most important components of infrastructure in today's world. Every nation is dependent on the security and stability of its own power grid to provide electricity to the households and industries. A malfunction of…
The smart electricity grid enables a two-way flow of power and data between suppliers and consumers in order to facilitate the power flow optimization in terms of economic efficiency, reliability and sustainability. This infrastructure…
In this note, we discuss potential advantages in extending distributed optimization frameworks to enhance support for power grid operators managing an influx of online sequential decisions. First, we review the state-of-the-art distributed…
With growing use of internet and exponential growth in amount of data to be stored and processed (known as 'big data'), the size of data centers has greatly increased. This, however, has resulted in significant increase in the power…
This research addresses distributed proportional power sharing of inverter-based Distributed Generators (DGs) in microgrids under variations in maximum power capacity of DGs. A microgrid can include renewable energy resources such as wind…
In many state-of-the-art control approaches for power systems with storage units, an explicit model of the storage dynamics is required. With growing numbers of storage units, identifying these dynamics can be cumbersome. This paper employs…
The increasing demand for direct electric energy in the grid is also tied to the increase of Electric Vehicle (EV) usage in the cities, which eventually will totally substitute combustion engine Vehicles. Nevertheless, this high amount of…
An energy management scheme is presented for a grid-connected hybrid power system comprising of a photovoltaic generator as the primary power source and fuel-cell stacks as backup generation. Power production is managed between the two…
A modern-day society demands resilient, reliable, and smart urban infrastructure for effective and in telligent operations and deployment. However, unexpected, high-impact, and low-probability events such as earthquakes, tsunamis,…
Cloud computing revolutionised the industry with its elastic, on-demand approach to computational resources, but has lead to a tremendous impact on the environment. Data centers constitute 1.1-1.5% of total electricity usage in the world.…
Decentralized management and coordination of energy systems are emerging trends facilitated by the uptake of the Internet of Things and Blockchain offering new opportunities for more secure, resilient, and efficient energy distribution.…
This paper presents a flexible and modular control scheme based on distributed model predictive control (DMPC) to achieve optimal operation of decentralized energy systems in smart grids. The proposed approach is used to coordinate multiple…
Power plant is a complex and nonstationary system for which the traditional machine learning modeling approaches fall short of expectations. The ensemble-based online learning methods provide an effective way to continuously learn from the…
With their expansion, national power grid have had to work with huge sets of data received from a vast number of substations and power plants. Given their large volume and variety, these data can be classified as big data. Managing this…