Related papers: AI-based Optimal scheduling of Renewable AC Microg…
A robust power scheduling algorithm is proposed to schedule power flow between the main electricity grid and a microgird with solar energy generation and battery energy storage subject to uncertainty in solar energy production. To avoid…
Accurate short-term energy consumption forecasting is essential for efficient power grid management, resource allocation, and market stability. Traditional time-series models often fail to capture the complex, non-linear dependencies and…
We present a novel approach to optimize wind farm layouts for maximum annual energy production (AEP). The optimization effort requires efficient wake models to predict the wake flow and, subsequently, the power generation of wind farms with…
This paper presents a new active power control algorithm designed to maximize the power reserve of the individual turbines in a farm, in order to improve the tracking accuracy of a power reference signal. The control architecture is based…
Wind power forecasting (WPF), as a significant research topic within renewable energy, plays a crucial role in enhancing the security, stability, and economic operation of power grids. However, due to the high stochasticity of…
We study a smart grid with wind power and battery storage. Traditionally, day-ahead planning aims to balance demand and wind power, yet actual wind conditions often deviate from forecasts. Short-term flexibility in storage and generation…
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…
Short-term load forecasting is one of the crucial sections in smart grid. Precise forecasting enables system operators to make reliable unit commitment and power dispatching decisions. With the advent of big data, a number of artificial…
Microgrids have emerged as a pivotal solution in the quest for a sustainable and energy-efficient future. While microgrids offer numerous advantages, they are also prone to issues related to reliably forecasting renewable energy demand and…
The paper presents a spatio-temporal wind speed forecasting algorithm using Deep Learning (DL)and in particular, Recurrent Neural Networks(RNNs). Motivated by recent advances in renewable energy integration and smart grids, we apply our…
It is crucial today that economies harness renewable energies and integrate them into the existing grid. Conventionally, energy has been generated based on forecasts of peak and low demands. Renewable energy can neither be produced on…
This work considers energy management in a grid-connected microgrid which consists of multiple conventional generators (CGs), renewable generators (RGs) and energy storage systems (ESSs). A two-stage optimization approach is presented to…
Online decision-making in the presence of uncertain future information is abundant in many problem domains. In the critical problem of energy generation scheduling for microgrids, one needs to decide when to switch energy supply between a…
Decentralized energy management is of paramount importance in smart microgrids with renewables for various reasons including environmental friendliness, reduced communication overhead, and resilience to failures. In this context, the…
This paper presents a comprehensive survey of AI-driven mini-grid solutions aimed at enhancing sustainable energy access. It emphasises the potential of mini-grids, which can operate independently or in conjunction with national power…
Rising global energy demand from population growth raises concerns about the sustainability of fossil fuels. Consequently, the energy sector has increasingly transitioned to renewable energy sources like solar and wind, which are naturally…
The integration of wind energy into power grids necessitates accurate ultra-short-term wind power forecasting to ensure grid stability and optimize resource allocation. This study introduces M2WLLM, an innovative model that leverages the…
Electric energy is difficult to store, requiring stricter control over its generation, transmission, and distribution. A persistent challenge in power systems is maintaining real-time equilibrium between electricity demand and supply.…
Cooperating interconnected microgrids with the Distribution System Operation (DSO) can lead to an improvement in terms of operation and reliability. This paper investigates the optimal operation and scheduling of interconnected microgrids…
The microgrids design for remote locations represents one of the most important and critical applications of the microgrid concept. It requires the correct sizing and the proper utilization of the different sources to guarantee the…