Related papers: Prognostic Watch of the Electric Power System
In recent years, probabilistic forecasts techniques were proposed in research as well as in applications to integrate volatile renewable energy resources into the electrical grid. These techniques allow decision makers to take the…
The battery management system plays a vital role in ensuring the safety and dependability of electric and hybrid vehicles. It is responsible for various functions, including state evaluation, monitoring, charge control, and cell balancing,…
Microgrids are integrated systems that gather and operate energy production units to satisfy consumers demands. This paper details different mathematical methods to design the Energy Management System (EMS) of domestic microgrids. We…
An accurate load forecast is always important for the power industry and energy players as it enables stakeholders to make critical decisions. In addition, its importance is further increased with growing uncertainties in the generation…
The scheduling and operation of power system becomes prominently complex and uncertain, especially with the penetration of distributed power. Load forecasting matters to the effective operation of power system. This paper proposes a novel…
In current Medium Voltage DC (MVDC) Shipboard Power Systems (SPSs), multiple sources exist to supply power to a common dc bus. Conventionally, the power management of such systems is performed by controlling Power Generation Modules (PGMs)…
Short-term forecasts of energy consumption are invaluable for the operation of energy systems, including low voltage electricity networks. However, network loads are challenging to predict when highly desegregated to small numbers of…
The energy sector is experiencing rapid transformation due to increasing renewable energy integration, decentralisation of power systems, and a heightened focus on efficiency and sustainability. With energy demand becoming increasingly…
The paper introduces a real-time monitoring and forecasting system for ecological phenomena. The process yields a collection of ecological parameters viewed as distributed time series, which are measured by means of wireless network of…
Power system robustness against high impact low probability events is becoming a major concern. To depict distinct phases of a system response during these disturbances, an irregular polygon model is derived from the conventional trapezoid…
With the increasing frequency of natural disasters, operators must prioritize improvements in the existing electric power grid infrastructure to enhance the resilience of the grid. Resilience to extreme weather events necessitates lowering…
Since the depletion of fossil fuels, the world has started to rely heavily on renewable sources of energy. With every passing year, our dependency on the renewable sources of energy is increasing exponentially. As a result, complex and…
The increasing importance of renewable energy, especially solar and wind power, has led to new forces in the formation of electricity prices. Hence, this paper introduces an econometric model for the hourly time series of electricity prices…
Probabilistic load forecasting (PLF) is a key component in the extended tool-chain required for efficient management of smart energy grids. Neural networks are widely considered to achieve improved prediction performances, supporting highly…
With the expansion of renewables in the electricity mix, power grid variability will increase, hence a need to robustify the system to guarantee its security. Therefore, Transport System Operators (TSOs) must conduct analyses to simulate…
We apply tipping point analysis to measurements of electronic components commonly used in applications in the automotive or aviation industries and demonstrate early warning signals based on scaling properties of resistance time series. The…
Given increasing risk from climate-induced natural hazards, there is growing interest in the development of methods that can quantitatively measure resilience in power systems. This work quantifies resilience in electric power transmission…
Power demand forecasting is a critical task for achieving efficiency and reliability in power grid operation. Accurate forecasting allows grid operators to better maintain the balance of supply and demand as well as to optimize operational…
Recent advances in Machine Learning(ML) have led to its broad adoption in a series of power system applications, ranging from meter data analytics, renewable/load/price forecasting to grid security assessment. Although these data-driven…
Accurate electrical load forecasting is of great importance for the efficient operation and control of modern power systems. In this work, a hybrid long short-term memory (LSTM)-based model with online correction is developed for day-ahead…