Deregulated electricity markets encourage firms to compete, making the development of renewable energy easier. An ordinary parameter of electricity markets is the electricity market price, mainly the day-ahead electricity market price. This paper des...
Accurate forecasting of demand load is momentous for the efficient economic dispatch of generating units with enormous economic and reliability implications. However, with the high integration levels of grid-tie generations, the precariousness in dem...
The global rainfall pattern has changed because of climate change, leading to numerous natural hazards, such as drought. Because drought events have led to many disasters globally, it is necessary to create an early warning system. Drought forecastin...
South Africa’s transition to a renewable-powered grid faces critical challenges due to the inherent variability of wind and solar generation as well as the need for economically viable and reliable dispatch strategies. This study proposes a sce...
Accurate metal price forecasting is the precondition for optimal and sustainable mine production planning. This paper combined two methods for time series analysis. The developed model represents the combination of the Grey System Theory and a Stocha...
This paper considers a flexible class of time series models generated by Gegenbauer polynomials incorporating the long memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the corres...
One of the problems of forecasting events in news feeds, is the development of models which allow for work with semi structured information space of text documents. This article describes a model for forecasting events in news feeds, which is based o...
The emission of greenhouse gases is a major contributor to global warming. Carbon emissions from the electricity industry account for over 40% of the total carbon emissions. Researchers in the field of electric power are making efforts to mitigate th...
In this empirical study, multifactor stochastic volatility models for the financial Nordic/Baltic power markets are developed, implemented, and analyzed. Stochastic volatility projections are the primary aim, followed by volatility forecasts and mark...
Relatively large deformations of the steel arch support in underground coal mines in the Republic of Serbia present one of the main problems for achieving the planned production of coal. Monitoring of the critical sections of the steel arch support i...
The output of photovoltaic (PV) power generation systems remains uncertain primarily due to the uncontrollable nature of weather conditions, which may introduce disturbances to the power grid upon integrating PV systems. Accurate short-term PV power...
This paper builds and implements multifactor stochastic volatility models for the international oil/energy markets (Brent oil and WTI oil) for the period 2011–2021. The main objective is to make step ahead volatility predictions for the front month c...
In this paper, an emission- and reliability-aware stochastic optimization model is proposed for the economic planning of electric bus parking lots (EBPLs) with photovoltaic (PV) and wind-turbine (WT) resources in an 85-bus radial distribution network...
Stochastic models can be used for predicting the availability of residual woody forest biomass, considering the variability and uncertainty associated with climatic, operational, and economic factors. These models, such as ARIMA, GARCH, state transit...
The National Oceanic and Atmospheric Administration’s (NOAA) cloud-permitting high-resolution operational Hurricane Weather and Research Forecasting (HWRF) model includes the sophisticated hybrid grid-point statistical interpolation (GSI) and E...
We present a probabilistic framework tailored for solar energy applications referred to as the Weather Research and Forecasting-Solar ensemble prediction system (WRF-Solar EPS). WRF-Solar EPS has been developed by introducing stochastic perturbations...
Whether due to natural causes or human carelessness, forest fires have the power to cause devastating damage, alter the habitat of animals and endemic species, generate insecurity in the population, and even affect human settlements with significant...
Gold is often used by investors as a hedge against inflation or adverse economic times. Consequently, it is important for investors to have accurate forecasts of gold prices. This paper uses several machine learning tree-based classifiers (bagging, s...
This paper focuses on electricity demand forecasting and its uncertainty representation using a hybrid machine learning (ML) model in the eastern control area of southeastern Mexico. In this case, different sources of uncertainty are integrated by ap...
Population projections serve various actors at subnational, national, and international levels as a quantitative basis for political and economic decision-making. Usually, the users are no experts in statistics or forecasting and therefore lack the m...
The inherent uncertainty of inflow forecasts hinders the reservoir real-time optimal operation. This paper proposes a risk analysis model for reservoir real-time optimal operation using the scenario tree-based stochastic optimization method. We quant...
In recent times, there has been a notable global phenomenon characterized by a double predicament arising from the concomitant rise in worldwide life expectancy and a significant decrease in birth rates. The emergence of this phenomenon has posed a s...
In this study, three model perturbation schemes, the stochastically perturbed parameter scheme (SPP), stochastically perturbed physics tendency (SPPT), and multi-physics process parameterization (MP), were used to represent the model errors in the re...
The interferometric synthetic aperture radar (InSAR) technique is widely utilized to measure ground-surface displacement. One of the main limitations of the measurements is the atmospheric phase delay effects. For satellites with shorter wavelengths,...
This paper aims to present the significance of predicting stochastic loads to improve the performance of a low voltage (LV) network with an energy storage system (ESS) by employing several optimal energy controllers. Considering the highly stochastic...
This paper introduces a complement statistical test for distinguishing between the predictive accuracy of two sets of forecasts. We propose a non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS) test, referred to as the KS P...
In the past two decades increasing computational power resulted in the development of more advanced claims reserving techniques, allowing the stochastic branch to overcome the deterministic methods, resulting in forecasts of enhanced quality. Hence,...
This study proposes a novel hybrid forecasting approach designed explicitly for long-horizon financial time series. It incorporates LMD (Local Mean Decomposition), SD (Signal Decomposition), and sophisticated machine learning methods. The framework f...
Demographic change is leading to the aging of German society. As long as the baby boom cohorts are still of working age, the working population will also age—and decline as soon as this baby boom generation gradually reaches retirement age. At...
When there is uncertainty in the value of parameters of the input random components of a stochastic simulation model, two-level nested simulation algorithms are used to estimate the expectation of performance variables of interest. In the outer level...
We forecast short time series iteratively using a model based on stochastic differential equations. The recorded process is assumed to be consistent with an α-stable Lévy motion. The generalized moments method provides the values of the...
The evaporation duct could significantly affect the work status of maritime microwave communication systems in the South China Sea. Therefore, the exact forecasting of the evaporation duct is vital for the normal operation of the systems. This study...
Financial time series in volatile markets often exhibit non-stationary behavior and signatures of stochastic chaos, challenging traditional forecasting methods based on stationarity assumptions. In this paper, we introduce a novel multi-expert foreca...
Generalized age–period–cohort (GAPC) models are mortality models that incorporate stochasticity, which can be represented in a generalized linear or non-linear context. By fitting the data to either mortality model, one can make forecasts...
Beyond their deterministic predictability limits of ≈10 days and 6 months, the atmosphere and ocean become effectively stochastic. This has led to the development of stochastic models specifically for this macroweather regime. A particularly pr...
In order to improve the accuracy of forecasting crude oil prices, a new crude oil price forecasting method is introduced in the paper that is a combination of the FNN model and the stochastic time effective function—namely, the WT-FNN model. Th...
Rational Water Resources Management requires effective collaboration between decision-makers involved in the operational management of water resources and scientists, who can allow them to operate in an informed manner through forecasting and decisio...
This paper proposes a semiparametric realized stochastic volatility model by integrating the parametric stochastic volatility model utilizing realized volatility information and the Bayesian nonparametric framework. The flexible framework offered by...
This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals...
The distribution laws of various natural and anthropogenic processes in the world around us are stochastic in nature. The development of mathematics and, in particular, of stochastic modeling allows us to study regularities in such processes. In prac...
Increasing retirement ages in an automatic or scheduled way with increasing life expectancy at retirement is a popular pension policy response to continuous longevity improvements. The question addressed here is: to what extent is simply adopting thi...
Dock door congestion is an essential and persistent concern within the realm of outbound warehouse logistics. The inability to accommodate outbound vehicles at the loading docks, especially during peak hours, disrupts internal warehouse operations, l...
A demand side management technique is deployed along with battery energy-storage systems (BESS) to lower the electricity cost by mitigating the peak load of a building. Most of the existing methods rely on manual operation of the BESS, or even an ela...
Runoff forecasting is of great importance for flood mitigation and power generation plan preparation. To explore the better application of time-frequency decomposition technology in runoff forecasting and improve the prediction accuracy, this researc...
This paper focuses on developing a predictive model for wind energy production in Italy, aligning with the ambitious goals of the European Green Deal. In particular, by utilising real data from the SUD (South) Italian electricity zone over seven year...
This study examines the potential role that an Electric Vehicle Battery (EVB) can play in Home Energy Management System (HEMS) based on a future development on the performance and costs of batteries. The value of EVB in an HEMS with different home co...
The fundamental modeling of energy systems through individual unit commitment decisions is crucial for energy system planning. However, current large-scale models are not capable of including uncertainties or even risk-averse behavior arising from fo...
Short-Term Load Forecasting (STLF) is essential for the efficient management of power systems, as it improves forecasting accuracy while optimizing power scheduling efficiency. Despite significant recent advancements in STLF models, forecasting accur...
Due to the rapid development of computers, researchers have made efforts since the 1990s to develop typhoon forecasting models and stochastic typhoon simulation models to assess typhoon disasters and risks. Typhoon forecasting models are primarily us...
Since the beginning of the 2000s, most of the West-African countries, particularly Benin, have experienced an increased frequency of extreme flood events. In this study, we focus on the case of the Ouémé river basin in Benin. To investi...
of 13