In this paper, we investigate mathematical models of meteorological forecasting based on the work of neural networks, which allow us to calculate presumptive meteorological parameters of the desired location on the basis of previous meteorological da...
In the context of climate change and energy transition, the growing frequency of extreme weather events threatens the safety and stability of power systems. Given the limitations of existing research on load characteristic analysis and load forecasti...
Solar irradiance prediction is significant for maximizing energy-saving effects in the predictive control of buildings. Several models for solar irradiance prediction have been developed; however, they require the collection of weather data over a lo...
Various algorithms predominantly use data-driven methods for forecasting building electricity consumption. Among them, algorithms that use deep learning methods and, long and short-term memory (LSTM) have shown strong prediction accuracy in numerous...
The time resolution and prediction accuracy of the power generated by building-integrated photovoltaics are important for managing electricity demand and formulating a strategy to trade power with the grid. This study presents a novel approach to imp...
The gradually increased penetration of photovoltaic (PV) power into electric power systems brings an urgent requirement for accurate and stable PV power forecasting methods. The existing forecasting methods are built to explore the function between w...
A primary energy consumption and CO2 emission source stems from buildings and infrastructures due to rapid urbanisation and social development. An accurate method to forecast energy consumption in a building is thus critically needed to enable succes...
Photovoltaic systems have become an important source of renewable energy generation. Because solar power generation is intrinsically highly dependent on weather fluctuations, predicting power generation using weather information has several economic...
Owing to the need for continuous improvement in building energy performance standards (BEPSs), facilities must adhere to benchmark performances in their quest to achieve net-zero performance. This research explores machine learning models that levera...
The Internet of Things (IoT) plays a critical role in remotely monitoring a wide variety of different application sectors, including agriculture, building, and energy. The wind turbine energy generator (WTEG) is a real-world application that can take...
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...
Due to the development of photovoltaic (PV) technology and the support from governments across the world, the conversion efficiency of solar energy has been improved. However, the PV power output is influenced by environment factors, resulting in fea...
Sustainable energy systems rely on energy yield from renewable resources such as solar radiation and wind, which are typically not on-demand and need to be stored or immediately consumed. Solar irradiance is a highly stochastic phenomenon depending o...
10 December 2021
A strong heat load in buildings and cities during the summer is not a new phenomenon. However, prolonged heat waves and increasing urbanization are intensifying the heat island effect in our cities; hence, the heat exposure in residential buildings....
An optimized heat pump control for building heating was developed for minimizing CO
Optimizing building equipment control is crucial for enhancing energy efficiency. This article presents a predictive control applied to a commercial building heated by a hydronic system, comparing its performance to a traditional heating curve-based...
Nowadays, many buildings are equipped with various energy sources. The challenge is how to efficiently utilize their energy production. This includes decreasing the share and costs of external energy—usually electrical energy delivered from the...
Currently, artificial intelligence (AI) is emerging as a dominant force in various technologies, owing to its unparalleled efficiency. Among the plethora of AI techniques available, neural networks (NNs) have garnered significant attention due to the...
Flood disasters are a natural occurrence around the world, resulting in numerous casualties. It is vital to develop an accurate flood forecasting and prediction model in order to curb damages and limit the number of victims. Water resource allocation...
The present paper is focused on short-term prediction of air-conditioning (AC) load of residential buildings using the data obtained from a conventional smart meter. The AC load, at each time step, is separated from smart meter’s aggregate consumptio...
In this study, a novel general multi-step ahead strategy is developed for forecasting time series of air pollutants. The values of the predictors at future moments are gathered from official weather forecast sites as independent ex-ante data. They ar...
With the increase of natural gas consumption year by year, the shortage of urban natural gas reserves leads to the increasingly serious gas supply–demand imbalance. It is particularly important to establish a correct and reasonable gas daily lo...
The forecasts of electricity and heating demands are key inputs for the efficient design and operation of energy systems serving urban districts, buildings, and households. Their accuracy may have a considerable effect on the selection of the optimiz...
Space heating consumption prediction is critical for energy management and efficiency, directly impacting sustainability and efforts to reduce greenhouse gas emissions. Accurate models enable better demand forecasting, promote the use of green energy...
The building sector constitutes 40% of global electric energy consumption, making it vital to address for achieving the global net-zero emissions goal by 2050. This study focuses on enhancing electric load forecasting systems’ performance and i...
Electricity consumption forecasting is a vital task for smart grid building regarding the supply and demand of electric power. Many pieces of research focused on the factors of weather, holidays, and temperatures for electricity forecasting that requ...
The purpose of this work is to determine internal and external factors affecting the cooling energy demand of a building. During the research, the impact of weather conditions and the level of hotel occupancy on cooling energy, which is necessary to...
Meeting the required amount of energy between supply and demand is indispensable for energy manufacturers. Accordingly, electric industries have paid attention to short-term energy forecasting to assist their management system. This paper firstly com...
The monitoring of power consumption and the forecasting of load profiles for residential appliances are essential aspects of the control of energy savings/exchanges at multiple hierarchical levels: house, house cluster, neighborhood, and city. Extern...
Given the growing number of residential photovoltaic installations and the challenges of self-consumption, accurate short-term PV production forecasting can become a key tool in supporting energy management. This issue is particularly significant in...
Although the main concern of consumers is to reduce the cost of energy consumption, zero-energy buildings are the main concern of governments, which reduce the carbon footprint of the residential sector. Therefore, homeowners are motivated to install...
The proliferation of pollutants affects the world’s population, mainly those who live in large cities. Neurological and cardiovascular dysfunctions have a correlation with air particulate matter concentration, among other chronic diseases. Ther...
The aim of this research was to develop a simulation model of the works carried out by helicopters, which are used in the construction of buildings under harsh natural conditions. This work identified that even technologies that we do not normally en...
Buildings are responsible for almost half of the world’s energy consumption, and approximately 40% of total building energy is consumed by the heating ventilation and air conditioning (HVAC) system. The inability of traditional HVAC controllers to re...
A method based on Long Short-Term Memory (LSTM) networks is proposed to forecast hourly energy consumption. Using an office building in Shanghai as a case study, hourly data on occupancy, weather, and energy consumption were collected. Daily energy c...
As solar energy generation has become more and more important for the economies of numerous countries in the last couple of decades, it is highly important to build accurate models for forecasting the amount of green energy that will be produced. Num...