Search

Our goal is to examine the efficiency of different intraday electricity markets and if any of their price prediction models are more accurate than others. This paper includes a comprehensive review of Germany, France, and Norway's (NOR1) day-ahead and intraday electricity market prices. These markets represent different energy mixes which would allow us to analyze the impact of the energy mix on the efficiencies of these markets. To draw conclusions about extreme market conditions, (i) we reviewed the market data linked to COVID-19. We expected higher volatility in the lockdowns than before and therefore decrease in the efficiency of the prediction models. With our analysis, (ii) we want to draw conclusions as to whether a mix based mainly on renewable energies such as that in Norway implies lower volatilities even in times of crisis. This would answer (iii) whether a market with an energy mix like Norway is more efficient in highly volatile phases. For the analysis, we use data visualization and statistical models as well as sample and out-of-sample data. Our finding was that while the different price and volatility levels occurred, the direction of the market was similar. We could find evidence that our expectations (i–iii) were met. [ABSTRACT FROM AUTHOR]

The e-commerce industry has been developing extremely dynamically for many years. This development was intensified during the COVID-19 pandemic. According to the research conducted by the authors of this paper, in Poland, during the pandemic, the number of delivered parcels increased 20–100%, depending on the courier company. The research of the authors of this article focused on the energy efficiency of the last mile, which is very important for the efficiency of the entire delivery process to customers. As the authors calculated, the last mile can consume over 70% of energy of the whole distribution channel. The article presents the results of research concerning the energy efficiency of deliveries performed by couriers and express companies in Poland. Two models of distribution used Poland have been compared—direct deliveries to final customers, and deliveries to parcel lockers. The research methods are interviews with the managers and couriers, analysis of the literature, and the simulation method. According to the results of the simulations performed by the authors, distribution with the use of parcels lockers can help reduce the consumption of fuel even by 74–87% per parcel or 36% per m3. Apart from this, the authors calculated the impact of scale of operations on the energy efficiency of the transport processes on the last mile, which is an indirect effect of the growth of the e-commerce market, caused by the pandemic. Based on the results of the original research of the authors, it can be assessed that the growth of the number of the delivered parcels during the pandemic resulted in the consumption of fuel per one parcel being reduced in some cases by over 36%. The novelty of the authors' research is that the conducted simulations regarded not only the efficiency of the processes, but also the energy consumption in delivering parcels at the last mile and during the pandemic. [ABSTRACT FROM AUTHOR]

This paper proposes methodological approaches to assessing the impact of renewable energy and energy efficiency development on emerging economies' energy security. It is suggested to supplement the current methodology for assessing energy security with the decoupling index of the renewable energy financial burden on the state budget, the energy efficiency decoupling index, the households' energy poverty indicator, the index of capacity development for balancing electricity generation volumes, and the energy fluctuations indicator. These indices provide a comprehensive assessment of energy security under the latest challenges. Thus, the COVID-19 pandemic in the Ukrainian energy sector led to the "green and coal paradox", when the government decided to keep green electricity generation but limit nuclear generation. It required increased flexible capacities (thermal generation) and led to a rise in electricity prices and environmental pollution. Forecasting energy fluctuations with Butterworth filters allows minimizing the risks of maximum peak loads on the grid and timely prevention of emergencies. The energy fluctuations within the 20% range guarantee energy security and optimal energy companies' operation. It is proposed to smooth out energy consumption fluctuations through green energy development, smart grids formation, energy efficiency improvements, and energy capacities balancing to ensure energy and economic sustainability. [ABSTRACT FROM AUTHOR]

The built environment is the global sector with the greatest energy use and greenhouse gas emissions. As a result, building energy savings can make a major contribution to tackling the current energy and climate change crises. Fluid dynamics models have long supported the understanding and optimization of building energy systems and have been responsible for many important technological breakthroughs. As Covid-19 is continuing to spread around the world, fluid dynamics models are proving to be more essential than ever for exploring airborne transmission of the coronavirus indoors in order to develop energy-efficient and healthy ventilation actions against Covid-19 risks. The purpose of this paper is to review the most important and influential fluid dynamics models that have contributed to improving building energy efficiency. A detailed, yet understandable description of each model's background, physical setup, and equations is provided. The main ingredients, theoretical interpretations, assumptions, application ranges, and robustness of the models are discussed. Models are reviewed with comprehensive, although not exhaustive, publications in the literature. The review concludes by outlining open questions and future perspectives of simulation models in building energy research. [ABSTRACT FROM AUTHOR]

Reducing energy waste is one of the primary concerns facing Remote Industrial Plants (RIP) and, in particular, the accommodations and operational plants located in remote areas. With the COVID-19 pandemic continuing to attack the health of workforce, managing the balance between energy efficiency and Occupation Health and Safety (OHS) in the workplace becomes another great challenge for the RIP. Maintaining this balance is difficult mainly because a full awareness of the OHS will generally consume more energy while reducing the energy cost may lead to a less effective OHS, and the existing literature has not seen a system that is designed for the RIPs to conserve energy usage and improve workforce OHS simultaneously. To bridge this gap, in this paper, we propose an AI Empowered Cyber Physical Ecosystem (AECPE) solution for the RIPs, which integrates Cyber-Physical Systems (CPS), artificial intelligence, and mobile networks. The preliminary results of lab experiments and field tests proved that the AECPE was able to help industries reduce the corporate annual energy cost that is worth millions of dollars, optimise the environmental conditions, and improve OHS for all workers and stakeholders. The implementation of the AECPE can result in efficient energy usage, reduced wastage and emissions, environment-friendly operations, and improved social reputation of the industries. [ABSTRACT FROM AUTHOR]

Worldwide increasing awareness of energy sustainability issues has been the main driver in developing the concepts of (Nearly) Zero Energy Buildings, where the reduced energy consumptions are (nearly) fully covered by power locally generated by renewable sources. At the same time, recent advances in Internet of Things technologies are among the main enablers of Smart Homes and Buildings. The transition of conventional buildings into active environments that process, elaborate and react to online measured environmental quantities is being accelerated by the aspects related to COVID-19, most notably in terms of air exchange and the monitoring of the density of occupants. In this paper, we address the problem of maximizing the energy efficiency and comfort perceived by occupants, defined in terms of thermal comfort, visual comfort and air quality. The case study of the University of Pisa is considered as a practical example to show preliminary results of the aggregation of environmental data. [ABSTRACT FROM AUTHOR]