Search Results (39)

Data mining is vital for smart grids because it enhances overall grid efficiency, enabling the analysis of large volumes of data, the optimization of energy distribution, the identification of patterns, and demand forecasting. Several performance metrics, such as the MAPE and RMSE, have been created to assess these forecasts. This paper presents new performance metrics called Evaluation Metrics for Performance Quantification (EMPQ), designed to evaluate forecasting models in a more comprehensive and detailed manner. These metrics fill the gap left by established metrics by assessing the likelihood of over- and under-forecasting. The proposed metrics quantify forecast bias through maximum and minimum deviation percentages, assessing the proximity of predicted values to actual consumption and differentiating between over- and under-forecasts. The effectiveness of these metrics is demonstrated through a comparative analysis of short-term load forecasting for residential customers in Dubai. This study was based on high-resolution smart meter data, weather data, and voluntary survey data of household characteristics, which permitted the subdivision of the customers into several groups. The new metrics were demonstrated on the Prophet, Random Forest (RF), and Long Short-term Memory (LSTM) models. EMPQ help to determine that the LSTM model exhibited a superior performance with a maximum deviation of approximately 10% for day-ahead and 20% for week-ahead forecasts in the “AC-included” category, outperforming the Prophet model, which had deviation rates of approximately 44% and 42%, respectively. EMPQ also help to determine that the RF excelled over LSTM for the ‘bedroom-number’ subcategory. The findings highlight the value of the proposed metrics in assessing model performance across diverse subcategories. This study demonstrates the value of tailored forecasting models for accurate load prediction and underscores the importance of enhanced performance metrics in informing model selection and supporting energy management strategies. Full article

The rapid proliferation of electric vehicles (EVs) presents both opportunities and challenges for the electrical grid. While EVs offer a promising avenue for reducing greenhouse gas emissions and dependence on fossil fuels, their uncoordinated charging behavior can strain grid infrastructure, thus creating new challenges for grid operators and EV owners equally. The uncoordinated nature of electric vehicle charging may lead to the emergence of new peak loads. Grid operators typically plan for peak demand periods and deploy resources accordingly to ensure grid stability. Uncoordinated EV charging can introduce unpredictability and variability into peak load patterns, making it more challenging for operators to manage peak loads effectively. This paper examines the implications of uncoordinated EV charging on the electric grid to address this challenge and proposes a novel dynamic optimization algorithm tailored to manage EV charging schedules efficiently, mitigating grid power peaks while ensuring user satisfaction and vehicle charging requirements. The proposed “Proof of Need” (PoN) charging algorithm aims to schedule the charging of EVs based on collected data such as the state of charge (SoC) of the EV’s battery, the charger power, the number of connected vehicles per household, the end-user’s preferences, and the local distribution substation’s capacity. The PoN algorithm calculates a priority index for each EV and coordinates the charging of all connected EVs at all times in a way that does not exceed the maximum allocated power capacity. The algorithm was tested under different scenarios, and the results offer a comparison of the charging power demand between an uncoordinated EV charging baseline scenario and the proposed coordinated charging model, proving the efficiency of our proposed algorithm, thus reducing the charging demand by 40.8% with no impact on the overall total charging time. Full article

The limited number of charging stations for electric vehicles (EVs) necessitates periodic charging, resulting in extended queues at charging stations as drivers await their availability. This study contributes to the existing body of literature by providing estimates of consumer preferences for allowable waiting times at charging stations, as well as furthering the understanding of the roles of the explanatory variables influencing these preferences. The study also compares the average and maximum waiting times experienced by EV drivers, with the acceptable waiting time. Responses from the stated preference survey in Japan in 2021 were analyzed using a generalized ordered logit model. The results show that (a) the sex, age, household income, employment status, and vehicle usage frequency significantly influenced the preferences for allowable waiting times, and (b) the allowable waiting time preferences were significantly associated with the charging locations. Our estimation model indicated a positive association of convenience stores, large commercial facilities, and highway locations with short and medium allowable waiting times. The results provide useful insights into the policy implications of the charging infrastructure. Full article

The conventional point-estimate human health risk assessment (HHRA) primarily uses average concentrations of a limited number of samples due to the high monitoring costs of heavy metals in groundwater. The results can be erroneous when concentrations significantly deviate from the average across the collected samples in an investigation region. The present research developed a hierarchical fuzzy-based HHRA (F-HHRA) framework to handle variations in limited data sets and subjectively established a broader range of risks for various exposure groups. Groundwater samples from 80 to 120 m deep in shallow wells were collected from agricultural farms along Wadi Rumah in the Qassim Region of Saudi Arabia. Laboratory testing found total dissolved solids much higher than the promulgated drinking water quality standards. As the aftertaste issue eliminated the raw water potability, the study considered dermal exposure for HHRA. The collected samples were tested for thirteen potential heavy metals (HMs), including barium (Ba), boron (B), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), lead (Pb), lithium (Li), manganese (Mn), silver (Ag), strontium (Sr), thallium (TI), and zinc (Zn). Cu, Fe, Pb, Ag, and TI were lower than the detectable limit of the inductively coupled plasma mass spectrometry device. Concentrations of the remaining HMs in wastewater outfalls that were much less than the groundwater eradicated the impact of anthropogenic activities and affirmed natural contamination. Apart from 10% of the samples for Mn and 90% of the samples for Sr, all the other HMs remained within the desired maximum allowable concentrations. Point-estimate and fuzzy-based approaches yielded ‘low’ dermal non-cancer risk and cancer risk for all groups other than adults, where dermal cancer risk of Cr remained in the ‘acceptable’ (1 × 10⁻⁶ and 1 × 10⁻⁵) risk zone. Although dermal risk does not require controls, scenario analysis established the rationality of F-HHRA for more contaminated samples. The proposed hierarchical F-HHRA framework will facilitate the decision-makers in concerned agencies to plan risk mitigation strategies (household level and decentralized systems) for shallow well consumers in Saudi Arabia and other arid regions. Full article

In a time of environmental degradation and increasing demand for safe food production, traditional fish farming is gaining global attention. Utilizing indigenous agricultural methods founded on traditional knowledge contributes to sustainability by safeguarding the ecosystem and preserving biodiversity. However, it is still less studied whether traditional farming systems based on indigenous knowledge currently in place are improving the socioeconomic conditions of farmers. Hence, this study was conducted with the following objectives: (i) to reveal the present status of traditional fish farming systems, (ii) to define the socioeconomic profile of the farmers, (iii) to identify the problems associated with traditional fish farming, and (iv) to show the inter-relationship between fish farming and socioeconomic development. For achieving these objectives, data were collected from 100 small-scale fish farmers from a rural coastal area of Bangladesh through a well-structured questionnaire, focus group discussion, and cross-check interviews. Our findings showed that most of the homestead ponds were small-sized (44%) and shallow (61%) where a polyculture system was prevalent (91%). The majority of the ponds (77%) were found to be perennial, 60% of which had single ownership. Socioeconomic data revealed that the highest number of farmers (42%) earned 1000.00 to 1500.00 USD annually, and 62% of the respondents took fish farming as their secondary occupation. Among the farmers, 62% had primary education, whereas 7% had no education, and only 26% of the farmers had official training in fish farming, indicating that culture management was mainly based on indigenous knowledge. A total of 55% of the farmers had 5 to 10 family members, and 80% of them lived in joint families. Furthermore, 40% of the farmers owned tin shed houses, whereas the maximum (60%) utilized katcha toilets. However, almost half of the farmers (57%) utilized their own funds for fish farming, and the majority (90%) had access to their own tube well. The study found that the biggest obstacles to fish farming were pressure from large families, a lack of education and training, a lack of quality seed and feed, outbreaks of fish diseases, an inadequate supply of water during the dry season, and a lack of adequate funding. However, Pearson correlation showed that there was a significant positive association between age and experience (r = 0.908, p < 0.01) and age and income (r = 0.326, p < 0.01). Multiple regression analyses also demonstrated that age and experience in fish farming played a significant role in increased annual income. In conclusion, 94% of the respondents claimed that fish farming had improved their socioeconomic situation. Homestead pond fish farming through indigenous knowledge increased household fish consumption with a source of protein and micronutrients, improved dietary diversity, and generated extra household income, which inferred their better sustenance. Full article

The aim of our paper is to construct a multidimensional financial inclusion (FI) index to measure the level of FI in 91 countries across different income groups. In order to address our research problem, we use the principal component analysis method. This approach addresses the criticism of the arbitrary selection of weights and reflects the degree of financial inclusion in depth. The data are drawn from the International Monetary Fund (IMF) Financial Access Survey (FAS), the World Development Indicators (World Bank) and the Global Findex Database during the period of 2004–2020. This paper is the first to consider so many indicators of financial inclusion (13 indicators), belonging to three different dimensions of FI, in order to take into account the maximum number of aspects related to this concept. In addition, unlike previous work, this paper considers both developing and developed countries, which makes it possible to identify differences between them. The proposed index has some advantages. First, it is robust, comparable across countries and has good predictive power in tracking household microeconomic indicators (accounts and savings). It is also well correlated with macroeconomic variables such as literacy rate, poverty, GINI index, real interest rate and employers. Second, our results clearly show that, as a country’s income level grows higher, its level of financial inclusion also grows higher. Full article

This article focuses on determining the optimum structure for a hybrid generation and storage system designed to power a single-family housing estate, taking into account the different number of electric vehicles in use and an assumed level of self-consumption of the generated energy. In terms of generation, two generation sections—wind and solar—and a lithium-ion container storage system will be taken into account. With regards to energy consumption, household load curves, determined on the basis of the tariff for residential consumers and modified by a random disturbance, will be taken into account, as well as the processes for charging electric cars with AC chargers, with power outputs ranging between 3.6 and 22 kW. Analyses were carried out for three locations in Poland—the Baltic Sea coast (good wind conditions), the Lublin Uplands (the best insolation in Poland) and the Carpathian foothills (poor wind and insolation conditions). The mathematical and numerical model of the system and the MOPSO (multiobjective particle swarm optimisation) algorithm were implemented in the Matlab environment. The results include Pareto fronts (three optimisation criteria: minimisation of energy storage capacity, minimisation of energy exchanged with the power grid and maximisation of the self-consumption rate) for the indicated locations and three electromobility development scenarios with determined NPVs (net present values) for a 20-year lifetime. The detailed results relate to the inclusion of an additional expert criterion in the form of a coupled payback period of no more than 10 years, a maximum NPV in the last year of operation and a self-consumption rate of at least 80%. The economic calculations take into account the decrease in PV installation capacity as a function of the year of operation, as well as changes in electricity and petrol prices and variations in energy prices at purchase and sale. Full article

The need to reduce pollution and the shortage of fossil fuels has led to the increased development of hybrid and full electric vehicles. There is also increased development and an increased use of renewable energy resources such as photovoltaic, wind, tidal, etc. These two trends pose serious challenges to the existing grids: a lack of supply power when the demand is high, deficient management of excess power, an increased number off grid faults, grid instabilities and others. One way to increase the penetration of electric vehicles (EV) into the market and to keep the existing grid infrastructure is to combine renewable energy resources with the grid and local battery packs to make EV charging stations. This paper focuses on developing such an EV charging station. The main advantages of the proposed EV charger include the fact that it uses only off-the-shelf inverters, and it is intended to be used in households where the maximum installed power is 3.6 kW to enable fast-charging operation modes or to reduce the costs of energy while charging the EV battery; it can reduce the energy demand from the grid during peak power consumption; it has the potential to lower electrical energy costs; it offers the possibility of vehicle-to-home (V2H) implementation; it is modular (if other technologies become available and more affordable, the consumers can easily update the system, adding more power or adding other types of renewable resources). Full article

Climate change requires urgent action; however, it can be challenging to identify individual-level behaviours that should be prioritised for maximum impact. The study aimed to prioritise climate change mitigation behaviours according to their impacts on climate change and public health, and to identify associated barriers and facilitators—exploring the impact of observed behaviour shifts associated with COVID-19 in the UK. A three-round Delphi study and expert workshop were conducted: An expert panel rated mitigation behaviours impacted by COVID-19 in relation to their importance regarding health impacts and climate change mitigation using a five-point Likert scale. Consensus on the importance of target behaviours was determined by interquartile ranges. In total, seven target behaviours were prioritised: installing double/triple glazing; installing cavity wall insulation; installing solid wall insulation; moving away from meat/emission heavy diets; reducing the number of cars per household; walking shorter journeys; and reducing day/weekend leisure car journeys. Barriers related to the costs associated with performing behaviours and a lack of complementary policy-regulated subsidies. The target behaviours are consistent with recommendations from previous research. To ensure public uptake, interventions should address behavioural facilitators and barriers, dovetail climate change mitigation with health co-benefits and account for the long-term impacts of COVID-19 on these behaviours. Full article

Renewable energy sources are rapidly increasing in demand and importance as governments and countries around the globe begin to understand their vital role in reducing climate change. This project aimed to design and create an optimised micro-hydro turbine system for downpipes to harness the currently untapped potential energy from rainwater. Experimental methods were used to determine the magnitude of voltage output available at different rainfall intensities by simulating such flow rates on a hydraulic bench. The viability of this energy to power household appliances was then evaluated, and methods of increasing the voltage output were assessed, such as layering the turbines in a single downpipe or placing multiple downpipes around the building. The study determined that, during average rainfall in the UK, a single turbine could produce a maximum of 7.21 V of DC voltage, or 50.49 V during heavy rainfall—enough energy to power a mobile device charger or a vacuum cleaner, respectively. Therefore, this proves a high potential in rainwater energy harvesting as a renewable energy source. It was also concluded that a positive correlation occurred for both the number of turbines in a downpipe and the number of pipes around the building with the voltage output of the whole system. Full article

Providing electricity for isolated areas or emergencies (snowstorms, earthquakes, hurricanes, etc.) is an important challenge. In this study, a prototype of a self-powered fan based on a thermoelectric system was built to enhance the heat dissipation of the thermoelectric generator (TEG) systems using household stoves as heat sources. To improve output performance of the system, a heat collector consisting of a heat-conducting flat plate and a heat sink with fan cooling was designed to integrate several thermoelectric modules (TEM). The effects of the fan operating conditions (airflow velocity), number of thermoelectric modules, electrical connection mode under different heat flux among the performance of the TEG system are studied. The data obtained showed a higher heat flux and lower flow velocity are required to realize self-sustained cooling of the system. The maximum electric power is more sensitive to the heat flux than the fan operation conditions. It is also observed that more modules provide a higher power output but lower efficiency. The maximum power of four modules in series is larger than that in parallel, and the difference between them increases with increasing heat flux of the heat collector. In the case of self-sufficiency: the maximum output power and maximum net power with four thermoelectric modules are 10.92 W and 5.26 W, respectively, at a heat flux of 30,000 W/m². Additionally, the maximum conversion efficiency of 1.8% is achieved for two modules at a heat flux of 14,000 W/m², providing an effective strategy for the installation of TEMs and cooling fans in TEG. Full article

A major advantage of online organic produce shopping is the fact that it saves energy and reduces emissions otherwise generated by customers during their time spent on the road and while shopping. Organic products in general positively impact sustainability, the environment, and the regions of their origin along with the social changes in these regions and further rural development. Moreover, these products positively impact the perceived health benefits and quality of food labeled as organic. The Czech Republic has currently seen a rise in organic food purchasing and supply trends. This study maps the factors possibly influencing consumers’ decision to go shopping for organic food online. Observed factors include the following demographic characteristics of consumers (respondents): gender, age, education, household income, number of children in the household and number of household members. A total of 757 respondents from the Czech Republic from September 2020 to December 2020 took part in the research. Logistic regression, used for data processing, identified the statistically significant effects of education, income and number of household members on online purchases. These conclusions were confirmed by a detailed contingency tables analysis, including the almost monotonous trend of the dependencies, with only minor deviations in a maximum of one category. The strongest influence of some categories on the emergence of partial dependencies was found by residue analysis. The research confirmed that the frequency of online grocery shopping increases significantly with increasing education and income of respondents and decreases with increasing the number of household members. Most respondents apparently shop for groceries online because of time savings, better product choice and more convenient and easier search. Full article

Air pollution is considered one of the most significant risk factors for human health. To ensure air quality and prevent and reduce the harmful impact on human health, it is necessary to identify and measure the main air pollutants (sulfur and nitrogen oxides, PM₁₀ and PM_2.5 particles, lead, benzene, carbon monoxide, etc.), their maximum values, as well as the impact they have on mortality/morbidity rates caused by respiratory diseases. This paper aims to assess the influence of air pollution on respiratory diseases based on an analysis of principal pollutants and mortality/morbidity data sets. In this respect, four types of data are used: pollution sources inventory, air quality data sets, mortality/morbidity data at the local and national level, and clinical data of patients diagnosed with different forms of lung malignancies. The results showed an increased number of deaths caused by respiratory diseases for the studied period, correlated with the decreased air quality due to industrial and commercial activities, households, transportation, and energy production. Full article

Considering the imperative reduction in CO₂ emissions, both from household heating and hot water producing facilities, one of the mainstream directions is to reduce hydrocarbons in combustibles by replacing them with hydrogen. The authors analyze condensing boilers operating when hydrogen is mixed with standard gaseous fuel (CH₄). The hydrogen (H₂) volumetric participation in the mixture is considered to vary in the range of 0 to 20%. The operation of the condensing boilers will be numerically modeled by computational programs and prior validated by experimental studies concluded in a European Certified Laboratory. The study concluded that an increase in the combustible flow with 16% will compensate the maximum H₂ concentration situation with no other implications on the boiler’s thermal efficiency, together with a decrease in CO₂ emissions by approximately 7%. By assuming 0.9 (to/year/boiler), the value of CO₂ emissions reduction for the condensing boiler determined in the paper, and extrapolating it for the estimated number of boilers to be sold for the period 2019–2024, a 254,700-ton CO₂/year reduction resulted. Full article

The global COVID-19 pandemic has hit the agriculture sector hard around the world. A study was conducted to assess the impact of the pandemic on cropping patterns, crop management, usage of chemical inputs and their organic alternatives, harvesting, and marketing avenues through a survey approach in the two states of Kerala and Tamil Nadu in India. A total of 250 farmers participated in the study, the data was analyzed by Chi-square test and Kruskal–Wallis test. The assessment of the impact of COVID-19 on some aspects was undertaken by dividing the study period into three phases. Though a smaller number of people were infected with COVID-19 in the initial phase of the pandemic compared to the later phases, farm operations and the procurement of inputs were significantly affected at this phase as there was a sudden disruption in transportation due to COVID-19-induced movement restrictions. During the entire study period, commodities such as rice, bananas, vegetables, coconuts, and flowers suffered maximum crop loss compared to pulses, groundnuts, cotton, and rubber. Among fertilizers, the maximum shortage was observed for chemical fertilizers (46%) and biofertilizers (30%) compared to cow dung (18%) and poultry manure (6%), indicating that farmers tended to use more local materials that could be easily procured and accessed compared to shop-based inputs. A rise in the cost of cultivation, scarcity of farm workforce, and difficulty in hiring farm machinery all have contributed to the loss of profit during the pandemic period. As a response to COVID-19, growers initiated post-harvest processing of commodities, and cropping systems remained the same during the period. The paper also discusses some remedial measures to be adopted by households in the future, to minimize the impacts of such pandemics in the agrarian sector. Full article