Home Consumption Research Articles

Optimized Smart Home Energy Management System: Reducing Grid Consumption and Costs through Real-Time Pricing and Hybrid Architecture

Utility authorities utilize various methods to promote end-user energy conservation, including higher tariff rates and demand response (DR) strategies. This paper investigates an Optimized Smart Home Energy Management System (OSHEMS) designed to minimize grid dependence and energy bills while ensuring reliable load delivery. A hybrid architecture prototype was implemented, integrating a photovoltaic (PV) array, battery storage, and the electrical grid. The system combines Maximum Power Point Tracking (MPPT) solar chargers and Pure Sine Wave (PSW) inverters for efficient energy management. The Home Energy Management Whale Optimization Algorithm (HEMWOA) was employed to optimize energy usage and achieve cost reduction while enhancing user comfort. Real-time pricing (RTP) tariffs incentivizing flexible energy consumption during peak hours were incorporated. OSHEMS manages, schedules, and monitors energy sources and appliances, determining the optimal consumption mix. Experimental results demonstrate a significant decrease in grid reliance (46.6%) and energy costs (57.7%) compared to non-scheduling scenarios. These findings highlight the potential of OSHEMS in promoting sustainable and cost-effective energy consumption in smart homes.

A process evaluation of a home garden intervention

BackgroundMost reviews of nutrition-sensitive programs assess the evidence base for nutrition outcomes without considering how programs were delivered. Process evaluations can fill this void by exploring how or why impacts were or were not achieved. This mid-term process evaluation examines a home garden intervention implemented in a large-scale, livelihoods improvement program in Odisha, India. The objectives are to understand whether the intervention was operating as planned (fidelity), investigate potential pathways to achieve greater impact, and provide insights to help design future home garden programs.MethodologyData collection and analysis for this theory-driven process evaluation are based on a program impact pathway that shows the flow of inputs, processes, outputs, outcomes, and impacts. Quantitative and qualitative data from focus group discussions, semi-structured interviews, and a Process Net-Mapping exercise with beneficiaries, frontline workers, and program management staff.ResultsDespite a mismatch between the design and implementation (low fidelity), the process evaluation identified positive outputs, outcomes, and impacts on home garden production, consumption, income, health and nutritional outcomes, and women’s empowerment. Flexibility led to greater positive outcomes on nutrition, the adoption of sustainable agricultural practices and easy-to-understand nutrition models, and the likelihood of the intervention being sustained after the program ends.ConclusionsTo help food systems in rural settings reduce food insecurity by utilizing more sustainable agricultural practices, we recommend that home garden interventions include instruction on easy-to-understand nutrition models and on how to make natural fertilizer. Finding local solutions like home gardens to help address critical supply issues and food insecurity is paramount.

Day-ahead multi-criteria energy management of a smart home under different electrical rationing scenarios

With the recent global energy crisis, some countries have implemented electrical rationing (ER), making it necessary for smart homes to play a pivotal role in optimizing energy consumption and contributing to sustainable practices. To effectively manage smart home consumption, a stochastic programming approach for a grid-connected smart home energy management system (SHEMS) is proposed in this paper. The system includes PV, battery, diesel, and gas-based heating/cooling systems (HCS). Additionally, a demand response program (DRP) has been employed under time-of-use tariffs in the Syrian energy market. The main objective is to minimize the day-ahead expected cost and consumer discomfort by optimizing the operation of dispatchable units and loads. To manage the risks associated with the expected cost due to potential uncertainties in PV energy generation and electrical rationing programs, the conditional value-at-risk (CVaR) approach is adopted. Two methods are proposed to model the uncertainty in PV energy generation; interval bands and interval-based scenarios. The problem is modeled as a mixed-integer non-linear programming (MINLP) model, and coded in GAMS to test different cases. Based on the results obtained, substantial reductions reached 56.2% in worst-case cost scenarios when employing concurrent DRP-risk management.

Review of Enset (Tree Against Hunger and Drought) Value Chain Opportunities and Constraints in Agricultural Food Sector of Ethiopia

In sub-Saharan Africa Enset is widely dispersed wild plant species that ensures food security for many Africans. In similar view, in South and South-west parts of Ethiopia more than 20 million people depends on Enset as stable food and it is called drought tolerant food of root crop. Due to its multidimensional significant roles, its resilience and versatility during the times of famine Enset has earned the name 'The Tree against Hunger'. Besides, food items like ‘Amicho’, ’Kocho’, and ‘Bulla’ are obtained from Enset for home consumption and marketing. Besides, the value chain is the full range of activities which are required to bring a product or service from conception, through the different phase of production which involves a combination of physical transformation and the input of various producer services, delivery to final consumers, and final disposal after use. Thus, the main intent of this article was to review the value chain of Enset from its respective opportunities and challenges from perspective of Ethiopia. Regarding to this, the information used in this paper was the secondary source information that was extracted from journal articles and dissertation papers. Then the collected information were analyzed qualitatively and presented in narrative ways. Finally, based on the review results of this article conclusions and recommendations are given in advances.

Vertical Farming: A Promising Solution to Urban Agriculture

Urban agriculture refers to the agricultural activities such as plant production for home consumption and income generation in the urban areas especially cities. The concept of urban agriculture has been popularizing but in today’s century it is also facing certain problems such as limited land resources, population increase etc. Vertical farming is a type of urban agriculture, through which we could seek solutions to the problems that urban agriculture has been facing in the recent times. Vertical farming refers to the growing of crops in vertically stacked structures especially under controlled environmental conditions and using a suitable growing medium to increase the crop production per square metre by utilizing the vertical space for cultivation [1]. A wide range of crops can be cultivated in vertical farming with the use of techniques such as hydroponics, aeroponics, aquaponics, artificial lighting, inside the controlled environment of a greenhouse. Vertical farming is needed to provide solution to the problems of urban agriculture in terms of providing food security to the growing population, efficient land utilization, water conservation, increased crop production etc. However, vertical farming has certain disadvantages as well such as high initial investment cost, high energy cost and high maintenance cost. Therefore, further research and development strategies are necessary to overcome such disadvantages for increasing its effectiveness to meet the food demands of the growing population as well as the future generation in a sustainable manner.

Advances in fuzzy control systems for energy management in smart homes

The drive towards energy efficiency and sustainability has spurred technological innovations for managing energy consumption in residences, with fuzzy control systems standing out. These systems, based on fuzzy logic, offer adaptive and intuitive solutions to optimize energy use in smart homes, dealing with uncertainties and imprecisions in environmental conditions and occupant preferences. Fuzzy logic allows for refined control of devices such as lighting, heating, ventilation, and air conditioning (HVAC), adjusting in real-time to variations in conditions and user behaviors. Recent studies have demonstrated the effectiveness of these systems in various applications. Kontogiannis, Bargiotas, and Daskalopulu (2021) developed a fuzzy control system to recommend optimal energy consumption values based on environmental data, using the Mamdani approach and decision tree linearization. Keshtkar and Arzanpour (2017) introduced an autonomous thermostat combining supervised learning with wireless sensors and dynamic electricity pricing, adjusting temperatures and maintaining user comfort. Ain et al. (2018) proposed a Fuzzy Inference System that incorporates humidity and internal temperature variations to optimize energy consumption without sacrificing comfort. Additionally, Khalid et al. (2019) presented an energy management controller for smart grids using fuzzy logic and heuristic optimization techniques, improving load management and reducing costs and consumption. Collotta and Pau (2015) explored the integration of IoT technology with fuzzy-based systems using Bluetooth Low Energy (BLE) to manage energy consumption in home automation networks. These studies highlight that fuzzy control systems are crucial for optimizing energy consumption in smart homes, balancing efficiency and comfort, with ongoing advancements promising continuous improvements in energy management.

Assessment of livestock husbandry practices and production constraints among smallholder mixed crop-livestock production systems in the Majang zone, southwest Ethiopia

Livestock production plays a significant role in improving the livelihoods of poor smallholder farmer households in the Majang zone. However, despite its importance, there is limited information on husbandry practices and constraints on livestock production to design and implement effective interventions to maximize productivity. The aim of this study was to assess husbandry practices and major constraints on livestock production in the Majang zone, southwest Ethiopia. A semi-structured questionnaire was used to collect data from a randomly selected sample of 168 households (HHs) through a face-to-face interview from January to May 2021. The results revealed that mixed crop-livestock farming is the dominant livestock production system in the study area. The overall average herd size per household (HH) was 2.15 ± 0.11 cattle, 0.15 ± 0.01 sheep, 0.31 ± 0.09 goats, 0.10 ± 0.02 donkey, 0.04 ± 0.00 mule, 0.13 ± 0.02 horses and 0.24 ± 0.02 chickens. Overall herd size did not differ significantly by AEZ except for sheep (p < 0.05). The primary reason for keeping cattle, goats, sheep, equines and poultry were milk production (27.4 %), meat for home consumption (33.9 %), cash income (33.3 %), transportation (85.1 %), and meat for home consumption (72 %), respectively. In the dry and wet seasons, natural pasture, crop residues, indigenous fodder trees and shrubs (IFTSs), nonconventional feed resources (NCFRs), crop stubbles and improved forages were the main livestock feed resources. The majority (60.1 %) of respondents practiced free-grazing systems. Separate sheds, family dwellings, kraals, and open-walled sheds were the main housing systems used for animals. The majority (79.2 %) of respondents used rivers as a source of livestock drinking water. Trypanosomiasis (18.45 %), African horse sickness (66.1 %) and Newcastle disease (47.02 %) were the most important diseases of livestock. Diseases (35.7 %), lack of access to artificial insemination (35.7 %) and inadequate veterinary services (11.3 %) were identified as the top three constraints limiting production. It is recommended that constraints identified by farmers should be considered in developing and implementing effective interventions to improve livestock productivity and their contribution to poverty alleviation in the study area.

Seafood Purchasing Behavior in the U.S. during the Early Recovery Period from the COVID-19 Pandemic

This study examined seafood consumption during the early period of economic recovery following the COVID-19 pandemic. Specifically, surveys of U.S. consumers compared seafood purchasing behavior of the first two quarters of 2021 (Q1, 1 January through 31 March 2021, and Q2, 1 April through 30 June 2021) with those of 2020. Each survey included 100 seafood consumer respondents in each of the 20 U.S. metropolitan market areas. Following data cleaning, there were 1885 valid responses for Q1-2021 and 1940 for Q2-2021. A majority (57%) of respondents had received at least one dose of the COVID-19 vaccine before March 2021 and 70% had received at least one dose as of June 2021. Regardless of vaccination status, few respondents (6% to 9.5% for food generally and 4% to 6.5% for seafood) reported changes in seafood consumption. Seafood consumption away from home increased significantly in Q1-2021 as compared to 2020 and continued to increase but to a lesser degree in Q2-2021. Demographic differences were found in shopping behaviors by age, education, income, and gender, but not by ethnic group. Generally, higher-income females with higher education tended to purchase more seafood. Respondents reported increased numbers of shopping trips per year in Q1-2021 as compared to 2020, which continued into Q2-2021 for general food, but shopping trips for seafood decreased as compared to 2020. The frequency of takeout purchases (times/year) of prepared meals for home consumption of seafood decreased during Q1 from 2020 and remained at that level in Q2-2021, but home delivery purchases of prepared meals of seafood increased during this period. Approximately 50–55% of respondents reported no change in overall seafood consumption levels, while 28% noted an increase in seafood consumption compared to pre-pandemic periods, a significant increase from the 19% who had reported doing so pre-pandemic. In contrast, those reporting a decrease declined from 31% to 17% in comparison to pre-pandemic levels. Seafood consumption in the U.S. remained stable and recovered in early 2021, with a preference for dining out. Consumer behaviors varied by age, income, education, and gender, but not by ethnicity. These changes were primarily driven by access, availability, and income, indicating the need for further research on long-term consumption patterns. This study found apparent stability of seafood consumption by U.S. consumers, which recovered from pandemic consumption levels in early 2021, and there was little change in seafood consumption, frequency, or the types of seafood consumed. Vaccination status did not appear to affect seafood consumption.

Husbandry Practices, Reproductive and Production Performance of Indigenous Goats in Ahferom District of Central Tigray, Northern Ethiopia

The study, aimed to investigate indigenous goats’ husbandry practices, productive and reproductive performances, and constraints, was conducted in Ahferom district of central Tigray, Northern Ethiopia. Two peasant associations from midland and one from lowland in the district were purposively selected based on their potentiality. Simple random sampling technique was employed to select 147 smallholder goats’ keepers. A pretested semi-structured questionnaire was used to gather data. Focus group discussions (FGDs) were also held with knowledgeable farmers and key informants. The collected data were analyzed using SPSS statistical software Version 28.0. In the study area, goats were kept by farmers for sale (52.5%), home consumption (24.4%), saving (13.1%), manure (10%), and prestige (1.0%) in the midland. Nevertheless, goats were kept for sale (33.3%), home consumption (33.3%), saving (12.5%), manure (16.6%), and prestige (4.1%) in the lowland. Goats were mainly dependent on browsing plants in both wet and dry seasons. The overall sources of water in the study area were water wells (40.1%), hand pumps (32.7%), and ponds (27.2%). Most (89.8%) farmers used separate houses for their goats. The mean amount of milk produced/day from a lactating goat was estimated to be 0.2 liters. The overall mean litter size, age at first kidding and kidding interval were 2.350.59, 13.010.96 months and 7.440.76 months, respectively. Based on the FGDs with knowledgeable farmers and key informants, “litter size varied from parity to parity and increased as age advanced. At first, the litter size in most cases was single, increased to twins in middle age, and then remained constant after fourth and fifth parity”. Feed/land shortages, drought, diseases and parasites, inadequate extension support, predators and water shortages in descending orders were the most important identified problems. Designing sustainable improvement programs calls for understanding the husbandry practices and reproductive performance of goats in the study area

Socio-economic aspects and farming practices of goats in Southern Tunisia.

This study aims to describe socio-economic aspects, farming practices and production limitations of goats by surveying 53 farms holding 5507 head in the regions of Tataouine-Tunisia. It was revealed that goats represented a major source of income for most of the producers (66.1%). Approximately 35.8% of the farmers had not received formal education, with the majority (56.6%) having been engaged in goat breeding for over 10 years. Additionally, 50.9% of stockholders relied on technical knowledge for animal breeding. The investigated herds were mostly (97.4%) comprised of local goat breeds. The most common management system was semi-intensive (49.1%) based on grazing in communal rangelands and supplementation with agricultural by-products and concentrates. The fertility, fecundity and prolificacy rates were 91.3 ± 8.3, 109.8 ± 19.5 and 127.0 ± 15.4%, respectively. The main reasons for keeping goats were their major contribution to the income by the sale of male kids and the provision of milk for home consumption. Sale of male kids at an age of 7.7 months was practiced mostly via intermediaries (94.3%) and rarely directly to butchers and markets (5.7%). The total amount of milk produced on each farm was on average 15.1l/day, and more than half of farmers (54.7%) consumed goat milk as part of their daily diet. The majority (71.7%) of respondents locally processed milk into Leben, Rayeb and cheese because the goat milk market faced constraints in the Tataouine regions, mainly in terms insufficient milk production and low consumer acceptability. Goats contribute to the income source in rural zones of southern Tunisia, where their breeding is mainly for the purpose of meat sale and the provision of milk for home consumption. The development of goat milk market can represent an added value to this sector.

The Impact of Smart Home Technologies on Energy Efficiency, Cost Savings, and Environmental Benefits

The results of this study addressed the effectiveness of smart home technologies in terms of energy consumption, cost reduction, and environmental advantages in Nigerian homes. Given the growing energy requirements and concern for the environment, assessing the efficiency of such technologies is critical for socioeconomic development. We collected data using a combination of surveys and statistical analysis in five major Nigerian cities: Lagos, Abuja, Kano, Port Harcourt, and Enugu. We evaluated smart home technologies such as smart thermostats, lighting systems, appliances, plugs, and energy monitoring systems based on their energy savings (%), monthly cost savings (NGN), kilogram of CO2 emissions cut, and percent adoption. We used descriptive analysis and regression modeling to analyze the data collected from the respondents. The introduction of smart technologies reduced general energy use by fifteen to twenty-five percent, with smart appliances recording the highest reduction of up to 25%. This feature demonstrated how monthly cost savings varied depending on the technology and geographical location, resulting in significant increases of up to 4000 NGN per household, each household saw a reduction in CO2 emissions by 500 kg to 700 kg annually, resulting in significant environmental benefits. According to the studies, smart home technologies can help promote energy conservation and therefore reduce CO2 emissions in Nigerian households. However, there are still widely recognized obstacles, like high initial costs and a low level of awareness. offering financial incentives, improving Information Promotion of existing policies and overhauling the distribution systems to increase the pace of uptake and impact returns.

Husbandry Practices of Indigenous Goats Types in South West Shewa Zone, Oromia, Ethiopia

This study was conducted in South west Shewa zone, to identify Husbandry practices in Tole and Becho districts. Data were collected through questionnaire and, focal group discussion. A total of 180 households were selected for interview. Data collected via questionnaire were summarized with descriptive statistics and analyzed using SPSS, V.21. Chi–square test was employed for categorical data. Indices were calculated to provide ranking. Castration was primarily practiced to improve the fattening potential and acquire better price by selling fattened goats. Most of castration carried out at the age of &amp;gt;6months. Majority of respondents use shelter constructed in the main house and the remaining respondents use separate house. The primary feed resource during dry season was natural pasture followed by Shrubs and during wet season the primary feed resource was Shrubs and bushes followed by natural pasture. Majority of the respondents herd their goats separated from kids adult mainly to protect kids from attack by predators and to protect the does from losing their weight. The primary source of water during dry season River followed by spring and the primary source of water during wet season was Rain water followed by river. The primary disease affects goats were Orf followed by Foot root. The primary cause of death for goats was disease followed by accident. Generally, goats play a significant role for farmers as source of income generation and home consumption throughout the year. The primary feed resource during dry season was natural pasture followed by Shrubs, to increase production productive the goats in the study its better if focused on improving feed source and concentrated feed.

Home loans and Muslims – an Australian perspective

PurposeThis study aims to investigate how Australian Muslims make consumption-related decisions regarding the purchase of home loan products.Design/methodology/approachThis exploratory research used in-depth semistructured interviews with community leaders from leading Muslim ethnic communities. Seventeen community leaders from the six largest Muslim community groups by country of birth and living in Melbourne and Sydney were selected for the interviews. The interview data was analyzed using NVivo 12.FindingsThe findings suggest that despite knowledge of and concern for Islamic tenets regarding the consumption of banking and financial products, including home loans, most Muslims viewed conventional home loans (CHL) as being permitted, essential or innocuous. Reasons for such views include the interpretation of Islamic tenets, limited awareness of available Islamic home loan offerings, convenience factors related to accessing CHL offerings, service quality levels, availability of technology-based services such as internet banking, and the influence of social groups and communities.Research limitations/implicationsThis research helps marketers understand the attitudes, subjective norms (SN) and behavioral factors related to the Muslim consumption of home loans.Practical implicationsThe findings of this research can facilitate the development of financial products and marketing strategies that better appeal to Muslims. Such loan products can improve the uptake of home loans (and, in effect, homeowners) by Muslims, potentially improving social and financial inclusion.Social implicationsThis research helps marketers understand the attitudes, SNs and behavioral factors related to the Muslim consumption of home loans, which can facilitate the development of financial products and marketing strategies that better appeal to Muslims. Such loan products can improve the uptake of home loans (and, in effect, homeowners) by Muslims, potentially improving social and financial inclusion.Originality/valueThis qualitative study explores the drivers of Muslim consumers’ uptake of home loans in Australia. Drawing upon the theory of planned behavior and the literature, antecedents to attitude, SNs and perceived behavioral control that influence intention and behavior were investigated. It identifies factors influencing decision-making related to home loans by Australian Muslims, contributing to a theoretical framework to investigate Muslims’ consumption of financial products.

Optimizing energy consumption in smart homes using GA-LSTM

The need to optimize energy consumption arises from the inadequate energy supply many homes face. However, to optimize energy consumption in a home, one must be equipped with the knowledge of the energy consumption rate and energy supply rate in the home. This paper proposed the use of a Long Short-Term Memory (LSTM) model optimized by Genetic Algorithm (GA) to optimize the energy consumption in a smart home. The model was designed using 8 input variables, which were observed weather information of a given region over a span of 350 days. The data set was split into a training data set and a test data set in the ratio 4:1. Both the baseline LSTM model and our proposed GA-LSTM model was used to train and test the data. The results of the baseline LSTM model showed a Mean Average Percentage Error (MAPE) of 0.15 and a Root Mean Square Error (RMSE) of 0.0007, while our proposed GA-LSTM recorded an MAPE of 0.07 and RMSE of 0.0004. The implication of these results is a better performance of our proposed GA-LSTM model over the baseline LSTM model. This paper demonstrated how the Genetic Algorithm was able to optimize the baseline LSTM model by selecting the best weights during the LSTM training process. The findings of this paper are recommended for smart homes having the capability to monitor energy usage of installed electrical appliances and the ability to predict to weather condition of the region the home is sited.

Alcohol home delivery usage and its relationship to alcohol consumption in New South Wales during COVID-19

Background: Rapid growth in the use of alcohol home delivery services, combined with increases in home drinking during COVID-19, raises potential concerns around increased consumption. This paper aims to assess the relationship between alcohol home delivery use and consumption across levels of COVID-19 restrictions in New South Wales (NSW), Australia. Methods: A 5-wave longitudinal survey of 586 NSW residents (Mage = 35; 65.3% female) conveniently sampled across 2020. Home delivery usage and the number of daily standard drinks consumed during a typical week were assessed with a survey. Logistic regression models were estimated within each wave to identify predictors of home delivery usage, and hierarchical logistic mixed effects models were estimated to predict purchase source (home delivery vs other) at the occasion level. Results: From baseline, alcohol home delivery use rose significantly during lockdown (20% to 34%), with respondents using home delivery during lockdown and the partial re-opening wave consuming significantly more than those who were not. Use of home delivery was significantly higher during lockdown and the partial re-opening amongst people who drank more heavily, with respondents aged 36 or older more likely to use delivery services in all waves except lockdown. Conclusions: Alcohol home delivery usage increased during lockdown suggesting restrictions impeding on-premise consumption coincided with an increase in home delivery. Associations between persons who drink more heavily and use of home delivery during lockdown and the partial re-opening suggest a subset of the population that may be at increased risk of harmful consumption when accessing alcohol delivery services.

Standby Power Reduction of Home Appliance by the i-HEMS System Using Supervised Learning Techniques

Electricity consumption in homes is on the rise due to the increasing prevalence of home appliances and longer hours spent indoors. Home energy management systems (HEMSs) are emerging as a solution to reduce electricity consumption and efficiently manage power usage at home. In the past, numerous studies have been conducted on the management of electricity production and consumption through solar power. However, there are limited human-centered studies focusing on the user’s lifestyle. In this study, we propose an Intelligent Home Energy Management System (i-HEMS) and evaluate its energy-saving effectiveness through a demonstration in a standard house in Korea. The system utilizes an IoT environment, PID sensing, and behavioral pattern algorithms. We developed algorithms based on power usage monitoring data of home appliances and human body detection. These algorithms are used as the primary scheduling algorithm and a secondary algorithm for backup purposes. We explored the deep connection between power usage, environmental sensor data, and input schedule data based on Long Short-Term Memory network (LSTM) and developed an occupancy prediction algorithm. We analyzed the use of common home appliances (TV, computer, water purifier, microwave, washing machine, etc.) in a standard house and the power consumption reduction by the i-HEMS system. Through a total of six days of empirical experiments, before implementing i-HEMS, home appliances consumed 13,062 Wh. With i-HEMS, the total consumption was reduced to 10,434 Wh (a 20% reduction), with 9060 Wh attributed to home appliances and 1374 Wh to i-HEMS operation.

Eating Habit in Childhood: A Systematic Review of The Literature

Purpose: One of the consumer groups most targeted by the food industry is children. Food consumption in homes and schools has resulted in overweight and obesity. The objective of this work was to identify food consumption habits in childhood, highlighting the importance of food education from preschool onwards. Methodology: The Systematic Literature Review was used with the support of the Methodi Ordinatio, which selects relevant articles on specific topics, identifying food consumption habits by children in the family and school environment. Results and Discussion: The results reveal a growing concern about healthy and sustainable eating, especially in the context of children. However, there are still gaps in the literature. Food and sustainable education from an early age is essential to ensure healthy habits and reduce the impact on children's health. Parents, schools, companies, researchers, and the State must work together to promote healthy and sustainable eating for children, aiming for a healthy and sustainable future for the next generations. Implications of the Research: It is expected that the results presented will serve as input for future studies and, research on the topic of infant nutrition and contribute to positive changes. Originality and Value: The research innovates in presenting a research agenda based on studies carried out in English literature and interventions carried out in the family and school environment in Australia, Canada, and the United States of America.

Impact of tariff liberalization on economic and social benefits: Computable general equilibrium application to Kenya

AbstractThis study employed computable general equilibrium policy simulations to examine the impact of import tariff liberalization on socioeconomic outcomes including living standards, cost of living, gross domestic product (GDP) from expenditure, total investment expenditure, intermediate input demand, output, value‐added, tariff revenue, sales tax revenue, indirect tax revenue, direct income tax revenue, factor income tax revenue, and factor demand. Findings from the simulations have policy implications touching on a need to embrace reciprocal tariff liberalization under agreements like strategic trade and investment partnerships and economic partnership agreements as they are associated with welfare gains, reduction in cost of living, and GDP growth. Targeted policy incentives could be directed to specific domestic sectors since tariff liberalization has negative impacts on investment expenditure. Incentives regarding intermediate inputs should be directed to the manufacturing and services sectors for liberalization of agrifood commodities. Targeted policy incentives should be directed to the manufacturing and services sectors which experience decrease in output with tariff reductions. Liberalization of manufactured commodities should be accompanied by value‐added incentives directed to the agrifood and home production–home consumption sectors. For the liberalization of manufactured commodities, targeted policy incentives should be directed to the services sector which experiences job losses while for the liberalization of tariffs on imports of agrifood commodities, targeted policy incentives should be directed to the agrifood and the home production–home consumption sectors, which also lose jobs. These targeted policy incentives could support industrial activity and compensate for revenue loss, especially from customs duties.Related ArticlesGruber, Lloyd. 2013. “Trade, Growth, Poverty, and Politics: Toward a Unified Theory.” Politics &amp; Policy 41(5): 723–64. https://doi.org/10.1111/polp.12034.Onyango, Gedion, and Japheth Otieno Ondiek. 2022. “Open Innovation During the COVID‐19 Pandemic Policy Responses in South Africa and Kenya.” Politics &amp; Policy 50(5): 1008–31. https://doi.org/10.1111/polp.12490.Soto, Gloria. 2012. “Environmental Impact of Agricultural Trade Liberalization under NAFTA.” Politics &amp; Policy 40(3): 471–91. https://doi.org/10.1111/j.1747‐1346.2012.00354.x.

Numerical analysis of the thermal behavior of a solar heat exchanger using multiple phase change materials

Currently, solar energy is the most abundant and cleanest source of renewable energy, making it a good substitute for increasing energy efficiency. Solar water heaters can significantly reduce the cost of electricity consumption in homes and help reduce greenhouse gas emissions. Most homes use water heaters to produce domestic hot water at a temperature between 50 °C and 60 °C. A latent heat phase change module is created to account for variations in energy supply to solve the inherent intermittency problem. The solar water/PCM heat exchanger, a phase change heat storage system, is designed in this work. A numerical analysis was conducted to examine the impact of various cooling temperatures on the solidification thermal cycle of the phase change material. As this temperature range is suitable for its melting. The phase change material (PCM) can be used to effectively control the temperature. Depending on the PCM and its storage capacity, the temperature of the produced water is controlled. Through the tubes, the water used for heat transfer from the solar collector transfers the heat from the sun’s rays to the PCM. During the discharge phase, the heat that has been stored in the PCMs is then transferred to the water and heats it up. In order to quantitatively evaluate the thermal performance of the water heat exchanger, a numerical simulation using the finite volume method was also analyzed.

Enhancing smart grid electricity prediction with the fusion of intelligent modeling and XAI integration

This study examines the vital role of accurate load forecasting in the energy planning of smart cities. It introduces a hybrid approach that uses machine learning (ML) to forecast electricity usage in homes, improving accuracy through the extraction of correlated features. The accuracy of predictions is assessed using loss functions and the root mean square error (RMSE). In response to increasing interest in explainable artificial intelligence (XAI), this paper proposes a framework for predicting energy consumption in smart homes. This user-friendly approach helps users understand their energy consumption patterns by employing shapley additive explanations (SHAP) techniques to provide clear explanations. The research uses gradient boosting and long short-term memory neural networks to forecast energy usage. In the context of sustainable urban development, it emphasizes the importance of conserving energy in homes. The paper explores AI and ML methods for predicting residential energy use, aiming to make socially meaningful impacts. It highlights the need to understand the factors affecting predictions to improve the accountability, reliability, and justification of decisions in energy optimization. Explainable AI techniques are used to gain insights into the prediction models and identify factors influencing household energy consumption. This research aids in decision-making processes related to electricity forecasting, advancing discussions on intelligent decision-making in power management, especially in smart grids and sustainable urban development.