Do Facts Matter? Consumer Misperceptions About Adopting Electrification Technologies

Development of the effective defrosting criterion for electric vehicles transcritical CO2 heat pumps under constant heating capacity operation

Integration of PV power into future low-carbon smart electricity systems with EV and HP in Kansai Area, Japan

This study proposes a distribution-level Energy System Integration and Aggregation (ESIA) model to evaluate the flexibility value of electric vehicles (EVs) and heat pump water heaters (HPWHs) under distribution transformer constraints. The model optimizes their operation based on household demand, photovoltaic generation, and mobility patterns.Using Japan’s FY2022 spot prices, simulation results show that day-ahead market optimization significantly reduces electricity procurement costs. Anticipated congestion-based control further mitigates reverse power flow with minimal cost increase, especially for HPWHs and EV charging. However, EV discharging faces opportunity loss due to reduced arbitrage flexibility during reserved periods.

The problems associated with youth behaviours in the Niger Delta region necessitated the study. The specific objectives were to collate the current agricultural development intervention programmes; compare the attitude of youth leaders and non-leaders to agricultural development intervention programmes, and examine the factors militating against youth involvement in agriculture. Questionnaires were used to elicit information from respondents. Simple random sampling was used to select respondents. The sample was made up of 71 youths comprising 18 leaders and 53 non-leaders. Data were analysed by the use of mean and t-test. It was found that 5 agricultural development programmes currently existed in the study area. The non-youth leaders disagreed with the 5 positive attitude statements and agreed with 4 out of the 5 negative statements. The youth leaders disagreed with 5 positive attitude statements and agreed with the 5 negative attitude statements. There was no significant difference in the mean attitude scores between youth leaders and non-leaders (t=0.05; p>0.05). The factors militating against youth involvement in agriculture were lack of basic infrastructure (x=2.62), lack of modern agricultural equipment (x=3.46), lack of land/land tenure system (x=3.34), lack of credit facilities (x=2.99), and poor incentives/ incomes(x=3.00). Youths should be motivated to take up agriculture through extension campaigns, and provision of inputs and land for large scale farming.

The design and analysis of two exhaust heat recovery systems for public shower facilities

The aim of this paper is to compare energy consumptions, CO2 emissions, and operative costs of condensing boilers, electric vapour compression heat pumps and gas driven absorption heat pumps to provide space heating and domestic hot water. The analysis is performed for 140 m2 single-family houses in five different Italian cities whose envelope features depend on the location. For each location, two different envelope conditions are considered. The first one is a non-insulated building, while the second one is the same building, but an external thermal insulation is added on vertical walls and roof. To avoid internal renovation, radiators are maintained as emission system. Combined dynamic simulations are performed to appreciate building and system interactions. A 6 second time step is set to evaluate properly interactions and the DHW profile demand. In addition, the GHP dynamic model is a grey box model experimentally validated. The results show that electric vapour compression heat pumps reach the highest non-renewable primary energy savings (>32%) compared to condensing boilers, but their operative costs are higher due to the higher specific cost of electricity in Italy. Gas driven absorption heat pumps achieve a lower consumption reduction than electric heat pumps (>22%), but they have also the minimum operative cost among the three technologies.

Exploring the willingness of consumers to electrify their homes

<p>As nations set ambitious targets to phase out internal combustion engine (ICE) vehicles and electrify transport and household systems, it is anticipated that there will be a surge in demand for electric vehicles (EVs), heat pumps (HPs), and electric water heaters (EWHs). Utility providers must assess what this shift means for the existing grid. Although generation may be sufficient, attention must turn to local distribution, particularly individual street- level transformers. As EV chargers are installed and households replace gas systems with HPs and EWHs, the grid faces rising pressure. Many consumers prefer to charge vehicles at home in the evening, placing extra demand on local infrastructure. When several residents charge EVs while using water heating and cooling systems, transformer capacity may be exceeded. This study uses data from an Ontario utility to examine new loading scenarios as EVs, HPs, and EWHs are adopted in Canadian neighbourhoods. One transformer showed a maximum hourly load increase of 706.59% at 25% uptake and 1292.22% at 50%. Sustained high loads accelerate insulation ageing and raise the risk of early failure<strong>, </strong>with overloads possible when 11 EVs charge simultaneously at high speed.</p>

The decarburization of heat and transport using electric vehicles (EVs) and heat pumps (HPs) needs an important investment in low-voltage (LV) networks. This article proposes an optimization approach to estimate the availability of headroom for domestic EV charging and optimization on LV networks under various penetrations of heat pumps. The proposed optimization approach is called dynamic differential annealed optimization (DDAO). The objective of the proposed approach is to maximize the hosting capability of low-voltage networks for EVs and HPs by optimizing the flexibility of EV charging. The DDAO is used to optimize different aspects of EV charging and LV networks. The DDAO approach is implemented in three steps: (a) HP headroom assessment, (b) EV optimization, and (c) validation. The performance of the proposed method is validated on a MATLAB platform and compared with the existing Binary Spring Search Algorithm (BSSA), Manta Ray Foraging Optimization Algorithm (MRFO), and Chaos Game Optimization methods. In comparison to the total prices of 3.5£ in BSSA, 4.5£ in MRFO, and 5.5£ in CGO, the proposed DDAO method achieves a lower total price of 3.2£. This suggests that the DDAO method is more cost-effective than the existing techniques.

Experimental evaluation of electric vehicle compressor lubricating oil robustness for heat pump application

Knowledge bases (KBs) about notable entities and their properties are an important asset in applications such as search, question answering and dialog. All popular KBs capture virtually only positive statements, and abstain from taking any stance on statements not stored in the KB. This paper makes the case for explicitly stating salient statements that do not hold. Negative statements are useful to overcome limitations of question answering systems that are mainly geared for positive questions; they can also contribute to informative summaries of entities. Due to the abundance of such invalid statements, any effort to compile them needs to address ranking by saliency. We present a statistical inference method for compiling and ranking negative statements, based on expectations from positive statements of related entities in peer groups. Experimental results, with a variety of datasets, show that the method can effectively discover notable negative statements, and extrinsic studies underline their usefulness for entity summarization. Datasets and code are released as resources for further research.

<p class="apa">The aim of this study is to investigate whether entrepreneurship trainings can reduce stereotypes against women entrepreneurship. With this aim socio-psychological obstacles to women entrepreneurship in Turkey are examined, and an experimental study is carried out. Entrepreneurship courses were given with a special emphasis on women entrepreneurship and gender issues. To evaluate the out puts of the experimental study, a questionnaire was designed and applied to students. In order to make a comparison, the same questionnaire was applied to students from two other universities, who have taken entrepreneurship courses through the classical method and curricula.</p><p class="apa">Survey tool includes 21 statements on women entrepreneurship, 5 positive and 16 negative. A non-parametric Mann-Whitney U test was conducted to evaluate the hypothesis that the experimental group would score lower in negative statements and higher in positive statements, on the average, than the non-experimental group. Test results indicate that mean ranks for the two groups differ significantly from each other in 12 items (p<.05). Experimental group score significantly higher than the non-experimental group in 4 positive and 1 negative statements; and lower than the non-experimental group in 7 negative statements. Compared to non-experimental group, experimental group seems to have higher scoring for awareness and advocacy of women entrepreneurship and lower scoring for socio-psychological obstacles against women entrepreneurship. According to the survey results, it can be concluded that modification of entrepreneurship education curricula will contribute to reduce stereotypes hindering women entrepreneurship.</p>

We examine the impact of signals regarding the Eurozone’s bail-out commitment on government bond spreads in the Eurozone’s periphery, analysing the effect of positive, negative and mixed statements and decisions by the EU, the ECB and Germany. We construct a dataset of relevant events, and estimate their effects using distributed lag models, providing a number of robustness checks. Our main argument is that investors react to statements from credible actors, but largely ignore statements from less-credible actors, awaiting actual decisions. Accordingly, positive statements from the ECB have clear effects, while those from Germany and the EU do not. Furthermore, ECB decisions appear to be anticipated and thus have no short-term effects, while we find clear effects of positive decisions by Germany and the EU.

This paper presents the development of an open-source, utility-friendly tool designed to evaluate distribution transformer overloading under adjustable levels of residential electrification using real utility data. The tool integrates load profiles from smart meters with submetered electric vehicle (EV) and heat pump (HP) consumption data collected from Iowa utilities. The tool development consists of two stages: First, seasonal variations in EV and HP consumption are analyzed through data clustering, and representative patterns are extracted and stored as a database serving as the electrification baseline. Next, the tool performs realistic load aggregation based on user-defined EV and HP penetration levels to reflect electrified customer consumption. Finally, the framework compares the aggregated load with the transformer nameplate capacity and evaluates overload conditions. This tool is fully built on and validated with real-world data, and it offers a practical and scalable solution for utilities preparing for increasing electrification.

A smart city (SC) includes different systems that are highly interconnected. Transportation and energy systems are two of the most important ones that must be operated and planned in a coordinated framework. In this paper, with the complete implementation of the SC, the performance of each of the network elements has been fully analyzed; hence, a nonlinear model has been presented to solve the operation and planning of the SC model. In the literature, water treatment issues, as well as energy hubs, subway systems (SWSs), and transportation systems have been investigated independently and separately. A new method of subway and electric vehicle (EV) interaction has resulted from stored energy obtained from subway braking and EV parking. Hence, considering an SC that simultaneously includes renewable energy, transportation systems such as the subway and EVs, as well as the energy required for water purification and energy hubs, is a new and unsolved challenge. In order to solve the problem, in this paper, by presenting a new system of the SC, the necessary planning to minimize the cost of the system is presented. This model includes an SWS along with plug-in EVs (PEVs) and different distributed energy resources (DERs) such as Photovoltaics (PVs), Heat Pumps (HPs), and stationary batteries. An improved grey wolf optimizer has been utilized to solve the nonlinear optimization problem. Moreover, four scenarios have been evaluated to assess the impact of the interconnection between SWSs and PEVs and the presence of DER technologies in the system. Finally, results were obtained and analyzed to determine the benefits of the proposed model and the solution algorithm.