Small-scale Users Research Articles

Techno-economic assessment and grid impact of Thermally-Integrated Pumped Thermal Energy Storage (TI-PTES) systems coupled with photovoltaic plants for small-scale applications

The growing share of Renewable Energy Sources (RES) is rising the amount of curtailed energy to preserve grid security. With the aim of evaluating a complementary storage solution to electric batteries for both new and revamping RES power plants, this study investigates the performance of a Thermally Integrated Pumped Thermal Energy Storage (TI-PTES) system integrated with a Photovoltaic (PV) power plant aimed to enhance the energy self-sufficiency of small-scale users. The assessment is carried out for a case study characterized by a demand of electricity, heating and cooling that vary throughout the year. The studied PTES system is based on the integration of a High Temperature Heat Pump (HTHP), two Thermal Energy Storage (TES) sections and an Organic Rankine Cycle (ORC) power plant. Results show the influence of the main design parameters, such as PV size, HTHP size and TES capacities on the overall system performance, evaluated by means of the energy self-sufficiency, energy self-consumption, round-trip efficiency, Levelized Cost of Storage and the Grid Impact indicator, which quantifies the energy exchanges with the grid (feed-ins and withdrawals) to the overall user demand. The influence of seasonality on the energy performance indicators was studied as well. For the case study considered, the best combination of design parameters for the PV-PTES system is identified with reference to a PV plant whose yearly energy production equals the energy demand and for a 55 kWe High Temperature Heat Pump, a 10 kW ORC and a storage volume of 48 m3 for each of the two TES units. The PTES system is characterized by a LCOS of 0.72 $/kWh, a round-trip efficiency of 28.2 % and its integration offers several advantages over the use of a PV plant without any storage section. In particular, the PTES unit leads to a substantial increase in the self-sufficiency, within the range 1–14 %, and a considerable decrease of the grid impact indicator, within the range 2–28 %.

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing.

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station's capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station's use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station's open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

Cutting through complexity: Coordinated demand response and future directions in global communication technologies

The global electricity market is undergoing a transformative shift, envisioning a future resembling commodity trading platforms. Enabled by mature communication technologies, this evolution empowers energy consumers worldwide to actively engage in the energy market, negotiating arrangements for adjusting energy demand during grid stress and optimizing costs. In this era of technological advancements, this vision is materializing globally. Commercial and industrial entities are playing active roles in ancillary services markets, providing crucial grid support. Efforts are expanding to engage smaller users through third-party aggregators. However, many initiatives retain opt-in structures, limiting customer engagement. A promising solution is local energy markets, integrating modest flexibility reserves globally. This empowers small-scale users to choose services aligned with their preferences. This paper delves into the essential components facilitating the transition to globally applicable, aggregator-mediated demand-side management markets. Anchored in dynamic consumer engagement and nurtured by reciprocal information flows, this shift signals a fundamental reshaping of the global energy landscape. The paper introduces a universally adaptable demand response aggregation framework for energy enterprises to systematically devise consumer-centric programs. This framework serves as a foundational structure, fostering a strategic and flexible approach to meet evolving consumer preferences in demand response initiatives worldwide.

Effectiveness of Microfinance in Poverty Alleviation and Entrepreneurship Opportunities

Poverty continues to affect billions of lives worldwide. Microfinance is one of the many tools that strive to end poverty. In particular, microfinance meets the poor need for financial services. The poor have traditionally been excluded from legitimate financial services, but with new financial products, such as group lending, small financial institutions have been able to meet the challenges of lending to the poor. Today micro finance plays a key role in the financial market. The study focuses on the success of small investments in the fight against poverty and entrepreneurial opportunities. This study was made up of baseline data with a sample size of 110 small-scale users selected in a simple random random sample. The study was conducted at ESAF Small Finance Bank in the Trissur region. Identifying awareness of microfinance and its services among its customers. Identifying challenges in obtaining microfinance. Evaluating the effectiveness of small incomes in the fight against poverty Identifying the effectiveness of small incomes in business opportunities. Mathematical tools used in this data collection to analyze simple percentages, Chi-square and ANOVA. The findings of this study revealed the popularity of small amounts of money for its customers and most of the women borrowed from microfinance. Awareness among customers about microfinance and ESAF is very high.

Short-term fast forecasting based on family behavior pattern recognition for small-scale users load

Short-term fast forecasting based on family behavior pattern recognition for small-scale users load

Blockchain‐based framework of power demand response in China

Demand response is recognized as an effective solution for eliminating power fluctuations and satisfying capacity constraints in power systems. A growing customer base equipped with energy storage and intelligent power meter on the demand side has resulted in the strong interest of China's power companies in demand response. However, most exiting demand response programs in China are based on a centralized framework, which is easier for management, but cannot support a large number of scattered small-scale users' participation effectively. Therefore, taking the desired features of blockchain technology, such as decentralization, trustworthiness, trackability, and immutability into consideration, the applicability of blockchain in demand response is analyzed. On this basis, a new blockchain-based framework of China's typical demand response programs is proposed, in which consensus mechanism, encryption algorithm, and smart contract of blockchain are applied to the process of invitation, bidding, and settlement in demand response. Furthermore, the development suggestions of China's demand response based on blockchain technology are put forward from the aspects of trading products, credit management, and platform construction at the end of this work.

The Impact of Using Small-Scale Irrigation Motor Pumps on Farmers’ Household Incomes in Ethiopia: A Quasi-Experimental Approach

Sectoral economic growth data in Ethiopia show that the agriculture sector has the lowest growth, which is caused by frequent drought and inefficient technologies, among other factors. As a result, the productivities of land and labor, as well as the income of small-scale farm households, are very low, and rural areas have a relatively high poverty rate. A quasi-experiment was applied to understand the impact of using small-scale irrigation motor pumps on farmers’ livelihood improvement. Specifically, a survey was conducted in 2019 on a sample of 92 small-scale irrigation motor pump and canal irrigation users as the treatment and control groups. The weighted propensity score matching method was applied to eliminate initial differences and adjust sampling proportions across the groups. Based on the average treatment effect on the treated estimation results, we cannot state that the mean income difference in small-scale irrigation motor pump users and canal irrigation system users is different from zero. This indicates that countries with little capital to invest in large-scale irrigation projects can introduce household-level small-scale irrigation motor pumps to improve farmers’ incomes.

Research on Electricity Information Acquisition System Based on Sample Data Mining Model

In power user information collection and detection, power companies generally have a variety of different detection needs, or need to solve the problem while having additional requirements for certain aspects. Therefore, the SVM classification technology is used in the paper to carry out more detailed pattern recognition of power consumption characteristics for small-scale users or users with major suspicions. Moreover, given the imbalance of the abnormal electricity detection data set, a comprehensive processing model of unbalanced samples is constructed. Meanwhile, the differential evolution algorithm is applied to complete the SVM parameter optimization, which not only solves the problem that the SVM classification performance is significantly affected by the parameters, but also ensures the operating efficiency of the integrated classification model.

Comparison of Small-Scale Wind Energy Conversion Systems: Economic Indexes

Wind energy is considered as one of the most prominent sources of energy for sustainable development. This technology is of interest owing to its capability to produce clean, eco-friendly, and cost-effective energy for small-scale users and rural areas where grid power availability is insufficient. Wind power generation has developed rapidly in the past decade and is expected to play a vital role in the economic development of countries. Therefore, studying dominant economic factors is crucial to properly approach public and private financing for this emerging technology, as industrial growth and energy demands may outpace further economic studies earlier than expected. In this study, a strategy-focused method for performing economic analysis on wind energy based on financial net present value, levelized cost of energy, internal rate of return, and investment recovery period is presented. Numerical and simulation results depict the most optimal and economical system from a 3 and a 10 kW wind energy conversion system (WECS). Moreover, the aforementioned criteria are used to determine which WECS range is the most suitable investment with the shortest payback period. Finally, an economically viable and profitable wind energy system is recommended.

Peer-to-peer electricity transaction decision of user-side smart energy system based on SARSA reinforcement learning method

With the deep integration of advanced information technologies such as artificial intelligence and traditional energy technologies, smart energy systems have been proposed as a method to provide the best solution for the coordination, balance, and control of the entire energy system. As a new way of energy balance and interaction in the user side energy market, peer-to-peer (P2P) electricity transaction can effectively promote energy sharing within the user group and improve the economic benefits of users participating in the energy market. Reinforcement learning (RL) is an artificial intelligence method in which agents continuously acquire relevant experience and knowledge during the interaction with the environment, automatically update their decision-making behavior, and achieve maximum return. It is suitable for P2P transaction decision analysis of small-scale users in the context of smart energy. Firstly, this paper establishes a P2P transaction model that includes a participant model, equipment model and price model. Secondly, the transaction problem is equivalent to a Markov decision process (MDP) and each learning element model is established. Then, the MDP problem is solved and analyzed using SARSA RL algorithm with average discrete processing. Finally, a case study of a community with multiple users is conducted to verify the effectiveness, economy, and security of RL method in solving energy storage action selection and transaction decision problems of energy storage users.

Monthly Electricity Consumption Forecasting Method Based on X12 and STL Decomposition Model in an Integrated Energy System

With the rapid development and wide application of distributed generation technology and new energy trading methods, the integrated energy system has developed rapidly in Europe in recent years and has become the focus of new strategic competition and cooperation among countries. As a key technology and decision‐making approach for operation, optimization, and control of integrated energy systems, power consumption prediction faces new challenges. The user‐side power demand and load characteristics change due to the influence of distributed energy. At the same time, in the open retail market of electricity sales, the forecast of electricity consumption faces the power demand of small‐scale users, which is more easily disturbed by random factors than by a traditional load forecast. Therefore, this study proposes a model based on X12 and Seasonal and Trend decomposition using Loess (STL) decomposition of monthly electricity consumption forecasting methods. The first use of the STL model according to the properties of electricity each month is its power consumption time series decomposition individuation. It influences the factorization of monthly electricity consumption into season, trend, and random components. Then, the change in the characteristics of the three components over time is considered. Finally, the appropriate model is selected to predict the components in the reconfiguration of the monthly electricity consumption forecast. A forecasting program is developed based on R language and MATLAB, and a case study is conducted on the power consumption data of a university campus containing distributed energy. Results show that the proposed method is reasonable and effective.

Expansion of Natural Dye Colour Gamut for Use by the Local Textile and Craft Industry

Natural dyes have been used since long back in various areas such as textiles, craftwork, food colouring and also as medicine. This work was based on expansion of the colour shade that can be obtained from natural dyes for use by the small scale users. The natural dye was extracted from three naturally available plants locally in Zimbabwe using the cold extraction under gravity method. An alcohol was used to extract the dye using a vacuum pump and left to dry.

Interplay between structural change in Central Asian agriculture and institutional scarcity of land and water: evidence from Tajikistan

Abstract:This contribution focuses on the interaction between structural change in agriculture and the availability of key natural resources – land and water. The relationship is not unidimensional; therefore, we propose three dimensions of resource-induced structural change. The first dimension describes the links between the two critical input factors into agricultural production, namely land and water. To systematize this perspective, we use the concept of linking patterns that depict direct and indirect intersectoral linkages from a property rights perspective. Second, we examinee the dimension of how structural change in agriculture can be triggered by scarcity of natural resources. The third dimension describes structural change that may lead to overuse and scarcity. In this regard, we introduce resource scarcity not only as physical but most important as institutional scarcity. To illustrate these dimensions, we have chosen a case in Central Asia, where the availability and the control of access and withdrawal rights to land and water is of utmost importance for the agricultural sector. Tajikistan faces physical and institutional scarcity in arable land. The institutional scarcity is due to the non-transparent and costly processes that need to be followed to gain land rights. Likewise there is sufficient supply in water, in Tajikistan, but the de-facto access rights to water are limited for some groups. For instance, the post-socialist irrigation infrastructure is now inappropriate to serve all small-scale users on a canal. In the future, land use change due to a predicted increase of major investors, will have additional impact on the de-facto water rights. We conclude that a solid study not only on the physical but also on the institutional relations of agriculture to natural resources is important to come to reliable predictions of structural change in agriculture. We also show that structural change in agriculture may have wider implications for rural society that go beyond the agricultural sector.

Spectrum Sensing Algorithm to Detect Small-Scale Primary Users Based on Maximum-Minimum Eigenvalue

Spectrum Sensing Algorithm to Detect Small-Scale Primary Users Based on Maximum-Minimum Eigenvalue

Adaptive capacity to changes in terrestrial ecosystem services amongst primary small-scale resource users in northern Norway and Sweden

ABSTRACTThis paper presents results from case studies in which we investigate the interrelations between changes in ecosystem services (ESs) and adaptive capacity among small-scale users of multi-use forest or outfields resources in northern Sweden and Norway. The study presents a framework that utilizes scenarios for changes in ESs under climate change in combination with qualitative interviews with outfield resource users in order to assess their adaptive capacity to the projected changes. The study illustrates that ESs may change significantly under climate change, and in particular affect winter snow and ice conditions, for instance increasing the duration of the growing season but with consequences for pasture quality. We find that given structural constraints, the key factors that influence the selected resource users’ adaptive capacity at an individual level include motivation and entrepreneurial inclinations, which are related to the lifestyle choice of making a livelihood based on small-scale and multi-use occupations.

PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data.

The lack of reproducibility with animal phenotyping experiments is a growing concern among the biomedical community. One contributing factor is the inadequate description of statistical analysis methods that prevents researchers from replicating results even when the original data are provided. Here we present PhenStat – a freely available R package that provides a variety of statistical methods for the identification of phenotypic associations. The methods have been developed for high throughput phenotyping pipelines implemented across various experimental designs with an emphasis on managing temporal variation. PhenStat is targeted to two user groups: small-scale users who wish to interact and test data from large resources and large-scale users who require an automated statistical analysis pipeline. The software provides guidance to the user for selecting appropriate analysis methods based on the dataset and is designed to allow for additions and modifications as needed. The package was tested on mouse and rat data and is used by the International Mouse Phenotyping Consortium (IMPC). By providing raw data and the version of PhenStat used, resources like the IMPC give users the ability to replicate and explore results within their own computing environment.

ANALISA SUPPLY DAN DEMAND BETON READYMIX DI KOTA MALANG

As civil constructions are growing rapidly in Malang, readymix concrete is in a great demand. The writer intends to find out the capacity of average readymix supply of 4 different companies, the capacity of average readymix demand of some construction projects in Malang, and some influential problems of both readymix supply and demand. This thesis includes a qualitative descriptive study. Questionnaires were distributed to some users and producers of readymix concrete in Malang.The questionnaires result is average 117.5 m3/day capacity of readymix supply in normal production and average 200 m3/day capacity of readymix supply in peak production, average 92 m3/day capacity of readymix demand large scale users, average 45 m3/day capacity of readymix demand medium scale users, average 17 m3/day capacity of readymix demand small scale users, and some problems of less material to make readymix concrete and less concrete mixer truck unit to service users.Keywords: demand, producer, readymix concrete, supply, user

Development of Control System of the Single Phase Multi-input Inverter for Microgrids

Scheme of the small-scale microgrid inverter control system is investigated and described. The researched microgrid is intended for small-scale power users, which maximum capacity does not exceed 5 kW. Results of the control system research are presented. Method of mathematical modelling was used for researches of the system. The MATLAB/SIMULINK model was worked out for this purpose. The model was based on the SymPowerSystems library. The main target of the researches was active and reactive power control in the microgrid. The curves reflecting the possibility and quality of the independent active and reactive power control in the microgrid are presented and discussed. DOI: http://dx.doi.org/10.5755/j01.eee.20.9.8711

Priority General Authorisations in rights-based water use authorisation in South Africa

This article unravels the notions of justice in statutory water law in Sub-Saharan Africa in general and South Africa in particular. These laws, which allocate and regulate water resources, are licence (or permit) systems. Three forms of injustices are identified for small-scale water users who typically encompass all poor water users: the reinforcement of the historical injustices by which colonial powers captured ownership of water resources and undermined customary water law; administrative discrimination as a result of governments' lack of capacity to license the large numbers of small-scale users; and discrimination of the smallest-scale users whose exemption from the obligation to apply for a licence relegates them to a second-class entitlement to water. Based on the texts and implementation experiences of the National Water Act (1998) and the pro-poor prioritisation rules in the National Water Resource Strategy-2 (2013), the authors propose the transformative legal tool of priority General Authorisations for black small-scale users to overcome these injustices. Via this tool all black small-scale users, including the poor, would obtain equal access to minimum quantities of water needed to progressively achieve constitutional rights to water, food, and non-discrimination, while the remaining water resources would be allocated to high-impact users through licences with strict and enforceable conditions.

Explicit Expressions for Solar Panel Equivalent Circuit Parameters Based on Analytical Formulation and the Lambert W-Function

Due to the high dependence of photovoltaic energy efficiency on environmental conditions (temperature, irradiation...), it is quite important to perform some analysis focusing on the characteristics of photovoltaic devices in order to optimize energy production, even for small-scale users. The use of equivalent circuits is the preferred option to analyze solar cells/panels performance. However, the aforementioned small-scale users rarely have the equipment or expertise to perform large testing/calculation campaigns, the only information available for them being the manufacturer datasheet. The solution to this problem is the development of new and simple methods to define equivalent circuits able to reproduce the behavior of the panel for any working condition, from a very small amount of information. In the present work a direct and completely explicit method to extract solar cell parameters from the manufacturer datasheet is presented and tested. This method is based on analytical formulation which includes the use of the Lambert W-function to turn the series resistor equation explicit. The presented method is used to analyze commercial solar panel performance (i.e., the current-voltage–I-V–curve) at different levels of irradiation and temperature. The analysis performed is based only on the information included in the manufacturer’s datasheet.