Electricity Bill Research Articles

EMPOWERING A MOSQUE COMMUNITY IN MELAKA WITH SOLAR LIGHTING TECHNOLOGIES APPLICATION: A COMMUNITY-BASED APPROACH

This research presents a community-based approach to address energy security and energy-saving initiatives through the installation of solar lighting systems for a mosque community in Melaka. The aim is to foster community development while promoting sustainable energy practices, thereby fostering a sense of ownership and responsibility towards sustainable practices. It employs action-based research on-site, which involves participatory projects and empirical observation. The significance of this research lies in its dual focus on community empowerment and environmental sustainability by engaging stakeholders and local people to ensure energy self-sufficiency and sustainability of the project through green resources. A mosque in Merlimau, Melaka, has been selected as a case study and involves a mixed-method approach that leads towards collaborative efforts between researchers, community leaders, and local residents in the decision-making process. Ultimately, this research has ensured engagement among the locals, which aligns with the daily energy priorities of the mosque. By harnessing the power of 25 solar lighting systems (ranging from 10 watts to 200 watts), this mosque has managed to reduce its reliance on traditional energy sources, thus contributing to energy security and saving 10% from the monthly electricity bills. It has served as a tangible demonstration of the benefits of solar energy, inspiring broader adoption within other mosque communities in Malaysia. In the near future, the dissemination of solar lighting technologies is anticipated to contribute towards more sustainable mosques and increase the community development through resilient approaches.

PERANCANGAN PEMBANGKIT LISTRIK TENAGA SURYA (PLTS) PADA ATAP GEDUNG PARKIR BANDAR UDARA INTERNASIONAL I GUSTI NGURAH RAI

Using sustainable energy as a source of electrical energy is a safe way to increase ecosystem energy. One of them is the utilization of photovoltaic directed energy by upgrading the PLTS on top of the structure as a mechanism for introducing photovoltaic modules. The study finalized the plan to install PLTS on the roof of the I Gusti Ngurah Rai Airport parking lot as a source of electrical energy to reduce PLN electricity bills. The I Gusti Ngurah Rai Airport Parking Roof Solar Power Plant uses a battery-free on gridsystem with 600 units of 555Wp monocrystalline solar-based modules and four 100kW inverter units. The solar power plant to be built on the car park of Terminal I Gusti Ngurah Rai will have a capacity of 333kWp and will produce 604.929kWh of energy annually. The required speculation cost is Rp 3.004.620.000 and payback period for 6 years.

Impact of Multi-Energy System and Different Control Strategies on a Generic Low-Voltage Distribution Grid

The rising electricity costs, cost of space heating, and domestic hot water end up driving consumers toward reducing expenses by generating their electricity through devices like photovoltaic systems and efficient combined heat and power plants. When coupled with thermal systems via an energy management system (EMS) in a Multi-Energy System (MES), this self-produced electricity can effectively lower electricity and heating bills. However, MESs with EMSs can serve various purposes beyond cost reduction via self-consumption, such as reacting to variable electricity prices, meeting special grid connection conditions, or minimizing CO2 emissions. These diverse strategies create unique prosumer profiles, deviating significantly from standard load profiles. The potential threat to the power grid arises as grid operators lack visibility into which consumers employ which control strategies. This paper investigates the impact of controlled MESs on the power grid compared to average households and answers whether new control strategies affect the planning strategies of low voltage grids. It proposes a comprehensive four-step toolchain for the detailed simulation of thermal–electrical load profiles, MES control strategies, and grid dynamics. It includes a new method for the grid impact analysis of extreme and average bulk values. As a result, this study identifies three primary factors influencing distribution power grids by MESs. Firstly, the presence and scale of photovoltaic (PV) systems significantly affect extreme values in the grid. Secondly, MESs incorporating combined heat and power (CHP) and heat pump (HP) units impact the overall grid performance, mainly reflected in bulk values. Thirdly, the placement of an MES with heating systems, especially when concentrated in one feeder, plays a crucial role in grid dynamics. Despite the three distinct factors identified as impactful on the power grid, this study reveals that the various control strategies, despite leading to vastly different grid profiles, do not exhibit divergent impacts on buses, lines, or transformers. Remarkably, the impact of MESs remains consistently similar across the range of control strategies studied. Therefore, different control strategies do not pose an additional challenge to the grid integration of MESs.

Modeling the impact of end-user flexibility and bill structure on future transmission grid load

Demand-side flexibility is expected to play a key role during the transition towards renewable-dominated power systems and the electrification of transportation and heating sectors. Following this, massive investments in transmission capacities will be required, which may be reduced if end-users appropriately exploit their flexibility from the edge of the network. However, modeling the end-user flexible behavior and its impact on transmission grid load during the planning stage is not straightforward. The rationale behind this is that it results from the aggregation of atomistic loads and that it may be unlocked implicitly, i.e., via the structure of electricity bill. In this paper, assuming economically rational end-users, we develop an equilibrium model of end-users minimizing their electricity bill, while taking into account the elasticity of electricity prices. The proposed approach is used to derive updated transmission load projections, highlighting the benefits of considering end-user flexibility for transmission system planning.

Evaluating a floating offshore wind farm: Households’ willingness to pay in South Korea

South Korea intends to install a floating offshore wind farm (FOWF) with a capacity of 9 GW off its east coast by 2030. This article seeks to apply contingent valuation, analyze households’ willingness to pay (WTP) for this installation quantitatively, and derive some implications. Data on WTP were collected through a survey of 1000 households across the country. WTP was induced through the one-and-one-half-bound question method, and positive WTP and zero WTP were analyzed together through the spike model. Statistical significance was secured for the main estimation results of the model. The average WTP was KRW 3302 (USD 2.58) per household per month, which was about 7.5% of the average electricity bill. In addition, it was found that the respondents’ education level, income level, residence, and perceptions had a significant effect on their WTP. Finally, along with five challenges faced by the FOWF identified during the survey process, possible solutions to these are presented. For example, the most important challenge was acceptance by fishers.

Enhanced DC Building Distribution Performance Using a Modular Grid-Tied Converter Design

This work quantifies the techno-economic performance of AC and DC residential building distribution. Two methods, utilising software and hardware configurations, are showcased to improve DC distribution: (i) a novel rule-based battery dual-objective operation (DOO) and (ii) a modular Master/Slave design of the grid-tied converter (GC). Both methods use the GC’s load-dependent efficiency characteristic, eliminating partial-load operation and enhancing energy efficiency. The work uses measured annual PV and load data to evaluate the performance of the methods compared to AC and DC references. The techno-economic analysis includes the annual net electricity bill and monetised battery degradation. The results show that the DOO eliminates GC partial-load operation at the cost of increased battery usage, resulting in marginal net savings. In contrast, the modular converter design significantly reduces losses: −157 kWh/a (−31%) and −121 kWh/a (−26%), respectively, relative to the DC and AC references. For a parametric sweep of electricity price and discount rate, the Lifetime Operating Cost (LOC) comparison shows savings from DC of up to USD 575 compared to AC.

Implementations of The Digital Madrasah

The demands of the times demand the world of education to be able to adapt and use technological developments in an effort to improve the quality of learning. The current development of information technology provides its own challenges in the world of education especially madrasah. Basically, the madrasah is an important Islamic educational institution in Indonesia, where its existence has proven to have marked a generation of nations with deep religious insights and the soul of nationalism. Therefore, the educational institutions of the Madrasah must be able to adapt to such massive technological developments. The madrasas must be capable of utilizing and integrating technology in teaching activities so that it becomes relevant and contextual with the development of the times. The aim of this research is to take stock of the efforts made by MTsN 1 Makassar in transforming into a digital madrasah, to find out the supporting factors and obstacles in implementing the digital madrasah policy. This type of research is qualitative descriptive. The results of the research describe the efforts made at MTsN 1 Makassar in transforming into a digital madrasah starting from the planning stage of both activity planning and budget planning, strengthening the quality of SDM by forming the learning revolution team 4. Supporting factors are the large number of digital flatforms that are open access, the support of the parents of the students and the factors that hinder are the price of relatively expensive digital devices, large electricity bills and a less stable internet network.

Optimal sizing and energy management strategy for an office building with photovoltaic, heat pump, thermal tank, and electric vehicle under time-of-use tariff

The increasing demand for sustainable energy solutions is driving the integration of various renewable energy technologies. Integrating electric vehicle batteries, photovoltaics, heat pumps, and thermal tanks into building energy systems offers a promising approach to enhancing energy flexibility and efficiency. However, research on such integrated energy systems is still in its infancy. Optimizing the configuration and operation of the system may lead to significant cost savings and improved energy management. A coupled model and simulation-based optimization approach are used to optimize the thermal tank capacity and key operational parameters to minimize the annual total cost. The results show that the integrated energy system reduces the annual total cost by 36.35% and monthly electricity bills by up to 69.26% compared to the base system. As for energy flexibility, only 13.91% of electricity demand is supplied by the grid during peak periods, and the monthly load coefficient, load cover ratio, and photovoltaic self-consumption ratio of the integrated energy system are significantly improved. This study demonstrates the economic and operational benefits of integrating various renewable energy technologies into building energy systems and provides new insights into their design and optimization.

Efficient energy management of domestic loads with electric vehicles by optimal scheduling of solar-powered battery energy storage system

The increasing adoption of electric vehicles (EVs) and variable energy usage patterns substantially strain the electrical grid; indeed, optimal energy management, monitoring, and utilization are required for the reliable operation of the grid. This paper introduces a novel model design of a solar-powered battery energy storage system (SPBESS) as a viable substitute for conventional demand-side management (DSM) and time of use (ToU) pricing schemes, intending to optimize energy management and utilization with IoT monitoring. In addition, the IoT-based prototype has been developed to monitor and control the proposed system. To validate the proposed SPBESS model, the study examines two distinct cases: one encompassing domestic loads and the other integrating EV loads alongside household demand. Using ToU pricing, it determines the optimal charging and discharging strategies for the SPBESS, evaluates their implications for the system configuration and grid ToU pricing, and quantifies the annual reductions in power purchases, electricity bills, energy costs, and carbon emissions. Moreover, the study comprehensively analyzes the optimal power exchanges between the photovoltaic system, battery energy storage system, and the grid, precisely considering the specific load requirements and grid ToU pricing. The conducted research findings manifest considerable decreases in energy costs, with the domestic load condition witnessing a reduction from $0.312 per kilowatt-hour to $0.245 per kilowatt-hour and the scenario involving EV and residential loads experiencing a decline from $0.27 per kilowatt-hour to $0.197 per kilowatt-hour. Furthermore, the annualized cost savings for cases 1 and 2 amount to $1,336 and $4,544, respectively, yielding substantial reductions in polluting gas emissions. Besides, the IoT-based constructed prototype model design for real-time power parameters monitoring and control shows the importance of IoT-based monitoring for remote load control, allowing users to maximize energy efficiency, resource utilization, and system visualization.

Smart Electricity Meter Monitoring and Prediction using I-Socket

As the world's population and energy needs continue to grow, the demand for power is ever-increasing. This has put a strain on natural resources and renewable sources of power, which are not yet developed enough to operate self-sufficiently. In this context, optimal power sharing and efficient energy consumption is essential. To this end, a smart electricity meter monitoring and prediction system has been developed using i-Socket, a hardware module that tracks the energy consumed by each device in a house and estimates the monthly electricity bill. This system notifies the user when the bill surpasses a set limit and sets the monitoring rate of a connected device to the socket based on the type of device, making it an energy efficient system. Current sensor used is the ACS712 sensor and the microcontroller is Arduino UNO. A Boost converter is used for the power supply and the software application is developed for monitoring electricity bills. This system takes input of present data of current and predicts the meter reading for the following months. However, the same can also be achieved by using a python server for holding an ML model that will be developed to predict future price of the bill based on the current usage of power. This is acts as an affordable alternative to that by using the iSocket

ინოვაციური კონსტრუქციის მობილური კონდიციონერი

Mobile air conditioner is a portable device that is used to cool the air in rooms where it is not possible to install an air conditioner. It can be used in apartments, offices, hotel rooms, camps and other places. The basic principle of operation of mobile air conditioner is to take air from the air-conditioned room through the built-in fan, then the air passes through the filters and is cooled or heated in the built-in evaporator. The processed air is supplied back to the room through a flexible duct. One of the main advantages of mobile air conditioner is its portability. It can be easily moved from one room to another, and such air conditioner can also be taken to any address. Mobile air conditioner does not require complex installation and can be connected to a regular mains electricity supply. In addition, some mobile air conditioners may have a heating function during the cold season. However, mobile air conditioner has some disadvantages. It is usually not as efficient as air conditioner that requires installation (such as split type air conditioners), especially, in large rooms. It can also be noisy and take huge space in a room. It consumes more energy than built-in air conditioners, which can lead to higher electricity bills.

Towards sustainable smart cities: Integration of home energy management system for efficient energy utilization

Smart Homes (SHs) play a crucial role in the broader context of smart cities, contributing to the overall efficiency, sustainability, and quality of life for residents. This work presents a computationally efficient mathematical model for Home Energy Management Systems (HEMS) to activate the Demand Side Management (DSM) while minimizing the energy consumption costs of SHs. The proposed model is represented as a standard Mixed-Integer Linear Programming (MILP) optimization problem. The proposed HEMS provides the optimal scheduling of home appliances and plugging time for charging Electric Vehicles (EV) at home. The main objective of this optimization problem is to minimize the electricity bills while improving the load profile of the distribution system in the context of smart cities. In this study, load management for a typical household has been studied considering several electricity tariffs in Portugal. The simulation results confirm that in the presence of the proposed HEMS, the electricity bill will be effectively reduced while consumer behavior is changed. The cost savings that can be attained through only shifting loads is 5.7 %, while it can reach 67.65 % by installing a hybrid energy system at the studied smart home. The weekly cost reduction percentage due to charging the EV at home is around 16.24 % compared to charging the EV using public charging stations regardless of the traveling time and waiting at the public charging stations.

Non-price energy conservation information and household energy consumption in a developing country: Evidence from an RCT

We use a randomized controlled trial in Bangladesh to test three types of non-price energy conservation strategies that influence electricity consumption of households: (i) advice on electricity conservation methods (knowledge treatment); (ii) (median) electricity consumption of others in the suburb (suburb comparison); and (iii) (median) electricity consumption of neighbors (neighbor comparison). We find that providing advice on saving energy could reduce households' electricity consumption and bills significantly. The effects are stronger for advice on electricity conservation methods than neighbor and suburb comparisons. The effects of providing information about own electricity consumption relative to neighbors’ electricity consumption is similar to the effects of giving information about own electricity consumption relative to electricity consumption of households in the same suburb. The effects among households who were inefficient users in neighbor and suburb comparison groups are almost as strong as those in the knowledge treatment group. The effects across all treatment groups become stronger over time as they receive repeated information.

Second-best electricity pricing in France: Effectiveness of existing rates in evolving power markets

The adoption of time-varying pricing in the French electricity market has been historically low despite their availability to consumers well before the deployment of smart metering. However, as the share of variable renewable electricity increases and carbon prices grow, the demand-side response will become increasingly important to achieve efficiency gains. Relying on the historical hourly consumption of French electricity consumers and multiple prospective weather years, we study the gain allowed by the broader adoption of time-varying electricity retail rates in low-carbon power systems. We develop a four-stage methodology to assess the efficiency and stability of the electricity supply cost component of the electricity bill in France for historical and prospective years. Our analysis demonstrates that peak pricing schemes have increasing interest in the context of further deployment of renewable capacity, capturing 25% to 50% of the welfare gain reached by real-time pricing schemes. The corresponding deadweight loss of peak pricing schemes represents 0.4 to 1 bn EUR per year in 2030 compared to real-time prices (RTP) schemes. Conversely, deadweight loss of current time-of-use (ToU) rates represents 1 to 1.2 bn EUR per year in 2025 and increases over time. The current design of TOU rates does not provide adequate incentives in future power systems. Besides the tariff efficiency, the results underlined an increasing price difference between on-peak and off-peak rates. This questions the social acceptance of time-varying retail rates for consumers unable to hedge against peak prices. By analysing the effectiveness and limitations of time-varying rates, our findings underline the importance and value of price-based DR in future power systems in general. Our results highlight the need to revise the end-user tariff design in the French power system, notably with regard to the conveyed price signals.

A Numerical Analysis Based Internet of Things (IOT) and Big Data Analytics to Minimize Energy Consumption in Smart Buildings

The new wave of performant technology devices generates massive amounts of data. These devices are used in cities, homes, buildings, companies, and more. One of the reasons for digitalizing their tasks is that over the past few years, there has been an interest in reducing carbon emissions and increasing energy efficiency to create a friendly ecosystem and protect nature. One of which granted the explosion of data. After deploying these new devices, a significant increase in the use of the other face of energy to implement the components of the new devices was noticed. Above all, the interconnection of these intelligent devices is the central concept of the Internet of Things (IoT). This domain has widened the possibilities for the interconnection of building management systems (also named Smart Grids) and devices for better energy management. Furthermore, its potential is realized only after organizing and analyzing a large amount of data. Real-time management and maintenance of big data are critical to improving energy management in buildings. The benefits of big data analytics go beyond savings on electricity bills. It can provide comfort for building users and extend the life of building equipment, enhancing the value of commercial buildings. Intelligent interconnection of a building’s technical installations (lighting, heating, hot water, photovoltaic installations, etc.) not only allows for connected management of this equipment but also meets high energy efficiency criteria that indicate an increase in comfort and energy savings. With building automation, the technical installations of a building interact optimally. In this article, we will simulate an intelligent building based on the Cisco packet tracer software. To better manage the energy consumption of our project, we will focus on the processing of data in real-time, especially since we will have a massive amount of data generated by the sensors.

Energy Consumption Analysis and Management Strategies for the Dairy Farm in India Towards Sustainable Development

Environmental pollution and the rapid decline in the availability of fossil fuels are the major concerns of the electric power industry in recent years. Effective utilization of electrical energy is the need of the hour in building the nation towards sustainable development. This study presents the energy consumption analysis and management performed in a diary firm located in Tamil Nadu, India. Initially, the energy usage of the firm is estimated based on its electricity bills, meter readings, and survey followed by detailed energy consumption analysis and evaluation. The study employs guidelines provided by the Indian Bureau of Energy Efficiency for energy management. The detailed analysis performed finds scopes for improvement in efficient energy usage. Numerical analysis shows that implementation of proposed action plans that include installation of automatic power factor correction, replacement of overheating equipment, and replacement of lighting systems with energy-efficient lighting would save annual energy of 123.96 kWh which in turn results in the reduction of annual CO2 emission by 117.76 tonnes. Furthermore, this paper also proposes a novel optimal process scheduling which optimally schedules different processes in the firm without affecting productivity. This makes an additional savings of INR 4,23,360 per annum in the energy cost by minimizing the maximum demand of the firm with zero investment. A comparison of the proposed approach with existing methodologies available in the literature shows the effectiveness of the proposed technique.

Customer's response to dynamic pricing in utility energy Tariff quality and reliability with the time of use: An Empirical case study of household electricity customers in Indonesia

Time of Use (ToU) is one of the types of dynamic pricing strategies at which a pricing scheme employs a variable rate rather than a fixed one causing electricity tariffs over a particular consumption period to rise once in high consumer demand at peak times and to fall once the demand is low at off-peak times. Owing to the important factor of perceiving customers' response to the successful implementation of the ToU tariff scheme, this study examines the household electricity customers' response in Indonesia - especially residents of Java Island and Bali Island - to future implementation of this dynamic pricing strategy in utility energy tariff quality and reliability. Data on the behavior of the PLN customers need to be thoroughly gathered and then analyzed quantitatively for well-informed decisions on a set of variable rates based on peak/off-peak times of the day and the season to establish in a board of directors' room. Hence, survey work is conducted, and a questionnaire is carefully designed and developed in this study to help collect and analyze the data on consumer behavior. The results show that customers’ response exhibits a promising outcome. At the total number of 451 respondents, 63 % of the survey participants expect to opt into the ToU scheme and the reason for this is their sensitivity to a bargain price of the electricity rate. However, 37 % of the respondents find ToU burdensome to implement and very demanding, as a result they opt out of the ToU scheme. From the results of the survey, it can also be inferred household energy-related activities that customers are quite willing to shift are washing and ironing clothes where a shift in these activities would lead to potential savings in the electricity bills of 26 % off the regular price. From the use of the quantitative method in this study, the total potential daily load reduction of energy consumption with the ToU tariff scheme could reach 3,23 kW for each customer. The findings conclude that customers have presented an encouraging response to future implementation of ToU and express their thoughts ToU seems to bring potential benefits of saving electricity bills and looks as if it is fairly easy for customers to adapt to shifting their energy usage from peak times to off-peak times.

The economics of public transport electrification: The charging dilemma

The electrification of public transport has the potential to mitigate greenhouse gas emissions and support the electricity system, however this potential depends on how intraday charging interfaces with grid emissions and wholesale prices. Our paper explores these trade-offs by using boundary analysis to evaluate a least-cost tariff-based aggregate bus fleet charging strategy and comparing it to charging strategies that either minimise indirect greenhouse gas emissions or wholesale price exposure, based on the metropolitan Melbourne bus network. We develop a novel two-state fleet charging optimisation model, that allows us to perform a counterfactual analysis across 5 years of historical (2017–2021) and 5 years of modelled (2022–2026) changes to wholesale electricity prices and emission intensities in Australia's National Electricity Market, in response to the three charging strategies. We find that current Australian commercial tariff structures with high daytime volumetric usage and demand charges mute climate and wholesale market signals. By charging to minimise greenhouse gas emissions over bill savings, the fleet can achieve (on average) a further 33.4% reduction in indirect emissions but incurs a 103% increase in annual electricity bills. Alternatively, by charging to minimise wholesale price exposure, the fleet can achieve (on average) a 13.4% reduction in indirect emissions while incurring a 69% increase in electricity bills. Improving the temporal alignment of commercial electricity tariffs with wholesale prices should thus simultaneously reduce indirect emissions and wholesale electricity costs. This necessitates urgent tariff reforms to allow relevant wholesale price signals to pass through to commercial EV operators.

Impact of Economic Awareness on Sustainable Energy Consumption: Results of Research in a Segment of Polish Households

This manuscript explores the relationship between the economic awareness (as a part of energy awareness) of Polish households and their sustainable energy consumption practices. Sustainable consumption is measured by the frequency of behaviors such as turning off electrical devices when not in use, removing mobile device chargers from sockets, switching off lights when leaving a room, preferring showers over baths, using washing machines and dishwashers only when full, and purchasing energy-efficient appliances and light bulbs. Economic awareness is gauged through variables such as knowledge of electricity tariffs, understanding of electric bill components, awareness of electricity prices, exact knowledge of electricity expenses, electricity usage in kWh, knowledge of effective energy-saving methods, and familiarity with the energy efficiency classes of appliances and light bulbs. This study presents profiles of households with high and low economic awareness regarding their electricity expenditures and examines how these profiles differ in their sustainable energy consumption behaviors. This research is based on a survey of 1407 Polish households conducted online in 2023. Data collected from the survey were subjected to statistical analysis and are presented in tables and graphs. The findings are discussed in the context of the existing literature in the field, highlighting the implications of economic awareness on sustainable energy consumption practices. This research contributes to understanding how economic knowledge influences energy-saving behaviors among Polish households, providing insights for policymakers and energy conservation initiatives. One of the key findings of this paper is the significant association between economic awareness, energy-saving knowledge, and the adoption of sustainable energy consumption behaviors among Polish households. This study reveals that households with higher levels of economic awareness demonstrate a notably higher frequency of practices related to sustainable energy consumption compared to those with lower economic awareness. Similarly, households equipped with greater knowledge about energy-saving techniques exhibit a higher propensity to adopt energy-efficient behaviors. This underscores important roles of economic literacy and education in fostering behavioral changes towards more sustainable energy practices, highlighting the importance of targeted interventions and educational campaigns aimed at enhancing economic awareness and promoting energy-saving knowledge among consumers.

State and potential of digital financial services among farmers in Bangladesh: An in-depth study

Technologies like digital mobile services have a greater role in societies, particularly among agricultural communities for financial transactions. Keeping this in mind, the current study investigated the present status and potential of digital financial services (DFS) among farmers in Bangladesh. A total of 400 farmers were interviewed directly through a random selection to assess the present status and conducted 30 KIIs for potential. The study utilized a mixed-method approach, incorporating quantitative analysis via the Relative Importance Index (RII) and qualitative analysis through transcriptions. It was found that 87.3% of the farmers use DFS, with bKash being the most popular platform. However, the use of DFS was relatively limited when it comes to farm transactions. In case of farm's electricity bill payments, the number of responses was higher compared to other items. Furthermore, the study highlighted that farmers have lower satisfaction level with DFS than cash in case of farm transactions. This is due to the fact that farmers perceive using DFS for financial transactions as very difficult, which is compounded by a lack of knowledge on PIN changes (70.5%) and familiarity with terms and conditions (72%). Additionally, 42.86% of farmers reported experiencing scams, a higher prevalence compared to other issues. In such instances, farmers lodged complaints with agents but did not receive satisfactory resolutions. Therefore, the study suggests to implement user-friendly DFS interfaces tailored for agricultural use, initiate farmer-focused financial literacy programs, enforce robust security measures, and establish a regulatory framework for DFS integration into agriculture.