CC BY
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COMPETITIVENESS OF A MOBILE APPLICATION IN TERMS OF ITS ENERGY
EFFICIENCY
R.M. Ismailova, Graduate Student
N.T. Sailaubekov, Doctor of Economic Sciences, Professor Kazakh-German University (Kazakhstan, Almaty)
DOI:10.24412/2411-0450-2024-5-1-200-205
Abstract. This article analyzes innovative technological approaches to improving energy efficiency and energy management through mobile applications. Focused on practicality and real-world effectiveness, the author conducts a thorough analysis of two distinct applications, assessing their competitiveness across various metrics including functionality, efficiency, and practical utility. The impact of these applications on changing user energy consumption behaviour is also examined.
Keywords: mobile application, energy management, smart app, energy efficiency, energy consumption.
Smart energy applications represent a modern fusion of human interaction and technological advancement, playing a significant role in influencing various energy habits towards developing sustainable urban environments. As highlighted by Pfenninger et al. [1], it's vital to utilize the behavioural insights of energy consumers when formulating effective energy policies intended for a green residential energy transition. Smart energy applications are seen as a cost-effective method to encourage sustainable energy habits, offering valuable energy insights to multiple stakeholders. They are also advantageous in executing widespread behavioural interventions to stimulate lasting behavioural modifications. Thus, these applications have the capacity to encourage behavioural changes driven by technology and promote investments in sustainability. According to Piero et al. [2], several app features can enhance the visibility and tangibility of the link between energy usage and environmental impact, and engaging with these apps can elevate awareness and initiate long-term change. The authors further suggest that data collected by smart meters can be directly displayed on smartphone interfaces, providing a real-time visualization of energy consumption data. The availability of market signals and weather data on the app also enables users to adjust their energy consumption in support of demand-side management [3]. Additionally [4],
it's argued that smartphones, given the considerable amount of time people spend on them nowadays, are the ideal platform for providing feedback and intervening in behaviour.
One type of mobile application designed to promote energy efficiency is the personal assistant app, also known as "smart energy apps," which provides residential users information about their energy consumption and tips to save energy. These apps enable two-way communication between utility companies and their clients, giving consumers comprehendible feedback about their energy usage habits. Studies show that digital interventions like smart energy apps can influence energy behaviour change at scale.
Smart energy apps offer an array of features to help households better understand and manage their energy consumption. Apps provide real-time feedback on electricity usage, displaying metrics like current and projected cost and kilowatt-hour consumption [4]. Many apps offer budgeting and goalsetting tools so users can set targets to reduce costs and environmental impact. Some apps incorporate elements of gamification, using points, badges, and leader boards to motivate users [5].
Darby [6] investigates the optimal design of smart meters, in-home displays, or web applications that can facilitate household engagement with energy consumption. Based on
her research, she suggests that a display should provide the following information:
- The instantaneous rate of consumption in kilowatts (kW).
- The corresponding spending rate in the local currency per hour.
- The total spending accumulated in the current day.
- The option to switch between monetary and energy units for spending.
Moreover, the display should allow users to access and compare their historical data in different time intervals, such as:
- Daily data for the past week.
- Weekly data for the past month.
- Monthly data for the past quarter.
- Quarterly data for the past year.
Additionally, the display should include
features that enable users to benchmark their usage against other households and to view the regional demand curve to gain a broader perspective on their energy consumption. Darby notes that these features are more feasible to implement in a web application than in an in-home display. However, she also acknowledges the drawback of web applications, which require users to actively seek out the information online rather than having it readily available in their homes.
Comparative analysis of two specific mobile applications.
For the purpose of this analysis, we selected two existing local mobile applications that are linked to a photovoltaic system on the rooftop of the Kazakh-German University. The first application is the VRM app, which communicates with the first photovoltaic system DKU.
This application enables real-time monitoring of solar energy generation. The application is compatible with both Google Play and App Store platforms.
The application contains such information
as:
1. Visual system of SES operation
2. Energy production status in kW
3. Information about connected devices
4. SES data collection archive with lots of options of time intervals:
- Last: 1, 3,6,12,24 hours;
- Last: 2,7,30,90 days;
- Yesterday, day before, this day last week, previous month, previous week, last 6 months;
- Today, this week, month, year;
- Future: tomorrow, next 2 days, day after tomorrow, next 7 days.
For the purpose of comparative analysis, the second mobile application was chosen -FusionSolar, which is connected to solar panels on the DKU roof and is available for download on the Google Play and AppStore platforms.
Compared to VRM, FusionSolar has advanced functionality, including:
1. Real-time monitoring of energy production and consumption (statistics);
2. Visual representation of connected systems;
3. Energy management section;
4. Section on environmental benefits;
5. Information about connected devices.
6. Setting the price of electricity;
7. Archive of collected data on SES with time intervals: day; month; year; entire service life.
FusionSolar provides three main aspects: energy management, revenue statistics and environmental benefits:
- Energy Management: Displays the energy production, energy consumption and self-consumption of a facility in different time dimensions. This helps analyze energy consumption trends and optimize energy costs. In energy storage scenarios, energy is stored and discharged, which improves the self-consumption rate.
- Revenue statistics: Calculates the amount of income from the sale of electricity (electricity sold multiplied by the tariff) and savings on electricity bills (self-consumed electricity multiplied by the purchase price). This allows you to display the benefits that a photovoltaic installation brings.
- Environmental benefits: Unlike thermal power plants, photovoltaic (PV) power plants generate electricity without CO2 emissions, which is equivalent to planting trees. Greenhouse gas emissions have increased global temperatures, causing severe impacts such as rising sea levels and extreme weather events (floods, droughts, hurricanes, etc.) [7].
How much CO2 can be avoided for every kilowatt-hour of electricity produced by PV? How many trees are equivalent to avoided CO2 emissions?
Saved and avoided fossil fuels and CO2 emissions:
If fossil fuels are used, 1 kWh of electricity consumes 400g of coal (international standard value), resulting in approximately 438g of CO2 (global average) [8]. When using PV, no CO2 is released. Formula:
Energy output PV x Avoided CO2 Emissions Factor (0.438) = Avoided CO2 Emissions (unit: kg)
Equivalent of trees planted: For example, if a tree has a lifespan of 40 years, the average amount of CO2 that can be absorbed each year is 18.3 kg. Formula:
CO2 Emissions Avoided / Tree Planted Equivalent Factor (18.3) / 40 = Tree Planted Equivalent.
Environment saving calculation example: Based on statistical data, the daily energy output from the solar power plant amounts to 45.77 kilowatt-hours (kWh). By applying the coefficient of CO2 emissions avoided (which stands at 0.438), we can infer the positive environmental impact resulting from this energy generation:
Equivalent CO2 emissions avoided - 20 (45,77*0,438 = 20,04726)
Equivalent trees planted - 2,7 (20,04726/18.3/40 = 0,02738697)
Based on the empirical data, we observe that the environmental benefits align with the calculated outcome, specifically indicating the preservation of two trees. This finding underscores the positive impact of sustainable practices on our ecosystem.
Figure 1 is described as a diagram of the structure of the FusionSolar mobile application. The structure includes several key elements and connections between them. First, the PV device (photovoltaic device) is connected to a communication module, which in turn is integrated with the Smart PV control system. Next, the FusionSolar app is used for device commission and can be accessed on both mobile phone and computer. Visually, the diagram shows the following: The PV device is connected to a communication module, which provides communication. In the upper left corner, the icon representing the device commission depicts a mobile phone with gears on the screen. The Smart PV control system is depicted as a cloud with graphs and data in the upper right corner. Another mobile phone icon, labelled FusionSolar app, is in the lower right corner and shows bar graphs on the screen. All these elements are connected by dotted lines, showing their interaction: the PV device is connected to a communication module, which in turn is connected to the device commission and the Smart PV control system, accessible through the FusionSolar application.
Figure 1. The structure of the FusionSolar App [7]
In addition, this application stands out for its visual appeal and ease of use, which is
confirmed by the following characteristics: an aesthetic white background, a pleasant font
size and style, the use of light colour palettes for various sections, and a variety of graph types (columns and circles). In their research, Costanza et al. conducted a field study titled «Understanding Domestic Energy Consumption through Interactive Visualization» [9]. The study explored an interactive visualization system designed for energy management, which was tested in real-world settings. This system enabled users to interact with their consumption data, linking it to specific activities in their daily lives. One of the system views presented a time-based plot showing average power usage within households. Users had the flexibility to navigate through time, zoom in, and examine shorter or longer periods in detail. Notably, users could annotate real-life events by selecting time intervals and adding symbols and textual descriptions.
This annotation feature effectively shifted users perception of energy consumption from being solely appliance-driven to being influenced by their activities [10].
Figure 2 is a chart that displays areas illustrating the comparative analysis of two previously researched mobile applications across 16 potential functional characteristics: For Android and iOS users; Real-time energy generation; Real-time energy consumption; Remote control of switch appliances on/off; Data archive by time intervals; Set saving goals; Recommendations and tips of energy usage; Monetary spending units; Green footprint; Display temperature outside; Customer support; Shopping store; Connection of smart devices; Payment function for energy invoice; Information about energy (news, papers, knowledge etc.); Gamification and rewards.
Figure 2. Visual diagram of VRM and FusionSolar
The chart above analyzes two important mobile apps: VRM and FusionSolar, shown in blue and red respectively. They are separated from each other by a ruler of their colour for visual comparison. The horizontal axis displays 16 potential functions that characterize mobile applications. Based on the results of the analysis, it can be seen that the mobile application, indicated in red, has a significantly wider range of functional features, exceeding VRM by a factor of two. This indicates the superiority of FusionSolar in a functional
aspect and highlights its potential for effective use compared to VRM.
FusionSolar: For Android and iOS users; Real-time energy generation; Real-time energy consumption; Data archive by time intervals; Monetary spending units; Green footprint; Display temperature outside.
VRM: For Android and iOS users; Realtime energy generation; Data archive by time intervals.
Rosenberg's model. To analyze the competitiveness of two mobile applications (VRM and FusionSolar), we resort to using the Ros-
enberg's model. This method is expressed by the following formula:
¿i = Zr=iViy,
where Aj - represents the subject of the suitability of the product (attitude to the product); Vj - importance motive for the consumer; n - number of motives; Ijj - subjective assessment of the suitability of the product to satisfy motive [11].
This method has the advantage that each product, in these case mobile applications, can be assigned a numerical rating, which makes it easier to compare their competitiveness: the higher the number, the more competitive the product [12].
However, identifying important motives for a product is often a difficult task, and the assessment depends on the subjective views of experts. Feedback from interviewees does not always provide insight into what product features need to be changed, nor does it provide comparisons with ideal features. To calculate the competitiveness of two mobile applications, FusionSolar and VRM, we will take the Rosenberg model based on the provided functional parameters and their weights. We assigned ratings to each of the parameters on a scale from 1 to 10, where 1 is low effectiveness or no function, and 10 is high efficiency or full compliance with the function. Based on the data provided, we determine the weight of each parameter (see the table).
Table. Evaluation of mobile applications
Parameters Weight FusionSolar scale VRM scale
Functionality 0.4 9 4
Ease of use 0.3 10 5
Performance 0.2 7 5
Safety 0.1 8 8
Total score 8.8 4.9
For FusionSolar App:
Afs = (0.4x9)+(0.3x10)+(0.2x7)+(0.1x8) = 3.6+3+1.4+0.8 = 8.8
For VRM App:
Avrm = (0.4x4)+(0.3x5)+(0.2x5)+(0.1x8) = 1.6+1.5+1+0.8= 4.9
According to Rosenberg's model, FusionSolar has a higher competitiveness with an overall score of 8.8 compared to VRM, which has an overall score of 4.9.
Conclusion.
The comparative study of the following mobile applications has shed light on several key points. First of all, the analysis conducted using the Rosenberg model confirmed that FusionSolar was highly competitive, scoring an overall score of 8.8, while VRM only scored 4.9. This indicates FusionSolar's significant superiority in terms of functional competence and market potential. In addition, a close analysis of the functionality of both mobile applications, presented in Figure 2,
demonstrates striking differences. FusionSolar offers a wide range of features - as many as 7, while VRM has only 3. This suggests that FusionSolar provides a more complete and effective set of capabilities, which can be a key factor in deciding which application to choose. It should be noted that these findings have important implications for various applications. A feature-rich app like FusionSolar can be an important tool for maximizing the benefits of solar energy, optimizing energy costs and promoting sustainability. Such innovations can help reduce dependence on traditional energy sources and facilitate the transition to cleaner and more sustainable solutions. Thus, considering the functionality and competitiveness of mobile applications such as FusionSolar and VRM highlights the need to select optimal solutions to achieve specific energy and sustainability goals.
References
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КОНКУРЕНТОСПОСОБНОСТЬ МОБИЛЬНОГО ПРИЛОЖЕНИЯ ПО ЭНЕРГОЭФФЕКТИВНОСТИ
Р.М. Исмаилова, магистрант Н.Т. Сайлаубеков, д-р экон. наук, профессор Казахско-Немецкий университет (Казахстан, г. Алматы)
Аннотация. В данной статье анализируются инновационные технологические подходы к повышению энергоэффективности и энергоменеджменту посредством мобильных приложений. Сосредоточив внимание на практичности и реальной эффективности, автор проводит тщательный анализ двух различных приложений, оценивая их конкурентоспособность по различным показателям, включая функциональность, эффективность и практическую полезность. Также рассматривается влияние этих приложений на изменение поведения пользователей в области энергопотребления.
Ключевые слова: мобильное приложение, энергоменеджмент, смарт-приложение, энергоэффективность, энергопотребление.
