Technical and Economic Analysis of the Use of Electricity Generated by a BIPV System for an Educational Establishment in Poland

Abstract

In the face of ongoing climate changes and the current geopolitical situation, Renewable Energy Sources (RES) are continuously gaining popularity in many countries. Objectives related to environmental protection and the use of RES set by different countries all over the world, as well as by the European Union (EU), are becoming priorities for many. The increase in the installed capacity of photovoltaic systems has been growing steadily for several years, leading to the creation of new systems accompanying PV installations; this phenomenon has also been observed in Poland. This paper presents a photovoltaic system in the form of a bicycle shed next to a school building as an example of building-integrated photovoltaics (BIPV) without connection to the power grid. It was shown that the energy consumption profile should be properly correlated with the production profile, otherwise significant losses occur. Alternative methods to improve the correlation of production and energy consumption by using SCADA systems or building automation to properly manage the electricity generation and consumption installation were also proposed. Furthermore, it was shown that adopting a fixed discount rate in financial analyses can distort the picture of real profits. An analysis of the changes in the NPV ratio using variable discount rates was carried out when analyzing the entire life of the solar plant.

1. Introduction

The current geopolitical situation around the world, and especially in Europe, is conducive to the continuous development of renewable energy technologies (RES) and their application in various areas of life and the economy, including in Poland. Following the great boom in photovoltaic micro-installations aimed at prosumers, many companies have been investing in their own sources of electricity generation in order to become independent of electricity supplies and prices, and to participate in the energy transition of their country and the European Union (EU). In the situation that has arisen, individual EU member states have been creating their own programs aimed at achieving common RES targets set by the EU. At the end of 2022, the capacity of all generation sources in Poland had exceeded 60 GW (a year-on-year increase of 1 GW) and the share of RES was as high as 36% (22 GW), of which more than 55% is accounted for by photovoltaics and 36% by wind power. Thus, Poland had already met the minimum objectives for the amount of RES in the country’s power system for the year 2040 in 2022. However, large installed capacities in unstable RES cause problems in power grids and contribute to frequent shutdowns of PV inverters. Therefore, it is necessary to upgrade the power distribution grid, or to take other measures to support the local consumption and storage of energy generated from PV micro-installations. At the end of April 2023, the total capacity of PV plants connected to the electricity grid in Poland exceeded 13.5 GW, of which more than 70% (9.48 GW) were low-power prosumer installations. The average capacity of a new PV installation constructed in April 2023 was around 26 kW, while at the same time in 2022 it was approximately 14 kW. The result is a demonstrable increase in the per-unit installed capacity in micro-installations. This is due to the already quite strong saturation of the domestic installation market and the increased interest and investments in PV installations by small and medium-sized enterprises, which can install PV installations up to 50 kW under the Prosumer Act [1,2,3].

An important factor in the design and analysis of PV systems is the costs of the installation over its lifetime. For this purpose, computer software is used to help analyze the energy potential of a designed PV system placed at a selected latitude. The use of programs such as PVSOL or PVsyst is common in many publications [4,5]. Calculating and selecting the appropriate equipment for a PV system is only the first part of the design process. The second, and equally important, parts are the economic considerations, which determine the profitability of the investment. This approach can be found in a great number of publications. One of these is [6], whose authors estimated the discount rates and presented a profitability analysis for a photovoltaic installation located in Spain using the financial approach. On the other hand, in Malaysia and Indonesia, paper [7] presents an analysis of the cost of energy generation and determines the payback time for different assumed values of the discount rate, which remain constant throughout the life of the installation. Another example is a technical–economic analysis of a PV system for a residential building located in the UK [8], which provides indicators such as net present value (NPV) and discounted payback period (DPP) for feed-in tariffs (FITs). It was determined that the system was able to cover the building’s electricity needs between April and October, with excess electricity being exported to the grid during this period. The payback period for the investment was determined to be around nine years. In the article [9], for a household located in Croatia, the capacity of the photovoltaic system was determined taking into account the payback period. A payback time set at 10 years, and discount rates of 0% and 4.5%, were adopted in the optimization. The authors in the article [10] determined the cost-effectiveness of the investment using the NPV ratio for Germany, the state of Colorado and Spain. It was determined that the NPV over the entire lifetime may be overestimated without considering the possible replacement of system components (mainly inverters and energy storages).

Other types of investments, not limited to households, are also considered for this type of economic analysis. One example is an analysis of the possible transition from agricultural to manufacturing activities in Ukraine using PV [11]. A discount rate of cost-effectiveness was determined, ranging between 1.26 and 3.24, together with carbon footprint per hectare of land occupied by a PV system. Furthermore, the payback period of the installation was determined to be between 5 and 10 months. Similar objectives were adopted by the authors of paper [12], whose area of study focused on the establishment of willow and poplar plantations. For the 5% discount rate and three subsidy scenarios, economic profitability was analyzed on the basis of discounted cash flows, net present value (NPV), internal rate of return (IRR) and profitability ratio (PI).On the other hand, the article [13] provided a comparative analysis for ground-mounted photovoltaics and agricultural crops for areas in Poland and Ukraine with the most insolation. Among the authors’ findings was the determination that the net present value of photovoltaic projects exceeds that of crop-growing projects. However, they have lower profitability rates than the commonly used agricultural practices.

The introduction of new solutions with bPV (bifacial) panels was presented, for example, in [14]. Analysis based on the measure of the levelized net cost of electricity generation (LCOE) showed an increase in power output between 5% and 30% for initial costs that were 0–15.6% higher, and a decreased levelized cost of energy (LCOE) by 2–6% in comparison to single-sided technology (mPV). A similar study is presented in [15], where the authors analyzed a photovoltaic system using flexible panels on flat, cylindrical and hemispherical bases. The determined annual energy production was, respectively, 810 kWh, 960 kWh and 100 kWh, followed by an economic analysis, identifying NPVs of approximately USD 697 and 956, with internal rates of return (IRR) of 34.81%, 39.29% and 40.47%.

The integration of photovoltaics into a smart building is also being studied. The paper [16] presents a model of the McFarland Science Building at Texas A&M University Commerce in Texas, for which an economic analysis of two popular green roof systems and a BIPV system was carried out. The averaged results of the study show that the levelized cost of electricity (LCOE) of the green roof system is approximately 39.77% higher than that of the BIPV system at a discount rate of 5%. A study of building integration with photovoltaics has also been carried out, focusing on reducing the carbon footprint by replacing elements of the façade during building renovation in South Korea. The calculations of cost-effectiveness and carbon footprint were performed for the periods of 25 and 50 years. Data analysis indicates a 30% reduction in greenhouse gases, and a payback period from 12 years for flats to 41 years for multi-purpose buildings [17]. An analysis based on deterministic methods was carried out in [18], investigating a conventional and a BIPV installation in Brazil. It was found that the systems in the eight cities included in the study achieved a positive NPV. On the other hand, the authors of [19] demonstrate a 25% decrease in electricity consumption when using smart building management systems without the necessity of altering the comfort of life of the users in any way.

Electricity management is a very important element of reducing peak energy consumption. The authors in [20] present a PV management system combined with energy storage and an electric vehicle forming a microgrid, which is used to describe the advantages in the form of flattening the energy demand characteristics in the residential sector. Another example in which energy management increases self-consumption from approximately 20–30% to approximately 50% is described in [21].This work focuses on the study of smart microgrid solutions with PV and energy storage connected to the internet with a view to optimizing the costs of electricity procurement. The authors of [22] achieved a 50% reduction in energy costs. Another example is provided in paper [23], wherein the authors demonstrate a hybrid PV installation, with management solutions that allow for increased consumption for their own needs from 7% to 18% in a monthly period, and 13% annually.

According to [24], the use of BIPV technology facilitates, as well as energy savings, many other economic, social, cultural and architectural benefits. BIPV systems can be better integrated into building architecture without standing out; it can be argued that they bring about a positive effect on the building’s aesthetics, especially of historical and sacral buildings, in which case the Monument Conservator Office often does not give permission for installing traditional BAPV systems. Furthermore, BIPV components also have a positive impact on the entire energy performance of the building.

As follows from the literature survey, the current research efforts focus on managing the electricity generated by photovoltaic systems in order to increase energy self-consumption. To this end, the entire system design is often software-assisted. However, from the perspective of the investor, the payback period on the investment is the primary concern. In the articles presented, the authors use fixed discount rates over the period of the planned investment, which do not always provide representative results. Particular attention should be paid to recent years, in which economic instability has affected the profitability of many investments. One suggestion is provided by [25], in which the authors suggest an adjustment to the discount rate value of investments based on natural resources, which will indirectly account for changes in resource prices.

The increase in the unit power in PV micro-installations, the problem of their frequent switching on and the resulting periods in which they do not produce energy under even the best possible weather conditions cause losses for investors, and call for countermeasures in the form of, for example, the installation of an energy management system and changes to the load profiles to match the current PV energy output. Therefore, the authors of this paper presented a concept of a BIPV installation in a primary school in Poland. An analysis of its operation and energy yields was carried out using a system that protects the energy outflow to the grid using an on-grid inverter. It was recognized that the period of energy production would not exactly correspond with the energy consumption in the facility (as the school is closed in July and August, when there is a large PV energy output). Therefore, a portion of the energy produced in this period will be lost, due to the protection system preventing its outflow into the grid. With the goal of reducing these losses, the authors of the study attempted to improve the current solution. Therefore, an economic analysis of the existing installation was carried out in several variants, with alternative solutions proposed to improve the economic indicators of the installation. A PV system based on traditional PV panels was analyzed, leading to a significant improvement in profitability, including automation and smart control of the distribution of the energy output, with the objective of not limiting the productivity of the installation. The impact of the discount rate on the values of the achieved economic indicators was also analyzed; in the current geopolitical and economic situation prevailing in the world, these remain significant factors influencing investment profitability and feasibility. The majority of available analyses still utilize constant discount rates throughout the entire lifetime of the installation, whereas the authors of this paper demonstrate that even minor changes to the rates, amounting to only a few percent accrued over a period of 25 years, will affect the feasibility of investment in a PV installation.

In summary, the authors of this paper, based on the analysis of data from an actual photovoltaic installation integrated with a school building, propose the following:

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The PV installation is to be equipped with a building automation system, enabling the use of more energy generated by the PV system (reducing the non-productive time of the existing installation, which results from the existing off-grid implementation together with a protection system preventing energy outflow into the power grid), which serves to reduce the payback period of the investment, as well as to limit the occurrences and frequency of system shutdowns;

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The SCADA system is to be employed to monitor the operation of the PV installation together with the electrical devices in the school facility, with the option to control their operation and also data archiving.

The authors performed comparative economic analyses of different PV solutions: an existing off-grid school BIPV system, an on-grid BIPV system, and a free-standing system based on traditional PV panels. In addition, they demonstrated the impact of adopting a fixed and variable discount rate for the NPV of the investment.

The work has been structured as follows: Section 1 contains the literature background and an indication of the authors’ contribution to the researched topic. Section 2 describes the weather conditions and energy yields of the BIPV installation installed in a school in central Poland. The improvements introduced to the PV installations through the integration of SCADA systems and building automation are presented in Section 3, while the economic analysis of the analyzed PV systems is provided in Section 4. Section 5 presents a comparative discussion of the results of the implementation of the various systems that were analyzed, and Section 6 provides synthetic conclusions drawn from the work.

2. Characteristics of the BIPV Installation at a School in Rokietnica

2.1. Characteristics of the PV Installation

The presented photovoltaic installation at the school in Rokietnica serves a dual function. In addition to its primary energy generating function, it is also used as a bicycle shed for the pupils. The system, installed at the end of 2017 and manufactured by ML System, comprises two parts: the roof section includes 132 photovoltaic modules with a capacity of 158 W each, while the side wall includes 124 photovoltaic fins featuring glass-to-glass technology and a per-unit power of 70 W (Figure 1). The total output of the PV system is 29.54 kW. The energy produced by the system is exclusively for the school’s own consumption, as the installation is not connected to the main grid. When the system’s energy production exceeds the consumption, a special protection system triggers to prevent the outflow of energy to the grid. The installation uses Fronius 20 kW and 8.2 kW on-grid inverters, respectively, for the roof and wall sections of the PV system thanks to the protection system, which controls and blocks the energy outflow to the grid. The modern and functional photovoltaic installation, together with many other adapted sustainable features, allowed the school building to receive the title of “Best Ecological Building in the Public Sector” awarded by the Polish Green Building Association [26,27,28].

The energy management system used is characterized by the following functions [29]:

• Visualization of the status of each inverter in the photovoltaic system;
• Visualization of energy yields;
• Failure diagnostics of each inverter in the photovoltaic system;
• Web-based access to the interface for multiple operators at the same time;
• Anonymous access, with no login required, in order to visualize the yield on a public website—e.g., presentation of CO₂ savings;
• Measuring and statistical data are stored in a secure SQL database.

The electrical switchboards of the building and the PV system (shown in Appendix A to Figure A1) were fitted with energy analyzers communicating with the PV inverters. The devices used with the software analyzed the operation and productivity of the PV installation, as well as the energy consumption of the facility via the Ethernet and TCP/IP-based communication protocol for the correlated control and management of the system operation as a whole.

Given the fact that the PV installation was not connected to the power grid, despite the use of an on-grid inverter, it was necessary to create an Energy Reduction System (ERS, as part of the energy management subsystem), which managed the operation of the PV inverters, based on the measurements of the PV system’s energy output and the facility’s own consumption. The Energy Reduction System consists of three basic components [29]:

(1)

PV inverters equipped with a communication card;

(2)

The Energy Reduction System Controller;

(3)

The Electricity Network Metering System that communicates directly with the ERS controller. It measures the electricity in the four quadrants and the result of the analysis is captured by the ERS controller, according to Figure 2.

The ERS system operates in the following steps [29]:

• After initiation of the power supply, the ERS controller tests the power grid for 60 s;
• The ERS controller establishes a connection to the inverters during this time and checks their readiness for synchronization with the power grid. The photovoltaic inverters are interconnected via an internal communication bus—the first inverter provides the measuring data together with the communication interface (e.g., TCP/IP);
• The contactors S1 and S2 in the power switching station remain switched off until the initiation of the connections of the ERS controller to all components is completed. During this time, the ERS controller analyzes the amount of energy consumed by the facility. The software implemented in the controller knows the available power in the system and, based on the current DC voltage values of the inverters, determines the power the inverters should supply to the power grid;
• The ERS controller sends a command to the PV inverters to set them to a certain percentage of their nominal power. After the command has been sent, a time delay (usually 2 s) is allowed for the ready response from the inverters regarding the desired power range setting;
• The ERS controller switches the contactor in the main switching station on/off, and this couples the photovoltaic installation with the power grid;
• Photovoltaic inverters begin to operate, returning the power to the main switching station of the building at a preset power output;
• The ERS controller analyzes the data received from the power grid analyzer (at the connection to the building).If a change in the amount of energy consumed by the building is observed, the controller sends a command to the inverters to decrease or increase the amount of energy supplied. The time required to change inverter settings ranges between 1 and 10 s (most often 2 s), and this is related to the change in the capacitor battery capacity in the photovoltaic inverters and the need to tune the MPPT systems to the new settings.

The Energy Reduction System reduces the amount of energy generated proportionally on all inverters, so that the total generated power does not exceed the consumed power minus 25%. The energy returned to the building is reduced in three stages [29]:

(1)

Switching on of additional loads in the building (e.g., water heaters, washing machines, pumping stations, water treatment plants, etc.);

(2)

Reduction in the amount of energy released by the photovoltaic inverters (Figure 3);

(3)

Total disconnection of the photovoltaic installation from the building’s electrical system, which occurs when an anomaly in the energy generated is detected or when the following limit conditions are exceeded:

• Undervoltage protection—U = 195 V, t = 100 ms;
• Overvoltage protection—U = 253 V, t = 100 ms;
• Sub-frequency protection—f = 47.5 Hz, t = 100 ms;
• Over frequency protection—f = 51.0 Hz, t = 100 ms;
• Island operation protection—t = 200 ms;
• Amount of energy returned to the power grid—Po > 0.5 kW, t = 200 ms;
• Reconnection to the grid after an emergency shutdown—tmin = 300 s.

Figure 3. PV inverter power reduction process diagram [30].

Figure 3. PV inverter power reduction process diagram [30].

2.2. Analysis of the Climatic Conditions at the Installation Site

In order to present the conditions of insolation prevailing in the area of the Rokietnica commune, the data for the Typical Meteorological Year provided on the website of the Ministry of Infrastructure and Development were used [31]. Additionally, the developed data were accepted by the European Committee for Standardisation and were incorporated in the standard EN ISO 15927-4Hygrothermal performance of buildings—Calculation and presentation of climatic data—Part 4 Data for assessing the annual energy for cooling and heating systems(Polish version: PN-EN ISO 15927-4:2007—Cieplno-wilgotnościowe właściwości użytkowe budynków—Obliczanie i prezentacja danych klimatycznych—Część 4: Dane godzinowe do oceny rocznego zużycia energii na potrzeby ogrzewania i chłodzenia PN-EN ISO 15927-4:2007) [32]. Figure 4 shows the aggregate value of the total solar irradiance incident on the horizontal surface for the city of Poznań (geographical coordinates 52°25′ N, 16°51′ E). This location was chosen because it is the closest (about 15 km) to the discussed photovoltaic installations. At the location given, the average energy yield from photovoltaic installations is more than 1000 kWh/kW [31,33].

As follows from the above graph presenting the distribution of total solar radiation, only five months (summer period) exceed the limit of 100 kW/m² in the yearly period. This is evidently the most favorable period for electricity generation from photovoltaic modules. In the winter or the late fall months, the insolation conditions are unfavorable for the efficient and effective operation of photovoltaic panels, and the value of the total solar irradiance incident on the horizontal plane ranges between 18,375 and 45,552 W/m². For photovoltaic systems installed on school buildings, this situation is not ideal, because the highest demand for electricity by schools is seen during the winter months, whereas in the July–August period, when the conditions for photovoltaic systems are very good, schools are not used by students.

2.3. Analysis of Energy Production by the PV Installation

The PV system installed at the school in 2022 generated 24,005 kWh of energy, which accounted for 39% of the building’s total demand. Additionally, energy equal to 37,533 kWh was drawn from the grid. The total electricity consumption of the school building was 61,538 kWh.

The average annual energy output of the PV installation, over the five years of its operation, is approximately 17,642 kWh, which, considering the rated system capacity of 29.54 kW, represents an annual yield of only about 600 kWh/kW. Figure 5 shows the electricity production for each month of the year, for the years 2017–2022. One can infer that the most productive period, given the entire range, was in 2022, whereas the least productive period was in 2019. However, it must be remembered that the installation only produces electricity to meet the current demand, so in the summer months, when weather conditions are most favorable and, furthermore, the school was closed due to the COVID-19 pandemic (2020), the installation did not operate for long periods, as it was shut off by the protection system preventing energy from flowing into the grid.

When analyzing the graph from the standpoint of PV output, it can be noted how important the summer months are for the total energy output of the PV system. For the year 2022, the periods from November to February amounted to 9.7% of the total electricity in the entire year. By comparison, the energy production in July 2022 alone exceeded, by 4.34%, the output of the entire November–February period. This demonstrates the importance of matching the output of the energy generation system and ancillary equipment with the type of activity taking place at the facility, which translates into an energy consumption profile.

If a traditional, ground-based, on-grid PV installation, with an identical capacity of 29.54 kW, were to be built instead of the analyzed BIPV system in the form of a bicycle shed, its annual energy yield would be approximately 31,644 kWh, i.e., 32% more than the actual yield of the system constructed in 2022.

Assuming a coefficient of avoided CO₂ emissions of 823.257 kg CO₂/MWh [34] due to the operation of the PV system for 25 years, it can be calculated that this system will contribute to 446.63 or 588.76 tons of avoided CO₂ emissions, respectively, for the school BIPV system and the free-standing solution.

2.4. Economic Information on School Facilities in Poland

Public establishments are required to include electricity purchasing in the municipal budget, allowing for the continued prospect of investment opportunities. For this reason, in accordance with Art. 132 et seq. of the Public Procurement Law (Journal of Laws of 2021, item 1129 as amended), local governments invite energy distributors to submit bids in an open tender procedure. Then, in accordance with Article 139 of the Public Procurement Law, the contracting authority evaluates the bids submitted for eligibility and attractiveness, and finally selects the most advantageous bid in terms of its final conditions. At the time of the construction of the photovoltaic system in Rokietnica, the applicable price of electricity was PLN 0.3396/kWh, as set by the tender held in 2019, and fixed for the years 2020–2022. In the case of the year 2023, the price of electricity is PLN 0.785/kWh, this being the maximum rate for local government units, as approved by the Council of Ministers [35,36].

The total cost of the photovoltaic installation in the form of a bicycle shed was PLN 536,439 and comprised, in addition to the PV incorporated in the BIPV system, the various associated systems. The subsidy for this investment, within the framework of the project “Expansion of the Nobel prizewinners’ lower secondary school in Rokietnica”(Gimnazjum im. Noblistów w Rokietnicy), financed by the Wielkopolska Regional Operational Programme 2014–2020, amounted to PLN 176,220 [29]. The price of the investment is approximately three times higher than a traditional PV installation, but the installation under analysis serves as an example implementation of the BIPV technology, i.e., photovoltaics integrated into the building with additional energy management systems. BIPV photovoltaic modules and lamellas are characterized by a higher price compared to traditional ones, due to their different wattages, colors and sizes. In this implementation, such a number of modules serves the additional function of protecting the bicycles from adverse weather conditions.

3. SCADA and Intelligent Building Systems as Methods to Increase the Profitability of Investments in Photovoltaics

As shown in the earlier part of this paper, the photovoltaic installation under consideration could generate a significantly higher amount of electricity when compared to an on-grid inverter system with an ERS controller to manage the building’s own needs. From an economic point of view, the difference in the amount of energy generated and managed represents a loss that will lengthen the payback period of the investment. Thus, mechanisms need to be introduced to increase the level of self-consumption, i.e., the correlation of generation characteristics to load characteristics. This can be done in two ways. The first is to install some type of energy storages, allowing the storage of excess energy at times of overproduction, to be used at times of increased demand. Unfortunately, this solution entails large investments, further increasing in proportion to the increased level of self-consumption. The second approach is to fine-tune the load characteristics to the momentary values of the generated energy, by switching on additional receivers whose operation is not necessary but possible at a given moment. This can be achieved in a number of ways, each of which will be based on real-time operation with data regarding generation and demand and the ability to control individual groups of receivers. This method, albeit in a very simplified way, was used in the previously mentioned ERS controller. Two main types of approach are considered as far as these types of solutions are concerned: SCADA systems and modern BMS systems.

3.1. SCADA System

The implementation of the SCADA (Supervisory Control and Data Acquisition) system typically entails a computer system managing the devices connected to the grid, which collects and processes the relevant data, allowing for their mapping for visualization purposes, at the same time recording them for archiving purposes and exerting control capabilities. This allows a three-layer control of device operation, with current changes being tracked in real time and the initiation of appropriate responses. If the connection with the SCADA system is lost, this role is taken over by the PLC. The functions of alarm signaling, reporting or data archiving serve to significantly improve process efficiency and reduce the risk of failure. The SCADA systems have been used in many applications, but are the most prevalent in industry as well as in the energy, water and wastewater sectors. The broad range of functionality and flexibility of this software makes it ideal for supervising the process of energy generation in photovoltaic systems. The rapid detection of failures of photovoltaic system components, reporting of actual conversion efficiency of DC energy into AC energy, monitoring the actual efficiency of photovoltaic modules and provision of information about the necessary inspections and expiring warranties are among the basic functionalities the SCADA system employed in the control of photovoltaic installations [37,38,39].

In the installation discussed in Section 2, the presence of several actuators and different applications monitoring the operation of the photovoltaic system necessitated the decision to create a SCADA system designed in the CitectSCADA 2016 software (Figure 6). Its main objective was to simultaneously monitor the operation of all installations (belonging to the Rokietnica Municipality and installed in several schools under its authority) in a single software environment with the possibility of extending the control algorithm of the receivers and better adapting the load characteristics to the generation output. This was enabled by attaching an additional PLC unit, whose outputs could activate individual loads; the activation algorithm is based on the programmed event systems in the SCADA environment. This solution does not replace the ERS controller, but supports it by performing additional actions. The HMI panel of the implemented SCADA system also serves an educational function, displaying information about, e.g., the reduction in CO₂ emissions, energy production by the installations and graphs showing irradiance and energy produced as a function of time.

With the appropriate user access level, it is possible to access the control panel of the selected photovoltaic system after logging in (Figure 7 shows the synoptic screen for the analyzed BIPV installation in Cerekwica). The designed SCADA software contains many typical functionalities characteristic of this software environment. The software generates reports providing information on the energy generated by the system and the energy load status of the school building. It sends alerts regarding the limit values generated by the system and records user activity in the system.

Such a solution both facilitates the control of the electricity generation process in the installation and also serves as an interesting method for educating students about renewable energy sources.

3.2. Grenton BMS System

The use of BMS serves as an alternative to the previously presented SCADA control implementation. By definition, a Building Management System collects all the information from the building in one place. It allows for a real-time response to external and internal changes in order to achieve the optimum performance of a given building in terms of economy, comfort and safety. As an integrated building management system, the BMS connects all the smaller systems of a building. This includes ventilation, air conditioning, heating, lighting, irrigation, as well as alarms, the opening of windows and doors or controlling blinds and shutters. A properly designed system allows:

• Individual system components to be tracked and controlled;
• Operating parameters to be changed;
• Schedules and operating scenarios to be defined;
• System diagnostics and optimization of energy consumption.

The analyzed building, equipped with the photovoltaic installation under consideration, does not have a BMS, but is provided with the necessary actuation for its implementation. Grenton’s (wired/wireless) system components will serve as an example. The main and most important component is the “CLU” (Common Logic Unit) module, which stores the system’s pre-programmed configurations (push-button configuration, light scenes, logics, scenarios). Other input/output modules can be connected to it via the bus or wirelessly. In this case it is necessary to employ the “Gate MODBUS”, i.e., a module facilitating the integration of devices that communicate via the MODBUS protocol. It enables the integration of heating systems, ventilation systems and photovoltaic systems, as well as electricity meters and any other devices supporting the MODBUS RTU standard. It will enable the acquisition of all the necessary data relating to the current energy generation and demand. The BMS installation can be equipped with other Grenton modules that increase the possibilities of controlling load characteristics. These include [40]:

• Relay 4HP—high-power relay output module, allowing four different independent devices (consuming a maximum current of 16A) to be switched on, with simultaneous measurement of the energy consumed by them;
• Analog In/Out—integration by means of voltage and current analogue signals, i.e., control of temperature, humidity, wind speed or light intensity;
• Roller Shutter—allowing the control of shutter drives or blinds (including those incorporating photovoltaic elements to increase the amount of energy generated);
• Gate HTTP—allowing for even wider integration with external devices and systems with http and https protocol support such as weather services, IFTTT-type websites;
• I/O Module 8/8—control of eight independent low-power electrical devices and additionally the possibility of connection of eight elements containing contact inputs.

The implementation of the BMS on the above-mentioned systems (presented in Appendix A to Figure A2)allows for an increase in the amount of consumed energy from the examined photovoltaic installation through an extended and more diversified range of receivers that can be switched on immediately. The Relay 4HP module can switch both large receivers, such as hot domestic water tank heaters, and small systems, such as cleaning robots, with the simultaneous and continuous monitoring of energy consumption.

Additionally, the use of the BMS will result in the rational use of energy through preset automatic operating algorithms, such as:

• Switching off the recuperation systems in favorable weather conditions and tilting the windows via a system of actuators;
• Automatic lowering of the window blinds on the south side of the building to reduce heat build-up in the summer months and vice versa in the winter months;
• Automatic closing of windows in the event of extreme wind conditions preventing unwanted cooling of the building.

These measures will not only facilitate the adjustment of electricity generation and consumption, but also affect user comfort and the overall energy demand of the building from the standpoint of various utilities.

4. Economic Analysis

4.1. Economic Indicators for the Evaluation of Profitability of the Investment in PV

4.1.1. Simple Payback Period PP

The payback period can be defined as the time needed to recover the costs in a given investment. This indicator allows for the determination of the time after which a given investment will pay for itself [41,42,43]:

$$PP=\frac{I}{K}$$

(1)

where I—investment outlays, K—average annual profit, PP—simple payback period (years).

4.1.2. Net Present Value NPV

The criterion of Net Present Value is used to present the difference between the financial proceeds provided by the finished investment project and the expenditures incurred, during both its construction and operation, taking into account changes in the value of money over time [40,43,44]:

$$NPV={\displaystyle \sum _{t=0}^T}\frac{S_t-K_t}{{\left(1+p\right)}^t}-{\displaystyle \sum _{t=0}^T}\frac{I_t}{{\left(1+p\right)}^t}$$

(2)

where S_t—sales proceeds in year t, I_t—investment outlays in year t, K_t—operating costs (fixed and variable) in year t, p—discount rate, T—period of construction and operation

The economic viability of a given investment, using the NPV criterion, is determined on the basis of the total value of discounted flows over the entire period of construction and operation of the investment. The economic assessment is carried out as follows [41]:

• NPV > 0, the investment is profitable;
• NPV = 0, the investment is on the verge of being profitable;
• NPV < 0, the investment is not profitable.

4.1.3. Internal Rate of Return IRR

The internal rate of return, which also takes into account the change in the time value of money, represents the actual rate of return on a given investment. Immediately after the NPV criterion, it is the most widely used discount method for assessing the profitability of investment projects.

Similarly to the NPV criterion, the profitability of a given investment can be assessed on the basis of certain established conditions. In the case of the internal rate of return, the indicator to which we compare the obtained IRR value is the discount rate. These conditions are as follows [43,45]:

• IRR > p, the investment is profitable;
• IRR = p, the investment is on the verge of being profitable;
• IRR > p, the investment is not profitable.

4.1.4. Cost of Electricity LCOE

The Levelized Cost of Electricity (LCOE) is an indicator that compares the production costs of a given source against others. The Levelized Cost of Electricity can be defined as the expenditure incurred for the investment during its construction and operation, divided by the total energy produced by the source. In the case of the analyzed installation, this indicator will be used to compare the variant with and without subsidy. The LCOE is calculated based on the following formula [46,47]:

$$LCOE=\frac{CAPEX+OPEX}{EE}$$

(3)

where CAPEX—initial investment outlay, OPEX—costs associated with the maintenance of the given energy source, EE—total electricity generated.

4.2. Economic Analysis of the School’s BIPV Installation

To perform the economic analyses for the different variants, electricity price values were adopted as given in

Table 1. Electricity charges for the analyzed economic options [34,35].

Electricity Charges		Variant
		Variant I	Variant II	Variant III
Unit price of electricity	0.2674	0.2674	0.785	0.2674
Variable network fee		0.1458	0.0619	0.1458
Quality fee		0.0125	0.0242	0.0125
RES fee		0.00	-	0.00
Cogeneration fee		-	0.00496	-

. In turn, the variants adopted and their descriptions are as follows:

• Variant I—energy price and distribution charges as applicable at the start of assembly of the installation (2017);
• Variant II—energy price and distribution charges as applicable at the time of performing the economic analysis (2023);
• Variant III—energy price and distribution charges in force for the last electricity invoice received by the school (2017), without taking into account the subsidy received.

Additionally, the decrease in efficiency of the photovoltaic modules for this installation is 20% over 25 years; therefore, the efficiency of the system is reduced by 0.8% per year. The discount rate, p, is assumed to be 5%, and the increase in the price of electricity and distribution charges is equal to 2% per year. The assumed annual maintenance price is PLN 450/year. The guarantee period provided by Fronius for inverters up to 10 kW is maximum 10 years, whereas for inverters above 10 kW the maximum guarantee is 7 years. It was therefore assumed that a Fronius 20.0-3-M inverter priced at PLN 18,000 would be replaced in the seventh year of operation of the installation, and a Fronius 8.2-3-M inverter priced at PLN 10,000 will be replaced in the tenth year of its operation.

Table 2. Summary of the obtained economic indicators for the BIPV installation for the analysed variants.

Investment Profitability Indicators	Variant I	Variant II	Variant III
Simple payback period PP (year)	45.04	19.64	65.48
Net present value NPV (PLN)	−266,712	−113,886	−442,932
Internal rate of return IRR (%)	−4.0	2.0	−7.0
LCOE (PLN/MWh)	1001.90		1443.82

summarizes the determined values of the analyzed economic indicators for the installation in question in the three assumed variants.

The analysis of the obtained values demonstrates that none of the options are cost-effective when considering the energy production of the installation alone. The current electricity rates (adopted in Variant II in 2023) mean that, according to a simple payback period, the installation would pay off after less than 20 years. In the other two options analyzed, the payback periods significantly exceed the lifetime of the installation itself. Also, the internal rate of return in these cases takes on a negative value. In the case of the levelized cost of energy (LCOE), the variant that includes the subsidy is more favorable by PLN 441.92/MWh in comparison to the variant without this relief. The cost of energy generation is still much higher in comparison to its purchase from the grid, which further undermines the rationale for this investment. Due to the fact that the NPV is the most commonly used economic indicator, the decision was taken to present the NPVs as a function of the elapsed years for the three studied variants in the form of a bar graph (Figure 8). As can be seen from the graph showing NPVs as a function of time, none of the presented variants are economically viable.

4.3. Comparison of Economic Indicators for Different PV Systems

Three systems will be analyzed:

• The actual BIPV system of the school (BIPV Variant III);
• The school BIPV system connected to the power grid (BIPV on-grid);
• The standalone PV installation.

The analyzed systems have an identical capacity of 29.54 kW. The information on the energy yield for 2022 from the actual system and the values obtained from the simulation performed with PVGIS will be used as input data. For the on-grid BIPV system, identical yield values were adopted as for the standalone system. The annual energy yield from the two installations would be approximately 31,644 kWh and the price of the standalone system was set at PLN 155,000. The results of the comparative analysis for the unsubsidized variant are summarized in

Table 3. Summary of the obtained economic indicators of the compared PV installations.

Investment Profitability Indicators	BIPV (Variant III)	BIPV On-Grid	Free-Stand PV
Simple payback period PP (year)	48.13	30.04	11.84
Net present value NPV (PLN)	−400,297	−249,112	32,327
Internal rate of return IRR (%)	−5	−2	7
LCOE (PLN/MWh)	1061.15	665.16	271.62

and the change in the NPV ratio is plotted in Figure 9.

As follows from analyzing the variants of the deployed PV solution, the current system is still not cost-effective according to all indicators, and its payback period exceeds the lifetime of the installation. Connection of the existing installation to the power grid, while eliminating or modifying the current energy management system, through increased energy yields and continuous operation of the PV installation (without limiting its operation to match the building’s energy demand), would contribute to improving the economic indicators; however, the investment is still not cost-effective, even if the same investment subsidy were obtained as for its current form. Only by changing the BIPV system to a traditional on-grid photovoltaic system (i.e., by reducing the investment outlay) would the investment become profitable, achieving a7% return rate, which is comparable to the currently available bank deposits.

4.4. Analysis of the Impact of the Discount Rate on Economic Indicators for Different PV Systems

The economic analyses performed for PV systems are encumbered by certain errors, or underestimations, which relate to the assumed rigid parameter values describing the change in the value of money over time, i.e., the so-called discount rate. The analyses assume a constant value for the discount rate over the lifetime of the installation, i.e., 25 years, which is not appropriate. Over the last few years, due to the current global geopolitical situation, the discount rate has varied between 0.15% and 8.62%. For the on-grid PV system, analyses were carried out for fixed discount rates of 1%, 3%, 5% and 7% (the results are summarized in

Table 4. Summary of changes in the NPV ratio for the studied standalone PV system with a variable discount rate.

Investment Profitability Indicators	p (%)
	1	3	5	7
Net present value NPV (PLN)	147,999	80,267	32,327	−2306

and Figure 10) as well as considering variable discount rates over the years for several variants, from the beginning of the investment (

Table 5. Summary of changes in the NPV ratio for the studied free-standing PV system with a variable discount rate.

Investment Profitability Indicators	Variant of Change to the Discount Rate p
	W1	W2	W3	W4	W5
Net present value NPV (PLN)	−2306	80,267	80,267	32,327	80,267

, Figure 11):

• W1—change in the discount rate every 8 years to the levels 3%, 5% and 7%;
• W2—change in the discount rate every 8 years to the levels 7%, 5% and 3%;
• W3—change in the discount rate every 6 years to the levels 5%, 7%, 5% and 3%;
• W4—change in the discount rate every 6 years to the levels 3%, 5%, 7% and 5%;
• W5—change in the discount rate every 6 years to the levels 1%, 3%, 7% and 3%.

Changing the value of the discount rate has a significant impact on the future cash flows and profitability of a given investment, and therefore its selection is critical for a reliable determination of the investment’s profitability. The lower the discount rate, the higher the actual return on investment.

A dynamic change introduced in the discount rate over the 25 years of operation of the PV installation demonstrates the changes in the current cash flows received. The analysis of the presented variants 1 and 2 concludes that a decrease in the discount rate is clearly preferable to its increase, despite the fact that the durations for the given values are identical, which is due to the small change in the value of money already after the investment has become profitable (in variant W2). Similarly, for variants W3 and W5, where the value of the discount rate is also low (3%) in the final period, a large NPV was obtained. The increase in the discount rate in variant W4 resulted in a lower NPV. Despite the same NPV values in variants W2, W3 and W5, there are different dynamics of change in each year of the investment’s operation, which can be seen when analyzing the data presented in Figure 11 in detail.

5. Discussion

As follows from the presented data and analyses, when designing an off-grid PV system, special attention should be paid to the proportion of energy generated by the PV system in relation to the energy consumed by the facility together with its load profile, so that generation and consumption periods coincide. Based on the data collected in

Table 6. Summary of the different indicators of the analyzed PV systems.

Indicator	PV System Variant
	BIPV	BIPV On-Grid	Free Stand
Energy yield (kWh)	24,005	31,644	31,644
Unit energy yield (kWh/kW)	600	1071	1071
NPV (PLN)	−2306	80,267	80,267
LCOE (PLN)	1061.15	665.16	271.62

, the earlier analysis concludes that the examined installation would need to be improved or supplemented with other elements in order to be able to fully exploit its energy generation potential.

When comparing the energy yield of an existing BIPV system, which is limited by ERS, approx. 32% of the energy that could have been used and would contribute to improved economic indicators and a faster payback time is lost. The cost of generating energy in a BIPV installation connected to the power grid, despite the much higher investment outlays due to the use of this technology instead of traditional PV panels, would be comparable to current market electricity prices. The replacement of BIPV with traditional PV solutions would lead to an approx. 60% decrease in the costs of energy generation. However, BIPV systems should not be considered solely as energy generation systems, as they perform additional functions that are sometimes difficult to measure in terms ofa monetary equivalent. Instead, it is important that the investment is profitable and provides a return on investment.

The economic indicators of the examined installation could be improved if it were to be expanded to include additional proposed components such as energy storage, SCADA systems or building automation systems to manage the operation of the entire arrangement. With a relatively small financial outlay, it would be possible to make full use of the generating capacity of PV installations, even with the use of the BIPV technology, as indicated, for example, by such ratios as NPV or LCOE shown in Table 6.

The analysis of the data included in Table 4 and presented graphically in Figure 10 confirms the information regarding the impact of the adopted discount rate (the change in the value of money in time) on the obtained financial profits past the installation’s lifetime. The higher the value of the p factor, the lower the final total profits from the investment (including the possibility of achieving no return on the invested funds).

Special consideration should furthermore be made of the analysis of the proposed changes in the NPV of PV systems, with consideration of the variability in the discount rate p during the lifetime of the installation, as presented in Figure 11 and Table 5. It appears that the fixed value of parameter p, which is frequently adopted in the economic analyses of PV systems, leads to a distorted picture of the actual cash flows over the lifetime of the installation. Comparing, for example, variant W3 with W5, where the adopted p-values are 3, 5 and 7% every 6 years, but in a different time frame, one can see a change in the NPV from PLN 32,327 to PLN 80,267, which results in an increase in expected profits by 2.5 times, representing approximately 50% of the investment value.

6. Conclusions

The presented installation is an example of the use of an on-grid inverter to create an island installation that is not connected to the power grid. This required the use of a special protection system to prevent excess energy from flowing into the grid. However, the analysis demonstrates the drawbacks of these solutions, such as limitations to the operation of the generation system during periods of reduced demand for energy by the facility. It is therefore important to properly correlate the generation profile with the consumption profile, or to use additional devices and control algorithms to limit possible losses. The use of an energy storage, installation control and visualization system, or the automatic management of the elements of an electrical installation, can optimize the energy consumption profile of a facility and allow the energy generation system to be used at full capacity, leading to a positive impact on the economic parameters of the investment. In Poland, as part of the investment in photovoltaic systems, it is even possible to obtain additional funding for energy management systems and energy storages utilized as system components.

In the case of the examined school building, the main challenges relate to the fact that during the holiday months (July, August), the school functions are limited and its energy demand is much lower than in other months. For facilities with a uniform energy demand, the process of system selection would be easier. However, the presented data show unequivocally the importance of the proper correlation of energy generation and consumption, studying the load profile of the building (not only on an annual or monthly basis, but also on a short-term basis (e.g., daily)), and taking into account school holidays and plant downtime, which would affect losses of generated energy not collected by the local RES systems.

The appropriate choice of parameters for the economic analysis is particularly important at the time the decision to invest is taken, as this illustrates its profitability and potential financial profits. Analyses should take into account the dynamic change in the value of money over time, just as in the case of investments based on natural resources, as this affects the final financial outcome.

In summary, the research and analyses conducted lead to the following conclusions:

-

When design ing a PV system, accounting for the facility’s own needs (off-grid), its size and productivity should be carefully correlated with the facility’s energy needs;

-

The use of SCADA and building automation systems allows for precise control of electrical receivers, management of the distribution of the energy generated from the PV system, as well as data-archiving and device monitoring;

-

The energy management system allows for an increase in the level of self-consumption of the generated energy, which also improves the profitability of the investment;

-

In the analyzed case of the school’s BIPV system, the calculations show a potential increase in energy generation by 32% if properly managed. This value is comparable to other studies, where the level of self-consumption with an integrated energy management system together with building automation can change from 20% to up to 50%;

-

Proper correlation of the size of the energy generation system and energy consumption through the use of a distribution and equipment management system serves to improve the economic indicators of the investment;

-

The use of dynamic discount rates in the economic NPV analysis allows for a more precise determination of the financial flows of the investment.