Photovoltaic Farms: Economic Efficiency of Investments in South-East Poland

Abstract

The main objective of this study was to identify the status and development opportunities and evaluate the economic viability of investments in large-scale photovoltaic installations in Southeastern Poland. The primary data sources used in the study were empirical materials from all photovoltaic installations implemented with support from the Regional Operational Program of the Lublin Voivodeship (ROP WL) for 2007–2013 (31 projects). The following indices were used to evaluate the economic efficiency of the investments studied: rate of return on investment (ROI), simple payback period (SPP), net present value of investment (NPV), internal rate of return (IRR), discounted payback period (DPBT), and averaged unit cost of electricity generation (LCOE). They were carried out for three scenarios–baseline, conservative, and optimistic–in two variants, for actual capital expenditures considering financial support used and without subsidies. It was determined that the expected lifetime of the studied investments would be 25 years. The sensitivity analysis shows that, regardless of the adopted scenario, investments in solar thermal power with the level of support that took place under the 2007–2013 financial perspective were reasonable long-term investments. In the least favorable scenario (conservative) included in the analysis, the discounted payback period ranged from 8.1 to 22 years. In the optimistic scenario, DPBT values ranged from 5.6 years to more than 15 years. The payback period (both simple and discounted) for investments with the subsidy was, on average, almost twice as fast as for investments without the subsidy, while the average unit cost of electricity generation with the subsidy was about 30% lower than without it.

1. Introduction

Since the second half of the twentieth century, phenomena limiting economic development, initially mainly related to the availability of natural resources, began to gain importance. Examples include energy resources and the “first oil shock”, which economists consider the cause of the most significant economic upheaval since the Great Depression of the 1930s. According to Henry Kissinger’s assessment, it “irrevocably changed the world as it was born in the post-war period” [1]. The shock of the 1973 “Yom Kippur” war, however, not only brought a crisis but also initiated a series of changes in both the economic and geopolitical spheres, including an energy revolution. Its main tenets boiled down to reducing independence from imported energy resources and improving the efficiency of their use. In France, the result of the efforts for energy independence was a program for the development of nuclear energy (Messmer Plan), adopted without parliamentary debate (based on Article 49.3 of the country’s constitution), which was justified by the statement “we have no oil, we have no gas, we have no coal, we have no choice” [2].

The search for new deposits of hydrocarbon resources was also intensified, as was the exploitation of those already known but not yet extracted due to very high costs (e.g., on the North Sea shelf and Alaska). In parallel, efforts were made to improve energy efficiency, a prominent example of which was the adjustment processes in the automotive industry. The main reason was the increase in demand for cars that use significantly less fuel than those produced to date [3], beginning the era of hatchbacks such as the Volkswagen Golf and Toyota Corolla, among others, which became bestsellers in 1974.

Although the first oil shock and the two subsequent energy crises triggered by the Iranian Islamic Revolution (1978–1979) and the Gulf War (1990–1991) negatively affected the economies of hydrocarbon fuel-importing countries, a much more severe global problem has become progressive climate change. This has led to weather anomalies, with annual losses in agriculture alone estimated at around $150 billion per year [4]. R. Newman and I. Noya [5] estimate the average annual global cost of extreme weather events attributable to climate change between 2000 and 2019 at $143 billion. There is also a legitimate concern that in the coming decades, this phenomenon could threaten the health and lives of people in most regions of the world or even the whole of civilization [6,7,8].

The transformation of economic models towards an efficient use of resources and the reduction of greenhouse gas (GHG) emissions has become one of the fundamental challenges of civilization [9]; given that most GHG emissions come from the use of fossil fuels, attempts to construct global, regional, and national climate policies inevitably revolve around the issue of energy sources and energy policies. While the provisions of the Paris Climate Agreement leave it up to countries to choose the path by which this goal will be achieved, the document’s introduction already includes recommendations about the need to promote increased use of renewable energy sources (RES) [10]. A similar statement but referring to the current situation (after Russia’s aggression against Ukraine) was included in the World Energy Outlook 2022 report issued by the International Energy Agency (IEA): “the energy crisis promises to be a historic turning point towards a clean and secure energy system” [11]. Electricity generation through photovoltaic systems is considered one of the future directions of RES use [12]. This is because all sources of energy (except for the energy of the tides of the seas—85 EJ/a, which is caused by gravitational interaction, mainly of the Moon, and the energy of the Earth’s interior—672 EJ/a), originate from absorbed solar radiation—3.93. 106 EJ/a [13]. However, despite such significant potential, its share in the structure of total energy consumption remains very low. In 2022, this indicator for the world, the European Union, and Poland, respectively, was 1.05%, 1.64%, and 0.78%, and for electricity, it was as follows: 4.55%; 7.44%, 4.63% [14,15,16,17]. This is because solar energy is diffuse, difficult to apply directly and efficiently in practice, and thus more expensive than conventional energy in most applications, “although time is working in favor of renewable energy sources” [18]. Furthermore, this process, slow for now, will be accelerated by the development of new technologies [19]. Methods for its transformation continue to be improved, which, combined with the introduction of economic incentives for systems using renewable energy sources, is increasing its importance [20,21]. The main objective of this study was to identify the status and development opportunities and evaluate the economic viability of investments in large-scale photovoltaic installations located in Southeastern Poland. The implementation of the main objective of the study was aimed at solving the following specific objectives: to determine the size of capital expenditures and operating costs, electricity produced and fed into the grid, and revenues, per unit of installed capacity. Hence, the following research questions were posed:

• What was the scale of support for large-scale photovoltaic projects under the Regional Operational Program of the Lublin Voivodeship 2007–2013?
• Is public support for the development of large-scale solar power generation justified?
• What was the variation in the level of capital expenditures, operating costs and economic efficiency of investments depending on the installed capacity?
• Is the production of electricity in photovoltaic installations economically an alternative to its production in conventional sources?

Efficiency is one of the basic categories used to describe the state, functioning, and development opportunities of various types of organizations, particularly economic organizations [22]. It is an ambiguous concept with many synonyms in both Polish and foreign literature and is used in many areas related to economic activity [23].

P. Samuelson and W. Nordhaus [24] defined efficiency as the use of economic resources in the most efficient manner. According to J. Stoner, R. Freeman, and D. Gilbert [25], it is a measure of the efficiency and effectiveness of the degree of achievement of set goals, while T. Dudycz [26] defined economic efficiency as the ratio of the results’ value to the input of factors used to obtain them. In the category of resource allocation in the Pareto sense, a comprehensive definition of effectivity was adopted, among others, by G. Debreu [27], M. Farrell [28], or D. Kamerschen, R. McKenzie, and C. Nardinelli [29], treating this quantity as the maximization of production resulting from the proper allocation of resources under given constraints of supply, producer costs and demand, consumer preferences [29]. J. Zieleniewski [30] defines efficiency as a quantitative characteristic of an activity reflected in the ratio of utility effects obtained in a specific time and aimed at satisfying the recipient’s needs to the inputs necessary to achieve this effect incurred in a specific time.

The economic literature distinguishes several methods and measures for studying the efficiency of economic entities and investments. The microeconomic approach was presented, among others, by such Polish economists as J. Rajtar [31], Z. Kowalski [32], J. Penc [33], E. Nowak [34], W. Jóźwiak [35], M. Sierpinska, and T Jachna [36]. E. Szymańska [37], J. Gerlach, and M. Gil [38] associate efficiency with the individual enterprise and generally define it as the relation of the results obtained by a given economic entity to the inputs incurred.

The selection methods for evaluating the economic efficiency of the photovoltaic installations under study were based on in-depth literature studies and suggestions from such international organizations in the renewable energy sector as the International Renewable Energy Agency and the U.S. Department of Energy’s National Renewable Energy Laboratory.

2. Materials and Methods

The primary sources of data used in the study were empirical materials from all photovoltaic installations implemented with support from the Regional Operational Program of the Lublin Voivodeship (ROP WL) for 2007–2013 under:

(a)

Priority Axis I. Entrepreneurship and innovation (29 projects):

• Measure 1.4 Investment subsidies for adaptation of enterprises to environmental requirements and renewable energy sources.

(b)

Priority Axis VI. Environment and clean energy (2 projects):

• Measure 6.2 Environmentally friendly energy.

Data on investment outlays, and sources of funding were obtained from the Lublin Agency for Entrepreneurship Support (LAWP), which performed tasks related to the implementation of Priority Axis I and II of the WL ROP for 2007–2013, and the Department for Regional Operational Program Management of the Lubelskie Voivodeship Marshal’s Office in Lublin, responsible for supervising projects from Priority Axis VI.

Statements of the amount of electricity injected into the grid monthly in 2017–2022 from photovoltaic installations implemented under the Regional Operational Program of the Lublin Province (ROP WL) 2007–2013 were obtained from Polska Grupa Energetyczna S.A. Distribution Branch of Lublin.

In the macroeconomic analyses, the retrospective analysis method was used to evaluate the changes taking place, using reports and statistical studies of the Energy Institute, which has been publishing the Statistical Review of World Energy since 1952, the Our World in Data platform, the EurObserv’ER Consortium, the European Statistical Office, the Central Statistical Office in Warsaw, the Energy Regulatory Office, and the Polish Power Exchange, on energy balances, energy efficiency, electricity prices, and property rights to certificates of energy origin (PME) and GHG emissions.

Polish and foreign scientific literature, specialized journals, scientific studies, and international, national, and regional regulations in the climate and energy policy field were also sources of information.

Because of the ongoing globalization processes, the United Nations Industrial Development Organization (UNIDO) has issued a Manual for the Preparation of Industrial Feasibility Studies [39], containing a set of methods for the economic evaluation of investment projects taking into account the state of the art in this field at the time. The study was popular with various government agencies, financial institutions, consulting companies, universities and scientific institutes, and investors. In 1991, a revised and expanded version was published to include issues of environmental impact assessment of investments, technology transfer, marketing, human resources, risks, and mobilization of funds [40]. The methodology proposed by UNIDO for calculating investment efficiency is based first on the determination of:

• investments (pre-feasibility and pre-production phases, fixed and current assets);
• revenues from the launched business;
• expenses (operating costs).

Efficiency is one of the basic categories used to describe the state, functioning, and development opportunities of various types of organizations, and economic ones in particular. The economic literature distinguishes a number of methods and measures for examining the efficiency of both economic entities and investments. In view of the ongoing globalization processes, the United Nations Industrial Development Organization (UNIDO) has issued a Manual for the Preparation of Industrial Feasibility Studies containing a set of methods for the economic evaluation of investment projects. It is from this study that the indicators most commonly used to assess the economic viability of energy projects were selected [40].

These values form the basis for calculating the value of net cash flow (NCF) in subsequent years of the period of implementation and operation of the assessed investment projects, which is the starting point of the conducted profitability calculus. Within the framework of this account, there are most often two primary groups of methods, distinguished according to the criterion of time factor and technique: static (simple) and dynamic (discounted):

• simple evaluation methods (do not take into account the change in the time value of money): simple payback period of capital expenditures, simple and accounting rate of return, break-even analysis;
• discount methods: net present value (NPV), internal rate of return (IRR).

The following simple methods were used to evaluate the projects studied:

(a)

Return on investment (ROI)

$$ROI={\displaystyle \frac{NP}{IC}}\times 100\%$$

(1)

(b)

Simple Payback Period (SPP)

$$SPP={\displaystyle \frac{IC}{NP}}$$

(2)

where:

• NP—net profit;
• IC—investment cost.

ROI is used to assess the profitability of an investment by comparing the net profit derived from the investment to the total costs incurred for the investment (from both equity and debt).

The SPP determines the time required to recover the investment outlay from the financial surplus achieved. The financial surpluses include net profit and depreciation, and if the source of financing is a loan, the surplus also includes interest. If the financial surpluses in subsequent years are identical, the payback period is calculated as the quotient of the expenditures incurred for the project and the annual surpluses plus the project’s duration. Full reimbursement of the expenditures incurred will occur in the year in which the accumulated financial surpluses balance the expenditures.

Due to the long-term venture of investing in a photovoltaic power plant, the following discount methods, which are more precise tools for assessing profitability, were also used in the study:

• NPV;
• IRR;
• discounted payback period DPBT (Dynamic Pay Back Time);
• Levelized Cost of Electricity (LCOE).

The first discounting method used is the net present value (NPV), which makes it possible to evaluate the updated flows (inflows and outflows). It is calculated as the sum of the discount for each year (or another period) of the net cash flows (NCF) realized over the entire analyzed period at a fixed discount (interest) rate.

$$NPV=\sum _{n=0}^N{\displaystyle \frac{F_n}{{(1+d)}^n}}=F_0+{\displaystyle \frac{F_1}{{(1+d)}^1}}+{\displaystyle \frac{F_2}{{(1+d)}^2}}+\cdots +{\displaystyle \frac{F_n}{{(1+d)}^n}}$$

(3)

where:

• NPV—net present value;
• F_n—net cash flow in year n;
• N—analysis period;
• d—annual discount rate.

The investment project under study is profitable if NPV ≥ 0. This is because a positive value of NPV means that this project’s profitability rate is higher than the cut-off rate determined by the interest rate taken into account [36].

Another method used in the dissertation to determine the effectiveness of the project is the internal rate of return (IRR), the second most commonly used discount method. This is the rate at which the present value of the NPV for the entire period of operation is zero (NPV = 0), so the value of the expense streams is equal to the present value of the cash inflow streams. IRR is the rate for which:

IRR→ NPV = 0

(4)

The dynamic payback time (DPBT) was also used to assess the profitability of the investment:

$$DPBT={\displaystyle \frac{\mathrm{I}\mathrm{C}}{\frac{\sum _{n=0}^N\frac{F_n}{{(1+d)}^n}}{N}}}$$

(5)

where:

• IC—investment cost;
• F_n—net cash flow in year n;
• N—analysis period;
• d—annual discount rate.

It is an improved version of the SPP method because it considers the change in the time value of money [41].

The Levelized Costs of Electricity (LCOE) method was also used to assess the profitability of the investment. The results of calculations with this method allow for a comparison of the cost of energy production from different sources, both renewable and conventional, including grid energy [41,42]. Using the following formula, the average cost of generating 1 MWh of electricity for the entire period of operation was determined:

$$LCOE={\displaystyle \frac{{\sum }_{t=1}^n\frac{I_t+M_t}{{\left(1+r\right)}^t}}{{\sum }_{t=1}^n{E}_{et}}}$$

(6)

where:

• I_t—capital expenditures in year t (depreciation and cost of capital) [PLN],
• M_t—other costs in year t [PLN],
• E_et—the amount of electricity generated in year t [MWh],
• r—average discount rate [%],
• n—the planned lifetime of the photovoltaic system [years].

Case Study

In the analysis, all the photovoltaic installations were implemented with support from the Regional Operational Program of the Lublin Province (ROP LP) for 2007–2013 [43] under:

(a)

Priority Axis I. Entrepreneurship and innovation (29 projects):

• Measure 1.4. Investment subsidies for adaptation of enterprises to environmental requirements and renewable energy sources.

(b)

Priority Axis VI. Environment and clean energy (2 projects):

• Measure 6.2 Environmentally friendly energy.

The aim of Measure 1.4 was to increase the production and use of energy from renewable sources and improve the competitiveness of micro, small, and medium-sized enterprises obliged to adapt their infrastructure to environmental requirements. Support under this measure was granted through grants from PLN 85 thousand to PLN 4 million. The maximum share of EU funds could be for micro and small enterprises—70%, and for medium-sized enterprises—60%. Subsidies were granted only for projects in which more than 50% of the energy generated from renewable sources was to be allocated for sale. Of the 29 beneficiaries of this measure, 21 were capital companies (limited liability companies), 2 were NGOs, and the rest (6) were partnership ventures.

Within the framework of Measure 6.2, Environmentally Friendly Energy, it was possible to implement projects concerning the use of energy from renewable sources under the Provincial Program for the Development of Alternative Energy Sources for the Lublin Province [44]:

• Investments in the development and use of renewable energy sources such as wind, water (taking into account the needs of nature conservation and ecological aspects of river maintenance), biomass, solar and geothermal energy, and others;
• Investments to reduce emissions of biogas generated at wastewater treatment plants and landfills through its energetic use;
• Modernization of boiler rooms fired by solid fuel to those fueled by ecological fuels, with particular attention to tasks carried out in educational and educational institutions, cultural institutions, and hospitals.

The beneficiaries of the program were local government units (JST—pl. jednostki samorządu terytorialnego) and their unions, agreements, associations, local government organizational entities of the public finance sector with legal personality, commercial law companies in which JST or their unions hold the majority of shares or stocks, and entities acting based on the Law of 19 December 2008, on public-private partnerships [45]. The value of co-financing for projects not covered by public aid was up to 85% of eligible costs. The aid could be granted for projects implemented in towns belonging to rural municipalities or urban-rural municipalities, except for towns with more than 5000 inhabitants or in towns belonging to urban municipalities with less than 5000 inhabitants. The maximum amount of aid for implementing projects in the production or distribution of energy from renewable sources in one municipality during the period of the program could not exceed PLN 3 million. PLN 265.5 million was allocated for projects using renewable energy sources under this measure, which accounted for 5.9% of the allocation of all ROP LP funds. More than 93% of this amount was allocated to “solar energy” investments. Such a significant share of solar energy projects confirms the validity of the thesis of the Program for the Development of Renewable Energy Sources for the Lubelskie Voivodeship (PROZEWL) [46], that the region’s nationally significant resources will allow it to become a national leader in the use of solar energy for heat and power generation.

Under this measure, two photovoltaic projects were implemented in the Wisznice and Wola Uhruska municipalities, with only 3.0% of the funds allocated. A survey of local governments shows that, at the turn of the first and second decades of the 21st century, the priority “RES investments” implemented by JST were solar thermal energy (solar collectors). Although the primary beneficiary group was local government units, the target group was households, where more than 32,000 devices with a total thermal power of 156.4 MW were installed. Households’ great interest in using solar energy to prepare hot water was due to the possibility of obtaining savings through reduced expenses on purchasing energy carriers. A total of 92.6% of Measure 6.2 funding was allocated for this purpose, while an inevitable surprise was the relatively small share of funding allocated for the energetic use of biomass (4.4%), which allowed for the installation of about 800 boilers with a total capacity of 24.3 MW [47]. Figure 1 shows the location of the photovoltaic farms studied.

The total installed capacity of the surveyed photovoltaic facilities is 29.61 MW. Six projects were located in urban areas, one in urban-rural areas, and the rest in rural areas.

Of the 31 projects, the most noteworthy is “Energia Dolina Zielawy Limited Liability Company”, based in Wisznice, which was established by the local governments of the five partner municipalities of the Zielawa Valley. It comprises three municipalities from Biala County, i.e., Rossosz, Wisznice, Sosnówka, and three from Parczew County-Milanów (not a shareholder of the Company), Jabłoń, and Podedwórze. The Company, as an independent business entity under commercial law, was registered with the District Court in Lublin VI Economic Department-National Court Register on 15 November 2012. Shares in the company were determined in proportion to the number of residents and the area of the municipalities. The Company’s core business is the generation of electricity through a 1.4 MW photovoltaic installation and its sale. The investment was completed in 2014, and part of the funds for its construction were obtained from the Regional Operational Program of the Lublin Province 2007–2013. The farm, built in 2014, was the largest of its kind in Poland at the time.

3. Results

3.1. Capital Expenditures

In mass statistics, capital expenditures are defined as financial resources used to purchase or upgrade fixed assets such as buildings, machinery, equipment, software, and other assets to increase an enterprise’s production capacity or improve efficiency [48,49]. They do not include only expenditures for:

• buildings and structures (including buildings and premises and civil engineering works), including, but not limited to, construction and erection works, design and cost documents;
• machinery, technical equipment, and tools (including instruments, movable property and equipment);
• means of transport;
• other, i.e., water reclamation, land improvement (enhancement), livestock (core stock), perennial planting, and interest on loans and investment credits during the investment period.

The first stage of analyzing the investment expenditures of the surveyed projects used anonymized data provided by the Lublin Agency for Entrepreneurship Support (LAWP) in Lublin. LAWP is a local government organizational unit of the Lubelskie Voivodeship, without legal personality, performing tasks related to the implementation of Priority Axis I and II of the Regional Operational Program of the Lubelskie Voivodeship 2007–2013, the Investment Priorities of the Regional Operational Program of the Lubelskie Voivodeship 2014–2020 entrusted to it, and the Detailed Objectives of the program European Funds for Lubelskie 2021–2027. The Agency’s tasks in implementing Priority Axis I and II of the Regional Operational Program of the Lubelskie Voivodeship 2007–2013 included reporting, monitoring, and accounting for reimbursing funds under financial engineering instruments [50].

The data provided information only on installed capacity, total project values, amounts of eligible expenditures, and subsidies, including from the RPOWL 2007–2013. On this basis, the level of investment outlays per unit of installed capacity (PLN/kW) and their structure in terms of financing sources were analyzed. The data in

Table 1. Structure of capital expenditures by subsidy and capacity.

No.	The Total Value of the Project	Amount of Eligible Expenditure	Funding		Power	Capital Expenditures		Share of Own Funds [%]	Share of Total Subsidies [%]	Share of ROP WL Grants [%]
			Total	WL ROP		Total	Own
	[PLN]				MW	PLN/kW
1.	5,839,638.04	4,644,540.00	2,786,723.99	2,368,715.39	0.92	6347	3318	52.28%	47.72%	40.56%
2.	209,100.00	167,500.00	117,250.00	99,662.50	0.03	6970	3062	43.93%	56.07%	47.66%
3.	7,128,240.87	4,998,000.00	2,998,799.99	2,548,979.98	1.00	7128	4129	57.93%	42.07%	35.76%
4.	11,487,661.19	9,032,598.83	4,516,299.41	3,838,854.49	1.99	5773	3503	60.69%	39.31%	33.42%
5.	9,839,883.17	7,776,431.00	4,277,037.04	3,635,481.48	1.47	6694	3784	56.53%	43.47%	36.95%
6.	6,230,854.71	4,946,339.10	2,473,169.55	2,102,194.11	0.96	6490	3914	60.31%	39.69%	33.74%
7.	5,442,690.39	4,330,885.00	2,598,530.99	2,208,751.34	0.99	5498	2873	52.26%	47.74%	40.58%
8.	1,717,080.00	1,396,000.00	697,999.99	593,299.99	0.30	5724	3397	59.35%	40.65%	34.55%
9.	5,300,576.94	4,459,855.52	2,229,927.75	1,895,438.58	0.96	5521	3199	57.93%	42.07%	35.76%
10.	6,197,126.84	4,878,000.00	2,439,000.00	2,073,150.00	0.93	6664	4041	60.64%	39.36%	33.45%
11.	6,455,004.83	4,981,790.37	2,490,895.18	2,117,260.90	1.20	5379	3303	61.41%	38.59%	32.80%
12.	6,499,848.84	3,332,235.56	1,666,117.78	1,416,200.11	0.99	6566	4883	74.37%	25.63%	21.79%
13.	5,712,644.31	4,549,413.11	2,274,706.53	1,933,500.54	0.99	5770	3473	60.18%	39.82%	33.85%
14.	537,755.53	524,513.20	367,159.24	312,085.35	0.09	5975	1896	31.72%	68.28%	58.03%
15.	6,877,706.54	5,510,700.00	3,306,420.00	2,810,457.00	0.99	6947	3607	51.93%	48.07%	40.86%
16.	8,732,726.33	6,826,598.78	3,413,299.39	2,901,304.48	1.25	6986	4256	60.91%	39.09%	33.22%
17.	6,075,954.33	5,814,931.34	2,907,465.66	2,471,345.79	1.00	6076	3168	52.15%	47.85%	40.67%
18.	4,652,015.26	4,490,756.09	2,245,378.02	1,908,571.31	0.79	5889	3046	51.73%	48.27%	41.03%
19.	8,929,384.88	6,272,337.50	3,136,168.72	2,665,743.39	1.52	5875	3811	64.88%	35.12%	29.85%
20.	2,290,014.00	1,746,669.10	873,334.55	742,334.36	0.35	6543	4048	61.86%	38.14%	32.42%
21.	4,823,857.79	3,880,365.60	1,940,182.80	1,649,155.38	0.78	6184	3697	59.78%	40.22%	34.19%
22.	4,290,078.64	3,268,480.00	2,124,512.00	1,805,835.19	0.70	6129	3094	50.48%	49.52%	42.09%
23.	5,498,551.93	4,968,747.83	3,478,123.47	2,956,404.94	0.96	5728	2105	36.74%	63.26%	53.77%
24.	4,371,298.33	2,333,205.34	1,633,243.72	1,388,257.16	0.60	7285	4563	62.64%	37.36%	31.76%
25.	10,313,321.46	8,282,090.60	5,797,463.40	4,927,843.87	1.98	5209	2281	43.79%	56.21%	47.78%
26.	4,919,355.00	4,871,360.00	2,435,680.00	2,070,328.00	1.00	4919	2484	50.49%	49.51%	42.09%
27.	6,299,814.00	5,034,300.00	3,020,580.00	2,567,493.00	0.99	6363	3312	52.05%	47.95%	40.76%
28.	6,090,243.82	4,867,724.99	2,920,634.97	2,482,539.72	0.99	6152	3202	52.04%	47.96%	40.76%
29.	6,777,059.67	5,435,885.84	2,717,942.91	2,310,251.46	0.99	6846	4100	59.89%	40.11%	34.09%
30.	3,075,983.56	2,425,144.11	1,212,572.05	1,030,686.23	0.50	6152	3727	60.58%	39.42%	33.51%
31.	7,639,072.57	6,085,694.38	3,042,847.19	2,586,420.11	1.40	5456	3283	60.17%	39.83%	33.86%
Total	180,254,543.77	142,133,093.19	78,139,466.29	66,418,546.15	29.61	6088	3449	56.65%	43.35%	36.85%

Source: own compilation based on information obtained from the Lublin Agency for Entrepreneurship Support (LAWP). PLN is for the 4 columns: Funding, The total value of the project, Amount of eligible expenditure.

show that the level of non-refundable support and the outlays per unit of installed capacity varied significantly. In the case of co-financing, the average share of support was 43.35%, of which 36.85% fell on the funds of the RDPL 2007–2013, with a disparity ranging from 25.63 to 68.28%, and for aid funds from 21.79 to 58.03%. The main reason for these disparities was the share of eligible expenses in total outlays. The rules for their categorization resulted from the “Guidelines for eligibility of expenditures under the WL ROP for 2007–2013. Manual on eligibility of expenditures.” [51]. This document aligns with the National Guidelines for the eligibility of expenditures under the Structural Funds and the Cohesion Fund for the 2007–2013 programming period.

The expenses that most reduced the eligible cost item included:

• costs of preparatory work related to the preparation of the project, e.g., preparation of the application for funding, fees associated with the need to obtain the necessary administrative decisions at the stage of project preparation, development of functional-utility programs, construction concept;
• costs of purchasing undeveloped land property above the level of 10% of the value of the total eligible expenses of the project;
• the costs of building electricity connections and grid connection fees.

The boxplot (Figure 2) illustrates the distribution of four key metrics related to project financing and expenditures: Total value of the project (PLN); Amount of eligible expenditure (PLN), Funding total (PLN); and Capital expenditures (PLN/kW). The first three metrics, expressed in millions of PLN, exhibit considerable variability, reflecting the diversity in project scales. In contrast, “Capital expenditures”, measured in PLN per kilowatt, shows a more compact and consistent distribution.

The median values for all metrics are marked within the boxes, with the interquartile ranges (IQRs) highlighting the central 50% of the data. Outliers are evident, particularly for the “Total value of the project” and “Eligible expenditure”, indicating exceptionally large projects. The narrower range of “Capital expenditures” suggests a uniform cost structure across projects, despite differences in overall scale and funding. This visualization underscores the variability in funding and project sizes while highlighting the stability of capital expenditure per kilowatt

The average level of expenditure per unit of installed capacity was 6088 PLN/kW but this varied significantly, from 4919 to 7285 PLN/kW (Figure 3), and was not due to economies of scale. Institute for Renewable Energy (IRE) analyses confirm the operation of the so-called cost effect of scale, as the data shows that the unit price of an installation decreases with the increase in the installation’s rated power. There are noticeable differences in the unit price between home prosumer installations and prosumer business installations. The unit price is significantly lower for PV farms than for other types of installations [52].

The statistical analysis, in which it was assumed that the explanatory variable (y) is the investment outlay (PLN/kW) and the explanatory variable (x) is the power of the installation (kW), shows that these relationships were explained in 8.9% (R2 = 0.089), hence the next stage of analysis compared the structure of investment outlays (

Table 2. Parameters of the approximated model for capital expenditure PLN/kW (Y) and installation power kW (X).

Specification	Est.	S. E.	t-Val.		R2
(Intercept)	6557.329	252.923	25.926	0.000	0.0891
X	−406.592	240.782	−1.689	0.102

Source: own study.

). Based on the materials provided by investors, the following types of inputs were identified:

• photovoltaic modules (PV);
• wiring (Cables);
• inverters (Inver.);
• frames (Frame);
• trafostations (Trafo);
• electricity connections and services (Attached.);
• earthworks, fencing (Fence);
• land acquisition (Land);
• investor supervision (Supervision);
• business plans, feasibility studies, project documentation (Studies);
• other costs: surveying work, project promotion, training, consulting services and others (Other).

Based on the capital expenditures thus extracted, their structure was calculated (

Table 3. Type structure of capital expenditures [%].

No.	PV	Cables	Inver.	Frame	Trafo	Attached.	Fence	Land	Supervision	Study	Other	Total
1.	51.65	14.38	11.44	8.61	4.87	3.18	1.92	1.46	0.77	0.81	0.90	100.00
2.	52.01	14.16	10.70	8.92	4.96	3.58	1.93	1.29	0.83	0.84	0.77	100.00
3.	50.35	14.95	11.42	9.00	5.15	3.77	1.58	1.30	0.78	0.85	0.86	100.00
4.	50.37	13.80	11.93	9.21	5.17	3.46	1.73	1.51	1.04	1.04	0.74	100.00
5.	51.97	13.51	10.82	9.40	5.15	3.36	1.84	1.33	0.93	0.85	0.82	100.00
6.	49.45	15.38	11.11	9.59	5.16	3.27	1.92	1.11	1.00	0.77	1.23	100.00
7.	50.94	14.30	12.27	9.67	5.01	3.35	1.30	0.00	0.91	0.91	1.35	100.00
8.	48.90	13.95	12.21	9.47	5.04	3.59	1.74	1.56	0.99	0.88	1.66	100.00
9.	51.50	14.09	12.09	9.75	5.12	3.26	1.25	0.00	1.09	0.81	1.05	100.00
10.	48.78	14.98	11.02	9.29	5.32	3.68	1.95	1.90	1.01	0.84	1.23	100.00
11.	50.74	14.23	11.96	9.83	5.18	3.26	1.30	0.00	1.08	0.93	1.49	100.00
12.	50.41	13.72	11.37	9.32	4.93	3.76	2.18	1.66	0.97	0.94	0.74	100.00
13.	51.80	13.70	12.13	9.36	5.03	3.26	1.34	0.00	0.97	0.87	1.55	100.00
14.	50.19	14.06	12.29	9.11	5.07	3.06	1.73	1.55	0.93	0.83	1.18	100.00
15.	50.73	14.82	10.94	9.09	5.10	3.60	1.80	1.19	0.98	0.94	0.82	100.00
16.	49.87	14.98	10.86	9.02	5.01	3.70	2.08	1.59	1.04	0.88	0.97	100.00
17.	49.35	15.28	11.99	8.98	4.94	3.27	2.03	1.62	1.00	0.98	0.55	100.00
18.	51.62	13.57	11.10	9.24	5.06	3.19	2.06	1.19	0.95	0.83	1.20	100.00
19.	51.58	13.62	10.72	9.25	5.11	3.06	2.28	1.33	0.98	0.82	1.25	100.00
20.	50.44	14.48	11.40	9.42	5.10	3.59	2.02	1.04	0.92	0.92	0.68	100.00
21.	50.45	14.55	11.79	9.18	5.06	3.07	1.61	1.59	0.97	0.89	0.84	100.00
22.	49.91	14.74	11.91	9.28	4.91	2.93	1.83	1.43	0.98	0.84	1.23	100.00
23.	52.20	13.94	11.62	9.41	4.86	2.99	1.55	0.00	0.99	0.87	1.57	100.00
24.	49.72	15.01	11.32	8.86	4.90	3.52	1.99	1.99	1.01	0.96	0.71	100.00
25.	51.12	15.12	11.73	9.86	4.88	2.76	1.34	0.00	0.96	0.88	1.35	100.00
26.	49.57	15.56	12.19	10.16	5.06	2.82	1.20	0.00	1.00	1.14	1.29	100.00
27.	49.01	14.96	11.82	9.57	5.11	3.12	1.96	1.60	0.94	1.23	0.67	100.00
28.	48.24	15.66	11.87	9.81	5.20	3.07	1.95	1.25	0.94	0.98	1.02	100.00
29.	51.42	14.61	10.84	9.17	5.16	2.82	1.82	1.12	0.67	0.99	1.38	100.00
30.	52.35	14.14	11.86	9.82	4.87	2.91	1.95	0.00	0.63	0.77	0.68	100.00
31.	49.59	14.57	11.52	9.70	5.38	2.93	2.09	1.62	1.05	0.78	0.75	100.00
Total	50.52	14.49	11.53	9.34	5.06	3.28	1.80	1.11	0.94	0.90	1.03	100.00

Source: own compilation based on information provided by investors.

).

In the structure of capital costs, the most significant item was the purchase and installation of PV panels—50.52% (48.24 to 52.35%), followed by cabling—14.49% (13.51–15.88%), inverters—11.53% (10.70–12.29%) and trafostations—5.06% (4.86–5.38%).

The information in Table 1 and Table 3 was cross-referenced to data in the latest report, Photovoltaic Market in Poland, which included results from 2023 [52]. In the same period, the share of expenditures related to purchasing and installing inverters and cabling increased by nearly half, especially on farms above 1 MW (Figure 4).

There were also significant reductions in unit capital expenditures between 2016 and 2023, from 25.9% (micro-installations) to 38.2% (PV farms over 1 MW). For installations from 51 to 1000 kW, the decrease was 28.8% (

Table 4. Investment expenditures for implementing PV installations by capacity in 2016–2023 [PLN/kW].

Market Segments	2016	2017	2018	2019	2020	2021	2022	2023
Micro-installations up to 50 kW	6344	5951	5712	5241	4719	4855	4958	4707
Installation from 51 to 1000 kW	5236	4819	4623	4412	4129	4253	3907	3735
Farms over 1000 kW	4768	4541	4287	4011	3873	3978	3387	2948

Source: own compilation based on [17,52,53].

).

3.2. Production and Revenue

The investment projects studied were implemented in 2014–2016; hence, it was decided to analyze the full-year production results obtained for 2017–2022. In the first stage, the amount of energy generated and fed into the grid and the yield (productivity) in MWh per 1 MW of installed capacity were determined. The amount of energy generated and fed into the grid was determined based on readings from installed electricity meters. The average annual volume of this indicator was 1040.98 MWh/MW. The study’s results confirmed the thesis that the Lublin Province is characterized by some of the most favorable locational conditions for photovoltaic installations [54]. Nevertheless, the productivity of the studied installations varied significantly, from 783 to 1180 MWh/MW (

Table 5. Productivity of PV installations by capacity [MWh/MW].

Power	Average	Minimal	Maximum	Median
Total	1040.98	783.87	1180.11	1047.51
Less than 0.1 MW	1069.72	971.22	1161.32	1052.81
0.1 to 1 MW	1036.15	783.87	1158.09	1044.01
above 1 MW	1049.34	937.42	1180.11	1067.49

Source: own study.

and

Table 6. The amount of electricity generated and fed into the grid and the productivity of the studied installations from 2017 to 2022.

No.	Power	Amount of Electricity Generated (MWh)						Amount of Electricity Injected into the Grid (MWh)						Electricity Input to Electricity Produced (%)						Productivity MWh/1MW of Installed Capacity
	MW	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022
1.	0.92	834.8	929.5	944.7	912.5	825.6	854.6	834.8	929.5	944.7	912.5	825.6	854.6	100.0	100.0	100.0	100.0	100.0	100.0	907	1010	1027	992	897	929
2.	0.03	32.2	31.1	29.9	32.1	30.6	31.1	5.2	6.3	6.3	6.7	6.8	8.7	16.1	20.3	21.1	20.9	22.2	28.0	1073	1037	997	1070	1020	1037
3.	1	978.1	1069.3	1003.2	977.3	961.2	838.2	978.1	1069.3	1003.2	977.3	961.2	838.2	100.0	100.0	100.0	100.0	100.0	100.0	978	1069	1003	977	961	838
4.	1.99	2137.1	2348	2282.9	2311.4	2198.7	2098.7	1007.2	1091.6	1095.2	1080	978.6	1071.7	47.1	46.5	48.0	46.7	44.5	35.9	1074	1180	1147	1162	1105	1049
5.	1.47	1501.2	1640.3	1536.9	1619.8	1522.9	1616.3	1501.2	1640.3	1536.9	1619.8	1522.9	1616.3	100.0	100.0	100.0	100.0	100.0	100.0	1021	1116	1046	1102	1036	1100
6.	0.96	932.4	1080	1062.2	1059.2	950.2	946.2	932.4	1080	1062.2	1059.2	950.2	946.2	100.0	100.0	100.0	100.0	100.0	100.0	971	1125	1106	1103	990	986
7.	0.99	971.3	1038.4	1066.2	1058.8	959.5	1003.9	971.3	1038.4	1066.2	1058.8	959.5	1003.9	100.0	100.0	100.0	100.0	100.0	100.0	981	1049	1077	1069	969	1014
8.	0.3	295.2	334	347.4	337.3	319.4	322.1	230.5	249.8	260.3	269.3	239.9	263.2	78.1	74.8	74.9	79.8	75.1	81.7	984	1113	1158	1124	1065	1074
9.	0.96	983.5	1006.9	1073.2	1093.1	989.4	1012.6	331.3	251.2	586.7	381.1	297.9	489.4	33.7	24.9	54.7	34.9	30.1	48.3	1024	1049	1118	1139	1031	1055
10.	0.93	971.5	1060.4	1039.9	1023.1	967.6	1013.5	971.5	1060.4	1039.9	1023.1	967.6	1013.5	100.0	100.0	100.0	100.0	100.0	100.0	1045	1140	1118	1100	1040	1090
11.	1.2	1234.1	1287.8	1300.9	1124.6	1188.4	1206.3	1014.8	1117.9	1128.9	1093.7	1068.9	1108.2	82.2	86.8	86.8	97.3	89.9	91.9	1028	1073	1084	937	990	1005
12.	0.99	948.6	1111.2	949.4	933.5	923.2	1004.1	948.6	1111.2	949.4	933.5	923.2	1004.1	100.0	100.0	100.0	100.0	100.0	100.0	958	1122	959	943	933	1014
13.	0.99	1017.6	1122.1	1124.5	1093.9	1045.3	986.7	1017.6	1122.1	1124.5	1093.9	1045.3	986.7	100.0	100.0	100.0	100.0	100.0	100.0	1028	1133	1136	1105	1056	997
14.	0.09	87.4	102.6	104.5	91.0	96.9	100.8	87.4	102.6	104.5	91.0	96.9	100.8	100.0	100.0	100.0	100.0	100.0	100.0	971	1140	1161	1011	1077	1120
15.	0.99	931.2	1129.3	1119.5	1029.4	1015.5	1305.3	931.2	1129.3	1119.5	1029.4	1015.5	1305.3	100.0	100.0	100.0	100.0	100.0	100.0	941	1141	1131	1040	1026	1318
16.	1.25	1372.2	1452.2	1444.3	1420.6	1327.5	1242.9	1372.2	1452.2	1444.3	1420.6	1327.5	1242.9	100.0	100.0	100.0	100.0	100.0	100.0	1098	1162	1155	1136	1062	994
17.	1	929.1	1079.7	1081.1	1039.5	1118.2	1092.7	929.1	1079.7	1081.1	1039.5	810.5	846.8	100.0	100.0	100.0	100.0	72.5	77.5	929	1080	1081	1040	1118	1093
18.	0.79	773.3	864.1	789.4	792.7	814.4	799.5	773.3	864.1	789.4	792.7	725.8	626.6	100.0	100.0	100.0	100.0	89.1	78.4	979	1094	999	1003	1031	1012
19.	1.52	1673.1	1723.9	1672.7	1567.2	1622.7	1554	640.2	746.9	723.7	690.7	651.7	666.8	38.3	43.3	43.3	44.1	40.2	42.9	1101	1134	1100	1031	1068	1022
20.	0.35	335	386.3	399.2	385	362.6	365.6	335	386.3	399.2	385	362.6	365.6	100.0	100.0	100.0	100.0	100.0	100.0	957	1104	1141	1100	1036	1045
21.	0.78	711	788.9	843.7	822.5	803.3	799.2	711	788.9	607.1	757.5	685.9	728.5	100.0	100.0	72.0	92.1	85.4	91.2	912	1011	1082	1054	1030	1025
22.	0.7	669.6	763.3	737.8	730.3	683.6	725.3	669.6	763.3	737.8	730.3	683.6	725.3	100.0	100.0	100.0	100.0	100.0	100.0	957	1090	1054	1043	977	1036
23.	0.96	896.7	955.1	1037.3	1030	947.1	1031.7	896.7	955.1	1037.3	1030	947.1	1031.7	100.0	100.0	100.0	100.0	100.0	100.0	934	995	1081	1073	987	1075
24.	0.6	478	469.9	581	646.7	590	603.2	478.2	469.9	58.01	646.7	590	603.2	100.0	100.0	10.0	100.0	100.0	100.0	797	783	968	1078	983	1005
25.	1.98	1911.6	2154.7	2140.7	2049.9	1906	1942.8	1911.6	2154.7	2140.7	2049.9	1906	1942.8	100.0	100.0	100.0	100.0	100.0	100.0	965	1088	1081	1035	963	981
26.	1	1271.2	1487.9	1427.9	1401.8	1296.7	1320.2	1271.2	1487.9	1427.9	1401.8	1296.7	1320.2	100.0	100.0	100.0	100.0	100.0	100.0	1271	1488	1428	1402	1297	1320
27.	0.99	1034.9	1068	999.5	1083.6	1044	1076.2	351.3	411.7	401.3	384.4	354.9	372.3	33.9	38.5	40.2	35.5	34.0	34.6	1045	1079	1010	1095	1055	1087
28.	0.99	1014.1	1076.6	1011.1	1044.2	1085.4	1076.2	493.3	576.3	567.4	544.5	503.6	519.5	48.6	53.5	56.1	52.1	46.4	48.3	1024	1087	1021	1055	1096	1087
29.	0.99	971.3	1030.6	1090	1057.8	959.5	1000.2	907.5	1025.2	1027.6	950.9	925.9	847.4	93.4	99.5	94.3	89.9	96.5	84.7	981	1041	1101	1068	969	1010
30.	0.5	503.2	579	564.1	552.3	500.2	514	503.2	579	564.1	552.3	500.2	514	100.0	100.0	100.0	100.0	100.0	100.0	1006	1158	1128	1105	1000	1028
31.	1.4	1321.9	1493.1	1524.7	1439.2	1354.5	1370	1321.9	1493.1	1524.7	1439.2	1354.5	1370	100.0	100.0	100.0	100.0	100.0	100.0	944	1067	1089	1028	968	979

Source: own calculations based on information obtained from the Lublin Agency for Entrepreneurship Support, the Department for Regional Operational Program Management of the Lubelskie Voivodeship Marshal’s Office in Lublin, Polska Grupa Energetyczna S.A. Distribution Branch of Lublin and Investors.

).

The reasons for this variation can be attributed mainly to the type of technology used, the quality of the modules as well as the inverters, the angle of the panels to the sun, shading, terrain, and air pollution [53,55]. The substrates of these disparities were not studied, focusing only on the relationship by power output. Micro-installations had the highest productivity. This result is consistent with one of the results of a study conducted by Z. Brodzinski et al. [53].

At the same time, it was characterized by high monthly variability, especially between the November–February and May–September periods (Figure 5 and Figure 6).

In most of the facilities surveyed (19), all the electricity generated was fed into the distribution system operator’s (DSO) grid. In the remaining 12 facilities, investors used part of the generated electricity for their needs. To the greatest extent, this way of managing the generated electricity, from 72.0 to 83.9%, is concerned with micro-installations. In the remaining 11 facilities, it ranged from 3.5 to 69.9%. The Operator of the Distribution System (DSO) into whose energy network this was introduced was “PGE Dystrybucja Spółka Akcyjna”, based in Lublin. The representatives of this entity provided the necessary anonymized data at the request of the Director of IRWiR PAN.

Based on information obtained from investors, revenues from generated electricity were determined. Their value consisted of:

• revenues from the sale of electricity generated in the studied photovoltaic systems and property rights to certificates of origin (COR);
• the value of generated and consumed electricity for investors’ use.

Revenue from the sale of generated electricity was obtained from only 12 investors. For the others, it was estimated based on the amount of electricity injected into the DSO network. The value of generated and consumed electricity for the investors’ needs was estimated based on average energy purchase prices published by the Energy Regulatory Office (

Table 7. Prices of electricity and property rights to certificates of origin.

Specification	2017	2018	2019	2020	2021	2022	2022 (2017 = 100)
Energy sales prices (PLN/MWh)	180	199	202	303	279	354	196.7
Consumed energy prices	361	571	731	718	912	1027	284.5
own purposes (PLN/MWh)	39	129	145	137	204	227	582.1

Source: own study.

).

In Poland, the Tradable Green Certificates system (TGCs) has been in use since 2006, with the regulator determining how they are allocated and leaving it to the market to determine the price [56]. Certificates of origin for electricity are granted for 15 consecutive years but no longer than until 31 December 2035. This period is counted from the date of energy generation for the first time, confirmed by an issued certificate of origin. The condition for their granting is the generation of energy in a RES installation, which produced energy for the first time before 1 July 2016. All of the examined installations took advantage of this opportunity. The revenues thus determined are summarized in

Table 8. Revenues from the development of electricity generated by the studied photovoltaic installations.

No.	Revenues from the Sale of Electricity						Value of Energy Consumed for Own Use						Revenue from Sales of PMSP						Total Revenues
	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022
1.	150.3	185.0	190.8	276.5	230.3	302.5	0.0	0.0	0.0	0.0	0.0	0.0	26.7	113.4	137.0	126.8	171.7	206.0	177.0	298.4	327.8	403.3	402.1	508.5
2.	0.9	1.2	1.3	2.0	1.8	3.0	9.7	14.2	17.3	18.2	21.7	23.0	0.2	0.8	0.9	0.9	1.4	2.0	10.9	16.2	19.4	21.1	24.9	28.0
3.	176.1	212.8	202.6	296.1	268.2	296.7	0.0	0.0	0.0	0.0	0.0	0.0	38.1	137.9	145.5	133.9	196.1	190.3	214.2	350.7	348.1	430.0	464.3	487.0
4.	187.3	227.1	220.1	317.5	270.1	373.0	407.9	717.4	868.2	884.1	1112.7	1054.7	36.3	153.9	170.9	150.1	198.7	227.2	631.5	1098.4	1259.2	1351.8	1581.5	1654.9
5.	276.2	326.4	315.1	489.2	438.6	601.3	0.0	0.0	0.0	0.0	0.0	0.0	66.1	210.0	235.1	217.1	310.7	342.7	342.3	536.4	550.2	706.2	749.3	943.9
6.	166.0	218.2	211.4	315.6	262.3	325.5	0.0	0.0	0.0	0.0	0.0	0.0	36.4	123.1	156.1	150.4	188.1	218.6	202.3	341.3	367.5	466.0	450.4	544.1
7.	174.8	206.6	215.4	320.8	267.7	355.4	0.0	0.0	0.0	0.0	0.0	0.0	37.9	134.0	154.6	145.1	195.7	227.9	212.7	340.6	370.0	465.9	463.4	583.3
8.	41.5	49.7	52.6	81.6	66.9	93.2	23.4	48.1	63.7	48.8	72.5	60.5	9.0	32.2	37.7	36.9	48.9	59.7	73.8	130.0	154.0	167.3	188.4	213.4
9.	59.6	50.0	118.5	115.5	83.1	173.2	235.4	431.5	355.6	511.2	630.6	537.3	12.9	32.4	85.1	52.2	60.8	111.1	308.0	513.9	559.2	678.9	774.5	821.7
10.	174.9	211.0	210.1	310.0	270.0	358.8	0.0	0.0	0.0	0.0	0.0	0.0	37.9	136.8	150.8	140.2	197.4	230.1	212.8	347.8	360.8	450.2	467.4	588.8
11.	182.7	225.8	211.1	343.4	290.7	386.8	79.2	97.0	125.7	22.2	109.0	100.7	51.8	130.8	144.5	152.0	222.3	267.1	313.6	453.6	481.3	517.6	622.1	754.6
12.	170.7	221.1	191.8	282.9	257.6	355.5	0.0	0.0	0.0	0.0	0.0	0.0	37.0	143.3	137.7	127.9	188.3	227.9	207.7	364.5	329.4	410.7	445.9	583.4
13.	183.2	223.3	227.1	331.5	291.6	349.3	0.0	0.0	0.0	0.0	0.0	0.0	39.7	144.8	163.1	149.9	213.2	224.0	222.9	368.0	390.2	481.3	504.9	573.3
14.	15.7	20.4	21.1	27.6	27.0	35.7	0.0	0.0	0.0	0.0	0.0	0.0	3.4	13.2	15.2	12.5	19.8	22.9	19.1	33.7	36.3	40.0	46.8	58.6
15.	172.3	237.2	228.4	330.4	306.7	475.1	0.0	0.0	0.0	0.0	0.0	0.0	39.1	155.8	161.2	146.2	211.2	305.4	211.4	393.0	389.6	476.6	517.9	780.6
16.	247.0	289.0	291.7	430.4	370.4	440.0	0.0	0.0	0.0	0.0	0.0	0.0	53.5	187.3	209.4	194.6	270.8	282.1	300.5	476.3	501.2	625.1	641.2	722.1
17.	167.2	214.9	218.4	315.0	226.1	299.8	0.0	0.0	0.0	0.0	280.6	252.5	36.2	139.3	156.8	142.4	165.3	192.2	203.5	354.1	375.1	457.4	672.1	744.5
18.	139.2	172.0	159.5	240.2	202.5	221.8	0.0	0.0	0.0	0.0	80.8	177.6	30.2	111.5	114.5	108.6	148.1	142.2	169.4	283.4	273.9	348.8	431.4	541.6
19.	115.2	148.6	146.2	209.3	181.8	236.0	372.9	557.9	693.7	629.3	885.6	911.2	25.0	96.4	104.9	94.6	132.9	151.4	513.1	802.9	944.8	933.2	1200.3	1298.6
20.	60.3	76.9	80.6	116.7	101.2	129.4	0.0	0.0	0.0	0.0	0.0	0.0	13.1	49.8	57.9	52.7	74.0	83.0	73.4	126.7	138.5	169.4	175.1	212.4
21.	123.7	148.3	120.2	233.3	200.3	254.2	0.0	0.0	173.0	46.7	107.1	72.6	22.8	111.2	91.7	97.7	138.6	154.4	146.5	259.5	384.8	377.7	445.9	481.3
22.	121.9	146.6	150.5	213.2	187.3	255.3	0.0	0.0	0.0	0.0	0.0	0.0	25.4	97.7	102.6	104.4	131.9	163.2	147.3	244.3	253.1	317.7	319.2	418.5
23.	161.4	190.1	209.5	312.1	264.2	365.2	0.0	0.0	0.0	0.0	0.0	0.0	35.0	123.2	150.4	141.1	193.2	234.2	196.4	313.3	359.9	453.2	457.4	599.4
24.	86.1	93.5	11.7	196.0	164.6	213.5	−0.1	0.0	382.3	0.0	0.0	0.0	18.6	60.6	8.4	88.6	120.4	136.9	104.7	154.1	402.4	284.5	285.0	350.5
25.	342.2	435.2	445.3	610.9	522.2	703.3	0.0	0.0	0.0	0.0	0.0	0.0	76.5	293.0	314.7	272.6	392.6	435.2	418.6	728.3	759.9	883.5	914.9	1138.5
26.	228.8	296.1	288.4	424.7	361.8	467.4	0.0	0.0	0.0	0.0	0.0	0.0	49.6	191.9	207.0	192.0	264.5	299.7	278.4	488.0	495.5	616.8	626.3	767.0
27.	63.2	81.9	81.1	116.5	99.0	131.8	246.8	374.7	437.3	502.0	628.5	722.9	13.7	53.1	58.2	52.7	72.4	84.5	323.7	509.8	576.5	671.2	799.9	939.2
28.	88.8	114.7	114.6	165.0	140.5	183.9	188.0	285.7	324.3	358.8	530.6	571.7	19.2	74.3	82.3	74.6	102.7	117.9	296.0	474.7	521.2	598.4	773.8	873.6
29.	156.1	203.0	207.6	296.7	248.1	289.8	23.0	3.1	45.6	76.8	30.6	156.9	28.1	132.3	155.2	121.7	192.6	206.8	207.3	338.3	408.4	495.2	471.4	653.5
30.	92.6	118.7	118.5	164.6	141.1	187.1	0.0	0.0	0.0	0.0	0.0	0.0	22.1	70.1	77.8	72.4	106.0	125.4	114.7	188.8	196.3	236.9	247.1	312.5
31.	236.6	298.6	304.9	439.0	373.8	486.4	0.0	0.0	0.0	0.0	0.0	0.0	48.9	195.6	216.5	202.9	269.5	283.6	285.5	494.2	521.4	641.9	643.4	769.9

Source: own calculations based on information obtained from the Lublin Agency for Entrepreneurship Support, the Department for Regional Operational Program Management of the Lubelskie Voivodeship Marshal’s Office in Lublin, Polska Grupa Energetyczna S.A. Distribution Branch of Lublin and Investors.

.

The analysis shows a sizable increase in revenues in the years under review, mainly due to rapidly rising electricity prices and property rights to certificates of origin. The average electricity sales prices entering the distribution system operator’s grid in 2022 were nearly double those of 2017. Even more significant differences were the prices for the purchase of energy by end users, which in the same period were not far from three times higher, which made some investors decide to mix sales and use them in their business activities. In the case of property rights to certificates of origin, these increases were almost sixfold.

3.3. Operating Costs

Operating costs are related to the operation and use of assets created during the project’s implementation [57]. Based on the materials provided by investors, the following categories of operating costs were identified:

• depreciation;
• materials;
• third-party services;
• taxes and other fees;
• salaries;
• insurance;
• other costs.

The data in

Table 9. Structure of operating costs [%].

No.	Depreciation						Materials						Third-Party Services						Taxes and Other Fees
	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022
1.	82.4	80.5	80.9	75.2	74.7	71.4	3.6	3.2	3.0	5.3	4.3	4.3	1.0	1.1	1.5	1.5	1.7	5.0	6.2	6.0	7.0	7.5	7.7	8.0
2.	45.4	46.4	47.5	42.4	41.8	37.5	21.6	19.3	25.4	25.3	16.4	16.5	4.9	7.2	2.3	2.5	4.5	6.7	9.2	9.4	10.7	11.1	14.4	17.0
3.	83.4	83.4	83.1	81.3	78.2	75.4	5.5	2.7	3.1	3.2	4.1	4.2	0.8	1.0	1.3	1.2	1.4	2.2	5.2	5.5	6.1	6.5	6.7	7.6
4.	82.4	81.1	78.4	77.1	73.8	73.2	4.9	3.0	3.0	2.6	3.2	3.7	0.8	1.1	1.6	1.7	1.9	3.5	6.0	6.1	8.1	8.1	9.0	7.9
5.	85.5	82.8	81.5	81.5	80.3	75.4	3.2	2.7	3.7	3.9	3.3	3.7	0.8	1.0	1.4	1.2	1.6	4.2	s5.4	5.4	5.8	5.4	5.7	7.1
6.	82.7	80.5	78.6	78.5	77.2	70.9	4.1	3.4	5.0	4.8	3.9	4.8	1.0	1.1	1.5	1.3	1.6	4.8	6.0	5.8	6.7	6.1	6.9	7.7
7.	75.6	72.7	70.7	69.2	67.6	63.5	5.1	4.3	5.8	6.2	5.8	5.5	1.4	1.6	2.1	2.2	2.5	6.1	8.8	8.4	9.4	9.5	9.9	10.8
8.	74.8	70.7	66.9	65.8	63.3	56.2	8.2	6.5	8.5	6.7	6.6	7.0	1.3	1.9	2.5	2.3	2.9	7.2	6.9	7.6	10.1	11.9	12.4	13.7
9.	75.4	73.1	71.3	69.3	67.9	65.3	6.1	4.4	3.8	5.3	4.9	5.5	1.4	1.7	2.2	2.2	2.2	3.6	8.3	8.4	10.2	10.1	11.7	11.3
10.	80.7	77.6	75.3	75.6	72.4	69.4	6.3	5.1	5.1	3.8	4.1	5.5	0.9	1.2	1.6	1.5	2.0	3.4	5.9	6.5	7.9	8.0	8.5	9.4
11.	77.0	72.1	70.7	69.9	70.2	67.4	5.6	5.5	4.5	4.7	4.8	5.3	1.3	1.4	2.2	1.9	1.7	3.6	7.8	8.5	9.4	9.9	10.5	10.2
12.	82.9	80.4	78.8	75.8	75.0	71.8	3.9	4.7	4.9	5.5	4.9	5.3	0.9	1.1	1.6	1.7	1.8	3.2	5.6	5.3	6.8	8.0	8.5	8.7
13.	76.3	73.1	70.0	69.1	67.3	65.6	5.3	5.8	5.8	5.0	5.2	5.9	1.3	1.5	2.2	2.3	2.4	3.6	8.5	8.0	9.8	10.4	11.3	10.8
14.	67.2	59.9	63.0	60.6	53.3	45.8	13.1	16.2	14.1	15.2	17.1	17.1	2.2	2.2	2.6	3.4	4.0	5.1	6.9	7.0	9.7	7.3	9.7	12.8
15.	81.7	82.2	80.7	80.0	78.4	75.5	5.8	4.6	4.5	4.2	3.9	4.4	0.9	1.0	1.4	1.5	1.8	2.6	5.7	5.2	5.8	5.8	6.4	8.0
16.	85.3	83.1	81.2	80.8	80.1	77.2	3.2	3.9	4.0	3.8	3.5	3.9	0.9	0.9	1.2	1.3	1.6	2.7	5.3	4.8	5.8	5.5	6.0	6.3
17.	79.1	77.1	75.1	73.8	72.6	68.9	5.7	5.2	5.0	5.4	4.6	5.1	1.1	1.2	1.8	1.9	2.2	5.2	6.6	6.4	7.1	7.3	8.8	9.2
18.	79.0	77.8	75.4	74.3	74.8	70.4	5.1	6.1	5.9	5.1	4.5	5.1	1.2	1.2	1.4	1.5	1.9	4.5	7.3	6.1	7.1	6.6	7.2	7.3
19.	82.1	80.9	79.9	77.6	76.7	74.5	4.5	4.0	4.0	4.0	4.0	4.2	0.9	1.1	1.4	1.5	1.7	2.7	6.2	5.7	6.3	6.5	7.9	7.9
20.	78.0	75.0	72.1	68.4	67.9	61.4	3.4	2.5	2.4	4.5	3.0	4.0	1.4	1.5	2.0	2.0	2.5	6.0	8.4	8.1	9.4	9.9	10.9	13.1
21.	81.2	81.2	79.5	78.4	79.0	75.2	4.9	3.8	4.6	4.1	3.3	3.8	1.0	1.2	1.4	1.5	1.7	4.6	6.4	5.8	6.2	6.6	6.5	6.7
22.	79.7	76.1	75.2	75.9	73.8	70.4	4.6	6.5	6.3	3.9	4.8	5.7	1.2	1.2	1.6	2.0	2.3	5.0	7.4	6.3	7.1	7.3	7.4	6.1
23.	78.2	73.4	71.2	71.4	68.2	66.1	4.1	5.7	5.7	4.5	4.8	5.0	1.3	1.5	2.1	2.5	2.6	4.3	8.1	7.7	9.0	9.2	10.8	10.1
24.	82.5	82.3	80.4	81.3	79.2	75.6	4.4	6.1	6.0	2.8	3.4	4.0	0.9	0.8	1.2	1.6	2.0	3.8	6.0	4.3	5.2	5.8	5.4	5.6
25.	76.4	73.9	73.6	72.5	68.5	65.3	4.5	4.4	3.5	3.1	4.0	4.4	1.4	1.5	2.0	2.1	2.4	4.4	8.8	8.2	9.5	10.2	10.2	10.5
26.	75.0	71.4	68.2	67.0	63.5	60.3	5.5	6.2	6.3	5.0	5.6	6.0	1.4	1.6	2.2	2.8	3.2	6.0	9.3	8.5	10.6	11.4	11.8	10.4
27.	82.0	83.1	80.5	80.4	78.3	73.6	4.5	3.2	4.8	3.9	3.5	4.0	0.9	1.2	1.4	1.5	1.8	3.0	6.2	4.8	5.8	6.1	6.3	7.6
28.	81.9	81.1	78.6	77.9	75.0	73.9	4.3	3.5	5.0	3.4	3.6	3.6	0.9	1.1	1.5	1.6	1.8	2.9	6.4	5.9	6.5	7.6	8.6	8.4
29.	82.3	80.3	81.7	80.8	79.5	76.7	5.6	7.3	4.5	3.8	3.5	3.9	0.8	1.1	1.3	1.4	1.8	2.4	5.7	4.5	5.6	6.0	6.6	6.5
30.	80.0	78.0	73.3	73.1	70.2	68.3	5.3	4.6	5.7	4.6	4.7	5.4	1.0	1.2	1.6	2.2	2.7	3.1	6.6	6.5	8.3	7.5	8.8	8.9
31.	82.4	81.2	81.0	77.6	75.1	70.2	3.4	2.0	2.0	4.0	4.7	4.8	1.0	1.1	1.6	1.6	1.6	5.8	6.7	6.5	7.3	7.4	7.2	7.1
No.	Salaries						Insurance						Other costs						Total
	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022	2017	2018	2019	2020	2021	2022
1.	4.5	6.5	5.5	7.8	8.8	8.3	0.2	0.3	0.3	0.5	0.6	0.6	2.1	2.3	1.9	2.2	2.2	2.4	100.0	100.0	100.0	100.0	100.0	100.0
2.	10.3	9.4	10.7	13.6	14.4	10.7	0.5	0.6	0.6	0.5	1.0	0.9	8.1	7.7	2.8	4.5	7.5	10.7	100.0	100.0	100.0	100.0	100.0	100.0
3.	3.5	5.4	4.7	5.6	7.2	8.1	0.2	0.3	0.3	0.4	0.5	0.6	1.4	1.6	1.6	1.8	1.8	1.9	100.0	100.0	100.0	100.0	100.0	100.0
4.	4.0	6.5	6.4	7.8	9.1	8.5	0.2	0.4	0.4	0.5	0.7	0.6	1.7	1.8	2.1	2.1	2.3	2.6	100.0	100.0	100.0	100.0	100.0	100.0
5.	3.5	5.7	5.8	6.2	6.7	7.0	0.2	0.3	0.2	0.3	0.5	0.5	1.5	2.1	1.6	1.4	1.9	2.2	100.0	100.0	100.0	100.0	100.0	100.0
6.	4.3	6.4	6.1	7.1	7.7	8.5	0.2	0.3	0.3	0.4	0.5	0.6	1.8	2.5	1.8	1.8	2.1	2.6	100.0	100.0	100.0	100.0	100.0	100.0
7.	6.1	9.3	9.1	9.4	10.8	10.6	0.3	0.5	0.4	0.6	0.7	0.8	2.7	3.3	2.5	2.9	2.7	2.7	100.0	100.0	100.0	100.0	100.0	100.0
8.	4.5	8.8	9.0	9.5	10.0	10.8	0.2	0.4	0.4	0.6	0.7	0.8	4.1	4.1	2.6	3.3	4.1	4.3	100.0	100.0	100.0	100.0	100.0	100.0
9.	6.0	9.0	9.4	9.8	10.1	11.0	0.3	0.5	0.4	0.6	0.8	0.8	2.6	3.0	2.8	2.8	2.4	2.5	100.0	100.0	100.0	100.0	100.0	100.0
10.	4.0	6.6	7.7	8.6	9.9	8.9	0.2	0.4	0.3	0.4	0.7	0.7	1.9	2.6	2.0	2.1	2.5	2.7	100.0	100.0	100.0	100.0	100.0	100.0
11.	5.6	9.4	10.4	10.6	9.9	10.2	0.3	0.5	0.4	0.5	0.7	0.8	2.5	2.6	2.5	2.5	2.2	2.6	100.0	100.0	100.0	100.0	100.0	100.0
12.	3.9	5.8	5.8	6.8	6.9	8.0	0.2	0.3	0.3	0.4	0.5	0.6	2.7	2.3	1.8	1.9	2.3	2.4	100.0	100.0	100.0	100.0	100.0	100.0
13.	5.7	8.6	9.0	9.9	10.3	10.7	0.3	0.5	0.4	0.6	0.7	0.8	2.6	2.5	2.7	2.7	2.7	2.7	100.0	100.0	100.0	100.0	100.0	100.0
14.	5.0	6.7	7.9	8.2	8.4	8.5	0.3	0.6	0.3	0.6	0.7	0.6	5.3	7.5	2.3	4.8	6.7	10.0	100.0	100.0	100.0	100.0	100.0	100.0
15.	4.0	5.5	5.8	6.5	7.1	7.0	0.2	0.3	0.3	0.3	0.5	0.5	1.7	1.4	1.5	1.7	1.9	2.1	100.0	100.0	100.0	100.0	100.0	100.0
16.	3.5	5.4	6.0	6.4	6.4	7.1	0.2	0.3	0.3	0.3	0.5	0.5	1.7	1.6	1.6	1.8	2.0	2.1	100.0	100.0	100.0	100.0	100.0	100.0
17.	4.8	7.2	8.6	9.1	8.8	8.6	0.2	0.4	0.3	0.5	0.6	0.6	2.5	2.4	1.9	2.1	2.4	2.4	100.0	100.0	100.0	100.0	100.0	100.0
18.	4.8	6.4	8.0	10.2	8.4	9.3	0.3	0.3	0.3	0.4	0.6	0.7	2.4	2.1	1.8	2.0	2.5	2.8	100.0	100.0	100.0	100.0	100.0	100.0
19.	4.3	6.2	6.5	8.2	7.2	7.9	0.2	0.3	0.3	0.4	0.5	0.6	1.9	1.8	1.7	1.8	2.1	2.2	100.0	100.0	100.0	100.0	100.0	100.0
20.	5.5	8.8	11.3	11.8	12.2	12.1	0.3	0.5	0.4	0.5	0.7	0.7	3.1	3.8	2.4	2.8	2.7	2.9	100.0	100.0	100.0	100.0	100.0	100.0
21.	4.2	6.0	6.3	7.1	7.6	7.7	0.2	0.3	0.3	0.4	0.5	0.5	2.0	1.6	1.7	1.9	1.4	1.6	100.0	100.0	100.0	100.0	100.0	100.0
22.	4.7	7.4	7.6	8.3	8.6	9.5	0.2	0.4	0.3	0.4	0.6	0.6	2.1	2.1	1.9	2.2	2.5	2.7	100.0	100.0	100.0	100.0	100.0	100.0
23.	5.6	8.5	9.2	9.4	10.3	11.1	0.2	0.4	0.4	0.5	0.7	0.7	2.5	2.8	2.4	2.5	2.5	2.9	100.0	100.0	100.0	100.0	100.0	100.0
24.	3.9	4.7	5.6	6.4	7.4	8.1	0.2	0.2	0.2	0.3	0.5	0.5	2.1	1.6	1.4	1.8	2.2	2.4	100.0	100.0	100.0	100.0	100.0	100.0
25.	6.0	8.9	8.5	8.8	11.1	11.4	0.3	0.5	0.4	0.6	0.8	0.7	2.6	2.6	2.6	2.8	3.0	3.3	100.0	100.0	100.0	100.0	100.0	100.0
26.	6.2	9.2	9.5	9.9	11.7	11.8	0.3	0.5	0.5	0.6	0.8	0.7	2.3	2.6	2.8	3.2	3.4	4.8	100.0	100.0	100.0	100.0	100.0	100.0
27.	4.4	5.4	5.7	5.8	7.4	8.7	0.2	0.3	0.3	0.4	0.5	0.5	1.9	2.0	1.6	2.0	2.3	2.6	100.0	100.0	100.0	100.0	100.0	100.0
28.	4.5	6.2	6.3	7.0	8.2	8.2	0.2	0.3	0.3	0.4	0.5	0.5	1.8	1.9	1.8	2.1	2.3	2.5	100.0	100.0	100.0	100.0	100.0	100.0
29.	3.7	4.7	5.2	5.8	6.1	7.7	0.2	0.3	0.2	0.3	0.5	0.6	1.8	1.8	1.5	1.9	2.0	2.2	100.0	100.0	100.0	100.0	100.0	100.0
30.	5.0	7.5	8.7	9.6	10.1	10.3	0.2	0.4	0.4	0.5	0.6	0.7	1.9	1.8	2.1	2.5	2.9	3.4	100.0	100.0	100.0	100.0	100.0	100.0
31.	4.6	7.0	5.9	7.1	9.0	9.6	0.2	0.4	0.3	0.5	0.6	0.7	1.8	1.8	1.9	1.9	1.8	1.7	100.0	100.0	100.0	100.0	100.0	100.0

Source: own compilation based on information provided by investors.

show that depreciation accounted for the most oversized item in the operating cost structure, from 37.5 to 85.3%, mainly due to high capital expenditures. The linear method was used to determine this for all the installations surveyed. This significant variation was proportional to the installed capacity. In facilities up to 0.1 MW, it ranged from 37.5 to 67.2%, and above 1 MW, from 65.3 to 85.3%. The highest average level of the share of depreciation in operating costs occurred in 2017 (78.7%), while the highest was in 2022 (66.9%). In subsequent years, the value of this ratio decreased due to an increase in other charges, primarily salaries and wages, from 4.9% in 2017 to 9.0%, and taxes and other fees, from 6.9 to 8.9%, respectively.

The article puts forward the thesis that “Photovoltaic power generation is economically alternative to its generation using conventional sources”. In order to verify it, the methodology used by the Energy Market Agency S.A. for determining unit technical costs of energy production was used. These costs are published in the yearbook Statistics of Polish Electricity Generation [17]. The basis for their calculation is the amount of energy produced during the year and the value of operating costs in various types of power plants and thermal power plants, including those using renewable sources.

Table 10. Technical unit cost of electricity generation by type of power and thermal power plants in 2017–2022 [PLN/MWh].

Specification	2017	2018	2019	2020	2021	2022
Lignite-fired utility power plants	133.5	120.7	243.5	165.0	145.2	158.7
Hard coal-fired utility power plants	155.3	203.9	203.3	215.1	218.6	351.8
Thermal coal-fired combined heat and power plants	137.2	160.4	163.9	191.5	180.9	280.7
Gas-fired combined heat and power plants	219.4	213.5	215.4	167.6	200.3	602.6
Commercial biomass/biogas power plants and combined heat and power plants	417.4	284.8	345.6	329.9	301.3	616.1
Hydroelectric power plants—natural tributary	110.3	98.1	146.8	137.3	138.9	244.9
Wind power plants *	197.7	114.7	131.0	154.7	184.7	193.2
Photovoltaic power plants *	-	-	-	-	-	172.0
Results based on surveyed photovoltaic installations without subsidies
Total	301.5	281.5	290.5	300.4	332.7	339.7
Less than 0.1 MW	422.2	403.9	385.4	431.4	473.7	525.4
0.1 to 1 MW	314.5	291.0	300.1	307.7	330.6	349.5
Above 1 MW	278.8	264.1	273.0	286.5	335.1	320.1
Results based on surveyed photovoltaic installations with subsidies
Total	196.4	185.8	193.8	201.9	226.5	238.4
Less than 0.1 MW	260.0	258.8	241.1	273.8	321.6	378.3
0.1 to 1 MW	204.0	191.2	199.6	206.1	224.1	245.9
Above 1 MW	183.1	175.9	183.4	194.0	229.7	223.4

*—for installed capacity ≥ 10 MW. Source: own compilation based on [17].

summarizes the unit technical costs of electricity generation taken from the Polish Power Industry Statistics yearbooks and calculated based on our research, considering the installed capacity and financial support provided.

3.4. Assessment of the Profitability of the Investment Projects Studied

The subject of the study was also the evaluation of the economic efficiency of investment projects in photovoltaic installations. As criteria for the evaluation of the investments under study, the following were adopted:

• simple return on investment (ROI);
• simple payback period (SPP);
• net present value of investment (NPV);
• internal rate of return on investment (IRR);
• DPBT discounted payback period;
• averaged unit cost of electricity generation (LCOE).

Calculations were carried out for each investment project in two variants: with and without subsidy.

Since the assumed expected lifetime of the studied investments will be 25 years, conducting a reliable analysis required making assumptions about revenues and costs over the period (2023–2041). In determining them, historical data from the first years of operation (2017–2022), experience gained, and observations of personnel employed or providing services to the studied facilities, market forecasts of electricity prices and property rights to certificates of energy origin, as well as the literature on the subject were used. On this basis, the following assumptions were made:

• based on the forecasts of the Energy Regulatory Office, it was assumed that the average baseline annual increase in the sales price of electricity injected into the distribution system operator’s grid in a non-auction procedure would be 2%/year. The exact rate was assumed for the prices of generated energy, which investors used for their own needs (the reference level was the corresponding average electricity prices in 2021–2022);
• increase in the price of property rights to energy certificates of origin—2%/year of needs (the reference level was the average price in 2021–2022); it was assumed that the period of their granting began on 1 January 2017 and will be completed on 31 December 2031;
• like other technical infrastructure equipment, photovoltaic plants are characterized by gradually decreasing efficiency over time. For the long-term analysis, a constant decline in the level of efficiency of electricity generation for the plants under study was assumed at 0.7% per year starting in 2023. This is the average rate of efficiency decline declared by panel manufacturers. The reference level was the average annual volume of electricity generated in 2017–2022;
• the operation of freestanding photovoltaic power plants involves incurring operating costs, such as, but not limited to: maintenance, purchase of materials, repairs, land lease (optional), accounting services, taxes, insurance, etc. For this group of costs, an annual price increase of 3.03% was assumed (NBP projection data—an average of 3 years 2021–2023);
• preparation of the forecast involves adopting a particular value of the discount rate; based on information collected from investors, its value was set at 3%.

Any long-term investment project and photovoltaic installations are fraught with risk; hence, an additional sensitivity analysis was conducted. In addition to the baseline scenario, which was developed based on the assumptions outlined above, calculations were made for a conservative scenario (energy and PMS prices as in the baselines, discount rate, and cost increase—4%) and an optimistic scenario (energy and PMS prices increase by 4%, and discount rate and price increase—2.5%). The full results are summarized in

Table 11. Profitability indicators of the studied photovoltaic farms.

No.	Without Subsidies						With the Grant
	ROI	SPP	NPV	IRR	DPBT	LCOE	ROI	SPP	NPV	IRR	DPBT	LCOE
	%	Years	PLN Thousands	%	Years	PLN/MWh	%	Years	PLN Thousands	%	Years	PLN/MWh
1.	7.0	14.3	−29.7	3.5	25.1	242.0	13.3	7.5	2757.0	2.7	13.1	164.3
2.	5.6	17.7	−40.9	3.6	31.1	490.8	12.9	7.8	76.4	2.6	13.6	400.2
3.	5.6	18.0	−1470.5	4.1	31.5	274.3	9.6	10.4	1528.3	3.7	18.2	191.6
4.	13.2	7.6	10,146.8	2.2	13.3	187.5	21.8	4.6	14,663.1	2.0	8.1	136.6
5.	8.2	12.2	1683.7	2.9	21.3	205.3	14.5	6.9	5960.7	2.4	12.1	141.3
6.	7.0	14.2	29.8	3.4	24.9	232.5	11.7	8.6	2503.0	2.9	15.0	170.7
7.	8.2	12.2	909.7	2.8	21.4	220.9	15.7	6.4	3508.2	2.5	11.2	158.8
8.	9.1	11.0	509.0	2.9	19.3	246.9	15.3	6.5	1207.0	2.8	11.4	195.0
9.	13.5	7.4	4864.1	2.4	13.0	207.3	23.2	4.3	7094.0	2.3	7.6	154.5
10.	7.6	13.2	492.4	3.1	23.2	226.0	12.5	8.0	2931.4	2.9	14.0	168.1
11.	9.6	10.4	2364.2	2.9	18.3	204.9	15.6	6.4	4855.1	2.5	11.2	155.5
12.	7.2	13.8	206.5	3.3	24.2	231.3	9.7	10.3	1872.6	2.9	18.0	191.1
13.	7.8	12.8	651.5	3.1	22.4	224.3	13.0	7.7	2926.2	2.6	13.5	170.0
14.	5.5	18.2	−116.5	3.8	31.9	310.6	17.3	5.8	250.7	3.4	10.1	222.2
15.	9.8	10.2	2692.5	2.9	18.0	184.8	18.8	5.3	5998.9	2.6	9.3	121.2
16.	7.2	14.0	169.9	3.2	24.5	223.7	11.7	8.5	3583.2	2.3	14.9	159.4
17.	10.2	9.8	2728.7	2.7	17.3	208.9	19.5	5.1	5636.2	2.3	9.0	144.4
18.	9.7	10.3	1775.5	2.9	18.1	211.5	18.7	5.3	4020.9	2.4	9.4	144.1
19.	13.4	7.5	8067.4	2.3	13.1	193.5	20.6	4.9	11,203.6	2.2	8.5	145.7
20.	6.5	15.4	−166.3	3.6	27.0	263.0	10.5	9.5	707.0	3.2	16.7	205.8
21.	8.7	11.5	1144.6	3.2	20.2	204.2	14.5	6.9	3084.8	2.5	12.1	145.7
22.	7.9	12.7	537.7	3.5	22.2	216.0	15.6	6.4	2662.2	2.7	11.2	145.5
23.	8.6	11.7	1220.2	2.9	20.5	211.2	23.3	4.3	4698.3	2.4	7.5	129.2
24.	6.8	14.8	−163.3	3.8	26.0	247.1	10.8	9.3	1469.9	3.2	16.3	180.9
25.	8.8	11.4	2581.7	2.7	20.0	207.9	20.0	5.0	8379.2	2.4	8.8	136.9
26.	12.8	7.8	4088.1	2.6	13.7	159.7	25.4	3.9	6523.8	2.6	6.9	115.8
27.	13.5	7.4	5815.0	2.5	13.0	202.8	25.9	3.9	8835.6	2.4	6.8	134.9
28.	12.9	7.8	5110.5	2.7	13.6	196.1	24.8	4.0	8031.1	2.4	7.1	130.5
29.	8.3	12.0	1243.5	3.2	21.1	222.7	13.9	7.2	3961.4	2.7	12.7	157.6
30.	8.1	12.3	491.5	3.6	21.6	223.1	13.4	7.4	1704.1	3.2	13.1	167.0
31.	8.4	11.9	1480.2	3.2	20.9	200.4	13.9	7.2	4523.0	2.4	12.6	147.5

Source: own calculations based on information obtained from the Lublin Agency for Entrepreneurship Support, the Department for Regional Operational Program Management of the Lubelskie Voivodeship Marshal’s Office in Lublin, Polska Grupa Energetyczna S.A. Distribution Branch of Lublin and Investors.

. The analysis of the results obtained authorizes the conclusion that, regardless of the installed capacity of individual photovoltaic power plants, all realized investments, in part due to financial support, were economically justified (NPV > 0). However, if they had been implemented without subsidies, six studied facilities would have been unprofitable.

One of the main reasons for this variation is the installed capacity (

Table 12. Cost-effectiveness of the studied photovoltaic farms depending on the installed capacity.

Power	Without Subsidies						With the Grant
	ROI	SPP	NPV	IRR	DPBT	LCOE	ROI	SPP	NPV	IRR	DPBT	LCOE
	%	Years	PLN Thousands	%	Years	PLN/MWh	%	Years	PLN Thousands	%	Years	PLN/MWh
Total	8.9	12.0	1904	3.1	21	228.4	16.4	6.6	4424	2.6	11.6	165.5
Less than 0.1 MW	5.6	18.0	−79	3.7	32	400.7	15.1	6.8	163.6	3.0	11.9	311.2
0.1 to 1 MW	8.9	11.8	1486	3.1	20.8	220.8	16.3	6.7	3803	2.7	11.8	158.5
Above 1 MW	9.8	10.7	3764	2.8	18.8	203.3	16.9	6.2	7595	2.3	10.9	146.1

Source: own study.

). The shortest payback period among the surveyed facilities was provided by photovoltaic power plants with an installed capacity of more than 1 MW. This group’s average payback period (SPP) was 6.7 years; if such investments were made without financial support, this time would increase to about 12 years. For the discounted payback period of DPBT, the ratios were 18.8 and 10.9 years, respectively. This relationship was also confirmed by the simple rates of return on capital expenditures, which were 9.8 and 16.9%, respectively.

An even more significant variation was observed when discounted profitability metrics were used. The facilities with the lowest installed capacity would have been unprofitable without the subsidies provided (NPV < 0). The NPV of the largest group was more than twice as high as the average for all facilities. Also, similar relationships applied to the averaged unit cost of electricity generation.

The results shown in Table 12 and Figure 7 confirm the advantageous position of solar power plants with the highest capacity as the most reasonable investment among the plants studied. The sensitivity analysis, presented in Table 12, shows that, regardless of the scenario adopted, investment in solar thermal power with the level of support that occurred within the framework of the 2007–2013 financial perspective was a reasonable long-term investment. In the least favorable scenario (conservative) included in the analysis, the discounted payback period ranged from 8.1 to 22 years. In the optimistic scenario, DPBT values ranged from 5.6 years to more than 15 years.

All the analyses show that the value of the financial support provided and the scale of the investment project had a decisive influence on the economic effects of the photovoltaic installations studied (

Table 13. Profitability of the studied photovoltaic farms depending on the scenario.

No.	Conservative								Base								Optimistic
	Without Subsidies				With Subsidy				Without Subsidies				With Subsidy				Without Subsidies				With Subsidy
	NPV	IRR	DBPT	LCOE	NPV	IRR	DBPT	LCOE	NPV	IRR	DBPT	LCOE	NPV	IRR	DBPT	LCOE	NPV	IRR	DBPT	LCOE	NPV	IRR	DBPT	LCOE
1.	−1004.0	5.2	30.2	291.3	1782.7	3.3	15.8	197.8	−29.7	3.5	25.1	242.0	2757.0	2.7	13.1	164.3	1153.6	3.5	20.9	201.4	3940.3	2.9	10.9	136.7
2.	−69.1	4.0	37.3	590.7	48.2	3.7	16.4	481.6	−40.9	3.6	31.1	490.8	76.4	3.6	13.6	400.2	−6.6	3.6	25.8	408.5	110.7	3.7	11.3	333.0
3.	−2419.3	6.8	37.8	330.2	579.5	3.4	21.9	230.7	−1470.5	4.1	31.5	274.3	1528.3	2.7	18.2	191.6	−318.3	4.1	26.2	228.3	2680.5	3.1	15.2	159.5
4.	6518.8	2.8	15.9	225.7	11,035.1	2.6	9.7	164.4	10,146.8	2.2	13.3	187.5	14,663.1	1.9	8.1	136.6	14,553.0	2.2	11.0	156.1	19,069.3	1.8	6.7	113.7
5.	−248.8	4.7	25.6	247.1	4028.2	2.8	14.5	170.0	1683.7	2.9	21.3	205.3	5960.7	2.2	12.1	141.3	4030.6	2.9	17.7	170.9	8307.6	2.1	10.0	117.6
6.	−1020.1	5.3	29.9	279.9	1453.1	3.5	18.0	205.4	29.8	3.4	24.9	232.5	2503.0	2.6	15.0	170.7	1304.9	3.4	20.7	193.5	3778.1	2.4	12.5	142.1
7.	−155.5	4.3	25.7	265.9	2443.0	3.2	13.4	191.2	909.7	2.8	21.4	220.9	3508.2	2.4	11.2	158.8	2203.5	2.8	17.8	183.8	4802.0	2.6	9.3	132.2
8.	135.7	3.6	23.2	297.2	833.7	3.3	13.8	234.7	509.0	2.9	19.3	246.9	1207.0	2.8	11.4	195.0	962.4	2.9	16.0	205.5	1660.4	3.4	9.5	162.3
9.	3159.5	7.2	15.7	249.5	5389.4	2.9	9.1	186.0	4864.1	2.4	13.0	207.3	7094.0	2.3	7.6	154.5	6934.3	2.4	10.8	172.5	9164.2	2.0	6.3	128.6
10.	−629.4	5.9	27.8	272.0	1809.6	3.1	16.9	202.4	492.4	3.1	23.2	226.0	2931.4	2.9	14.0	168.1	1854.8	3.1	19.2	188.1	4293.8	2.3	11.7	139.9
11.	885.3	4.0	22.0	246.7	3376.2	2.9	13.5	187.1	2364.2	2.9	18.3	204.9	4855.1	2.5	11.2	155.5	4160.4	2.9	15.2	170.6	6651.3	2.1	9.3	129.4
12.	−918.1	5.3	29.1	278.4	748.0	3.4	21.6	230.0	206.5	3.3	24.2	231.3	1872.6	2.9	18.0	191.1	1572.4	3.3	20.1	192.5	3238.5	2.5	15.0	159.1
13.	−415.8	5.1	27.0	270.0	1858.9	3.1	16.2	204.6	651.5	3.1	22.4	224.3	2926.2	2.6	13.5	170.0	1947.6	3.1	18.6	186.7	4222.3	2.3	11.2	141.5
14.	−187.1	4.7	38.3	373.8	180.1	3.6	12.2	267.5	−116.5	3.8	31.9	310.6	250.7	3.7	10.1	222.2	−30.6	3.8	26.5	258.5	336.6	3.8	8.4	185.0
15.	1087.6	4.1	21.6	222.4	4394.0	2.6	11.2	145.9	2692.5	2.9	18.0	184.8	5998.9	2.6	9.3	121.2	4641.6	2.9	14.9	153.8	7948.0	2.2	7.8	100.9
16.	−1323.1	6.3	29.5	269.2	2090.2	2.9	17.9	191.9	169.9	3.2	24.5	223.7	3583.2	2.4	14.9	159.4	1983.0	3.2	20.4	186.2	5396.3	2.4	12.4	132.7
17.	1252.2	3.6	20.7	251.4	4159.7	2.5	10.8	173.8	2728.7	2.7	17.3	208.9	5636.2	2.3	9.0	144.4	4521.9	2.7	14.3	173.8	7429.4	2.1	7.5	120.2
18.	697.6	4.1	21.7	254.6	2943.0	2.9	11.2	173.5	1775.5	2.9	18.1	211.5	4020.9	2.4	9.4	144.1	3084.5	2.9	15.0	176.1	5329.9	2.2	7.8	120.0
19.	5217.1	3.1	15.8	232.9	8353.3	2.3	10.2	175.3	8067.4	2.3	13.1	193.5	11,203.6	2.0	8.5	145.7	11,529.0	2.3	10.9	161.1	14,665.2	1.8	7.1	121.2
20.	−522.4	5.3	32.4	316.5	350.9	3.7	20.0	247.7	−166.3	3.6	27.0	263.0	707.0	2.2	16.7	205.8	266.3	3.6	22.4	218.9	1139.6	3.2	13.9	171.3
21.	143.7	4.5	24.3	245.8	2083.9	3.2	14.5	175.4	1144.6	3.2	20.2	204.2	3084.8	2.9	12.1	145.7	2360.1	3.2	16.8	169.9	4300.3	2.6	10.0	121.3
22.	−271.9	4.9	26.7	260.0	1852.6	3.3	13.5	175.1	537.7	3.5	22.2	216.0	2662.2	3.0	11.2	145.5	1521.0	3.5	18.5	179.8	3645.5	2.7	9.3	121.1
23.	93.5	4.7	24.6	254.2	3571.6	2.8	9.0	155.5	1220.2	2.9	20.5	211.2	4698.3	2.4	7.5	129.2	2588.6	2.9	17.0	175.8	6066.7	2.2	6.2	107.5
24.	−869.0	5.9	31.2	297.5	764.2	3.2	19.5	217.7	−163.3	3.8	26.0	247.1	1469.9	3.2	16.3	180.9	693.7	3.8	21.6	205.7	2326.9	2.8	13.5	150.6
25.	419.2	4.3	24.0	250.3	6216.7	2.7	10.5	164.8	2581.7	2.7	20.0	207.9	8379.2	2.1	8.8	136.9	5207.9	2.7	16.6	173.1	11,005.4	2.	7.3	113.9
26.	2577.6	3.5	16.4	192.2	5013.3	2.8	8.3	139.3	4088.1	2.6	13.7	159.7	6523.8	2.2	6.9	115.8	5922.6	2.6	11.3	132.9	8358.3	2.1	5.7	96.3
27.	3783.4	3.3	15.6	244.1	6804.0	2.5	8.1	162.4	5815.0	2.5	13.0	202.8	8835.6	2.0	6.8	134.9	8282.4	2.5	10.8	168.8	11,303.0	1.9	5.6	112.3
28.	3232.2	3.5	16.3	236.1	6152.8	2.5	8.5	157.1	5110.5	2.7	13.6	196.1	8031.1	2.1	7.1	130.5	7391.7	2.7	11.3	163.2	10,312.3	1.9	5.9	108.6
29.	−101.5	5.4	25.4	268.0	2616.4	3.1	15.2	189.7	1243.5	3.2	21.1	222.7	3961.4	2.7	12.7	157.6	2877.1	3.2	17.5	185.3	5595.0	2.5	10.5	131.2
30.	−106.8	5.5	25.9	268.5	1105.8	3.4	15.7	201.0	491.5	3.6	21.6	223.1	1704.1	3.2	13.1	167.0	1218.0	3.6	17.9	185.7	2430.6	2.7	10.8	139.0
31.	−49.1	5.1	25.2	241.2	2993.7	2.9	15.1	177.5	1480.2	3.2	20.9	200.4	4523.0	2.5	12.6	147.5	3337.5	3.2	17.4	166.8	6380.3	2.4	10.5	122.7

Source: own calculations based on information obtained from the Lublin Agency for Entrepreneurship Support, the Department for Regional Operational Program Management of the Lubelskie Voivodeship Marshal’s Office in Lublin, Polska Grupa Energetyczna S.A. Distribution Branch of Lublin and Investors.

and

Table 14. Average profitability of the studied photovoltaic farms depending on the scenario.

		NPV	IRR	DBPT	LCOE
Conservative	min	48.2	45,294.0	9.0	139.3
	average	609.4	42,472.2	32,268.8	274.9
	max	11,035.1	45,537.0	45,556.0	481.6
Base	min	76.4	2.0	9.0	115.8
	average	4424.4	41,020.0	39,539.6	165.5
	max	14,663.1	45,537.0	45,549.0	400.2
Optimistic	min	110.7	2.0	10.0	96.3
	average	5996.4	42,477.0	41,027.8	137.8
	max	19,069.3	45,537.0	45,548.0	333.0

Source: own study.

).

4. Discussion

The average level of expenditures per unit of installed capacity was 6088 PLN/kW but varied significantly, from 4919 to 7285 PLN/kW, which was not due to economies of scale. Institute for Renewable Energy (IRE) analyses confirm the operation of the so-called cost effect of scale, as the data show that the unit price of an installation decreases with the increase in the installation’s rated power. There are noticeable differences in the unit price between home prosumer installations and prosumer business installations. The unit price is significantly lower for PV farms than for other types of installations [52]. In total, expenditures on the purchase of the equipment and materials and their installation accounted for more than 90% of the total gross costs spent on implementing the surveyed facilities. The results obtained in terms of the generic structure of capital expenditures spent on the implementation of the surveyed photovoltaic facilities implemented in 2012–2016 are consistent with those presented both in the national literature [59,60,61] and the foreign literature [53,62,63,64]. In the group of PV installations up to 1 MW, expenditures related to the purchase and installation of PV panels continued to have the highest position in capital expenditures, but their share was half that of 2016. This is primarily due to significantly lower module prices in domestic and foreign markets [20,53].

In the facilities studied, the average annual amount of energy generated, then fed into the grid, and the yield (productivity) in MWh per MW of installed capacity. amounted to 1040.98 MWh/MW, and was higher than such results published in the lite-rature for other regions of Poland and even Bulgaria [65]. A study by Z. Brodzinski et al. [53] of 22 photovoltaic farms from 0.48 MW to 1979 MW, implemented in 2018/2019 in Northeastern Poland, shows that their productivity was lower. For installations up to 1 MW, it reached 1010.0 MWh; above 1 MW, it amounted to 960 MWh. Even lower values of these indicators (from 865.3 to 989.4 MWh/MW) were characterized by micro-installations in the Pomeranian Voivodeship [55]. Only slightly higher such ratios were recorded for micro-installations located in Greater Poland [66] and Mazovia [67]. The study’s results confirmed the thesis that the Lublin Province is characterized by some of the most favorable locational conditions for photovoltaic installations [54,68,69].

The analysis shows a sizable increase in revenues in the years under review, mainly due to rapidly rising electricity prices and property rights to certificates of origin. The average electricity sales prices entering the distribution system operator’s grid in 2022 were nearly double those of 2017. Even more significant differences were the prices for the purchase of energy by end users, which in the same period were not far from three times higher, which made some investors decide to mix sales and use them in their business activities. In the case of property rights to certificates of origin, these increases were almost sixfold [59,70].

The analysis shows that by 2021, the unit technical costs of electricity generation in the photovoltaic installations studied were significantly higher than those generated by power plants and thermal power plants powered by conventional fuels (lignite, hard coal, or gas), as well as natural flow hydropower and wind power. The financial support provided reduced these disparities or, as in 2018–2019, made photovoltaic installations competitive with coal- and gas-fired power plants. In 2022, the unit technical costs of electricity generation in the surveyed photovoltaic installations above 0.1 MW of installed capacity, even without considering subsidies, were already lower than those calculated for utility coal- and gas-fired power plants [17,71].

The following indices were used to evaluate the economic efficiency of the investments studied: rate of return on investment (ROI), simple payback period (SPP), net present value of investment (NPV), internal rate of return (IRR), discounted payback period (DPBT), and averaged unit cost of electricity generation (LCOE) [72,73,74,75].

5. Conclusions

The research carried out within the framework of the article aimed to identify the status, development opportunities, and economic evaluation of the effectiveness of investments in large-scale photovoltaic installations in the Lublin Province. The analysis shows that by 2021, the unit technical costs of electricity generation in the studied photovoltaic installations were significantly higher than those generated by power plants and thermal power plants fueled by conventional fuels (lignite, coal, or gas), as well as natural flow hydroelectric power and wind power. The financial support provided reduced these disparities or, as in 2018–2019, made photovoltaic installations competitive with coal- and gas-fired power plants. In 2022, the unit technical costs of electricity generation in the surveyed photovoltaic installations above 0.1 MW of installed capacity, even without considering subsidies, were already lower than those calculated for utility coal and gas-fired power plants.

The following indices were used to evaluate the economic efficiency of the investments studied: rate of return on investment (ROI), simple payback period (SPP), net present value of investment (NPV), internal rate of return (IRR), discounted payback period (DPBT), and averaged unit cost of electricity generation (LCOE). They were carried out for three scenarios—baseline, conservative, and optimistic—in two variants, for actual capital expenditures considering financial support used and without subsidies. It was determined that the expected lifetime of the studied investments would be 25 years. The reference period was the results, including capital expenditures, financial support value, revenue components, and operating costs in 2017–2022. For the baseline scenario, the following assumptions were made: an annual increase in the sale price of electricity and property rights to certificates of origin—2%; annual increase in costs—3.03%; and discount rate—3%. Calculations were also made for the other scenarios with the following assumptions: conservative (energy and COR prices as in the reference levels, discount rate, and cost increase—4%) and optimistic (energy and COR price increase of 4% and discount rate and price increase—2.5%). The analysis of the results obtained authorizes the conclusion that, regardless of the installed capacity of individual photovoltaic power plants, all realized investments, in part due to financial support, were economically justified (NPV > 0). However, six of the surveyed facilities would have been unprofitable if they had been implemented without subsidies. The sensitivity analysis shows that, regardless of the adopted scenario, investments in solar thermal power with the level of support that took place under the 2007–2013 financial perspective were reasonable long-term investments. In the least favorable scenario (conservative) included in the analysis, the discounted payback period ranged from 8.1 to 22 years. In the optimistic scenario, DPBT values ranged from 5.6 years to more than 15 years. The payback period (both simple and discounted) for investments with the subsidy was, on average, almost twice as fast as for investments without the subsidy, while the average unit cost of electricity generation with the subsidy was about 30% lower than without it.

The study also produced the following conclusions:

• Due to significant technological advances in the RES industry, resulting in increasingly lower equipment costs and higher energy efficiency, there is growing interest in using solar energy. Observation of the growth rate of this sector shows that it is much faster than assumed in the forecasts of “Poland’s Energy Policy until 2040”. From the estimates made based on the report “Photovoltaic Market in Poland 2023” and assuming that the efficiency of photovoltaic panels will be at the same level as in 2018–2020, the amount of electricity generated by this sector in 2022 will be as much as programmed for 2025;
• As of 31 December 2021, the installed electrical capacity of photovoltaic sources amounted to 7637.70 MW, including 5836.60 MW at prosumers. As recently as 2018, these values were many times lower: 565.56 MW and 275.54 MW, respectively. During the same period, the number of prosumers increased from 51,016 to 845,730. Such a significant development of photovoltaics in 2018–2021 contributed to an unprecedented increase in the share of electricity from this source to its total production, from 0.18% to 2.19%;
• However, such dynamic development of the entire RES sector would not have been possible without allocating public funds for this purpose. These funds were primarily allocated under the “Infrastructure and Environment” operational program, regional operational programs, the Rural Development Program, as well as the National and Provincial Funds for Environmental Protection and Water Management;
• The property rights system is an essential factor affecting investments’ profitability. However, it is imperfect, as producers cannot predict the value of the change in these prices, which involves uncertainty and some risk in managing the investment. These prices have fluctuated over the past decade, reaching values ranging from PLN 22.46 to PLN 300.42;
• In the European Union, energy acquisition from renewable sources increased more than two and a half times between 2000 and 2022. Most energy was generated from photovoltaic installations, solar panels, wind farms, heat pumps, biogas, bioethanol, and biodiesel. The primary factor for such significant growth in the renewable energy sector is the consistent implementation of the EU’s ambitious climate and energy policy;
• Aspects that positively affect the economic efficiency of the investment are the increase in the efficiency of photovoltaic panels and the decrease in their price;
• All the analyses show that the decisive influence on the economic effects of the photovoltaic installations studied was the value of the financial support provided and the scale of the investment project.

Summarizing the results of the study and the conclusions cited, the profitability of investment in large-scale photovoltaic power plants was economically justified, provided they are financially supported. In addition to economic aspects, an essential element is concern for the environment and climate change. Undoubtedly, investments in renewable energy are an essential part of climate and energy policy.

The research carried out within the framework of the article only considered investment projects operating under the Tradable Green Certificates system-TGCs. Current photovoltaic investments operate under new legal conditions, including the auction system and dynamic energy tariffs; hence, future research should consider these issues.