There are a lot of studies that show the legitimacy of subsidizing renewable energy; however, some mechanisms are defective, and there are problems with the appropriate allocation of funds. Therefore, this paper aims to look at the situation of allocating funds to photovoltaics (PV) micro-installations in Poland through the “My Electricity” program. The article presents the results of analyses aimed at identifying inequalities between provinces in the use of funds available under the “My Electricity” program and verifying whether these inequalities are getting worse and whether the intensity of support should not be territorially conditioned in terms of maximization an electricity production. As part of two editions of the “My Electricity” program (until 1 August 2020), over 64,000 PV micro-installations were created with an average power of approximately 5.7 kWp. The total installed PV capacity was 367.1 MWp (1st edition: 159.3 MWp, 2nd edition: 207.8 MWp). Financial resources (as a whole), in the second edition of “My Electricity” program, were distributed better than in the first edition. In the first edition, as much as 7.60% of funds were allocated inefficiently; in the second edition, it was only 3.88%. Allocation surpluses occur in provinces where the average disposable income is low and where there are a small number of households. There is a potential to introduce a territorial project selection criteria. The analysis shows that the criteria should promote provinces with higher disposable income and a larger number of households.

There are many financial ways to intensify the construction of new renewable energy sources installations, among others: feed in tariff, grants. An example of photovoltaic grant support in Poland is the "Mój Prąd" [My Electricity] program created in 2019. This program, with a budget of PLN 1 billion, is intended for households in which installations with a capacity range of 2-10 kWp have been installed. During its first edition 27,187 application were submitted. Over 98% of installations cost less than PLN 6,000/kWp. The total installed capacity is 151.3 MWp, which gives the average amount of co-funding per unit of power at the level of PLN 884.7/kWp. The average power of the installation on the national scale is 5.57 kWp, the indicator per 1000 inhabitants is 3.94 kWp, and per unit of area is 0.484 kWp/km 2 . These installations will produce around 143.5 GWh of electricity annually, contributing to the reduction of CO 2 emissions by approximately 109,800 Mg per year. Most applications came from the Silesian Province (3855), which translated into the largest installed capacity of 21.82 MWp, as well as 4.81 kWp/1000 inhabitants and 1.77 kWp/km 2 (over 3 times higher than the average in Poland).The installed capacity in the individual province was closely correlated with the population of the province (correlation coefficient -0.95), while the installed capacity indicator per 1,000 inhabitants with insolation (0.80). The highest power ratio per 1000 inhabitants was achieved in the Podkarpackie Province and amounted to 5.05, and the lowest in the West Pomeranian Province (2.41).

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Micro-cogeneration (mCHP) is a promising solution for the generation of heat and electricity in households, it contributes to reducing carbon dioxide emissions in countries where the production of electricity is mainly based on fossil fuels. Its dissemination in Poland faces barriers in the form of high purchase prices in relation to electricity productivity. In this work 1% of the household population in Poland was analyzed using the Monte Carlo method. It was found that for mCHP to become economically profitable for a group of at least 10,000 households, its price should fall from around 18,000 euros (711.5 euros/kWth and 18,000 euros/kWe) to 4800 euros (189.7 euros/kWth and 4800 euros/kWe) and for 100,000 households to 4100 euros (162.1 euros/kWth and 4100 euros/kWe). These calculations were made for fixed gas and electricity prices. The analysis also included cases of various changes in gas and energy prices. Faster growth of electricity prices than gas prices reduce the profitability barrier. In addition, a building located in Lesser Poland region was analyzed, with an above average demand for electricity and heat. Gas micro-cogeneration becomes profitable for this household at a price of 3700 euros (146.2 euros/kWth and 3700 euros/kWe) at fixed gas and electricity prices.

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According to the European Environment Agency (EEA 2018), air quality in Poland is one of the worst in Europe. There are several sources of air pollution, but the condition of the air in Poland is primarily the result of the so-called low-stack emissions from the household sector. The main reason for the emission of pollutants is the combustion of low-quality fuels (mainly low-quality coal) and waste, and the use of obsolete heating boilers with low efficiency and without appropriate filters. The aim of the study was to evaluate the impact of measures aimed at reducing low-stack emissions from the household sector (boiler replacement, change of fuel type, and thermal insulation of buildings), resulting from environmental regulations, on the improvement of energy efficiency and the emission of pollutants from the household sector in Poland. Stochastic energy and mass balance models for a hypothetical household, which were used to assess the impact of remedial actions on the energy efficiency and emission of pollutants, have been developed. The annual energy consumption and emissions of pollutants were estimated for hypothetical households before and after the implementation of a given remedial action. The calculations, using 122 the Monte Carlo simulation, were carried out for several thousand hypothetical households, for which the values of the technical parameters (type of residential building, residential building area, unitary energy demand for heating, type of heat source) were randomly drawn from probability distributions developed on the basis of the analysis of the domestic structure of households. The model takes the coefficients of correlation between the explanatory variables in the model into account. The obtained results were multiplied so that the number of hypothetical households was equal to 14.1 million, i.e. the real number of households in Poland. The obtained results allowed for identifying the potential for reducing the emission of pollutants such as carbon dioxide, carbon monoxide, dust, and nitrogen oxides, and improving the energy efficiency as a result of the proposed and implemented measures, aimed at reducing low-stack emission, resulting from the policy. The potential for emissions of gaseous pollutants is 94% for CO, 49% for NO x , 90% for dust, and 87% for SO 2 . The potential for improving the energy efficiency in households is around 42%.

This paper presents an attempt to the valuation of the operational flexibility of the energy investment project based on the example of combined cycle gas turbine (CCGT). For this purpose, the real options approach (ROA), net present value (NPV) method, and the Monte Carlo (MC) simulation have been used. Motivations to take up such a topic result from the fact that traditional valuation methods neglect flexibility embedded in CCGT assets. Operational flexibility was defined as the switching option to dynamically shut down and restart gas units. Valuation of the operational flexibility, the project’s extended net present value (XNPV), was based on a discounted cash flow model. The Monte Carlo simulation, allowing for better replication of the stochastic nature of market factors and some technical parameters, was introduced to the valuation model. The obtained results indicate that the value of the options significantly influences the NPV of the analyzed technology and its risk profile. The NPV was calculated at −169.1 million USD, while the XNPV amounted to 102.5 million USD. This difference, compared to the NPV distribution range at a significance level of 0.05, was more than 8.1% (almost 10.4% for α = 0.1). The results achieved help to explain the significance of the operational flexibility in the modeling profitability of CCGT technologies.