The paper analyzes the impact of potential changes in the price relation between domestic and imported coal and its influence on the volume of coal imported to Poland. The study is carried out with the application of a computable model of the Polish energy system. The model reflects fundamental relations between coal suppliers (domestic coal mines, importers) and key coal consumers (power plants, combined heat and power plants, heat plants, industrial power plants). The model is run under thirteen scenarios, differentiated by the ratio of the imported coal price versus the domestic coal price for 2020–2030. The results of the scenario in which the prices of imported and domestic coal, expressed in PLN/GJ, are equal, indicate that the volume of supplies of imported coal is in the range of 8.3–11.5 million Mg (depending on the year). In the case of an increase in prices of imported coal with respect to the domestic one, supplies of imported coal are at the level of 0.4–4.1 million Mg (depending on the year). With a decrease in the price of imported coal, there is a gradual increase in the supply of coal imports. For the scenario in which a 30% lower imported coal price is assumed, the level of imported coal almost doubles (180%), while the supply from domestic mines is reduced by around 28%, when compared to the levels observed in the reference scenario. The obtained results also allow for the development of an analysis of the range of coal imports depending on domestic versus imported coal price relations in the form of cartograms.

The dynamic development of wind power in recent years has generated the demand for production forecasting tools in wind farms. The data obtained from mathematical models is useful both for wind farm owners and distribution and transmission system operators. The predictions of production allow the wind farm operator to control the operation of the turbine in real time or plan future repairs and maintenance work in the long run. In turn, the results of the forecasting model allow the transmission system operator to plan the operation of the power system and to decide whether to reduce the load of conventional power plants or to start the reserve units.

The presented article is a review of the currently applied methods of wind power generation forecasting. Due to the nature of the input data, physical and statistical methods are distinguished. The physical approach is based on the use of data related to atmospheric conditions, terrain, and wind farm characteristics. It is usually based on numerical weather prediction models (NWP). In turn, the statistical approach uses historical data sets to determine the dependence of output variables on input parameters. However, the most favorable, from the point of view of the quality of the results, are models that use hybrid approaches. Determining the best model turns out to be a complicated task, because its usefulness depends on many factors. The applied model may be highly accurate under given conditions, but it may be completely unsuitable for another wind farm.

Taking the importance of time and risk into account has a significant impact on the value of

investment projects. Investments in the energy sector are long-term projects and, as such, are burdened

with uncertainty associated with the long-term freezing of capital and obtaining the expected

return. In the power industry, this uncertainty is increased by factors specific to the sector,

including in particular changes in the political and legal environment and the rapid technological

development. In the case of discounted cash flow analysis (DCF), commonly used for assessing the

economic efficiency of investments, the only parameter expressing investor uncertainty regarding

investment opportunities is the discount rate, which increases with the increasing risk of the project.

It determines the value of the current project, thus becoming an important criterion affecting

investors’ decisions. For this reason, it is of great importance for the assessment of investment

effectiveness. This rate, usually in the form of the weighted average cost of capital (WACC), generally

includes two elements: the cost of equity capital and borrowed capital. Due to the fluctuant

relationship between these two parameters in project financing, performing a WACC analysis in

order to compare the risks associated with the different technologies is not completely justified.

A good solution to the problem is to use the cost of equity. This article focuses on the analysis of this

cost as a measure of risk related to energy investments in the United States, Europe and worldwide.

With the upcoming implementation of the centralized capacity market in Poland, capacity auctions will be organized where domestic power companies will offer their available capacities. It is assumed that bidding will be auctioned according to the so called descending clock auction system with uniform-price (Pay-as-Clear), which will lead to the market equilibrium price. Some analysts, however, are of the view that it is more appropriate to organize capacity auctions in the Pay-as-Bid formula, as this system should lead to lower prices that those of Pay-as-Clear, hence lower costs of capacity purchase. However, this opinion does not confirm the practice – theoretical considerations do not take into account such important factors as the behavior of market players and the tendency of bidders to accept a higher risk or the lack of access to advanced analyses, and thus better information for all market participants. This paper presents a hypothetical calculation of the prices in the centralized capacity market using Monte Carlo simulations. The results of the study confirm that the price level for the Pay-as-Bid system, due to the asymmetry of information and the level of concentration of the power generation sector in Poland would lead to higher prices than for the Pay-as-Clear system on average by approximately 2.5%. The implementation of the PAB system would, therefore, be less efficient to electricity consumers.

Czym jest smog i z czego się składa? Jak powstaje? Jak zadymiona jest Polska w stosunku do innych krajów Europy?

The paper presents a global perspective of the current technologies used for steel production and the steel markets. The iron and steel industry is a very complex sector that is strongly related with the rest of the economy due to the importance of steel products for industries such as construction, automotive, and other manufacturing sectors. Moreover, the iron and steel industry demands significant amounts of raw materials and energy, and most companies producing raw materials are located remote from the areas of highest steel demand. In consequence, both steel products and inputs are traded internationally (mostly by sea) and in large quantities, what additionally complicates analyses of the iron and steel industry. Steel prices depend on several variables, and there is not a single price for steel since there is a great variety of steel products traded. Those prices depend on supply and demand interaction (between steel producers and consumers, but also on interaction with other industries competing for the same inputs), and on transport conditions. As concerns the ownership structure, the steel industry consists of some large firms that operate globally and produce significant output, and many small firms that operate at a lesser scale. Recently, some of those firms have consolidated into large multinationals (such as ArcelorMittal, formed in 2006 by the merger of Arcelor and Mittal Steel, Arcelor being the result of the previous merger of Aceralia (ES), Usinor (FR), and Arbed (LX) in 2002). The results of this article form the basis for further long- and mid-term analyses of the development of the global steel industry. The main conclusion of the paper is that any future analysis of the iron and steel industry should be based on quantitative modelling tools that: (i) properly capture the technological diversity of the industry and the key features of the supply chain, (ii) are able to consider the strategic behaviour of all the key players of the industry, and (iii) consider all those factors at the global scale.

What is smog, what does it consist of, and where does it come from? How badly polluted is the air in Poland in relation to other countries in Europe?

Natural resources and the extractive industries play a central role in the economy of developing countries and the lives of nearly half of the world’s population. The increasing demand for oil, gas, and mineral resources has led some countries to prioritize the extractive industries; yet, there is growing empirical evidence that in some cases governments have neglected other sectors of the economy, making them highly dependent and vulnerable to volatile commodity prices. Latin American countries face the challenge of changing their model of primary-export specialization and move away from their dependence on natural resource-intensive exports in order to avoid being vulnerable to commodity cycles. In this context, given the limited literature available on measuring the dependence on the extraction of oil, gas and minerals of the Ecuadorian economy, the objective of this article is to twofold. First, to provide a snapshot of the historical and current situation of Ecuador’s natural resource dependence. Second, to estimate the Extractives Dependence Index (EDI) scores for Ecuador for the years 2003 to 2017. The EDI is a generally accepted method for measuring a country’s aggregate dependence on natural and mineral resources. Based on the EDI scores obtained, we analyze the variation of this indicator and investigate the effect of extractives dependence on the Ecuadorian economy. Results show that despite the government’s significant efforts to diversify Ecuador’s economy, the country has a persistent dependence on the extractive sector.

The paper investigates the supply structure of the capacity market in Poland in the coming years. The results of the capacity auctions conducted in 2018 are analyzed for this purpose. Three auctions were held at that time. The products traded in the capacity market are capacity obligations for the following years: 2021, 2022 and 2023. The auctions were organized in accordance with (i) he Act of December 8, 2017 on the Capacity Market and the (ii) Capacity Market Regulations published by the Polish Power Grid. The source of data used in this study is the official information of the President of the Energy Regulatory Office on the final results of the main auctions for 2021–2023 delivery periods. The list of the capacity suppliers who won capacity auctions contains the type of capacity market units, the volume of capacity obligations, the duration of capacity agreements and the business name of the capacity suppliers. The conducted analysis indicates that the auction for 2021 was won mainly by existing units (45.81%) and refurbishing units (33.51%). In subsequent years, the share of existing generating units is significantly higher and amounts to 91.67% for 2022 and 84.54% for 2023. The results of the study carried out in this paper also show that one energy company, being the owner of power generating daughter companies, has a very high share in these capacity auctions. The PGE Capital Group contracted 51.95% for 2021, 69.92% for 2022 and 64.44% for 2023 of the total capacity obligation. The volume amounts to over 70% of their total installed capacity.

Recent empirical research has provided compelling evidence that the proliferation of intellectual property rights (IP) and the fragmentation of patent rights among different patent holders have created barriers to innovation and impediments to the commercialization of scientific discoveries. Legal and economic scholars have suggested that due to the rising number of patent applications, the limited resources in patent offices around the world and the lack of sufficient time to prior art search, examiners have failed to conduct thorough patent examination processes. Moreover, researchers have linked the growing number of overlapping intellectual property rights to the tragedy of the anticommons and to the concept of patent thickets. Multiple studies have been performed in order to develop measures that could verify the existence of patent thickets and to better understand the social and economic impact of fragmentary patent owners. When it comes to the energy sector, the problem of patent thickets is now even more important. As the technological innovation in this sector increases and the energy-related patenting continues to grow, it has been argued that the issue of patent thickets may have a direct impact on investment decisions and the long-run development of this sector. This paper presents an overview of literature on the definition of a patent thicket and summarizes some of the possible factors causing thickets to arise. Additionally, it discusses the recent developments in patent thicket measures and patent thicket identification methods.

The article attempts to identify environmental conditions for the development of cogeneration companies in Poland. The article systematizes knowledge about environmental regulations which concern this issue. Within the framework of identified environmental conditions, the authors characterize issues related to national legislation that regulates the operation of cogeneration companies, as well as the requirements resulting from European Union and national regulations in this matter. These regulations, directly and indirectly, affect the long-term future of cogeneration companies and the energy sector as a whole. Undoubtedly, in the current state of environmental regulations in force, the key change for a power company such as a cogeneration company is to meet the requirements for the emission of harmful substances. The change was introduced in 2016 as a result of more stringent emission limits and the adoption of the IED (Industrial Emissions Directive). The implementation of recommendations of the BAT (Best Available Techniques) Conclusions in 2017 additionally tightened the required limits. Undeniably, the key period for cogeneration companies will be 2021 as per the implementation of imposed harmful substances emission’s limits. The article comprehensively discusses the conditions that substantially affect the long-term growth of a cogeneration company and are crucial when making assumptions intended to address strategic development issues in the domestic fuel and power sector.

The Polish power generation system is based mostly on coal-fired power plants. Therefore, the coal mining sector is strongly sensitive to changes in the energy sector, of which decarbonization is the crucial one. The EU Emission Trading System (EU ETS) requires power generating companies to purchase European Emission Allowances (EUAs), whose prices have recently soared. They have a direct impact on the cost efficiency of hard coal-fired power generation, hence influence the consumption of hard coal on the power sector. In this context, the objective of this paper is to estimate the hard coal consumption in various regions of Poland under selected forecasts of the EUA price. To investigate this question, two models are employed:

 - the PolPower_LR model that simulates the Polish power generation system,

 - the FSM _LR model that optimizes hard coal supplies.

Three scenarios differentiated by the EUA price are designed for this study. In the first one, the average EUA price from 2014–2017 is assumed. In the second and third, the EUA prices are assumed accordingly to the NPS and the SDS scenario of the World Energy Outlook. In this study we consider only existing, modernized, under construction and announced coal-fired power generation units. The results of the study indicate that regardless of the scenario, a drop in hard coal consumption by power generation units is observed in the entire period of analysis. However, the dynamics of these changes differ. The results of this analysis prove that the volume of hard coal consumption may differ by even 136 million Mg (in total) depending on the EUA prices development scenario. The highest cumulated volume of hard coal consumption is observed in the Opolski, Radomski and Sosnowiecki region, regardless of the considered scenario.