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

The concept of risk is well known in the energy sector. It is normally recognized when it comes to price and cost forecasting, annual production calculation, or evaluating project lifetime. Nevertheless, it should be pointed out that the quantitative evaluation of risk is usually difficult. The discount rate is the only parameter reflecting risk in the discounted cash flow analysis. Therefore, knowledge of the discount rate along with the major components affecting its level is of fundamental significance for making investment decisions, capital budgeting, and project management. By referring to the standard coal-fired power generation projects the authors of the paper tackle the analysis of the composition of discount rate for onshore wind farm technologies in the Polish conditions. The study was carried out on the basis of a typical (hypothetical) onshore wind farm project assessed at the feasibility stage. To enable comparisons and discussions, it was assumed that the best reference point for such purposes is the real risk-adjusted discount rate, RADR, after-tax, in all equity evaluations (the ‘bare bones’ assumption); that is because such a rate reflects the inherent characteristics of the project risk. The study methodology involves the a priori application of the discount rate level and subsequently—in an analytical way—calculation of its individual components. The starting point for the analysis of the RADR’s composition was the definition of risk, understood as the product of uncertainty and consequences. Then, the risk factors were adopted and level of uncertainty assessed. Subsequently, using the classical sensitivity analysis of IRR, the consequences (as slopes of sensitivity lines) were calculated. Consequently, risk portions in percentage forms were received. Eventually, relative risks and risk components within cost of equity were assessed. Apart from the characteristics of the discount rate at the feasibility stage, in the discussion section the study was supplemented with an analogous analysis of the project’s cost of equity at the operating stage.

Our knowledge of discount rates plays an important role both in the discounted cash flow decision-making process and in the later phases of a project’s lifetime. It is useful than both for management and cash-flow monitoring purposes at operating stages. Investors putting money into power generation projects expect an appropriate rate of return to compensate them for a minimum acceptable real return available in the market (risk-free rate of interest) and the project’s specific risk. Due to its essential nature in the financial and economic evaluation of projects (it is the only parameter that reflects the risk), it is reasonable to assume that investors would also be interested in constituent components of that indicator. The discount rate is one parameter in the discounted cash flow analysis that takes into account the risk of a venture. Further, the previous research in this area has focused mainly on the dimension of this variable, and the structure of this parameter has not been dealt with any other studies. The proposed idea of this study met the expectations of the industry—it aimed to present a typical project implemented in the energy industry, a relatively simple methodology that allowed estimating the components within the cost of equity capital of the enterprise. In the power generation sector, one can find various types of discount rates—assessed for multiple technologies, at different development stages, and expressed differently. Owing to the know-how and decades-long experience, coal-fired power projects’ remarks may be a good benchmark for alternative low carbon technologies. That is why, in this work, a discount rate for valuing investment in new coal-fired power projects was evaluated. This assessment was made on the “bare-bones” assumption, meaning evaluations at 100% equity, after-tax, in constant (real) currency units. The analysis of the discount rate structure was performed by applying the procedure of the classical sensitivity analysis having the accuracy of key input parameters. Finally, the risk factors within the risk-adjusted discount rate were calculated. The obtained results showed the importance of individual risk factors within the risk-adjusted discount rate used in coal energy projects, which would enable a more pragmatic approach to controlling this parameter by decision-makers and understanding the risk.

This paper considers hypothetical options for the transformation of the Bolivian power generation system to one that emits less carbon dioxide. Specifically, it evaluates the influence of the weighted average cost of capital (WACC) on marginal abatement cost curves (MACC) when applying carbon taxation to the power sector. The study is illustrated with a bottom-up least-cost optimization model. Projections of key parameters influence the shape of MACCs and the underlying technology configurations. These are reported. Results from our study (and the set of assumptions on which they are based) are country-specific. Nonetheless, the methodology can be replicated to other case studies to provide insights into the role carbon taxes and lowering finance costs might play in reducing emissions.