Linas Martišauskas

With rising energy demands and environmental challenges, the need for energy efficiency becomes urgent. This paper presents a user-friendly, simple digital tool for evaluating energy-saving measures in private buildings, including lighting upgrades, insulation of walls and roof, window replacements, and energy-efficient appliances. The tool estimates energy and financial savings and calculates key financial indicators such as payback period (PBP), net present value (NPV), and internal rate of return (IRR). It aims to support informed decision-making by offering personalised recommendations and scenario comparisons. The developed tool promotes sustainability and cost-effective energy use across diverse building types.

The building sector accounts for over 40% of global energy consumption, and many buildings are old and inefficient. However, the current pace of building renovation is not sufficient to make a tangible impact. A new strategy is needed to accelerate the renovation process. Renovation at the district level and the use of digital tools, such as a digital twin (DT) of a city district, can provide a solution. This paper proposes a novel approach to city block renovation using renewable energy sources (RES), including photovoltaic (PV) solar panels, heat pumps (HP), and electric heaters (EH), while utilizing a DT of a city district to provide a user-friendly representation of the results and data needed for holistic solutions. The proposed method combines an optimization model of the optimal heating system with a solar PV simulation technique to analyse hybrid RES solutions and potential on-site energy generation and supply. Several scenarios are simulated to evaluate RES solutions in the renovation process of the city block using the DT concept. The simulation results demonstrate that a hybrid RES solution, which includes a PV system and a heating system, is optimal when the on-site generated energy is used not only for domestic electricity consumption, but also for the operation of HPs and EHs for heat generation. This study highlights the importance and significance of a DT approach to city block renovation and provides a new solution to accelerate the renovation process and reduce energy consumption in the building sector.

District heating systems are gaining global recognition as an essential tool for reducing greenhouse gas emissions and transitioning to a low-carbon-energy future. In this context, heat pumps are becoming an important technology, providing an effective solution for improving energy efficiency and reducing the reliance on fossil fuels in heating systems. Therefore, this study is focused on the optimal selection of heat pump systems for different types of buildings considering technical, economic, environmental, and social factors. This paper proposes a novel methodology based on mixed-integer nonlinear programming and multi-objective optimization that minimizes total costs and reduces CO₂ emissions for heat production and supply systems over a desired period. The methodology is applied to various building types, including renovated and unrenovated apartment buildings, schools, kindergartens, and a supermarket. The study analyzes various types of heat pumps and electric heaters for space heating and domestic hot water production. Optimization results showed that the optimal heating system includes air-to-water heat pumps and electric heaters. Furthermore, for schools and a supermarket, these systems are combined with hybrid heat pumps. The goal of making the heating system neutral in terms of CO₂ emissions was achieved for eight out of eleven buildings analyzed. The most profitable investments were in the heating systems of renovated five-story and unrenovated nine-story apartment buildings due to their low energy costs (0.0831 EUR/kWh), short payback periods, and high returns on investment.

The field of solar photovoltaic (PV) plants has seen significant growth in recent years, with an increasing number of installations being developed worldwide. However, despite advancements in technology and design, the impact of shading on the performance of PV plants remains an area of concern. Accurate 3D models produced using unmanned aerial vehicle (UAV) photogrammetry can provide aid to evaluate shading from nearby surroundings and to determine the potential of a site for electricity production via solar PV plants. The main objective of this paper is to address the problem of shadows significantly reducing energy yield in solar PV plants by proposing a methodology that aims at assessing the shading effects on PV systems and determining the optimal configuration for a PV module array using an accurate digital environment 3D model built using UAV photogrammetry. A high-level-of-detail 3D model allows us to evaluate possible obstacles for PV module array construction and accurately recreate the proximities that can cast shadows. The methodology was applied to grid-connected PV systems in Kaunas, Lithuania. The results of the case study show that electricity production in PV modules is highest at a 15° tilt angle when the distance between PV rows is 1.25 m. The proposed methodology gives an 11% difference in PV yield due to shading compared with other tools that do not include shading. This study also highlights that at least 30% financing support is necessary for solar PV plants to be economically attractive, resulting in a payback of 9 years and an internal rate of return of 8%. Additionally, this study can help optimize the design and layout of PV systems, making them more efficient and cost-effective.

The “Clean Energy for all Europeans” package highlights the need to create a resilient critical energy infrastructure in the European Union. Resilience is an emerging term to describe the energy system’s ability to withstand shocks caused by natural hazards, technical accidents, or intentional threats. In this paper, a framework to assess the resilience of energy systems using quantitative indicators is presented. Two main groups of resilience indicators are proposed that depend on what is being measured within the energy system: capacity (attribute-based) indicators or performance in the presence of disruption (performance-based) indicators. This study concentrates on the first resilience phase, when the energy system has to absorb the impact of the shock. The approach considers various disruptions (both internal and external) as triggering events. There is a particular focus on future shocks affecting the prospective energy system, which will have changed with respect to the current one. The future foresight capabilities and potential of the selected resilience indicators are demonstrated using calculations for the Lithuanian energy system. The results revealed that the most important factors that impact energy system resilience are a rich electricity production mix and the diversification of both supply and production in the prospective energy system.

This work aims to present an analysis of electricity and natural gas supply security in the four European Union countries with the highest level of consumption, namely Germany, France, Italy, and Spain. The goal of the study is to use and adapt a set of 22 indicators for estimating the level of energy security. The evaluation of an index called “Energy Security Level”, measuring the overall energy security, is performed for the period 2006–2018 in order to compare its evolution in each of the analyzed countries. The application of the proposed indicator system demonstrates which measures weakened or strengthened energy security in the past. The analysis of the energy security level demonstrates that Germany and France perform better than Italy and Spain in terms of energy security assurance. The main factors for these differences are the rich energy mix for Germany and the massive presence of nuclear power in France. These two elements make German and French energy systems more resilient than the Italian and Spanish ones. The results of sensitivity and uncertainty analysis demonstrate that the initial values of indicator weights have low impact on the uncertainty of energy security level estimations.