• Energy Research

Abstract The topic of low-energy buildings received a widespread and growing interest in last years, thanks to energy saving policies of developed countries. The design of a low-energy building is addressed with energy saving measures and renewable energy generation, but the correct assessment of phenomena occurring in a building usually requires to perform dynamic simulations and to analyze multiple scenarios to attain the optimal solution. The optimality of a technical solution may be subject to contrasting constraints and objectives. For this reason, designers may employ mathematical optimization techniques, a non-familiar topic to most of building designers. In this paper, a review on optimization of low-energy buildings design is provided, in order to collect the results of previous works and to guide new designers. The topic received an increasing interest in last years, with multi-objective optimization and genetic algorithms being the most popular. The most common objective functions are the costs and the operating energy consumption, while the environmental aspects are often neglected. As low-energy buildings should reduce the global energy demand, their design may benefit enormously from the assessment of energy consumption and environmental impacts in the whole life cycle, even in a simplified way.

When a single line to ground fault (SLGF) happens on the MV side of an HV/MV system, only a small portion of the fault current is injected into the ground by the ground grid of the faulty substation. In fact, the fault current is distributed between grounding electrodes and MV cables sheaths. In systems with isolated neutral or with resonant earthing, this may be sufficient to provide safety from electric shock. Experimental measurements were performed on a real MV distribution network: a real SLGF was made and fault currents were measured in the faulty substation and in four neighboring substations. In this paper, the problem of fault current distribution is introduced, the test system is described and the measurements results are presented.

The reduction of climate change effects (mitigation) is now mainly driven by the limitation of CO2 emissions which is currently becoming increasingly necessary and urgent to achieve. In this context, within the past Horizon 2020 program, the Urban Europe Joint Programming Initiative aimed to promote the development and deployment of at least 100 Positive Energy Districts by 2025. The latter are flexible, energy-efficient urban areas or groups of buildings that produce zero net CO2 emissions and actively manage annual renewable energy surplus production at the local or regional level. As they are connected to the electric power system, Positive Energy Districts have the ability to offer flexibility services to the grid, such as frequency or voltage regulation, being part of a larger scheme as the Italian energy communities recently regulated by the Milleproroghe Decree. In this paper, a blockchain-based architecture is proposed with the aim of providing a system for the trusted certification of energy self-sustainability and the management of energy trading among different districts or the supply of energy services delivered from the district to the electricity grid, promoting their effective integration with the power system.

This work describes a methodology for the identification of the optimal features for the envelope of a residential building. The optimization process allows minimizing operating energy consumption, investment costs and life cycle energy and environmental embodied impacts. A dynamic model for the estimation of building energy consumption during its use phase has been employed, while literature data were adopted for embodied energy and global warming potential impacts. The considered variables refer to the envelope of the building, i.e. external walls and roof insulation and external walls thermal mass. The model was obtained combining EnergyPlus building energy simulator and MOBO, a versatile freeware that allows running the optimization of building features. The optimization was solved using NSGA II, a widespread adopted multi-objective genetic algorithm available in MOBO. The same building was simulated in two different climatic zones, namely Palermo (Italy) and Copenhagen (Denmark), in order to compare differences attained in the optimal solutions. The case study shows that the adoption of glass wool for the roof insulation and small concrete layers for external walls are to be preferred, providing optimal results in both climates. The present work was developed within the framework of IEA EBC Annex 72.

This paper presents an assessment of the levelized cost of clean hydrogen produced in Sicily, a region in Southern Italy particularly rich in renewable energy and where nearly 50% of Italy’s refineries are located, making a comparison between on-site production, that is, near the end users who will use the hydrogen, and centralized production, comparing the costs obtained by employing the two types of electrolyzers already commercially available. In the study for centralized production, the scale factor method was applied on the costs of electrolyzers, and the optimal transport modes were considered based on the distance and amount of hydrogen to be transported. The results obtained indicate higher prices for hydrogen produced locally (from about 7 €/kg to 10 €/kg) and lower prices (from 2.66 €/kg to 5.80 €/kg) for hydrogen produced in centralized plants due to economies of scale and higher conversion efficiencies. How-ever, meeting the demand for clean hydrogen at minimal cost requires hydrogen distribution pipelines to transport it from centralized production sites to users, which currently do not exist in Sicily, as well as a significant amount of renewable energy ranging from 1.4 to 1.7 TWh per year to cover only 16% of refineries’ hydrogen needs.

The themes related to the enhancement of sustainability in the built environment have been gaining increasing concerns by the scientific community, other than by governments. Accordingly, there is a need for the availability of tools that can help scientists and policy makers in choosing the most appropriate intervention measures that simultaneously take into account environmental as well as energy and economic aspects. To this purpose, a literature review of scientific articles dealing with the optimization of the performance of buildings, making use of LCA, energy and economic analyses was conducted. The results of this earlier step of research (which would serve as the basis for future developments) are aimed at singling out a small set of indicators to be used in a multi-objective optimization methodology for the enhancement of buildings sustainability.

Electric vehicles are the future of the transport sector. The massive transition from traditional passenger vehicles to electric vehicles will play an important role in the decarbonization of the transport sector and moving toward zero emissions. The main problem will be the generation source of electricity to charge the huge fleet of future electric vehicles. Hence clean and renewable energy sources will play a vital role in making electric vehicles carbon-free. In this paper, the impact of the carbon dioxide emission factor of power systems on electric vehicles has been studied in detail. A carbon dioxide emission comparison has been done for traditional passenger vehicles and electric vehicles. The study has been carried out for three Italian regions, the Tuscany Region, Sicily Region, and Sardinia Region having low, medium, and high carbon dioxide emission factors of power systems respectively, with different penetration levels of electric vehicles. An ideal scenario with 100 percent renewable energy sources and an extreme Scenario with 0 percent renewable energy sources in the power system has also been studied for electric vehicles' role in the decarbonization of the transport sector. The result obtained in this study showed that renewable energy sources in the future power grids will have a significant impact in making electric vehicles zero-emissions cars and many European Union goals of making the transport sector zero carbon cannot be achieved without making the future power system grids renewable.

In this paper, an original scheduling approach for optimal dispatch of electrical Energy Storage Systems (ESS) in modern distribution networks is proposed. The control system is based on fuzzy rules and does not use forecasts since it repairs the past history according to the real time data on the electrical energy cost, renewable energy production and load. When the system detects a worsening of performances, the fuzzy logic rule-based control system self-adapts its membership functions using an economic indicator. The common use, in the relevant literature, of forecasted values in such systems can lead to large errors and economic losses. Moreover the speed of calculation guaranteed by the fuzzy control system allows the execution of new calculations even with high frequency. After the Introduction section, where the state of the art on the topic is outlined, the problem formulation is presented and an interesting application of the considered approach to the control on a medium size battery with real world data is proposed.