Legislative and economic tools of photovoltaic power support in Slovakia

One of the main trends in the development of solar photovoltaic (PV) grid-connected technology is the grid code compliance assessment for grid connection of PV power plant. But it is difficult to obtain the dynamic performance of the PV power plant under different operation scenarios through field test. In particular, it is costly to obtain the characteristics of the point of connection of PV power plant. The paper introduces support tools for simulation-based dynamic characteristics analysis of grid connection of PV power plant. Firstly, the function and flow chart of the developed support tools is described in detail. Then, the photovoltaic inverter detailed modelled. Finally, the support tools are developed based on the Powerfactory C++ API and Python package. The tools have many automation features that can be applied to online services which have be installed in the clean energy big data center. Test results have illustrated that the support tools can reflect dynamic performance of grid connection of PV power plant and can provide a decision support for the renewable energy priority scheduling.

The article deepens the theoretical foundations of building an organizational and economic mechanism for the development of rural construction. The essence of the organizational and economic mechanism, structure, and the place of economic and organizational tools are determined. The essence of economic tools is analyzed, and the main features of the organizational and economic mechanisms used to develop rural housing construction are determined. For the development of the organizational and economic mechanism, groups of tools were defined that provide the organizational and economic components of the construction orientation. Such groups include organizational tools that are divided into administrative, legal, and legislative. Economic tools also have adverse effects, namely, tools of motivation, responsibility, and support tools. As for the organizational component, when implementing the organizational and economic mechanism at the state level, the organizational component is provided by the President of Ukraine, the Verkhovna Rada, the Cabinet of Ministers, ministries and agencies, the executive power, regional authorities, and local self-government bodies. It has been established that the housing conditions of the population of Ukraine are changing due to socio-economic problems and instability factors that currently exist in Ukraine. The main directions of economic and organizational measures, which must be implemented based on the active use of relevant tools available to state authorities and local self-government bodies, are specified in order to develop housing construction in the long term. It was determined that in the implementation of the state policy of construction in rural areas, it is essential to use the market instruments by the executive authorities of the state within the framework of separate powers and management functions, which are implemented in the system of providing housing to rural residents through conditions and incentives. The organizational and economic mechanism is an integral element of the functioning of all economic objects and components of the national economy. Keywords: organizational and economic mechanism, housing stock, economic tools, rural areas, housing construction, construction enterprises, construction industry, economic recovery.

Electricity is one of the most essential keys in the evolution of nowadays civilization. Nevertheless, huge levels of electric power production and consumption could cause a negative impact on the environment, such as poor air quality, greenhouse emissions, climate change, and ecological disasters. Consequently, today's society needs sustainable solutions that can meet the geopolitical, socio-economic and climatic difficulties that energy production requires. Understanding this, international development programs have been modified approaching the use of sustainable sources of energy, which are gradually becoming economically viable. Among the valid options, photovoltaic (PV) systems have reached both the general and industrial public, becoming a sustainable energy source. Given these things, to gain a boost and to maintain a vital position in the market, it is necessary for prosumers to be aware and to recognize the mobility of characteristics in the fields of finance sphere, but also the structure of indicators able to measure a specific reality. We are calling it "specific reality" because we do not have enough business intelligence instruments in this sector and according to Eurostat, in 2020 only 3.09% of the electricity production in Romania came from photovoltaic panels and the increase was below one percent compared with 2019 when it was only 2.98%. The output power of a solar installation can be measured in several ways, including the competitiveness of the photovoltaic installations. To manipulate and guide the performances in this segment, we need Success Assessment Tools, that check a collection of characteristics used to calculate the outcomes and profitability of a prosumer’s movements. According to National Energy Regulatory Authority, in May 2020 there were only 514 prosumers in Romania (455 individuals, 59 legal entities). A huge untapped opportunity could be represented in Romania by individual households. According to a study custom-built by the European Commission, published in 2017, the theoretical Romanian potential would be about 3.36 million residential prosumers.

Fotovoltaik, güneş ışığını doğrudan elektriğe dönüştürme işlemidir. İlk yatırım maliyeti yüksek olsa da güneş enerjisi temiz ve yenilenebilir bir enerji kaynağı sunar. Fotovoltaik sistem kullanılarak elektrik enerjisi üretmek için; sistemin bulunduğu konum, ortam sıcaklığı ve dönüşüm sisteminin verimliliği gibi parametrelerin bilinmesi sistemin optimum çalışabilmesi için önemlidir. Bu sistemler tek panel ile kullanılabildiği gibi büyük enerji santrallerinde çok sayıda panelin birbirine bağlanması ile de kullanılabilir. Bu tarz bir sistem oluşturulurken hücrelerin güneşten aldığı enerjiye göre ürettiği gerilim ve akım değerleri kritik derecede önemlidir. Bu sistemlerin maksimum verimde çalışabilmesi için, sistem performansının analiz edilebildiği bir izleme sistemi kullanmak, fotovoltaik sistem tarafından üretilen enerji miktarını gerçek zamanlı olarak takip edebilmek ve öngörülen dönüşüm verimliliğinin, maksimum güç noktasını belirlemek son derece mühimdir. Bu çalışmada, LabVIEW programı kullanılarak fotovoltaik hücrelerin karakteristikleri, sistemin ürettiği elektrik enerjisi ve maksimum güç noktasının belirlenmesi için gerçek zamanlı ölçümlerin laboratuvar ortamında yapılması amacıyla kullanılacak bir donanım ve yazılım geliştirilmiştir. LabVIEW, endüstriyel olarak veri toplama sistemleri, test ve ölçüm cihazları gibi ihtiyaçları karşılamak için sıklıkla kullanılmaktadır. Sistemde kullanılan sensörlerden gelen bilgi, maksimum güç noktası izleme cihazı olarak kullanılan DC-DC dönüştürücüsünden okunmuştur. Elde edilen tüm veriler LabVIEW’ın arayüzünde, donanımda kullanılan mikrodenetleyiciye bağlı sensörlerden ve toplanan verilerin analiz edilebilmesi için LabVIEW ortamında hazırlanan görsel arayüz programı vasıtasıyla izlenmiştir. Önerilen sistem analiz ve veri toplama uygulamalarında kabul edilebilir bir performansa sahip olduğu görülmüştür.

"Parent-infant music therapy is a support tool for the relationship"

One important goal of the climate commitment in the European Union (EU) is to reduce primary energy demand in the transport sector and increase the use of renewables, since around 33% of primary energy is consumed in this sector. Therefore, the EU ordered its member states to raise the number of electric vehicles (EVs) within Europe. Consequently, the energy demand for electricity will rise as a function of the number of EVs. To avoid local grid overload and guarantee a higher percentage of clean energy, EV charging stations can be supported by a combined system of grid-connected photovoltaic modules and battery storage. In this paper, the focus lies on the feasibility and economic aspects of such systems. To provide an overview of the different e-charging station combinations, a support tool was modelled and developed, making it possible to size and manage EVs charging stations with only a few input parameters. Thanks to its easy handling, the tool suits a wide spectrum of users. Due to enhanced optional settings, this tool is suitable for detailed input parameters for professionals as well. Input categories are basically divided into the photovoltaic (PV) system, battery storage, the charging station itself, and investment analysis. The tool supports decisions for solar charging stations designed for different parking locations like offices, schools, and public and private places.

The urban configuration in the Mediterranean area, which has noticeable solar radiation and significant thermal oscillation, is one of the factors that affect the microclimate and the urban heat island phenomenon of the cities located in that zone. To contribute to the improvement of urban comfort, this work presents an experimental methodological proposal for the analysis and multicriteria optimization of performance indicators using a parametric workflow through Grasshopper. This workflow can lead to the development of a set of environmental design criteria as support tools in the design of the urban configuration. The methodology is based on the quantification of two parameters on the analysis and management of daylight in interior spaces by means of dynamic metrics and, on the other hand, on the evaluation of hygrothermal conditions and the urban heat island effect, which affect both the daytime comfort of passersby and the nighttime comfort of dwellings. This study considers the most typical variables of urban layout, both morphological and material. The case study analyzed is located in the city of Seville (Spain), which has a significant percentage of its contemporary buildings without a suitable adaptation to local climate conditions. The results obtained from the case study prove the potential of the proposed methodology to evaluate and optimize lighting and thermal performance at the neighbourhood scale. Thus, it provides urban planners with a powerful decision support tool for both urban expansion and urban renewal.

Clinical utility of a cluster of tests as a diagnostic support tool for clinical lumbar instability

Simple SummaryIdentifying cows with a higher risk of health disorders such as clinical mastitis, subclinical ketosis, lameness, and metritis could be advantageous for farms to prevent and ameliorate the negative effects of these disorders in a timely manner. In this study, we adopt eight machine learning algorithms using an R software for analyzing a dataset of 14-dimensions of dairy cows with health disorders across the whole lactation period in intensive Chinese dairy farms, applying automatic monitoring systems and milking systems. The variables analyzed by the machine learning algorithms include milk yield, physical activity, changes in rumination time, and the electrical conductivity of milk. Six parameters were presented to evaluate the performance metrics of the models, with the Rpart algorithm outperforming others and indicating a strong generalization ability of this algorithm. A total of 10 variables of greater importance in three models of Rpart, eXtreme Gradient, and Adaboost demonstrated the consistency of those variables as predictors for disorders of dairy cows monitored by automatic systems. The results obtained in this study highlighted the importance of using big data on the farm to develop predictive and prescriptive decision support tools to boost the development of precision livestock farming.We use multidimensional data from automated monitoring systems and milking systems to predict disorders of dairy cows by employing eight machine learning algorithms. The data included the season, days in milking, parity, age at the time of disorders, milk yield (kg/day), activity (unitless), six variables related to rumination time, and two variables related to the electrical conductivity of milk. We analyze 131 sick cows and 149 healthy cows with identical lactation days and parity; all data are collected on the same day, which corresponds to the diagnosis day for disordered cows. For disordered cows, each variable, except the ratio of rumination time from daytime to nighttime, displays a decreasing/increasing trend from d-7 or d-3 to d0 and/or d-1, with the d0, d-1, or d-2 values reaching the minimum or maximum. The test data sensitivity for three algorithms exceeded 80%, and the accuracies of the eight algorithms ranged from 65.08% to 84.21%. The area under the curve (AUC) of the three algorithms was >80%. Overall, Rpart best predicts the disorders with an accuracy, precision, and AUC of 81.58%, 92.86%, and 0.908, respectively. The machine learning algorithms may be an appropriate and powerful decision support and monitoring tool to detect herds with common health disorders.

Natural disasters affect the built environment’s infrastructure and disturb the economic sector’s sustainability and welfare. This requires a disaster recovery decision support tool that capitalizes on the redevelopment opportunities to elevate societies to a more-sustainable and less-vulnerable status. As such, this paper presents an agent-based model approach that aims to meet the objectives of stakeholders while decreasing the community’s economic vulnerability. Accordingly, the proposed model adopts a five-step research methodology: (1) implementing a comprehensive economic vulnerability assessment tool; (2) developing the objective functions and learning algorithms of the associated stakeholders; (3) modeling the different attributes and potential strategies of the various stakeholders; (4) creating an interdependent agent based model that simulates the aforementioned information; and (5) interpreting and analyzing the results generated from the developed model. The model is developed and tes...

Live sequence charts (LSCs) are a broad extension to message sequence charts (MSCs) to capture complex inter-object communication rigorously. A tool support for LSCs, named PlayEngine, is developed to interactively play-in and play-out scenarios. However, PlayEngine cannot automatically expose system design inconsistencies, e.g., conflicts between universal charts and etc. CSP is a formal language to specify sequential behaviors of a process and communication between processes, which has powerful tool supports, e.g., FDR. Semantically, system behaviors specified by LSCs correspond to CSP's traces and failures. This close semantic correspondence makes FDR a potential model checker for LSCs. The challenge is to discover a systematic way of constructing semantic preserving CSP models from LSCs. In this work, we investigate theoretical relations between LSCs and CSP. LSCs are formalized using trace and failure semantics so as to facilitate the semantic transformation from LSCs to CSP. The practical implication is that mature tool supports for CSP can be reused to validate LSCs. In particular, FDR is used to establish the consistency of an LSC model and perform various verifications.

For a complex activity like requirement engineering (RE), a powerful tool support is clearly useful. However, the mainstream of RE practice relies on office tools rather than targeted RE-tools (e.g. DOORS, CaliberRM, and RequisitePro). One of the reasons for not using RE-tools remains the difficulty to assess them before acquiring to organisation. Only few approaches are followed with some limited software tool support. Nor the approaches neither the tools are targeted towards the RE-tool domain; therefore, their applications are time consuming and domain knowledge demanding. Furthermore, the existing RE-tool frameworks list only RE-tool requirements which in most cases are development-oriented, and not supported by the application for the RE-tool evaluation. This paper presents a prototype tool of the evaluation framework for functional requirements of the RE-tools. The framework application is performed according to the systematic guidelines of the RE-tool evaluation approach (R-TEA).

Designing normative theories for ethical and legal reasoning: LogiKEy framework, methodology, and tool support

The article is devoted to the improvement of decision-making processes in the management of inter-budgetary relations between the regions and depressed mining municipalities. The tools of decision-making support in the form of economic and mathematical models included in the control circuit are proposed. Economic and mathematical tools are based on the application of the mathematical apparatus of the theory of stochastic automata in random environments. The constructed mathematical abstraction “stochastic automaton” describes the behavior of the decision-making subject in determining the norms of shared distribution of tax revenues between budgets on the vertical line of power. A stochastic automaton possesses the property of learningability of expedient behavior. The decisions made by the automaton regarding the values of the tax revenue distribution norms are quantified through interaction with the simulation model. The simulation model forms a random environment in which the stochastic automaton is immersed, and reacts to the administrative decisions made by the automaton through its encouragement and punishment. The article proposes the construction of a stochastic automaton, described by its transition function. The transition function of an automaton from state to state is formally represented by matrices. The authors derive analytical expressions for the final probabilities of the machine in each of its states. The efficiency of the economic and mathematical tools is demonstrated through the presentation of the results of the conducted experimental studies in the selection of options for decisions regarding the share of the distribution of tax revenues.

The paper presents a part of research focused on the definition of circular economy models in the regeneration of existing building stock in the Italian context, identifying policies improvements, strategic partnership and environmental and economic life cycle assessment tools for supporting decision.Through direct-interviews to operators (investors, designers, manufacturers, etc.), the paper analyses the typical relationships and dynamics among them in the Italian building regeneration process. The operators’ opinions and requests towards circular strategies (reuse/recycling at building and material levels) are pointed out, in order to highlight the obstacles and levers of circular economy application. The paper shows the strengths and the weaknesses for the regeneration of building stock by the application of circular economy, the opportunities and the threats for circular economy by its application in the regeneration of building stock. In order to achieve circular requalification processes, avoiding waste and enabling practices of reuse and recycling, the change of relationships, policies and business models are defined. Moreover, the paper discusses on the importance of environmental evaluation of circular practices, identifying the decision steps and operators which, with the support of environmental and economic life cycle assessment tools, can select circular strategies towards sustainable requalification process.