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The evolution of electricity in Romania took place in the last century. This paper presents the development of electricity sector in a seasonal evolution form. This approach has a cyclical character and highlights options for the future. The main stages of evolution, with a duration of several decades each, are associated with the four seasons: winter, spring, summer and autumn. The similarity features relate to the quantitative and qualitative ways of electricity production evolution, which is in line with the technological development level of a country. The conclusions highlight the idea of proactive rational action with regard to ensuring in the future the necessary human resources.

Abstract An alkaline earth boro-aluminosilicate glass (Eagle XG), a soda-lime glass, and a light-weight polyethylene-terephthalate (PET) foil, used as typical substrates for photovoltaics, were treated by an energetic proton beam (3 MeV, dose 106–107 Gy) corresponding to approx. 30 years of operation at low Earth orbit. Properties of the irradiated substrates were characterized by atomic force microscopy, optical absorption, optical diffuse reflectance, Raman spectroscopy, X-ray photoelectron spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and terahertz (THz) spectroscopy. Minimal changes of optical and morphological properties are detected on the bare Eagle XG glass, whereas the bare PET foil exhibits pronounced increase in optical absorption, generation of photoluminescence, as well as mechanical bending. On the other hand, the identical substrates coated with Indium-tin-oxide (ITO), which is a typical material for transparent electrodes in photovoltaics, exhibit significantly higher resistance to the modifications by protons while ITO structural and electronic properties remain unchanged. The experimental results are discussed considering a potential application of these materials for missions in space.

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.

Optimal control is a key element in today’s control applications, being widely used in many different fields. The linear-quadratic regulator (LQR) is an optimal control method which is frequently used in optimal control applications because of its efficiency and simplicity. Having this in mind, the authors studied the level control of a cascaded multitank system using the LQR algorithm. The approach of the authors consists of a piecewise linearization method, converting this nonlinear problem into a linear one. Results show that LQR is a very efficient method for this type of system, yielding good performances with reduced controller effort.

Abstract The sustainable indicators are characterized by a low degree of aggregation and a high amount of information. An indicator must show a synthetic representation of a real environmental, by using a value or a parameter, so that they can be easily used by policy makers. It is necessary to connect, therefore, the various systems in an appropriately integrated sustainable system. The indicators need to be aggregated based on the structure of the data. Each indicator must to be defined through a weight with reference to another weighted indicator. In this paper is illustrated the calculation of the assigned weights that uses a procedure based on fuzzy logic and to define a model that allows us to estimate the sustainability of a city. The final result is, therefore, a combination of values assigned by expert opinion for the various criteria, processed using fuzzy logic to obtain a weight with significant objectivity and as it is possible to estimate the sustainability of the city through the weights.

Abstract The present paper evaluates the feasibility of a process flowsheet for butanol bioproduction, as pure compound or as a blend with the biodiesel used as the liquid-liquid extraction (LLEx) solvent. In order to evidence this aspect, a modeling and simulation study was performed using Aspen Hysys commercial simulator. Process simulation results evidenced specific (per ton of butanol separated) power consumption of 22.5 kW/t and hot and cold utility specific consumptions were in power equivalences of 3.4 MW and 2.6 MW respectively. In order to achieve a feasible extraction process of biobutanol from the fermentative broth, a specific quantity of 1.125 t/t biodiesel (recovered as a blend) was required.

Economic dispatch is a cost minimization problem that seeks to identify an optimal program for generating units operating in different types of power plants and under different technical constraints. This article develops a new hybrid resulting from the combination of sine–cosine (SCA) and flower pollination (FPA) algorithms, but some of the features of these algorithms have been modified to improve performance. The characteristics of the SCA and FPA algorithms that have been modified are: the heuristics used to update the solutions and the way of generating values for some parameters specific to the mentioned algorithms. The generation of these chaotic values is done in the proposed hybrid by using the logistic map. The proposed hybrid, abbreviated HSC-FP, is applied to solve the economic dispatch problem with/without including wind power uncertainty (wind speed being modeled by a Weibull distribution) and considering various practical features of power systems, such as the valve-point effects, transmission line losses, prohibited operating zones (POZ), ramp limits, multi-fuel sources. The performance of the HSC-FP hybrid is tested on several systems with various dimensions (10-unit, 14-unit, 40-unit and 80-unit) and characteristics. The obtained results show that the HSC-FP hybrid is a promising algorithm that surpasses the performance of other algorithms used in solving the economic dispatch problem with/without the inclusion of wind power.

Nowadays, in order to optimize resource consumption and reduce costs, companies concern themselves with the adoption of innovative energy efficiency solutions. Substantiating the decision to implement energy efficiency measures is challenging, due to a high number of factors that influence the rentability of the project, such as weather conditions, energy pricing, laws and regulations, available resources and energy demand. Thus, each company faces a unique combination of factors that needs to be properly evaluated prior to the adoption of energy efficiency measures. The paper presents an IoT and Cloud-based energy monitoring and simulation platform that aims to help companies monitor energy production and consumption within various cost-centers, forecast the energy production potential and simulate the economic efficiency for multiple investment scenarios.

A p-NiO/n-KNbO3 heterojunction photocatalyst was synthesized via a photodeposition method and for the first time applied in photocatalytic N2 fixation under simulated sunlight.