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The economy is undergoing a radical transformation in all its structures, completely changing the methods of management. Changes are taking place on a global scale based on the digital technologies being implemented. The role of the state and executive authorities is being completely rethought. They are transforming themselves into “digital governments”, IT platforms, and forming their own digital structures with a list of services that are necessary for the population. In this study the following 4 directions of development of the public administration system were identified and reviewed in detail: digital reforms in the public administration system; long-term balance and sustainability of public administration; focusing on improving the quality and efficiency of public services; implementation of project management methods for the development and implementation of state programs. Based on the conducted research, current trends in public administration have been highlighted, and it was concluded that the trends in the development of modern economies include the mandatory participation of the state.

Insects have a pivotal role in ecosystem function, thus the decline of more than 75% in insect biomass in protected areas over recent decades in Central Europe1 and elsewhere2,3 has alarmed the public, pushed decision-makers4 and stimulated research on insect population trends. However, the drivers of this decline are still not well understood. Here, we reanalysed 27 years of insect biomass data from Hallmann et al.1, using sample-specific information on weather conditions during sampling and weather anomalies during the insect life cycle. This model explained variation in temporal decline in insect biomass, including an observed increase in biomass in recent years, solely on the basis of these weather variables. Our finding that terrestrial insect biomass is largely driven by complex weather conditions challenges previous assumptions that climate change is more critical in the tropics5,6 or that negative consequences in the temperate zone might only occur in the future7. Despite the recent observed increase in biomass, new combinations of unfavourable multi-annual weather conditions might be expected to further threaten insect populations under continuing climate change. Our findings also highlight the need for more climate change research on physiological mechanisms affected by annual weather conditions and anomalies.

This paper presents a mixed-integer model for the hourly energy and reserve scheduling of a price-taker and closed-loop pumped-storage hydropower plant operating in hydraulic short-circuit mode. The plant participates in the spot market and in the secondary regulation reserve market, taking into account the regulation energy due to the real-time use of the regulation-up and -down reserves. The proposed model is used to compare the maximum theoretical income of the plant with and without considering hydraulic short-circuit operation. Numerical results demonstrate that the operation in hydraulic short-circuit mode could help significantly to enlarge the income of the power plant and that the secondary regulation reserve market might be the main source of revenue in a realistic setting characterized by a high level of renewable energy sources in the generation mix. info:eu-repo/semantics/draft

One of the most important key factors for the development of non-urban areas is infrastructure, and energy generation is one of the fundamental infrastructure elements. This paper provides a new solution for energy generation based on wood chips which has a multi-sector effect because the authors offer to combine planning of forest cleaning cutting with bioenergy generation in one complex project, which will have socio-economic and ecological effects. The situation with forest fires makes the authors’ idea more attractive because after forest fires the problem of cleaning cutting in forest becomes very important and urgent by ecological and economical points: after cleaning cutting there are a lot of low quality wood which can be recycled into chips for the production bioenergy by the authors’ idea. This enriched methodology has successfully been applied into the regional strategical planning in the field of bioenergy and forestry of the Ural region of Russia; however, it is suitable for applications in regional development in any non-urban forested region of the world. © 2017, Editura Universitatii din Bucuresti. All rights reserved.

Power system state estimation is being faced with different types of anomalies. These might include bad data caused by gross measurement errors or communication system failures. Sudden changes in load or generation can be considered as anomaly depending on the implemented state estimation method. Additionally, considering power grid as a cyber physical system, state estimation becomes vulnerable to false data injection attacks. The existing methods for anomaly classification cannot accurately classify (discriminate between) the above mentioned three types of anomalies, especially when it comes to discrimination between sudden load changes and false data injection attacks. This paper presents a new algorithm for detecting anomaly presence, classifying the anomaly type and identifying the origin of the anomaly, i.e., measurements that contain gross errors in case of bad data, or buses associated with loads experiencing a sudden change, or state variables targeted by false data injection attack. The algorithm combines analytical and machine learning (ML) approaches. The first stage exploits an analytical approach to detect anomaly presence by combining χ2-test and anomaly detection index. The second stage utilizes ML for classification of anomaly type and identification of its origin, with particular reference to discrimination between sudden load changes and false data injection attacks. The proposed ML based method is trained to be independent of the network configuration which eliminates retraining of the algorithm after network topology changes. The results obtained by implementing the proposed algorithm on IEEE 14 bus test system demonstratethe accuracy and effectiveness of the proposed algorithm.

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Cross-border electrical interconnection projects are getting more attention all over the world. In this context, cost-benefit allocation is especially important due to the need for fair sharing of power trading benefits among the countries as well as allocating the investments in capital-intensive power lines. One convenient way of dealing with these issues is using cooperative game theory. However, even fair allocation methods, such as the Shapley value, do not guarantee the stability of negotiations on cross-border interconnection projects. The result of the allocation process strongly depends on the individual system’s data provided by each party involved. In this regard, the parties could have incentives to strategically provide data that would benefit themselves in the cost-benefit allocation process, potentially hindering the stability of the coalition. In this paper, we address the negotiation stability issues in terms of players strategic behavior and manipulability of cost-benefit allocation rules.

Climate change has been posing an increasing threat to the planet at the environmental and economic levels, and the rise of clean energy (CE) is ever more fundamental for ensuring a qualified alternative for the energy mix, attracting the financial interest of different investment entities. In this respect, the significance of corporate venture capitalists (CVCs) has been on a steady rise for every sector, even for CE, since the 1990 s, and it is shaping up to become a major force behind the worldwide innovation. The aim of this research is to investigate the essential profiles about the phenomenon regarding CVCs that are active in CE, with a focus on the Asia-Pacific (APAC) region, to understand how they act in pursuing their strategic intention. The specific contribution of this study, which adopts a quantitative approach to operate a descriptive analysis on the dynamics operating in the context under investigation by combining relating data from several institutional databases, is to provide a scenario analysis with explorative intention that may define the main characteristics, roles in innovation, and growing participation of CVCs in the CE sector, especially in the APAC area.

The problem of wastewater has long been ubiquitous and has great consequences for the environment and its inhabitants. Microbial fuel cells (MFCs) have enormous potential for the treatment of wastewaters polluted with azo dyes. The amount of energy that can be produced from a single-chamber MFC is sufficient to perform decolorization and degradation of such dyes, which are widely used in the textile industry. This study on the azo dye, reactive black 5 (RB5), provides an alternative method through three parallel-connected MFCs to obtain electricity that directly serves for the dye's electrochemical degradation. We examined degradation followed by decolorization of RB5 using Fe and Pt electrodes, together with H2O2, to achieve the electro-Fenton process. The amount of voltage produced (295 mV), the current density (276 mA m-3) and the power density (50 mW m-3) were sufficient to degrade 25 mg L-1 RB5 dye with 0.5 mM H2O2 in just 2 h. The dye degradation mechanism was investigated using UV-VIS, FT-IR and HPLC-MS/MS. The ecotoxicity of the degradation products was assessed using a bacterial model, Aliivibrio fischeri. These tests showed that there was successful degradation of the dye to products whose toxicity is less than that of RB5.