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The 2015 UN Paris Agreement reinforced and declared compatible the two goals of avoiding dire climate change and maintaining global economic growth, and it specified that technological innovation is ‘critical’ to this joint achievement. Unfortunately, any confidence that near-term global economic growth is consistent with a stabilized climate is severely undermined by empirical evidence. Despite the rapid increase of alternative energies in recent decades, global GDP growth continues to require burning greater quantities of climate-destabilizing fossil fuels. The dim outlook for sufficiently reducing CO2while maintaining economic growth is underscored by global data and Germany specific data on the decoupling of GDP from CO2. This paper summarizes pertinent climate science, substantiates the dependence of economic growth on fossil fuels, and uses the Kaya identity to demonstrate the unfavorable prospects for reducing CO2while maintaining GDP growth. [ABSTRACT FROM PUBLISHER]

Global warming, climate change, and resource depletion have forced us to reconsider energy usage and efficiencies over the last few decades. Residential and commercial buildings are both large energy consumers, so improving energy and material usage efficiency in this sector is a common research topic. According to a recent study, the Building Sector (BS) accounts for 40% of greenhouse gas emissions. The primary objective of this paper is to examine and assess the potential of Renewable Energy Systems (RES) and their combinations for enhancing energy efficiency in the BS. Specifically, the focus will be on converting low energy-efficient buildings into highly efficient ones. The potential of the RES and their combinations for the BS is evaluated based on payback durations, energy generation, and reduction of CO 2 emissions. The optimization flow charts for the RES, feasibility studies, commercialization road maps of energy storage systems and the necessity of control mechanisms for enhancing RES efficiency were discussed. Additionally, the technology drawbacks are discussed, along with various innovative techniques recommended to direct future study in this area. Finally, this article assists the audience clear idea in the selection of the right combination of potential RES based on different conditions to achieve deep decarbonization in BSs. • Buildings sector (BS) responsible for 40% of GHG emissions. • Study assesses potential of Renewable Energy System (RES) in BS. • RES evaluated on payback, energy generation, and CO 2 reduction. • Optimization, feasibility and commercialization studies were discussed. • Article recommends right RES combinations for deep decarbonization in BS. [ABSTRACT FROM AUTHOR]

Energy is crucial to economic progress, but the contemporary worldwide population increase that demands greater energy generated from conventional exhaustible resources, an energy price upsurge, and environmental concerns, imperils sustainable economic growth. Nevertheless, switching to renewable energy produced from naturally replenished resources promotes energy security, likewise addressing issues such as global warming and climate change. This paper aims at exploring the influence and causal relation between renewable energy, both overall and by type, and sustainable economic growth of European Union (EU)-28 countries for the period of 2003-2014. We notice that the mean share of renewable energy in the gross final energy consumption is 15%, while the mean share of renewable energy in transport fuel consumption is 3%, which are below the thresholds of 20% and 10%, respectively, as set by the EU Directive 2009/28/EC. By estimating panel data fixed-effects regression models, the results provide support for a positive influence of renewable energy overall, as well as by type, namely biomass, hydropower, geothermal energy, wind power, and solar energy on gross domestic product per capita. However, biomass energy shows the highest influence on economic growth among the rest of renewable energy types. In fact, a 1% increase of the primary production of solid biofuels increases GDP per capita by 0.16%. Besides, cointegrating regressions set on panel fully modified and dynamic ordinary least squares regressions confirm the positive influence related to the primary production of renewable energies on economic growth. A 1% increase in primary production of renewable energies increases GDP per capita by 0.05%-0.06%. However, the results of Granger causality based on panel vector error correction model indicate both in short-run and long-run a unidirectional causal relationship running from sustainable economic growth to the primary production of renewable energies, being supported the conservation hypothesis. [ABSTRACT FROM AUTHOR]

The recent climate change, global warming, environmental disasters and the economic crisis are only the first signs of the failure of an economic system that, for too long, shows an uncontrolled utilization of the planet wealth. The Italian electricity market, which is strongly dependent on hydrocarbons, only in recent years has seen a first attempt to change towards renewable resources for electricity production aimed at self-consumption and for feeding into the grid. This paper presents an economic analysis whose purpose is to evaluate the profitability of investments in renewable technologies for the production of electricity. Each renewable source has its own profitability dependent on a number of factors and subject to market fluctuations, cost and frequent changes in the incentive policies. Applying Portfolio Theory is possible to select the right mix of renewable energy sources and simulate its evolution. Moreover the presented analysis can be useful for energy planners to select future green scenarios finalized to the reduction of emissions and energy imports through the increasing use of renewable energy. [ABSTRACT FROM AUTHOR]

In today's energy system, the diffusion of renewable-based technologies is accelerating rapidly. Development of mechanisms that support the large-scale deployment of renewables towards global warming and climate change mitigation continues to remain an issue of utter importance. The most important challenges the energy system of Kosovo faces today is the difficulty to meet all the demand for electricity, low operating efficiency and high release of greenhouse gas emissions, but specifically a large source of carbon dioxide (CO2). Consequently, this influences not only the stability of the system but the society as a whole. This paper addresses several possibilities for designing an adaptable energy system in Kosovo with the ability to balance electricity supply and demand which will meet the requirements for a more efficient, reliable and secure system. A new way of energy generating through integration of new renewable and non-renewable technologies is developed using the EnergyPLAN model. The system is based on available technologies: existing hydro, wind, photovoltaic (PV), combined heat and power (CHP) and new solar thermal, heat pumps and biomass. The baseline scenario 2015 was expanded by four additional scenarios, two for the year 2030 and two for the year 2050. The contribution of renewable sources in the primary energy supply (PES) in the performed scenarios was 14.8%, 34.1%, 38.4%, 69.7% and 68.3% respectively. Further, a very important component of this paper is the investigation of integrating carbon capture and sequestration (CCS) technology in the coal-based power plant as part of the analysis in the second scenario for 2050. The shift to zero-carbon energy system in Kosovo requires additional research and assessment in order to identify the untapped potential of renewable sources. However, from the results obtained it can be concluded that the goal of a secure, competitive and sustainable energy system in Kosovo state which will meet its long-term energy needs can be certainly achieved. [ABSTRACT FROM AUTHOR]

In view of increasing concerns about climate change and global warming, various renewable energy sources are widely adopted in power systems to reduce greenhouse gas emissions. However, the widespread adoption of renewable energy sources exacerbates the problem of harmonics pollution. In order to improve power quality, it is urgent to develop a new approach for monitoring harmonics. By leveraging the structured sparsity and spatial sparsity of harmonic sources, this paper proposes a group sparse Bayesian learning method for solving harmonic state estimation problems. The proposed algorithm can employ a small number of measurements less than the number of state variables to pinpoint harmonic sources and to estimate the harmonic magnitudes and angles. Moreover, the proposed method achieves automatic hyperparameter adjustments and solves the system states in complex domain without splitting them into real and imaginary parts. Extensive results on a benchmark IEEE 14-bus system are presented to substantiate the superiority of the proposed method in terms of localization accuracy and harmonic magnitude and phase angle estimation. • A group sparse Bayesian learning method is proposed for harmonic state estimation. • The proposed algorithm achieves automatic hyperparameter adjustments. • The proposed method can directly handle the measurements in the complex domain. • Using a small number of measurements pinpoints the harmonic sources. • The proposed method has high localization precision and small estimation error. [ABSTRACT FROM AUTHOR]

Solar energy harvesting using Photovoltaic (PV) systems is one of the most popular sources of renewable energy, however the main drawback of PV systems is their low conversion efficiency. An optimal system operation requires an efficient tracking of the Maximum Power Point (MPP), which represents the maximum energy that can be extracted from the PV panel. This paper presents a novel control approach for the Maximum Power Point Tracking (MPPT) based on the differential flatness property of the Boost converter, which is one of the most used converters in PV systems. The underlying idea of the proposed control approach is to use the classical flatness-based trajectory tracking control where a reference voltage will be defined in terms of the maximum power provided by the PV panel. The effectiveness of the proposed controller is assessed through numerical simulations and experimental tests. The results show that the controller based on differential flatness is capable of converging in less than 0.15 s and, compared with other MPPT techniques, such as Incremental Conductance and Perturb and Observe, it improves the response against sudden changes in load or weather conditions, reducing the ringing in the output of the system. Based on the results, it can be inferred that the new flatness-based controller represents an alternative to improve the MPPT in PV systems, especially when they are subject to sudden load or weather changes. [ABSTRACT FROM AUTHOR]