The paper analyzes and compares the perspectives for reducing the energy consumption associated to the operation of Heating Ventilation and Air Conditioning system for climatic control of large-size ...non-residential buildings. Three different control strategies are considered comparing the use of boiler and heat pumps as heating systems and analyzing the use of demand-controlled ventilation, operating on the effective occupancy of the building. The control strategies are applied to two different educational buildings with shapes representative of typical educational structures. The results of the analysis show how the energy consumption can be reduced up to 70%, shifting from the actual values of the energy intensity of over 300 kWh/m2 for year to values of less than 100 kWh/m2 per year. The significance of the energy savings achieved in such different buildings has led to the identification of a possible benchmark for HVAC systems in the next future years which could help reach the environmental targets in this sector.
Most commentators expect improved energy efficiency and reduced energy demand to provide the dominant contribution to tackling global climate change. But at the global level, the correlation between ...increased wealth and increased energy consumption is very strong and the impact of policies to reduce energy demand is both limited and contested. Different academic disciplines approach energy demand reduction in different ways: emphasising some mechanisms and neglecting others, being more or less optimistic about the potential for reducing energy demand and providing insights that are more or less useful for policymakers. This article provides an overview of the main issues and challenges associated with energy demand reduction, summarises how this challenge is ‘framed’ by key academic disciplines, indicates how these can provide complementary insights for policymakers and argues that a ‘sociotechnical’ perspective can provide a deeper understanding of the nature of this challenge and the processes through which it can be achieved. The article integrates ideas from the natural sciences, economics, psychology, innovation studies and sociology but does not give equal weight to each. It argues that reducing energy demand will prove more difficult than is commonly assumed and current approaches will be insufficient to deliver the transformation required.
Memristors with tunable resistance states are emerging building blocks of artificial neural networks. However, in situ learning on a large-scale multiple-layer memristor network has yet to be ...demonstrated because of challenges in device property engineering and circuit integration. Here we monolithically integrate hafnium oxide-based memristors with a foundry-made transistor array into a multiple-layer neural network. We experimentally demonstrate in situ learning capability and achieve competitive classification accuracy on a standard machine learning dataset, which further confirms that the training algorithm allows the network to adapt to hardware imperfections. Our simulation using the experimental parameters suggests that a larger network would further increase the classification accuracy. The memristor neural network is a promising hardware platform for artificial intelligence with high speed-energy efficiency.
The understanding of how spins move and can be manipulated at pico- and femtosecond timescales has implications for ultrafast and energy-efficient data-processing and storage applications. However, ...the possibility of realizing commercial technologies based on ultrafast spin dynamics has been hampered by our limited knowledge of the physics behind processes on this timescale. Recently, it has been suggested that inertial effects should be considered in the full description of the spin dynamics at these ultrafast timescales, but a clear observation of such effects in ferromagnets is still lacking. Here, we report direct experimental evidence of intrinsic inertial spin dynamics in ferromagnetic thin films in the form of a nutation of the magnetization at a frequency of ~0.5 THz. This allows us to reveal that the angular momentum relaxation time in ferromagnets is on the order of 10 ps.Inertial dynamics are observed in a ferromagnet. Specifically, a nutation is seen on top of the usual spin precession that has a lifetime on the order of 10 picoseconds.
Energy service companies (ESCOs) have emerged to carry out energy efficiency retrofit projects, playing an essential role in mitigating carbon dioxide (CO2) emissions in China. However, it remains ...unclear how exactly ESCOs contribute to CO2 mitigation during urbanization and industrialization. We conducted regression analyses on data collected in 29 provinces in China as the first case study to investigate the moderating effect of ESCOs in relationships between urbanization, industrialization, and CO2 emissions. The results indicate that urbanization had a significantly negative influence on CO2 emissions. In contrast, industrialization displayed a statistically significant positive impact on CO2 emissions. ESCOs have a significant moderating effect on the relationship between industrialization, urbanization, and CO2 emissions. The analysis also revealed that ESCOs have a better performance in areas with lower industrialization and greater urbanization. ESCOs may invest more in regions with limited ESCO activities and huge CO2 emission reduction demand, while energy-saving technology innovation should be advocated in regions with sufficient ESCO activities.
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•Energy service companies (ESCOs) contribute to CO2 mitigation.•Relationships of industrialization, urbanization, and CO2 emissions are quantified.•Urbanization has a significant negative influence on CO2 emissions.•Industrialization shows a significant positive impact on CO2 emissions.•ESCOs exert an appreciable moderating effect on these relationships.
•2050 primary energy use can be the same as in 2010 with a 7-fold increase in GDP.•Coal use can peak around 2020, then oil in 2033, and natural gas in 2045.•Non-fossil energy is 28% in 2030, higher ...than China’s Paris Agreement goal of 20%.•Industry CO2 emissions can peak ∼2020, buildings ∼2029, and transportation ∼2035.•CO2 emissions can peak in 2025, earlier than China’s Paris Agreement goal of 2030.
As part of its Paris Agreement commitment, China pledged to peak carbon dioxide (CO2) emissions around 2030, striving to peak earlier, and to increase the non-fossil share of primary energy to 20% by 2030. Yet by the end of 2017, China emitted 28% of the world’s energy-related CO2 emissions, 76% of which were from coal use. How China can reinvent its energy economy cost-effectively while still achieving its commitments was the focus of a three-year joint research project completed in September 2016. Overall, this analysis found that if China follows a pathway in which it aggressively adopts all cost-effective energy efficiency and CO2 emission reduction technologies while also aggressively moving away from fossil fuels to renewable and other non-fossil resources, it is possible to not only meet its Paris Agreement Nationally Determined Contribution (NDC) commitments, but also to reduce its 2050 CO2 emissions to a level that is 42% below the country’s 2010 CO2 emissions. While numerous barriers exist that will need to be addressed through effective policies and programs in order to realize these potential energy use and emissions reductions, there are also significant local environmental (e.g., air quality), national and global environmental (e.g., mitigation of climate change), human health, and other unquantified benefits that will be realized if this pathway is pursued in China.
Recently, researchers introduced energy-efficient dynamic routing protocols for wireless sensor networks to avoid the premature end of network lifetime. This paper addresses the routing hole problem ...due to energy depletion and the trade-off between the network need for periodic setups to preserve connectivity and power constraints on sensor nodes. The paper solves the problem of the premature end of network lifetime in applications where the base station (BS) is far from the Region Of Interest (ROI). Therefore, we propose two distributed, energy-efficient, and connectivity-aware routing protocols for solving the routing hole problem. These protocols are On-Hole Children Reconnection (OHCR) with local nature and On-Hole Alert (OHA) with global nature. The proposed protocols preserve the connectivity of all single setup phase, single path networks with any topology in an energy efficient manner by avoiding topology reformation overhead. The simulation results proved that the proposed protocols outperform the recent ones in terms of network lifetime, node loss rate, and network overhead. Such that, the two protocols are examined on both Degree Constrained Tree (DCT) and Shortest Path Tree (SPT) to provide about 50% to 75% increase in network lifetime over the recent energy efficient routing protocols; like UCCGRA and NEECP. Additionally, applying OHCR and OHA to any network topology doesn't affect its stability period, since these protocols are triggered by routing hole occurrence.
The use of low-resolution digital-to-analog and analog-to-digital converters (DACs and ADCs) significantly benefits energy efficiency (EE) at the cost of high quantization noise for massive ...multiple-input multiple-output (MIMO) systems. This paper considers a precoding optimization problem for maximizing EE in quantized downlink massive MIMO systems. To this end, we jointly optimize an active antenna set, precoding vectors, and allocated power; yet acquiring such joint optimal solution is challenging. To resolve this challenge, we decompose the problem into precoding direction and power optimization problems. For precoding direction, we characterize the first-order optimality condition, which entails the effects of quantization distortion and antenna selection. We cast the derived condition as a functional eigenvalue problem, wherein finding the principal eigenvector attains the best local optimal point. To this end, we propose generalized power iteration based algorithm. To optimize precoding power for given precoding direction, we adopt a gradient descent algorithm for the EE maximization. Alternating these two methods, our algorithm identifies a joint solution of the active antenna set, the precoding direction, and allocated power. In simulations, the proposed methods provide considerable performance gains. Our results suggest that a few-bit DACs are sufficient for achieving high EE in massive MIMO systems.
Mobile-edge computing (MEC) is an emerging paradigm to meet the ever-increasing computation demands from mobile applications. By offloading the computationally intensive workloads to the MEC server, ...the quality of computation experience, e.g., the execution latency, could be greatly improved. Nevertheless, as the on-device battery capacities are limited, computation would be interrupted when the battery energy runs out. To provide satisfactory computation performance as well as achieving green computing, it is of significant importance to seek renewable energy sources to power mobile devices via energy harvesting (EH) technologies. In this paper, we will investigate a green MEC system with EH devices and develop an effective computation offloading strategy. The execution cost, which addresses both the execution latency and task failure, is adopted as the performance metric. A low-complexity online algorithm is proposed, namely, the Lyapunov optimization-based dynamic computation offloading algorithm, which jointly decides the offloading decision, the CPU-cycle frequencies for mobile execution, and the transmit power for computation offloading. A unique advantage of this algorithm is that the decisions depend only on the current system state without requiring distribution information of the computation task request, wireless channel, and EH processes. The implementation of the algorithm only requires to solve a deterministic problem in each time slot, for which the optimal solution can be obtained either in closed form or by bisection search. Moreover, the proposed algorithm is shown to be asymptotically optimal via rigorous analysis. Sample simulation results shall be presented to corroborate the theoretical analysis as well as validate the effectiveness of the proposed algorithm.
Energy efficiency optimization of wireless systems has become urgently important due to its impact on the global carbon footprint. In this paper we investigate energy efficient multicell multiuser ...precoding design and consider a new criterion of weighted sum energy efficiency, which is defined as the weighted sum of the energy efficiencies of multiple cells. This objective is more general than the existing methods and can satisfy heterogeneous requirements from different kinds of cells, but it is hard to tackle due to its sum-of-ratio form. In order to address this non-convex problem, the user rate is first formulated as a polynomial optimization problem with the test conditional probabilities to be optimized. Based on that, the sum-of-ratio form of the energy efficient precoding problem is transformed into a parameterized polynomial form optimization problem, by which a solution in closed form is achieved through a two-layer optimization. We also show that the proposed iterative algorithm is guaranteed to converge. Numerical results are finally provided to confirm the effectiveness of our energy efficient beamforming algorithm. It is observed that in the low signal-to-noise ratio (SNR) region, the optimal energy efficiency and the optimal sum rate are simultaneously achieved by our algorithm; while in the middle-high SNR region, a certain performance loss in terms of the sum rate is suffered to guarantee the weighed sum energy efficiency.
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