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We study the energy-efficient power allocation techniques for OFDM-based cognitive radio (CR) networks, where a CR transmitter is communicating with CR receivers on a channel borrowed from licensed primary users (PUs). Due to non-orthogonality of the transmitted signals in the adjacent bands, both the PU and the cognitive secondary user (SU) cause mutual-interference. We assume that the statistical channel state information between the cognitive transmitter and the primary receiver is known. The secondary transmitter maintains a specified statistical mutual-interference limits for all the PUs communicating in the adjacent channels. Our goal is to allocate subcarrier power for the SU so that the energy efficiency metric is optimized as well as the mutual-interference on all the active PU bands are below specified bounds. We show that the green power loading problem is a fractional programming problem. We use Charnes-Cooper transformation technique to obtain an equivalent concave optimization problem for what the solution can be readily obtained. We also propose iterative Dinkelbach method using parametric objective function for the fractional program. Numerical results are given to show the effect of different interference parameters, rate and power thresholds, and number of PUs.

Lowering the exergy content of heat required for heating purposes decreases the primary energy consumption. District heating systems are often an important link between facilities that generate heat with low exergy content and consumers. Exergetic efficiency of heat distribution is an important performance criterion in heat supply to consumers. It can serve as a criterion for optimization, towards a more sustainable distribution-network design and operation. This paper presents a methodology for an exergy-based distribution-network analysis in a district heating system. Criteria for performance evaluations are defined. They can be used to evaluate heat supply to different points in the network, or individual system components. A case study is performed on an existing district heating system. Energetic and exergetic efficiencies of supply lines are analyzed. Exergy destructions and exergy losses are studied. Large differences in efficiency of heat supply to different points in the network are discovered. Over-dimensioned parameters of the distribution network are investigated.

We examine the impact of public policies that aim to decarbonate electricity production by replacing fossil fuel energy by intermittent renewable sources, namely wind and solar power. We consider a model of energy investment and production with two sources of energy: one is clean but intermittent (e.g. wind), whereas the other one is reliable but polluting (e.g. coal). A carbon tax decreases electricity production while simultaneously increasing investment in wind power. This tax may however increase total capacity because the retailing price of electricity does not depend on energy availability, which means that windmill capacity must be backed-up by thermal power plants. Feed-in tariffs and renewable portfolio standards enhance investment into intermittent sources of energy. However, both are likely to boost electricity production beyond the efficient level, in which case they must be complemented with a tax on electricity consumption. We also determine the social value of two technologies to accommodate intermittency: energy storage and smart meters. Lastly, we consider the case of a monopoly thermal power producer. The entry of a competitive fringe of wind power producers makes the thermal power producer reduce further its production capacity, which increases the electricity price.

The ability to predict the expected internal behaviour of a given solid-propellant rocket motor under transient conditions is important. Research towards predicting and quantifying undesirable transient axial combustion instability symptoms typically necessitates a comprehensive numerical model for internal ballistic simulation under dynamic flow and combustion conditions. On the mitigation side, one in practice sees the use of inert or reactive particles for the suppression of pressure wave development in the motor chamber flow. With the focus of the present study placed on reactive particles, a numerical internal ballistic model incorporating relevant elements, such as a transient, frequency-dependent combustion response to axial pressure wave activity above the burning propellant surface, is applied to the investigation of using aluminum particles within the central internal flow (particles whose surfaces nominally regress with time, as a function of current particle size, as they move downstream) as a means of suppressing instability-related symptoms in a cylindrical-grain motor. The results of this investigation reveal that the loading percentage and starting size of the aluminum particles have a significant influence on reducing the resulting transient pressure wave magnitude.

Este artigo aborda o desenvolvimento da agroenergia no Brasil. O foco central é o papel das políticas públicas na promoção da sustentabilidade no meio rural nas regiões Nordeste (bioma Caatinga) e Centro-Oeste (bioma Cerrado). O objetivo é destacar interações entre os fatores determinantes do desenvolvimento das políticas e a sua relação com as diretrizes e metas do Programa Nacional de Produção e uso de Biodiesel e do Plano Nacional de Agroenergia. As fragilidades destacadas se referem à baixa inserção socioeconômica na etapa agrícola, frente à dinâmica do mercado e às contradições entre oportunidades e desafios da agroenergia, no contexto da relação campo-cidade e agricultura-indústria. This article discusses the agroenergy development in Brazil. The central focus is the public policies role in promoting sustainability in the rural areas in the Northeast (Caatinga biome) and Midwest (Cerrado biome). The aim is to highlight interactions between the policy development drivers and its relationship with the directives and goals of the Brazilian Biodiesel Program and the National Agroenergy Planning. The weaknesses found in the policies relate to low socioeconomic integration in the agricultural stage, in a dynamic market and the contradictions between the opportunities and challenges of agroenergy in the context of rural-urban and agriculture-industry relationship.

The development of decentralized sources of power out of renewable sources of energies has been triggering far-reaching consequences for Distribution System Operators over the past decade in Europe. Our paper benchmarks across 23 European countries the impact of the development of renewables on the physical characteristics of power distribution networks and on their investments. It builds on a large spectrum of databases of quantitative indicators about the dynamics of installed capacity of renewable energy resources and the power generation out of them, electricity independence, quality of electricity distribution, smart grids investments, Network System Operators capital expenditures, length of the distribution networks, overall costs of power networks paid by private agents, and electricity losses, all in relation with the development of decentralized generation. The heterogeneity of these indicators across Europe appears to be wide notably because of physical constraints, historic legacies, or policy and regulatory choices. A cluster analysis allows for deriving six groups of countries that display statistically homogenous characteristics. Our results may provide decision makers and regulators with a tool helping them to concentrate on the main issues specific to their countries as compared to the European median, and to look for possible solutions in the experience of other clusters which are shown to perform better for some indicators.

The diffusion of renewable energy in the power system implies high supply variability. Lacking economically viable storage options, renewable energy integration is possible thanks to the presence of modern mid-merit fossil-based technologies, which act as back-up capacity. This paper discusses the role of modern fossil-based power generation technologies in supporting renewable energy investments. We study the deployment of these two technologies conditional on all other drivers in 26 OECD countries between 1990 and 2013. We show that moving from the first to the third quartile of the distribution of modern fossil technologies is associated with an increase in yearly renewable energy investment of between 6 and 14 kW per thousand people, on average and ceteris paribus. This is a sizeable effect, considering that average yearly renewable capacity addition in our sample are around 12 kW per thousand people. These findings are robust to different econometric specifications, various definitions of modern fossil technologies and are stronger for wind, which is more intermittent and for which the mismatch between supply and demand is more marked. Our analysis points to the substantial indirect costs of renewable energy integration and highlights the complementarity of investments in different generation technologies for a successful decarbonization process.

Available online 11 February 2019 This paper investigates the effect of energy liberalization, compared to other drivers, on policies that support renewable energy in a long panel of OECD countries. We estimate this effect by accounting for the endogeneity of liberalization related to joint decisions within a country's energy strategy. Using regulation in other industries as instruments, we find that energy liberalization increases public support for renewable energy. The effect of liberalization is the second largest after the effect of per-capita income and is mostly driven by reductions in entry barriers, while the effect of privatization is unclear. This finding suggests that a reduction in the monopolistic power of state-owned utilities has a positive effect on renewable energy policies when various types of actors are ensured access to the grid instead of it being provided to only a few large private firms.

This paper analyzes the dynamic behavior of day-ahead spot prices in the German electricity spot market due to positive structural shocks in wind and solar power. It uses a dynamic structural vector autoregressive model to estimate the related structural impulse response functions. The estimates suggest that wind power shocks have a more prolonged negative effect on spot prices than solar power shocks. Significant autocorrelations of wind power for larger lags indicate these results. The total negative merit order effect of a solar power shock is larger when using a reasonable model specification. One reason might be that solar power shocks coincide with demand peaks. However, results regarding the relation of the effects of wind and solar should be dealt with carefully because these results do not hold for all specifications. Past static estimates show differences in the total average negative merit order effects. These estimates might be overstated if wind and solar power dynamics are transferred to the merit order effects.

Governments and network utilities are grappling with how to manage increasing costs of electricity supply, the prospect of distributed generation while still meeting social objectives of access and affordability in remote areas. Due to geographical isolation and dispersed populations, remote Australian communities are generally electrified by distributed networks using diesel generation. This is expensive, environmentally damaging and fails to exploit vast renewable resources available. These communities are often regarded as “low hanging fruit” from a renewable energy deployment perspective. This paper examines why that fruit has not been readily picked in Australia in the context of a case study of three remote West Australian communities. In Western Australia, the local electricity distribution network service provider (DNSP) responsible for regional networks, developed a scheme (the Scheme) to incentivise renewable energy deployment in remote communities. This scheme aims to encourage communities to install renewable energy from the “bottom up” by providing a feed-in tariff capped at $0.50/kW h, to reduce the supply cost and environmental damage from diesel generation. However, to date there has been limited deployment of renewable energy in remote communities. The scheme and viability of renewable energy is assessed for three indigenous communities located in the Kimberley region of Western Australia. These communities are connected to isolated, diesel powered networks. Viability is assessed from the DNSP and community perspectives and incorporates quantitative and qualitative financial, social / human and institutional factors. Renewable energy deployment is found to benefit the DNSP and can also benefit communities subject to their cost of capital and to the imposition of connection charges. However a range of barriers are currently frustrating deployment and a dynamic and adaptive approach that recognises local challenges and provides the communities with a pathway to installation is needed.

The state of Bihar in India has approximately 75 million people with no access to electricity. The government of India has pursued a policy of rural electrification through the provision of centralised coal-fired power which has been unable to resolve the low levels of electrification. Coal supply woes in India have led Indian companies to pursue new coal mines in Australia’s Galilee Basin. The costs of these mining ventures will be high due to the mining infrastructure required and long transport distances to rural India. A high level analysis of mining, transport and power station investment to meet rural demand in Bihar shows that the absolute investment requirement using coal, especially coal sourced from Australia, as an expensive option. Pursuing electrification through village level, renewable energy micro-systems requires lower financing and provides more flexibility. Pollution costs associated with coal-fired generation, employment benefits associated with many village implementations and a rural load unsupported by industry load, show the benefit associated with decentralised, renewable energy electrification.

One of the consequences of rapid economic growth and industrialization in the developing world has been deterioration in environmental conditions and air quality. While air pollution is a serious threat to health in most developing countries, environmental regulations are rare and the determination to address the problem is weak due to ongoing pressures to sustain robust economic growth. Under these constraints, natural gas, as a clean, abundant, and highly-efficient source of energy, has emerged as an increasingly attractive source of fuel, which could address some of the environmental and health challenges faced by these countries without undermining their economies. In this paper, we examine the impact of air pollution on infant mortality in Turkey using variation across provinces and over time in the adoption of natural gas as a cleaner fuel. Our results indicate that the expansion of natural gas infrastructure has caused a significant decrease in the rate of infant mortality in Turkey. In particular, a one-percentage point increase in the rate of subscriptions to natural gas services would cause the infant mortality rate to decline by 4 percent, which could result in 348 infant lives saved in 2011 alone. These results are robust to a large number of specifications. Finally, we use supplemental data on total particulate matter and sulfur dioxide to produce direct estimates of the effects of these pollutants on infant mortality using natural gas expansion as an instrument. Our elasticity estimates from the instrumental variable analysis are 1.25 for particulate matter and 0.63 for sulfur dioxide.

This paper reports on a cost-effectiveness analysis of four types of water heating systems operating in a situation where there is an unreliable water supply. These systems are electric water heating, a solar water heating system (SWHS) with electricity back-up, the SWHS with an LPG water heater, and an LPG water heater alone. It is found that in the conditions of North Cyprus, an SWHS with an LPG heater back-up is the most cost-effective, most convenient and most environmentally friendly system. The last two systems all have a cost per m 3 of hot water that is approximately 50% of the cost of heating water by electricity. This study finds that in situations where there is a winter or cloudy season, the choice of the source of energy for SWHS׳s back-up during this period is critical for its overall cost-effectiveness. When a pressurized supply of water is available, the cost of heating water is reduced by 20% for the SWHS with LPG back-up and for the heating of water by the LPG heater alone.

The energy transition from fossil fuels to alternative energy sources has important consequences for technological change and resource extraction. We examine these consequences by incorporating a nonrenewable resource and an alternative energy source in a market economy model of endogenous growth through expanding varieties. During the energy transition, technological progress is nonmonotonic over time: It declines initially, starts increasing when the economy approaches the regime shift, and jumps down once the resource stock is exhausted. A moment of peak-oil does no longer necessarily occur, and simultaneous use of the resource and the alternative energy source will take place if the return to innovation becomes too low. Subsidies to research and development (R&D) and to renewables production speed up the energy transition, whereas a tax on fossil fuels postpones the switch to renewable energy.

This paper analyzes the effect of environmental policies on the direction of energy innovation across countries over the period 1990-2012. Our novelty is to use threshold regression models to allow for discontinuities in policy effectiveness depending on a country's relative competencies in renewable and fossil fuel technologies. We show that the dynamic incentives of environmental policies become effective just above the median level of relative competencies. In this critical second regime, market-based policies are moderately effective in promoting renewable innovation, while commandand-control policies depress fossil based innovation. Finally, market-based policies are more effective to consolidate a green comparative advantage in the last regime. We illustrate how our approach can be used for policy design in laggard countries.

International audience; This paper studies the links between non-renewable and intermittent renewable energy sources in the production of electricity. Using U.S. state-level data from 1998 to 2015, we find that the relationship between the price of natural gas and investments in solar and wind capacity is non-linear and can be represented by an inverted U shape. Hence, for relatively low natural gas prices, the two modes of production are substitutes. After a price threshold is reached, the two are complementary. A theoretical explanation argues that this stylized fact is the result of a trade-off between two characteristics of these modes of production: the high degree of flexibility of electricity production using natural gas as an input and the low marginal cost of renewable energy sources.

"In light of Germany´s transition approaches towards a sustainable energy system this paper examines differences of employment structure and wage differentials between renewable energy establishments and their sector peers. To do so, we have developed a novel data set by linking company-level information from the German Renewable Energy Federation with establishment-level data of the IAB Establishment History Panel. According to our descriptive evidence, there are significant differences in wages and in several other characteristics. Looking at the top-four renewable energy sectors, our estimates show that human capital and other establishment- level characteristics mostly explain the wage differential among manufacturers and energy providers. However, we find a persistent 'renewable energy wage premium' of more than ten percent in the construction installation activities and the architectural and engineering services. We interpret this premium as a positive indirect effect of the promotion of renewable energies for the benefit of employees in renewable energy establishments within these two sectors." (Author's abstract, IAB-Doku) ((en)) Additional Information deutsche Kurzfassung

While wind energy production is relatively free from environmental externalities such as air pollution, it is frequently considered to negatively impact landscapes' visual aesthetic values, thereby inducing negative effects on tourism demand. Existing evidence for Germany indeed points towards a negative relationship between tourism demand and wind turbine construction. However, the existing studies primarily rely on interview data and simple bivariate statistics. In contrast, we make use of secondary statistics on tourism and wind turbine locations at the level of German municipalities. Using spatial panel regression techniques, we confirm a negative relation between wind turbines around municipalities and tourism demand for municipalities not located near the coast. In the latter regions, the relation between wind turbines and tourism demand is more complex.

To meet the increasing global demand for renewable energy, such as wind energy, an increasing number of wind parks are being constructed worldwide. Finding a suitable location requires a detailed and often costly analysis of local wind conditions. Plain average wind speed maps cannot provide a precise forecast of wind power because of the non-linear relationship between wind speed and production. We suggest a new approach to assess the local wind energy potential. First, meteorological reanalysis data are applied to obtain long-term low-scale wind speed data at specific turbine locations and hub heights. Second, the relation between wind data and energy production is determined via a five parameter logistic function using actual high-frequency energy production data. The resulting wind energy index allows for a turbine-specific estimation of the expected wind power at an unobserved location. A map of the wind power potential for Germany exemplifies our approach.

This article examines the efficiency of wind energy production. Using non-convex efficiency analysis, we quantify production losses for 19 wind turbines in four wind parks across Germany. In a second stage regression, we adapt the linear regression results of Kneip, Simar, and Wilson (2015) to explain electricity losses by means of a bias-corrected truncated regression analysis. The results show that electricity losses amount to 27% of the maximal producible electricity. Most of these losses are from changing wind conditions, while 6% are from turbine errors.

As rice husk is abundantly natural resource in Thailand, it has been used as the biomass energy resource in the stream turbine power plants, in particular to very small power producers (VSPPs). The VSPPs’ plants produced by rice husk is generally found in many regions of Thailand, however its performance efficiency and optimization has never been assessed at any level. This study aimed to fulfill this gap by adopting the method of data envelopment analysis (DEA) to relatively measure the performance efficiency of the decision making units, as well as to adjust input surpluses found in order to maximize the overall efficiency scores. The secondary data recorded in 2012 were collected from the power policy bureau of Thailand and Energy for Environment Foundation, totally 47 rice husk steam turbine power plants. The empirical results showed that a constant return to scale-DEA and variable return to scale-DEA model performed efficiency scores at 0.874 and 0.882, respectively. The input surpluses of capacity and purchasing cost of rice husk were emphasized to increase its unit efficiency. Achieving the Thai government’s aim of sustainable, renewable energy would boost up many utility plants to use rice husk for electricity generation in the nearer future.

Energy sectors of most industrialized countries are marked by a long history of state and corporate-owned and highly centralized energy generation (mostly from fossil-based sources) and distribution. Although technological developments and pressures from social/ecological movements resulted in an increased uptake of renewable energy (RE) technologies since the early 1990s, the application of these technologies have since predominantly taken place through largescale projects owned by corporate actors. In response, an increasing number of individuals and community groups have been forming renewable energy cooperatives (RE co-ops) in recent years to provide bottom-up and collective solutions to their local needs and global environmental issues. The goal of this literature review is to summarize the demonstrated impacts of RE co-ops in the economic, social and environmental realms. Thereby, their impact on community development and role in accelerating the transition towards a sustainable energy sector is assessed. Findings of this review show that successful RE co-ops generated positive outcomes for their members and the wider community while accelerating the social and perceptual dimensions of the global energy transition. However, it has also been revealed that RE co-ops’ success in generating positive impacts is often limited by various community-specific factors and by financial and perceptual barriers to their emergence and development.

The countries of the Gulf Cooperation Council (GCC) have both large fossil fuel resources and vast renewable energy potentials. Here, we investigate in a literature meta-analysis and a survey, whether there is a need for renewables in the GCC, what barriers and risks presently deter investments, and what possible policy-solutions could be. We find that there is a long-term need for renewables, to diversify the economy and prepare for a post-fossil fuel era. In the short term, two main obstacles deter investments: inefficient bureaucracy, and the combination of fossil fuel/electricity subsidies and the absence of renewable energy support. Removing fossil fuel and consumption subsidies or introducing a support scheme could make investments in renewables profitable. Eliminating energy subsidies appears particularly beneficial to the economic outlook but this seems particularly difficult to implement, due to the political economy of rentier states. Increased bureaucratic transparency and efficiency is needed, so that potentially attractive investments can rapidly and predictably obtain the necessary permissions. Hence, the administrative and economic environment for renewable energy investments in the GCC is not right today, and no breakthrough is on the horizon, but there is a range of policy solutions to enable investments in the future., Energies, 8 (8), ISSN:1996-1073

This research is aligned with the engineering challenge of scaling-up individual battery cells into a complete energy storage system (ESS). Manufacturing tolerances, coupled with thermal gradients and the differential electrical loading of adjacent cells, can result in significant variations in the rate of cell degradation, energy distribution and ESS performance. The uncertain transition from cell to system often manifests itself in over-engineered, non-optimal ESS designs within both the transport and energy sectors. To alleviate these issues, the authors propose a novel model-based framework for cell-in-the-loop simulation (CILS) in which a physical cell may be integrated within a complete model of an ESS and exercised against realistic electrical and thermal loads in real-time. This paper focuses on the electrical integration of both real and simulated cells within the CILS test environment. Validation of the CILS approach using real-world electric vehicle data is presented for an 18650 cell. The cell is integrated within a real-time simulation model of a series string of similar cells in a 4sp1 configuration. Results are presented that highlight the impact of cell variability ( i.e. , capacity and impedance) on the energy available from the multi-cell system and the useable capacity of the physical cell.

The enzyme-assisted aqueous extraction of oil from wet microalgae was employed to avoid the energy consumption of a dewatering process. In this paper, oil-rich microalgae Scenedesmus sp. G4 was hydrolyzed by enzyme mixtures for oil extraction. The results showed that the algae concentration had the greatest influence on yield of extracted oil, and the temperature and the ratio of enzyme mixtures affected the results as follows: the maximum yield of oil extracted from Scenedesmus sp. G4 reached 86.1% under optimal conditions with an algae concentration at 2.5 g/L, temperature 30/50 °C, pH 3.5/4.5 and a cellulase:pectinase:hemicellulase ratio of 1:1:1 or 1:2:1 (w/w/w). The results also indicated that the enzyme mixtures had a significant impact on the integrity of microalgae cells and the crystallization index increased from 30.7% to around 36.0% after enzymatic hydrolysis treatment. The cell wall of Scenedesmus sp. G4 has a high content of cellulose Iα and low crystallization, which is beneficial to the oil extraction by the enzyme-assisted hydrolysis method.

This article examines developments in the renewable electricity sector in Brazil and China since 2000. The two countries share many interests with respect to solar and wind power, but institutional differences in state–business relations led to different outcomes. In China, in a context of corporatist state–business relations, state interventions were more far-reaching, with the state coordinating with state-owned banks, offering large financial and investment incentives to state-owned or state-connected enterprises. By contrast, in Brazil’s public–private partnerships, state support to promote renewable energies was shaped by a stronger preference for competitive auctions and stricter financing rules. The differences in state–business relations help explain the observed developmental trajectories in wind and solar power.

This study was conducted to develop an artificial neural network (ANN)-based prediction model that can calculate the amount of cooling energy during the setback period of accommodation buildings. By comparing the amount of energy needed for diverse setback temperatures, the most energy-efficient optimal setback temperature could be found and applied in the thermal control logic. Three major processes that used the numerical simulation method were conducted for the development and optimization of an ANN model and for the testing of its prediction performance, respectively. First, the structure and learning method of the initial ANN model was determined to predict the amount of cooling energy consumption during the setback period. Then, the initial structure and learning methods of the ANN model were optimized using parametrical analysis to compare its prediction accuracy levels. Finally, the performance tests of the optimized model proved its prediction accuracy with the lower coefficient of variation of the root mean square errors (CVRMSEs) of the simulated results and the predicted results under generally accepted levels. In conclusion, the proposed ANN model proved its potential to be applied to the thermal control logic for setting up the most energy-efficient setback temperature.

Exploiting variation in the hourly production from wind turbines, this paper quantifies the heterogeneity in the marginal impact of renewable electricity on pollution. The results reveal that output from competing renewable capacity additions—e.g., wind turbines versus solar panels—provide different marginal external benefits. This finding suggests that, if governments continue to subsidize renewables, an emphasis should be placed on designing policies that internalize the heterogeneous benefits. More generally, my results highlight that, by incorrectly assuming renewable electricity is a homogenous good, we will understate the relative efficiency of the first-best pollution prices. (JEL L94, L98, Q42, Q48, Q51, Q53, Q58)

Energy storage devices are expected to be more frequently implemented in wind farms in near future. In this paper, both pumped hydro and fly wheel storage systems are used to assist a wind farm to smooth the power fluctuations. Due to the significant difference in the response speeds of the two storages types, the wind farm coordination with two types of energy storage is a problem. This paper presents two methods for the coordination problem: a two-level hierarchical model predictive control (MPC) method and a single-level MPC method. In the single-level MPC method, only one MPC controller coordinates the wind farm and the two storage systems to follow the grid scheduling. Alternatively, in the two-level MPC method, two MPC controllers are used to coordinate the wind farm and the two storage systems. The structure of two level MPC consists of outer level and inner level MPC. They run alternatively to perform real-time scheduling and then stop, thus obtaining long-term scheduling results and sending some results to the inner level as input. The single-level MPC method performs both long- and short-term scheduling tasks in each interval. The simulation results show that the methods proposed can improve the utilization of wind power and reduce wind power spillage. In addition, the single-level MPC and the two-level MPC are not interchangeable. The single-level MPC has the advantage of following the grid schedule while the two-level MPC can reduce the optimization time by 60%.

In the context of sustainable buildings, this paper investigates power flow management for an isolated DC microgrid and focuses on efficiency and energy cost reduction by optimal scheduling. Aiming at high efficiency, the local produced power has to be used where, when, and how it is generated. Thus, based on photovoltaic sources, storage, and a biofuel generator, the proposed DC microgrid is coupled with the DC distribution network of the building. The DC bus distribution maximizes the efficiency of the overall production-consumption system by avoiding some energy conversion losses and absence of reactive power. The isolated DC microgrid aims to minimize the total energy cost and thus, based on forecasting data, a cost function is formulated. Using a mixed integer linear programming optimization, the optimal power flow scheduling is obtained which leads to an optimization-based strategy for real-time power balancing. Three experimental tests, operated under different meteorological conditions, validate the feasibility of the proposed control and demonstrate the problem formulation of minimizing total energy cost.

This paper considers the problem of distributed frequency regulation based on the consensus control protocol in smart grids. In this problem, each system component is coordinated to collectively provide active power for the provision of ancillary frequency regulation service. Firstly, an approximate model is proposed for the frequency dynamic process. A distributed control algorithm is investigated, while each agent exchanges information with neighboring agents and performs behaviors based on communication interactions. The objective of each agent is to converge to a common state considering different dynamic load characteristics, and distributed frequency control strategy is developed to enable the agents to provide active power support. Then, the distributed proportional integral controllers with the state feedback are designed considering the consensus protocol with topology . The theory of distributed consensus protocol isfurther developed to prove the stability of the proposed control algorithm. Whenproperly controlled, the controllers can provide grid support services in a distributed manner that turn out the grid balanced globally. Finally, simulations of the proposed distributed control algorithm are tested to validate the availability of the proposed approach and the performance in the electrical networks.

With the increasing popularity enjoyed by ultra-micro scale turbomachinery, designers are often faced with severe challenges due to the substantial phenomenological difference between the low-Reynolds fluid-dynamics in rotating or strongly curved flows and the established knowledge acquired through decades of theoretical and experimental studies on medium and large-scale machines. The problem is complicated by the absence of an extended and reliable database that might be used for preliminary design and provide indications for scale-up or scale-down. As a result, custom-designed experimental campaigns are necessary that make the development of any new machine exceedingly costly. The situation has seen some improvement in recent years, after the publication of a sufficient number of experimental results and numerical simulations that pave the way towards a development of semi-empirical correlations. The purpose of this work is to present and discuss a preliminary and simple method to extend the currently available design maps into the small scale range (Re &lt, 105) by introducing in the Balje charts an efficiency correction that depends on the specific speed ns. The method results in a Stodola-like formula which originates a lower-than-standard Cordier curve on the classical Balje charts. A validation with some experimental results is also presented and discussed. Though the agreement is more than satisfactory, it must be stressed that the method provides only approximate results, and thus it must be considered as an evolving temporary solution, that needs to be updated as long as larger series of (numerical or physical) experimental results become available.

In this paper, we present the design and evaluation of a software-based wireless power transfer platform that enables the development of a prototype involving various open- and closed-loop power control functions. Our platform is based on a loosely coupled planar wireless power transfer circuit that uses a class-E power amplifier. In conjunction with this circuit, we implement flexible control functions using a National Instruments Data Acquisition (NI DAQ) board and algorithms in the MATLAB/Simulink. To verify the effectiveness of our platform, we conduct two types of power-control experiments: a no-load or metal detection using open-loop power control, and an output voltage regulation for different receiver positions using closed-loop power control. The use of the MATLAB/Simulink software as a part of the planar wireless power transfer platform for power control experiments is shown to serve as a useful and inexpensive alternative to conventional hardware-based platforms.

Inverter voltage control is an important task in the operation of a DC/AC microgrid system. To improve the inverter voltage control dynamics, traditional approaches attempt to measure and feedforward the load current, which, however, needs remote measurement with communications in a microgrid system with distributed loads. In this paper, a load current observer (LCO) based control strategy, which does not need remote measurement, is proposed for sinusoidal signals tracking control of a three-phase inverter of the microgrid. With LCO, the load current is estimated precisely, acting as the feedforward of the dual-loop control, which can effectively enlarge the stability margin of the control system and improve the dynamic response to load disturbance. Furthermore, multiple PR regulators are applied in this strategy conducted in a stationary frame to suppress the transient fluctuations and the total harmonic distortion (THD) of the output voltage and achieve faster transient performance compared with traditional dual-loop control in a rotating dq0 frame under instantaneous change of various types of load (i.e., balanced load, unbalanced load, and nonlinear load). The parameters of multiple PR regulators are analyzed and selected through the root locus method and the stability of the whole control system is evaluated and analyzed. Finally, the validity of the proposed approach is verified through simulations and a three-phase prototype test system with a TMS320F28335 DSP.

A linear function submission-based double auction (LFS-DA) mechanism for a regional electricity network is proposed in this paper. Each agent in the network is equipped with a battery and a generator. Each agent simultaneously becomes a producer and consumer of electricity, i.e., a prosumer, and trades electricity in the regional market at a variable price. In the LFS-DA, each agent uses linear demand and supply functions when they submit bids and asks to an auctioneer in the regional market. The LFS-DA can achieve an exact balance between electricity demand and supply for each time slot throughout the learning phase and was shown capable of solving the primal problem of maximizing the social welfare of the network without any central price setter, e.g., a utility or a large electricity company, in contrast with conventional real-time pricing (RTP). This paper presents a clarification of the relationship between the RTP algorithm derived on the basis of a dual decomposition framework and LFS-DA. Specifically, we proved that the changes in the price profile of the LFS-DA mechanism are equal to those achieved by the RTP mechanism derived from the dual decomposition framework, except for a constant factor.

In this study we design and test a novel solar tracking generation system. Moreover, we show that this system could be successfully used as an advanced solar power source to generate power in greenhouses. The system was developed after taking into consideration the geography, climate, and other environmental factors of northeast China. The experimental design of this study included the following steps: (i) the novel solar tracking generation system was measured, and its performance was analyzed, (ii) the system configuration and operation principles were evaluated, (iii) the performance of this power generation system and the solar irradiance were measured according to local time and conditions, (iv) the main factors affecting system performance were analyzed, and (v) the amount of power generated by the solar tracking system was compared with the power generated by fixed solar panels. The experimental results indicated that compared to the power generated by fixed solar panels, the solar tracking system generated about 20% to 25% more power. In addition, the performance of this novel power generating system was found to be closely associated with solar irradiance. Therefore, the solar tracking system provides a new approach to power generation in greenhouses.

Biodiesel as a clean energy source could reduce environmental pollution compared to fossil fuel, so it is becoming increasingly important. In this study, we investigated the effects of different pilot injection timings from before top dead center (BTDC) and exhaust gas recirculation (EGR) on combustion, engine performance, and exhaust emission characteristics in a common rail diesel engine fueled with canola oil biodiesel-diesel (BD) blend. The pilot injection timing and EGR rate were changed at an engine speed of 2000 rpm fueled with BD20 (20 vol % canola oil and 80 vol % diesel fuel blend). As the injection timing advanced, the combustion pressure, brake specific fuel consumption (BSFC), and peak combustion pressure (P max ) changed slightly. Carbon monoxide (CO) and particulate matter (PM) emissions clearly decreased at BTDC 20° compared with BTDC 5°, but nitrogen oxide (NO x ) emissions increased slightly. With an increasing EGR rate, the combustion pressure and indicated mean effective pressure (IMEP) decreased slightly at BTDC 20° compared to other injection timings. However, the P max showed a remarkable decrease. The BSFC and PM emissions increased slightly, but the NO x emission decreased considerably.

Household energy consumption has been increasing in the last decades, the residential sector is responsible for about 40% of the total final energy use in Europe. Energy efficiency measures can both reduce energy needs of buildings and energy-related CO2 emissions. For this reason, in recent years, the European Union has been making efforts to enhance energy saving in buildings by introducing various policies and strategies, in this context, a common methodology was developed to assess and to certify energy performance of buildings. The positive effects obtained by energy efficiency measures need to be verified, but measuring and monitoring building energy performance is time consuming and financially demanding. Alternatively, energy efficiency can also be evaluated by specific indicators based on energy consumption. In this work, a methodology to investigate the level of energy efficiency reached in the Umbria Region (Central Italy) is described, based on data collected by energy certificates. In fact, energy certificates, which are the outcomes of simulation models, represent a useful and available tool to collect data related to the energy use of dwellings. A database of building energy performance was developed, in which about 6500 energy certificates of residential buildings supplied by Umbria region were inserted. On the basis of this data collection, average energy and CO2 indicators related to the building heritage in Umbria were estimated and compared to national and international indicators derived from official sources. Results showed that the adopted methodology in this work can be an alternative method for the evaluation of energy indicators, in fact, the ones calculated considering simulation data were similar to the ones reported in national and international sources. This allowed to validate the adopted methodology and the efficiency of European policies.

This paper presents a reinforcement learning (RL)–based energy management strategy for a hybrid electric tracked vehicle. A control-oriented model of the powertrain and vehicle dynamics is first established. According to the sample information of the experimental driving schedule, statistical characteristics at various velocities are determined by extracting the transition probability matrix of the power request. Two RL-based algorithms, namely Q-learning and Dyna algorithms, are applied to generate optimal control solutions. The two algorithms are simulated on the same driving schedule, and the simulation results are compared to clarify the merits and demerits of these algorithms. Although the Q-learning algorithm is faster (3 h) than the Dyna algorithm (7 h), its fuel consumption is 1.7% higher than that of the Dyna algorithm. Furthermore, the Dyna algorithm registers approximately the same fuel consumption as the dynamic programming–based global optimal solution. The computational cost of the Dyna algorithm is substantially lower than that of the stochastic dynamic programming.

Fiber-optic daylighting systems have been shown to be a promising and effective way to transmit sunlight in the interior space whilst reducing electric lighting energy consumption. To increase efficiency in terms of providing uniform illumination in the interior, the current need is to illuminate optical fiber-bundle with uniform light flux. To this end, we propose a method for achieving collimated light, which illuminates the fiber-bundle uniformly. Light is collected through a parabolic concentrator and focused toward a collimating lens, which distributes the light over each optical fiber. An optics diffusing structure is utilized at the end side of the fiber bundle to spread light in the interior. The results clearly reveal that the efficiency in terms of uniform illumination, which also reduces the heat problem for optical fibers, is improved. Furthermore, a comparison study is conducted between current and previous approaches. As a result, the proposed daylighting system turns out convenient in terms of energy saving and reduction in greenhouse gas emissions.

Greenhouse gas emissions in China have been increasing in line with its energy consumption and economic growth. Major means for energy-related greenhouse gases mitigation in the foreseeable future are transition to less carbon intensive energy supplies and structural changes in energy consumption. In this paper, a bottom-up model is built to examine typical projected scenarios for energy supply and demand, with which trends of energy-related carbon dioxide emissions by 2050 can be analyzed. Results show that low-carbon technologies remain essential contributors to reducing emissions and altering emissions trends up to 2050. By pushing the limit of current practicality, emissions reduction can reach 20 to 28 percent and the advent of carbon peaking could shift from 2040 to 2030. In addition, the effect of electrification at end-use sectors is studied. Results show that electrifying transport could reduce emissions and bring the advent of carbon peaking forward, but the effect is less significant compared with low-carbon technologies. Moreover, it implies the importance of decarbonizing power supply before electrifying end-use sectors.

Densified Biomass Solid Fuel (DBSF) is a typical solid form of biomass, using agricultural and forestry residues as raw materials. DBSF utilization is considered to be an alternative to fossil energy, like coal in China, associated with a reduction of environmental pollution. China has abundant biomass resources and is suitable to develop DBSF. Until now, a number of policies aimed at fostering DBSF industry have been proliferated by policy makers in China. However, considering the seasonality and instability of biomass resources, these inefficiencies could trigger future scarcities of biomass feedstocks, baffling the resilience of biomass supply chains. Therefore, this review paper focuses on DBSF policies and strategies in China, based on the supply chain framework. We analyzed the current developing situation of DBSF industry in China and developed a framework for policy instruments based on the supply chain steps, which can be used to identify and assess the deficiencies of current DBSF industry policies, and we proposed some suggestions. These findings may inform policy development and identify synergies at different steps in the supply chain to enhance the development of DBSF industry.

The location of ground faults in railway electric lines in 2 × 5 kV railway power supply systems is a difficult task. In both 1 × 25 kV and transmission power systems it is common practice to use distance protection relays to clear ground faults and localize their positions. However, in the particular case of this 2 × 25 kV system, due to the widespread use of autotransformers, the relation between the distance and the impedance seen by the distance protection relays is not linear and therefore the location is not accurate enough. This paper presents a simple and economical method to identify the subsection between autotransformers and the conductor (catenary or feeder) where the ground fault is happening. This method is based on the comparison of the angle between the current and the voltage of the positive terminal in each autotransformer. Consequently, after the identification of the subsection and the conductor with the ground defect, only the subsection where the ground fault is present will be quickly removed from service, with the minimum effect on rail traffic. This method has been validated through computer simulations and laboratory tests with positive results.

The main objective of this study is to discuss the economical and the environmental analysis of a net zero energy (NZE) tourist village in Alexandria, Egypt, by maximizing the renewable energy fraction and minimizing the greenhouse gases (GHG) emissions. The hybrid photovoltaics (PV)/wind/diesel/battery system is found to be the optimum hybrid renewable energy system (HRES) for the proposed tourist village under the study. The optimum HRES consists of 1600 kW of PV panels (58.09% solar energy penetration), 1000 kW of wind turbines (41.34% wind energy penetration), 1000 kW of power converters, 200 kW diesel generator (only 0.57% diesel generator penetration) in addition to 2000 batteries with the capacity of 589 Ah each. The levelized cost of energy (COE) from the optimum HRES is $0.17/kWh and the total net present cost (NPC) of this system is $15,383,360. Additionally, the maximum renewable energy fraction is 99.1% and the amount of GHG emitted from the optimum HRES is only 31,289 kg/year, which is negligible in comparison with the other system configurations, therefore the optimum HRES can be considered as a green system. In addition to this, the achieved percentage of the capacity shortage and the unmet load in the optimal HRES is only 0% for both.

This paper presents a novel staggered-teeth cylindrical transverse-flux permanent-magnet linear machine (TFPMLM), which aims to improve the power factor and force density. Due to the compact structure and high performance requirement, thermal problems should be seriously considered. The three-dimensional (3-D) temperature field model is established. The determination of convection heat transfer coefficients is discussed. Equivalent thermal conductivities of stator core and winding are given to simplify the analysis. With the thermal effect of the adhesive coatings among permanent magnets (PMs) and mover yoke taken into account, the temperature field distribution and variation rules of the TFPMLM are obtained using the finite volume method (FVM). The influences of slot filling factor and air flow velocity on the temperature field distribution are analyzed. It is found that the hottest spot of the TFPMLM appears in the middle of the end winding, and there is no risk of demagnetization for PMs.

The paper discusses Home Area Networks (HAN) communication technologies for smart home and domestic application integration. The work is initiated by identifying the application areas that can benefit from this integration. A broad and inclusive home communication interface is analysed utilizing as a key piece a Gateway based on machine-to-machine (M2M) communications that interacts with the surrounding environment. Then, the main wireless networks are thoroughly assessed, and later, their suitability to the requirements of HAN considering the application area is analysed. Finally, a qualitative analysis is portrayed.

In recent years, the accumulated environmental problems resulting from excessive usage of fossil fuels have gradually loomed. Thus, an environmental tax, as an important policy tool, has been put on the agenda in China. In this paper, a dynamic recursive multi-sector Computable General Equilibrium (CGE) model is applied to explore the impacts of the environmental tax on China’s economy. To comprehensively analyze the impacts, we introduce four kinds of typical contaminants and set two kinds of scenarios: different tax rates and different tax refunds. The results show that the environmental tax is conducive to environmental improvement, but the economic variables are adversely affected, for example, the loss of GDP at the low level tax rate is 0.46%. In order to offset the negative impacts, we presume the government refunds the tax. The results show that this can indeed relieve the negative effects. When the government refunds the production tax and corporate income tax, 0.49% and 0.34% of GDP is relieved by respectively. This paper provides a comprehensive analysis of the implementation of the environmental tax in China and lays a solid foundation for the introduction of the environmental tax.

In order to solve environmental problems such as global warming and resource depletion in the construction industry, interest in new renewable energy (NRE) systems has increased. The ground source heat pump (GSHP) system is the most efficient system among NRE systems. However, since the initial investment cost of the GSHP is quite expensive, a feasibility study needs to be conducted from the life-cycle perspective. Meanwhile, the efficiency of GSHP depends most significantly on the entering water temperature (EWT) of the ground heat exchanger (GHE). Therefore, this study aims to assess the environmental and economic effects of the use of GHE for selecting the optimal GHE. This study was conducted in three steps: (i) establishing the basic information and selecting key factors affecting GHE performances, (ii) making possible alternatives of the GHE installation by considering EWT, and (iii) using life-cycle assessment and life-cycle cost, as well as comprehensive evaluation of the environmental and economic effects on the GHE. These techniques allow for easy and accurate determination of the optimal design of the GHE from the environmental and economic effects in the early design phase. In future research, a multi-objective decision support model for the GSHP will be developed.

Hydrothermal liquefaction (HTL) presents a viable route for converting a vast range of materials into liquid fuel, without the need for pre-drying. Currently, HTL studies produce bio-crude with properties that fall short of diesel or biodiesel standards. Upgrading bio-crude improves the physical and chemical properties to produce a fuel corresponding to diesel or biodiesel. Properties such as viscosity, density, heating value, oxygen, nitrogen and sulphur content, and chemical composition can be modified towards meeting fuel standards using strategies such as solvent extraction, distillation, hydrodeoxygenation and catalytic cracking. This article presents a review of the upgrading technologies available, and how they might be used to make HTL bio-crude into a transportation fuel that meets current fuel property standards.

Wave energy is one of the most promising alternatives to fossil fuels due to the enormous available resource; however, its development may be slowed as it is often regarded as uneconomical. The largest cost reductions are expected to be obtained through economies of scale and technological progress. In this sense, the incorporation of wave energy systems into offshore wind energy farms is an opportunity to foster the development of wave energy. The synergies between both renewables can be realised through these co-located energy farms and, thus, some challenges of offshore wind energy can be met. Among them, this paper focuses on the longer non-operational periods of offshore wind turbines—relative to their onshore counterparts—typically caused by delays in maintenance due to the harsh marine conditions. Co-located wave energy converters would act as a barrier extracting energy from the waves and resulting in a shielding effect over the wind farm. On this basis, the aim of this paper is to analyse wave energy economics in a holistic way, as well as the synergies between wave and offshore wind energy, focusing on the shadow effect and the associated increase in the accessibility to the wind turbines.