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Electric vehicles (EVs) are considered a substitute for fossil-fueled vehicles due to rising fossil fuel prices and accompanying environmental concerns, and their use is predicted to increase dramatically shortly. However, the widespread use of EVs and their large-scale integration into the energy system will present several operational and technological hurdles. In the energy industry, an innovative solution known as the EVs smart parking lot (SPL) is introduced to handle EV charging and discharging electricity and energy supply challenges. This paper investigates social equity access and mobile charging stations (MCSs) for EVs, where the owner of MCSs is the EV parking lot. Accordingly, a new self-scheduling model for SPLs is presented in this paper that incorporates scheduling of the MCSs as temporary charging infrastructures while considering social equity access and optimizes SPL energy generation and storage schedule. The main objectives of this research are to (i) develop MCSs accessibility measures and quantify the equity impacts of MCSs locations by modeling prioritized demand based on several indices; (ii) determine the optimal set-points of SPL components (i.e., combined heat and power (CHP), photovoltaic system, electrical and heat-energy storage, and MCSs) to manage electrical peak demand and to maximize the economic benefits of SPLs. Results indicate that the proposed demand prioritization function model can meet the required EV charging demands for prioritized events, and the self-scheduling model for SPLs satisfies the charging demand of the EVs in the SPL location. Also, the social equity access to the EV charging stations is satisfied by analyzing the operation of MCSs around the prioritized demand of the prioritized events and social equity access indices.

Abstract The implementation of energy efficiency measures is an effective way to gain energy savings in the Italian residential sector. This paper assesses the embodied energy impact related to the envelope insulation and evaluates the energy and carbon payback of the efficiency measures. The proposed method consists of (1) an estimation of the baseline operational energy consumption, (2) simulations of realistic retrofit solutions and, (3) the assessment of the ‘retrofitting’ embodied energy and the energy and carbon payback time calculation. The payback is based on the comparison between the saved operational energy and the embodied energy of the materials selected for insulation. Ten Italian cities are analysed, and the results show a deep dependence on the climate zone. In Northern Italian cities, envelope insulation gains relevance as the energy and carbon payback periods are shorter, about 3 years against the 84 years for the Southern city of Palermo. The optimal thickness is estimated for the city of Milan considering the building’s typology, the insulation materials, and the energy payback. This study shows how the total energy savings can be used as a criterion to obtain design indications.

Residential energy consumption in China increased dramatically over the period of 2002-2010. In this paper, we undertake a decomposition analysis of changes in energy use by Chinese households for five energy-using activities: space heating/cooling, cooking, lighting and electric appliances. We investigate to what extent changes in energy use are due to changes from appliances and to change in floor space, population and energy mix. Our decomposition analysis is based on the logarithmic mean Divisia index technique using data from the China statistical yearbook and China energy statistical yearbook in the period of 2002-2010. According to our results, the increase in energy-using appliances is the biggest contributor to the increase of residential energy consumption during 2002-2010 but the effect declines over time, due to energy efficiency improvements in those appliances. The second most important contributor is floor space per capita, which increased with 28%. Of the four factors, population is the most stable factor and energy mix is the least important factor. We predicted electricity use, with the help of regression-based predictions for ownership of appliances and the energy efficiency of appliances. We found that electricity use will continue to rise despite a gradual saturation of demand

Abstract Vinasse is a residue from bioethanol production that is produced in large quantities in Brazil and Europe and is applied to fields as a source of plant nutrients (fertirrigation). A side effect of this use is greenhouse gas (GHG) emissions during storage and transport in open channels to fields, and from fertirrigated soils. This study assessed GHG emissions in experiments simulating this vinasse management system, and the potential for reducing emissions of methane (CH4) and nitrous oxide (N2O) from vinasse via anaerobic digestion (AD) in biogas plants. During 21 days’ storage of untreated vinasse, 29% of dry matter (DM) and 40% of volatile solids (VS) were lost, which resulted in cumulative CH4 emissions of up to 43.8 kg CO2eq kg−1 C-vinasse. In contrast, there were no CH4 emissions from AD-treated vinasse (digestate) during storage. GHG emission was related to the biochemical characteristics of the untreated and digested vinasse. The accumulation of oxidised nitrogen (N) compounds was up to four-fold higher in soil amended with untreated vinasse than from digestate-amended soil. The N2O emissions from soil amended with untreated vinasse were also higher than from soil amended with digestate, ranging from 0.173 to 0.193 kg CO2eq m−2 in the former and from 0.045 to 0.100 kg CO2eq m−2 in the latter. Extrapolation of the results to a Brazilian case indicated that AD treatment prior to storage/transport and field application could reduce GHG emissions from the vinasse management chain by at least 48%, with further reductions from the use of biogas in power production.

Artículos en revistas Energy, and particularly electricity, has played and will continue to play a very important role in the development of human society. Electricity, which is the most flexible and manageable energy form, is currently used in a variety of activities and applications. For instance, electricity is used for heating, cooling, lighting, and for operating electronic appliances and electric vehicles. Nowadays, given the rapid development and commercialization of technologies and devices that rely on electricity, electricity demand is increasing faster than overall primary energy supply. Consequently, the design and planning of power systems is becoming a progressively more important issue in order to provide affordable, reliable and sustainable energy in timely fashion, not only in developed countries but particularly in developing economies where electricity demand is increasing even faster. Power systems are networks of electrical devices, such as power plants, transformers, and transmission lines, used to produce, transmit, and supply electricity. The design and planning of such systems require the selection of generation technologies, along with the capacity, location, and timing of generation and transmission capacity expansions to meet electricity demand over a long-term horizon. This manuscript presents a comprehensive optimization framework for the design and planning of interconnected power systems, including the integration of generation and transmission capacity expansion planning. The proposed framework also considers renewable energies, carbon capture and sequestration (CCS) technologies, demand-side management (DSM), as well as reserve and CO2 emission constraints. The novelty of this framework relies on an integrated assessment of the aforementioned features, which can reveal possible interactions and synergies within the power system. Moreover, the capabilities of the proposed framework are demonstrated using a suite of case studies inspired by a real-world power system, including business as usual and CO2 mitigation policy scenarios. These case studies illustrated the adaptability and effectiveness of the framework at dealing with typical situations that can arise in designing and planning power systems. info:eu-repo/semantics/publishedVersion

About 72 million households in rural India do not have access to electricity and rely primarily on traditional biofuels. This research investigates how rural electrification could be achieved in India using different energy sources and what the effects for climate change mitigation could be We use the. Regional Energy Model (REM) to develop scenarios for rural electrification for the period 2005-2030 and to assess the effects on greenhouse gas emissions, primary energy use and costs. We compare the business-as-usual scenario (BAU) with different electrification scenarios based on electricity from renewable energy, diesel and the grid. Our results indicate that diesel systems tend to have the highest CO2 emissions, followed by grid systems. Rural electrification with primarily renewable energy-based end-uses could save up to 99% of total CO2 emissions and 35% of primary energy use in 2030 compared to BAU. Our research indicates that electrification with decentralised diesel systems is likely to be the most expensive option. Rural electrification with renewable energy tends to be the most cost-effective option when end-uses are predominantly based on renewable energy, but turns out to be more costly than grid extensions when electric end-use devices are predominantly used. This research therefore elaborates whether renewable energy is a viable option for rural electrification and climate change mitigation in rural India and gives policy recommendations. (C) 2009 Elsevier Ltd. All rights reserved.

Abstract In the last years, a significant interest in research in stand-alone (SA) and grid-connected (GC) photovoltaic (PV)-wind hybrid renewable energy systems (HRES) is observed for their complementary in the satisfaction of the electrical energy demand in many sectors. However, direct comparisons between the techno-economic performance of two system modes under the same operating conditions are rarely carried out. Additionally, most of the researches are limited to specific weather conditions. This work aims to bridge the lack of this type of investigations providing a worldwide techno-economic mapping and optimization of SA and GC PV-wind HRES to supply the electrical demand of an office building district. For this purpose, energy and economic optimization problems were formulated to find the optimal SA and GC systems worldwide among 343 HRES system power configurations located in 48 different localities, uniformly divided in the sub-group of the Koppen classification. The energy reliability and economic profitability of optimal systems were geographically mapped worldwide. In general, the energy or economic optimizations of SA HRES do not lead to highly profitable systems; instead, feed-in-tariff to sell the energy in excess assures viable GC HRES in many localities. However, economically optimal SA and GC HRES, respectively, do not everywhere comply with the threshold value of 70% of the satisfied energy required by the load and are characterized by a high level of energy exchanged with the grid. The study highlighted that the most suitable climate conditions to install a SA HRES are: (i) Toamasina (Madagascar) from an energy point of view, with 76% of load satisfied and 76% of the energy generated utilized to supply the load; (ii) Cambridge Bay (Canada) from an economic point of view, with 11.1% of the capital cost recovered each year; instead, the most suitable climate conditions to install a GC HRES are: (iii) New Delhi (India) from an energy point of view, with 48% of energy exchanged with the grid per each kWh required by the load; (iv) Lihue (Hawaii, United States) from an economic point of view, with 24.3% of the capital cost recovered each year.

This paper deals with hybrid energy storage system (HESS) management strategies, optimized for urban road electric vehicle applications. These new control strategies aim to extend battery pack durability by reducing charging/discharging current peaks by means of supercapacitors. The optimization is carried out with reference to the case study of a HESS composed of a high power unit, i.e. supercapacitor module plus a high energy unit, i.e. a battery pack, based on nickel-chloride ZEBRA (ZEolite Battery Research Africa) technology. On-board integration of the two storage devices is obtained through a DC/DC bidirectional power converter, as this configuration is particularly convenient for many kinds of urban vehicle operations. The novelty of this work consists in an analytical methodology, based on non-linear programming and calculus of variations theory, to evaluate management strategies characterized by high effectiveness in reducing battery current transients. The identification and optimization of these strategies are initially performed on the basis of a vehicle model, built in the Matlab-Simulink simulation environment. To this purpose, the experimental characterization of the supercapacitor module is obtained with reference to three different models, whose selection depends on the required fitting performance and computational effort indexes, as evaluated in the paper. The energy management strategies identified show promising results in the simulation environment, followed by experimental activities carried out by means of a dedicated 1:1 scale laboratory test bench. The various experimental results presented in this manuscript highlight that the identified ?-control strategy presents effectiveness values up to 57%, close to the ideal results obtained in the simulation environment. In fact, the methodology proposed in this paper, validated by laboratory experiments, definitely reduces the negative consequences of power peaks on the HESS, indicating the real possibility of using these results in the design and control of urban road vehicles.