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Abstract The kinetics of methane hydrate decomposition was studied using a semibatch stirred-tank reactor. The decomposition was accomplished by reducing the pressure on a hydrate slurry in water to a value below the three-phase equilibrium pressure at the reactor temperature. The data were obtained at temperatures from 274 to 283 K and pressures from 0.17 to 6.97 MPa. The stirring rates were high enough to eliminate mass-transfer effects. Analysis of the data indicated that the decomposition rate was proportional to the particle surface area and to the difference in the fugacity of methane at the equilibrium pressure and the decomposition pressure. The proportionality constant showed an Arrhenius temperature dependence. An estimate of the hydrate particle diameters in the experiments permitted the development of an intrinsic model for the kinetics of hydrate decomposition.

This paper presents an overview of issues and technologies related to the proper design of charging infrastructures for road electric vehicles. The analysis is carried out taking into account that the recharging stations of electric vehicles might be integrated in smart grids, which interconnect the main grid with distributed power plants, different kinds of renewable energy sources, stationary electrical storage systems and electric loads. The study is introduced by an analysis of the main characteristics concerning different kinds of storage systems to be used for stationary and on-board applications. Then, different charging devices, modes and architectures are presented and described showing their characteristics and potentialities. DC and AC configurations of charging stations are compared in terms of the issues related to their impact on the main grid and the design of their main components. Specific attention was devoted also to the ultra-fast DC architecture, which appears a possible solution to positively affect a wide spread of plug-in hybrid and full electric road vehicles.

Abstract The modern revolutionary changes in power delivery systems with the advent of smart and flexible grids require systems interoperability, seamless integration of technologies and functionalities. This scenario is paving the way to new prospective of energy clusters that call for new methodologies for the dynamic energy management of distributed energy resources. This paper proposes a new management scheme of energy clusters (e.g., smart building, energy community or virtual power plant) that is based on a data driven decision-maker that daily deploys the activities of the day ahead, providing an optimized scheduling which will be the base for the operations for the next day. The new aggregator relies on some innovative features. It leverages an optimization process based on the elastic net regularization that proves to be an effective support for finding the best scheduling of the distributed resources according to specific key performance indicators, that presently is the unbalance. The decision process works on predicated data obtained through a recently assessed short term forecasting based on long short-term memory neural networks properly adapted to distributed environments. The method allows to extract insight from data and run what-if scenarios to define the best scheduling of resources. The technique uses a set of feasible rules to optimally aggregate the distributed resources and demand-side management programs. We tested the proposed aggregator on a real energy cluster making use of real measured data over two years period. The results show the effectiveness of the proposed approach that is able to predict any sort of unit and manage any sort of program. The significance of this work is to approach the energy management as an optimization and decision problem in a more robust way of reasoning, by employing forecasting/optimization over all the quantities in the community, resulting in a thoroughly complex and efficient method.

Carsharing is a mode of transportation that provides access to a set of vehicles in the form of organized short-term car rental, serving as a substitute for private car ownership with a number of transportation, environmental, and social benefits. Combining the mobility concept of carsharing with electric vehicles (EVs), referred to as e-carsharing, can contribute not only to more efficient use of the shared vehicles, but also to more sustainable urban mobility in smart cities. In this context, this paper advances the concept of university-based e-carsharing, to serve the mobility needs of an academic community in Bilbao, Spain, focusing on the technical design aspects to cover the energy requirements of the EV fleet of the proposed system through the installation of fast charging posts based on a battery-to-battery approach. In this regard, a MATLAB/Simulink model is implemented to simulate the fast charging infrastructure using the real-world data collected from the university parking lot in order to represent the potential utilization of the EVs. The simulation results confirm the effectiveness of the proposed system design, ensuring that the energy demand of the EVs is successfully covered and concurrently the charging station batteries operate out of the low charge zone.

Abstract Quest is a fully integrated Carbon Capture and Storage (CCS) project that started CO2 injection in August of 2015. The Quest CCS Project is located near Fort Saskatchewan, Alberta, Canada. It includes a capture facility which uses a Shell amine technology, a pipeline of about 65 km length, and three injection well pads. Each injection well pad has an injection well, a deep monitoring well, and shallow groundwater wells. The storage complex is geologically defined by the injection reservoir, a deep saline aquifer called the Basal Cambrian Sand (BCS) (about 45 m thick) and several seals, including the Middle Cambrian Shale (about 50 m thick) and Lotsberg Salts (about 120 m thick). As of August 2018, over three million tonnes of CO2 have been safely injected and permanently stored in the BCS. The Alberta Carbon Competitiveness Incentive Regulation (CCIR) requires the use of standard methods of quantification for reporting greenhouse gas (GHG) emissions for facilities with over 100,000 tonnes of carbon dioxide equivalent (CO2e) per year. An emission offset project is required to comply with CCIR, associated standards and protocols, to demonstrate a reduction in the specified gas emissions and, in the case of Quest, geological sequestration. Quest is the first CCS project to implement an offset project in the context of commercial scale on-shore CO2 geological sequestration within a saline aquifer. Quest uses the Quantification Protocol for CO2 Capture and Permanent Storage in Deep Saline Aquifers, from Alberta Environment and Parks. An offset project must develop an offset project plan (OPP) which demonstrates how the project meets the requirement of the protocol, describes how GHG emissions reductions are achieved, identifies risks associated with the quantification of emission reduction benefits, and describes methodologies used to quantify sources and sinks. Subsequent to completing the OPP, an offset project will put together offset project reports (OPR) to report on the net reductions of GHG emissions for a specific period. The intent of this paper is a) to provide an overview of the OPP and OPR for the Quest CCS project, and b) to discuss learnings from the initial compilation and submission of offset project reports. The key learning at this time is associated to the equipment improvements to the injection gas online analyzer.

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

The electric engine cooling system, where the coolant pump and the radiator fan are driven by electric motors, admits advanced control methods to decrease auxiliary energy consumption. Recent publications show the fuel saving potential of optimal control strategies for the electric cooling system through offline simulations. These strategies often assume full knowledge of the drive cycle and compute the optimal control sequence by expensive global optimization methods. In reality, the full drive cycle is unknown during driving and global optimization not directly applicable on resource-constrained truck electronic control units. This paper reports state-of-the-art engineering achievements of exploiting vehicular onboard prediction for a limited time horizon and minimizing the auxiliary energy consumption of the electric cooling system through real-time optimization. The prediction and optimization are integrated into a model predictive controller (MPC), which is implemented on a dSPACE MicroAutoBox and tested on a truck on a public road. Systematic simulations show that the new method reduces fuel consumption of a 40-tonne truck by 0.36% and a 60-tonne truck by 0.69% in a real drive cycle compared to a base-line controller. The reductions on auxiliary fuel consumption for the 40-tonne and 60-tonne trucks are about 26% and 38%, respectively. Truck experiments validate the consistency between simulations and experiments and confirm the real-time feasibility of the MPC controller.

Abstract The effects of CO2-brine-rock interaction on the physical and macro-mechanical properties of rock have been extensively studied in CO2 sequestration-related research. However, there are few studies focus on mechanochemical effects of the interaction of supercritical CO2 (SC−CO2), water, and rock and its effects on micromechanical properties of sandstone. In this work, we studied the micromechanical mechanism of crack initiation induced by SC−CO2-water saturated sandstone. A micromechanical model including parameters of fracture cohesive strength, friction coefficient, and fracture energy was proposed, which extended the “sliding surface” to include not only the friction, but also the cohesions on the surfaces and the tensile resistance at the crack-tips. To this end, tests of two saturation conditions, water and SC−CO2-water, were conducted on 25 mm diameter by 50 mm length Sichuan sandstone with a porosity of ∼15.57 % for 15 days and 30 days under temperature of 80 ℃ and pressure of 30 MPa. Afterward, samples were subjected to triaxial compression tests with confining pressure up to 24 MPa. The mineralogical alteration and induced crack morphology were examined to better understand the mechanism of mechanochemical coupling on compression failure induced by SC−CO2-water-rock interaction. Experimentally, mineralogical and microstructural changes induced by illite and kaolinite dissolution, weaken the quartz grain contacts in SC−CO2-water saturated sandstone. Compared to water-saturated sandstone, the SC−CO2-water saturated sandstone exhibits a maximum reduction by 18.82 % and 21.21 % in compressive strength and crack initiation stress respectively under unconfined condition. Additionally, reductions of 5%, 50 %, and 37.3 % were observed in friction coefficient, fracture energy, and cohesive strength respectively for SC−CO2-water saturated sandstone. The reductions of these three parameters, especially the fracture energy and cohesive strength, significantly weaken SC−CO2-water saturated sandstone. The results are representative for the partly saturated zone where SC−CO2 is displacing the in-situ pore fluid and could be used to analyze effects of CO2 injection on stability and integrity of storage formation under mechanochemical coupling effects of SC−CO2-water on sandstone.