Free Piston linear Generator becomes a new solution and device for energy conversion highly integrated engine and linear machine due to its potential application on hybrid vehicles. This paper investigated the starting process of an opposed-piston free-piston linear generator (OPFPLG), and a prototype was built to carry out the experimental research of the startup process. The prototype adopts a piston synchronization mechanism and a pipeline connecting two bounce chambers to improve the self-balance performance of the system. The linear machine is used to start the engine because of its flexibility and controllability. The control strategies combining mechanical resonance and synchronization control methods were applied on the prototype for starting operation, and the test data collected for further analysis. When the linear motor’s thrust force was 240N, the maximum pressure in combustion cylinder achieved was beyond 11.8 bar with a compression ratio of 12:1, indicating that the mixture was ready for ignition. The system frequency was up to 14Hz, and the piston amplitude was about 56.5mm with a synchronization error of the opposed pistons less than 1.5mm. Especially, the piston synchronization error of the inner and outer dead center was nearly zero. Both the variation of synchronization error and the cyclic fluctuation of starting process were demonstrated with different synchronization control methods. The piston sync error of the dual current command control mode was found to be lower than that of the master-slave mode, and the cyclical fluctuation was smaller. The dual current command control method will be implemented to the prototype to start and maintain the piston motion synchronization during the starting process of the OPFPLG system.
It was predicted in 2012 that the global demand for energy over a period of 28years (2012-2040) will increase by 48%. This will raise the total global energy consumption from 549 quadrillion British thermal units (Btu) in 2012 to 815 quadrillion Btu by 2040. As a strategic player in the energy mix, a reduction in the emission of CO2 to the environment from the natural gas network will result in environmental and cost savings. Although several researchers have alluded various opportunities associated with renewable energy feedstocks and have examined various strategies for optimized energy supply, the possible structural adjustments to gas infrastructure to align with future policies on climate will bring about a sustainable strategy for future economic growth. The motive of work is to investigate the problem associated with exogenous interruptions to a gas network resulting in loss of gas to the environment. The research also proposed a mitigation strategy for gas loss and emission reduction. To achieve this, a mixed integer linear programming (MILP) optimization model is developed that establishes a strategy for loss reduction in gas supply chain. Data from real case study have been accessed which enhances the applicability of the proposed model which was run on the GAMS 26.14 software using the CPLEX solver 12 in an intel ® core ™ i7 and a zero-optimality gap within reasonable solution time. The result obtained revealed a reduction from 555.1million kg of CO2 to 8.06 million kg of CO2 after optimization while still delivering on projected throughput. The proposed methodology can help natural gas operators to optimize performance considering disruption time estimation.
Access to deep energy resources (geothermal energy, hydrocarbons) from deep reservoirs will play a fundamental role over the next decades. However, drilling of deep wells to extract deep geo-resources is extremely expensive. As a fact, drilling deep wells into hard, crystalline rocks represents a major challenge for conventional rotary drilling systems, featuring high rates of drill bit wear and requiring frequent drill bit replacements, low penetration rates and poor process efficiency. Therefore, with the aim of improving the overall economics to access deep geo-resources in hard rocks, in this work, we focus on two novel drilling methods, namely: the Combined Thermo-Mechanical Drilling (CTMD) and the Plasma-Pulse Geo-Drilling (PPGD) technologies. The goal of this research and development project is the effective reduction of the costs of drilling in general and particularly regarding accessing and using deep geothermal energy, oil or gas resources. In this work, we present these two novel drilling technologies and focus on evaluating the process efficiency and the drilling performance of these methods, compared to conventional rotary drilling.
Vehicle energy management is the core technology of hybrid vehicles, which determines the fuel economy and emission performance of the vehicle. At present, most of the common energy management is based on known operating conditions, without considering actual road traffic information, which makes vehicles unable to achieve optimal energy management. With the development of GPS and ITS, future traffic information can be obtained in advance. In the paper, a hierarchical energy control method for hybrid electric vehicles is proposed. Model predictive control algorithm is utilized to predict the optimal vehicle velocity in the upper controller. The lower controller is designed to follow the optimal velocity, and uses the neural network control algorithm to optimize the power distribution between the engine and the motor to reduce fuel consumption. Compared with the traditional energy management strategy, the proposed method can prevent the vehicle from stopping at the red light, thereby reducing the fuel consumption of the vehicle to achieve the purpose of saving fuel consumption.
The traditional energy management system of hybrid electric vehicle did not take into account the future driving information. To realize the further energy optimization, the Bi-level energy management strategy in connected environment is studied in this paper. The upper controller is to predict the optimal velocity. Firstly, the target velocity range is first calculated based on the signal phase and timing (SPAT) information. Then the optimization function is designed to obtain the optimal acceleration. The lower controller is designed to follow the optimal acceleration and to save energy by optimizing the power split between the engine and motor under the condition of meeting the physical constraints. The rule-based and fuzzy logic controller based on genetic algorithm are adopted in this paper. Simulation results indicate that optimizing vehicle velocity trajectory in connected environment can effectively reduce fuel consumption and pollutant emission. Meanwhile, compared with Rule-based strategy, the fuzzy logic controller based on genetic algorithm contributes to realize the superior fuel economy performance and lower emissions.
In 2018, nuclear energy generated 55% of United States’ and one third of the world’s carbon free electricity. Nuclear energy can be a key tool in current efforts to mitigate climate change before 2050. However, nuclear construction costs escalated dramatically in recent years: from $3,000/kW in the 1990’s to over $7,000 today, and this has severely limited its potential for impact. Nuclear plants are construction megaprojects that require thousands of workers and a decade of construction. The capital costs and construction timelines were double the original estimates for the last five nuclear plants completed or under construction in western nations. Moreover, the current nuclear technology can only provide heat at low temperatures (300°C), which limits its use as a decarbonization tool to the electricity grid. Heat for industrial processes accounts for 10% of carbon emissions. High temperature gas reactors (HTGRs) can meet this need with carbon free nuclear heat. Unfortunately, the estimated cost of advanced reactor alternatives such as HTGRs are even higher than current Light Water Reactors (LWRs). In this paper, we built a simple model to estimate the capital cost of existing nuclear plants and apply it to HTGR designs. We propose a structures-first design framework to minimize cost and apply it to the HTGR, resulting in a horizontal, integrated HTGR. The reactor core and steam generator are mounted on rails and in-line with one another. The rail-mounted horizontal orientation simplifies installation and eliminates the overhead crane. The proposed concept reduced the reactor building size by more than 50%/kW relative to other HTGR designs, putting the building power density on par with LWR designs but with the inherent safety and high temperature capability of an HTGR. Finally, we estimate a >30% cost reduction from the new design and the potential impact on carbon emissions.
Approaches to reducing energy consumption in multi-family residential buildings can benefit from being more intentionally integrated with non-energy urban planning efforts. Despite the large volume of energy data available, some of the data that would be useful to plan more sustainable urban development or retrofit existing building stocks are incomplete or not integrated with data that is being used for decision-making. This article identifies data issues that limit the effectiveness of energy efficiency planning efforts and proposes solutions to surmount these challenges. Further, the role of an Energy Urban Planner (EUP) is proposed to resolve the identified gaps with consideration for more thoughtful and integrated planning approach. Lastly, the article discusses the potential implications of an EUP role for both urban planning more broadly and specific approaches to reduce energy consumption. The methodology combines qualitative research with key energy efficiency decision-makers in three municipalities and a data quality and spatial analysis case study of Chicago Energy Benchmarking data. The qualitative research consisted of interviews that were conducted to explore how municipalities and NGOs plan efforts to reduce energy consumption in multi-unit residential buildings. In the case study, 2017 energy benchmarking data (reported in 2018) are analyzed for data quality issues and patterns that emerge from geographic and urban form variables. The qualitative findings are combined with the results from the Chicago case study to identify the need for more integrated urban planning. The objective is to highlight data that can be intentionally integrated to bolster energy efficiency efforts across professions.
The emergence of increasingly affordable variable speed drive technology has changed the approach for how chilled water systems equipped with variable speed drives should be controlled. The purpose of this research was to estimate the potential energy savings that can be achieved through optimization of a single chiller system equipped with Variable Frequency Drives (VFDs) on all pieces of equipment in the condenser water system. Data for a case study was collected from a local museum’s chilled water system. To accomplish the objective, physical component models of the centrifugal chiller, cooling tower and condenser water pump were established with the goal of incorporating the system’s condenser water flow rate and cooling tower fan speeds as optimization variables. Furthermore, a cooling load prediction algorithm was developed using a multiple non-linear regression model to approximate the buildings cooling load subject to a range of environmental conditions. The inputs and outputs of the individual component models were linked to estimate how adjusting the cooling tower fan and condenser water pump speed would influence the system’s overall performance. The overall system model was then optimized using a generalized reduced gradient optimization algorithm to determine the potential energy savings through speed control with VFDs and ascertain a simple control logic strategy for the building automation system to operate the system. The saving potential of the optimized system was found to be 12-15%.
Air dehumidification through cooling is an energy-intensive process, which consumes about 20-40% of the overall energy for air-conditioning. Liquid desiccant dehumidification can separate dehumidification from space cooling and has potential to improve the cooling efficiency and reduce the overall energy consumption for air-conditioning. However, the drawbacks such as liquid carryover and corrosion, membrane contamination and blocking, limit its application. To eliminate these problems, a new dehumidifier using nonporous membrane and ionic liquid desiccant (ILD) was developed. The dehumidification performance of the new dehumidifier was characterized through a series of lab tests. Test results indicate that the new dehumidifier can achieve a moisture removal rate up to 180.3 g/h and a dehumidification effectiveness up to 12.7%. A parametric study found that the dehumidification performance is sensitive to the flowrates of the air and the ILD solution. A higher mass flow ratio between the ILD solution and the air could result in better dehumidification performance.
Thermal energy storage (TES) can alleviate peak demand on the electricity grid by offsetting building thermal loads, increasing the grid’s reliability and resilience. However, low energy density and poor energy performance of existing TES technologies limit their applications. Sorption-based thermal battery (STB) system is thus developed using three-phase sorption technology to harvest low-temperature heat, store it with a much higher energy density than common TES systems and dehumidify air or provide space cooling in buildings. Although STB has been experimentally proved to be feasible, influencing factors on its performance are still unknown by far. Therefore, this paper conducted a parametric analysis on crystallization and crystal dissolution performance of a developed STB test rig. The crystallization results showed that the energy density of the STB increased with reducing the solution flow rate and the cooling water temperature. The dissolution results showed that a higher discharge rate of the STB can be achieved with increasing the flow rate and temperature of inlet diluted solution. The work in this study is helpful to the optimal design and operation of the STB system.