Journal of Energy Engineering

Wood biomass is widely used as fuel in the so-called green power units producing heat and electricity. Wood biomass, like other solid fuels, contains many elements, most of which are found in trace amounts. The bark of Mediterranean pine cleaned of wood was chosen for the study presented in this paper. Thirty-five elements, of which 19 are trace elements (TEs), were identified in the pine bark. An experimental study on the ground pine bark burning at temperatures 650°C, 750°C, 850°C, and 950°C was conducted on a laboratory scale. Ashes formed from combustion at particular temperatures were analyzed. Experimental results and calculations of thermodynamic equilibrium were compiled in the form of a series of small graphs for major elements, minor ones, and TEs present in ashes, which allows quick evaluation of the results of the study. The consequence of an increase in the combustion temperature was the reduction of the content of K, S, Cu, and Pb in ash. TEs with the highest retention in ashes included Co, V, Cr, Sr, Ba, and Ni. The thermodynamic equilibrium calculations performed in the FactSage software version 6.3 made it possible to predict the occurrence of major, minor, and trace elements in ashes and flue gas.

Conventional exergy-based analysis can only identify the location and magnitude of thermodynamic inefficiencies (exergy destruction), while an advanced analysis can further reveal their source and avoidability by splitting each inefficiency into endogenous/exogenous and avoidable/unavoidable parts and their combinations. In this paper, a framework and implementation for a comprehensive evaluation of energy systems via conventional and advanced exergoeconomic analyses are summarized and performed to a state-of-the-art pulverized-coal power plant. An easy-to-implement procedure was proposed to calculate the endogenous exergy destruction. Different from the previous analyses of such plants, the boiler subsystem of the considered plant is simulated in detail with coal combustor and a series of (radiation- or convection-dominating) heat surfaces. The exergoeconomic performances (exergy dissipation as well as the related costs) of each component and the whole system are evaluated first. Then, the splitting of all exergy destructions and costs is performed for the insights of their sources and avoidability to suggest improvement measures. The results show that large parts of the exergy destructions within most of the components are endogenous; particularly, over half of the avoidable thermodynamic inefficiencies within most of the components are endogenous with the share of the avoidable part varying significantly among different components. Most costs related to either investment or exergy destruction are endogenous, and only nearly 10% of the costs of the whole system could be avoided for such a modern power plant. Moving convection-dominating heating surfaces into the furnace and increasing air-preheating temperature are suggested for performance enhancement.

A battery thermal management system (BTMS) is crucial to guarantee that lithium-ion (Li-ion) batteries attain high performance, long life, and a high level of safety. To investigate an effective cooling method of prismatic Li-ion batteries for an electric vehicle, a design of BTMS using minichannel cold plates is established. The performance of the BTMS are parametrically studied by using different configurations, flow rates, and inlet coolant temperatures. With this BTMS, the maximum temperature and the temperature difference of the cell at a discharge rate of 2 C is 33.8°C and 3.5°C, respectively, using flow rate of $0.002{\mathrm{kg}\mathrm{s}}^{-1}$ and inlet coolant temperature of 30°C. The C-rate is equal to the charge–discharge current divided by its rated capacity. At higher discharge rates, higher flow rates are needed to achieve the cooling performance, and the flow rate has upper limits given the efficiency of the cooling system. When the discharge rate is increased to 3 C and 5 C, the optimal flow rate needed is 0.003 and $0.02{\mathrm{kg}\mathrm{s}}^{-1}$, respectively.

Sediment microbial fuel cells (SMFCs) are an alternative renewable power supply for sensors and communication. However, their low power outputs limit their practical applications. Maximum power point tracking can overcome this limitation by boosting the output voltage and optimizing the energy generation of sediment microbial fuel cells. In the present work, an adaptive variable-step incremental-conductance algorithm is developed for the high-efficiency energy harvesting of sediment microbial fuel cells by the fast tracking of the maximum power, even in a complex internal environment with significant fluctuations in power output. Computer simulations suggested that this algorithm can decrease the convergence time from 1.78 to 0.9 s. The excellent performance of the algorithm is verified on a single-chamber 2-L SMFC with 26.86% overall system efficiency and ability to successfully power a wireless sensor every 23 min. This work has provided a new strategy to harvest and manage the power outputs of low-power energy-acquisition systems.

Thermal management of lithium-ion battery packs is a key technical problem that restricts the development of new-energy vehicles. The shape of air-cooled Lithium-ion battery packs is vital for thermal management system without replacing batteries. Here we proposed and optimized a novel Z-shaped battery pack structure, which was systematically analyzed and optimized by a computational fluid dynamics method. The results show that when the inlet airflow rate changes from $0.003–0.036\mathrm{kg}{\mathrm{s}}^{-1}$, the temperature difference increases (from 7.91 to 9.67 K), while the temperature nonuniformity of the battery packs increases (from 2.49 to 3.09 K). The maximum temperature, difference, and nonuniformity of temperature all increase in the initial phase with the increase of battery spacing when the battery spacing is 4 mm; the inflection point appears and then decreases gradually. Meanwhile, the cooling effect of the Z-shaped structure is improved greatly by adding deflectors and rounding-off chamfers. When the tilt angle of deflectors is 60° and the radius of round chamfers is 5 mm, the maximum temperature of the battery packs decreases by 2.52 K; besides, the temperature difference and nonuniformity decreases significantly, which improves the performance of lithium-ion battery packs effectively.

A smart grid is a two-way communication distributed energy network that enables efficient energy generation and distribution. Due to increased interest in renewable energy production and consumption, energy distribution using a centralized grid architecture has limited applicability. Blockchain technology has attained significant attention recently and provides a number of ways for reliable processing and storage of data in a decentralized manner. It is now recognized that trustless decentralized energy production and transfer using blockchain technology is a promising approach. This work proposes a novel blockchain-based decentralized green energy distribution system for trustless reliable energy exchanges in a smart grid. The proof of distribution problem in a decentralized environment is first formalized. The reliability and validity of the energy distribution system is established by way of a robustness evaluation model. An extensive experimental study is performed to evaluate the effectiveness and soundness of the solution. Finally, a decentralized green energy distribution smart-grid case study is presented to demonstrate the utility of the system in real-life situations.

This paper proposes the idea of independent models of a microgrid (MG) based on operation modes. In grid-connected operation, optimal power flow is proposed to minimize the power generation cost. A new decision variable was introduced to represent a MG as an equivalent unit from the viewpoint of the upstream network. In island operation, contingency condition was considered and reliability improvement of the MG through load restoration is proposed. A new performance index is proposed to model MGs as small self-adequate islands in contingency. The main distinction between this research and the literature is the consideration of the uncertainty of the components of the MG. Monte Carlo simulation (MCS) was used as a framework to consider the uncertainty of components, including load consumption, renewable power generation, and fault duration. The proposed probabilistic models can be used to assess the generation adequacy and to indicate vulnerable loads in grid-connected and island operation modes, respectively. The proposed method was applied to the IEEE 69-bus test system and the results were discussed.

Via partial hydrogenation, polyunsaturated fatty acid methyl esters (FAMEs) in biodiesel were largely converted to monounsaturated and saturated FAMEs, which brought the following changes in fuel properties: lower iodine value, better oxidative stability, higher cetane number, and slightly increased kinematic viscosity. Experiments were conducted to evaluate the combustion and emission performance in a diesel engine using diesel, B20 (80% diesel and 20% biodiesel), PHB10 (90% diesel and 10% partially hydrogenated biodiesel), and PHB20 (80% diesel and 20% hydrogenated partially biodiesel). The aforementioned four fuels almost shared the same equivalent specific fuel consumptions, owing to the combined effects of oxygen content, cetane number, and kinematic viscosity. Because the high cetane number of hydrogenated biodiesel overweighed its incremental kinematic viscosity in ignition, the ignition timings for B20, PHB10, and PHB20 compared with diesel were advanced by 0.8° crank angle (CA), 0.6°CA, and 1.4°CA, respectively. Simultaneously, the heat release rate peaks and pressure peaks for B20, PHB10, and PHB20 were advanced but decreased accordingly. B20, PHB10, and PHB20 exhibited reduced hydrocarbon (HC), carbon monoxide (CO), and smoke emissions and increased nitrogen oxides (${\mathrm{NO}}_{\mathrm{x}}$) emission compared with diesel. Overall, among the four fuels, PHB20 presented the lowest emissions excluding ${\mathrm{NO}}_{\mathrm{x}}$ emissions.