• Energy Research
• other engineering and technologies close
• GB close
• IN close
• SA close
• BE close

A thermoelectric generator with zero internal resistance, vanishing heat leakage and negligible production of Thomson heat is considered. It is shown that such a generator behaves as an ideal Carnot engine or an endoreversible Carnot engine depending upon whether the heat transfer mechanism at the junctions is reversible or a finite rate. Furthermore, the optimized power of the generator is found to be greater than that of the endoreversible Carnot engine.

Abstract This article introduces an effective stochastic operation framework for optimal energy management of the shipboard power systems including large, nonlinear and dynamic loads. The proposed framework divides the ship power system into several agents, which coordinate with each other based on their demands/supplies until. The alternating direction method of multipliers (ADMM) is deployed as the multi-agent framework to solve the reformulated distributed energy management problem in the ship. Two types of turbo-generators are considered in the proposed system model, including single-shaft and twin-shaft models, to increase the part-load efficiency in certain times when facing variable speed operation. The proposed distributed framework is equipped with a recursive mechanism, which helps the ship system for running optimal load scheduling when facing insufficient power generation. In order to model the uncertainty effects associated with the forecast error in the interval-ahead load demand, a stochastic framework based on unscented transform is devised which can work in the nonlinear and correlated environments of shipboard power systems. Due to the nonlinear cost function in each agent, a powerful optimization algorithm based on modified θ-firefly algorithm (Mθ-FOA) is proposed. This is a phasor algorithm, which helps for escaping from premature convergence and getting trapped in local optima. The appropriate performance of the proposed stochastic model is examined on the real dataset of a ship power system. The simulation results show the high robustness, guarantied consensus, economic operation and feasible solution when power generation shortage based on load shedding in the system.

A parametric numerical investigation is performed of the natural convection and heat transfer in an enclosure with opposing wavy walls, layered by a porous medium, saturated by a hybrid nanofluid, at different inclination angles. The Galerkin finite element method is used to obtain steady-state solutions of the heat and mass convection laws by application of the semi-implicit method for pressure linked equations algorithm. The Darcy-Brinkman model is used for representing the state variables change in the porous layer. The influence of six parameters on the flow and heat transfer rate is described. These are the inclination angle, varied from 0o to 90o, the Rayleigh number (104 ≤ 𝑅𝑎 ≤ 107), the Darcy number (10-5 ≤ 𝐷𝑎 ≤ 10-2), the porous layer width (0.2 ≤ 𝑊p ≤ 0.8), the number of undulation (1≤ 𝑁 ≤ 4), and the nanoparticle volume fraction (0 ≤ 𝜙 ≤ 0.2). It is found that the inclination angle is a very influential control parameter for the hybrid nanofluid in the enclosure. Its effect is modulated by the other parameters. The model predicts that adding the nanoparticles enhances the heat transfer between the opposing walls of the cell compared to the pure fluid over the whole range of inclination angles. Finally, a comparison of the heat transfer enhancement based on the suspension of Al2O3 nanoparticles in water as a single nanofluid versus using Cu-Al2O3 nanoparticles in water as a hybrid nanofluid indicates better heat transfer performance by the hybrid nanofluid.

Abstract The evolutionary algorithm of invasive weed optimization algorithm popularly known as the IWO has been used in this paper, to solve the unit commitment (UC) problem. This integer coded algorithm is based on the colonizing behavior of weed plants and has been developed to minimize the total generation cost over a scheduled time period while adhering to several constraints such as generation limits, meeting load demand, spinning reserves and minimum up and down time. The minimum up/down time constraints have been coded in a direct manner without using the penalty function method. The proposed algorithm was tested and validated using 10 units and 24 h system. The most important merit of the proposed methodology is high accuracy and good convergence speed as it is a derivative free algorithm. The simulation results of the proposed algorithm have been compared with the results of other tested algorithms for UC such as shuffled frog leaping, particle swarm optimization, genetic algorithm and Lagrangian relaxation and bacterial foraging algorithm.

The present work is dedicated to the steady-state analysis of electronic load controller (ELC) for three phase alternator. In an alternator employed in micro-hydro applications, the voltage is controlled by Automatic Voltage Controller (AVR) so here electronic load controller conforms itself to the control of frequency. It does so by diverting the difference between the rated power and consumer demand to the dump/ballast load for dissipation. The paper presents the mathematical and simulink model of Electronic Load Controller for three phase alternator. The developed mathematical model is first checked for its stability by employing Routh-Hurwitz criterion and then designed in MATLAB/Simulink which is then analyzed for its behavior under steady-state conditions. The controller is being modeled for proportional, proportional plus integral and proportional plus integral plus derivative control and the results are being compared and discussed.

(2002). Electrolytic Deposition (Electroplating) of Metals. Transactions of the IMF: Vol. 80, No. 2, pp. 67-72.

Lithium-ion batteries have emerged as a promising choice for electric vehicle applications. However, thermal runaway and related catastrophic issues perplex the research community when batteries are subjected to varying charging/discharging and different ambient temperatures. In order to keep the batteries under a safe zone of temperature, battery thermal management occupies utmost importance and hence researchers are switching over to a combination of either two or three strategies since single stragaty could not meet effective thermal management. In a combined strategy, the use of phase change materials and is highly essential due to their inherent thermo-physical properties; both organic and inorganic types have been explored. To enhance the heat dissipation, the phase change materials, regarded as composite phase materials, are being added with graphite powder, nanomaterials, metal foams, and fins are being arranged to the battery cells. The present review enumerates the recent progress made in achieving good thermal performance with hybrid/integrated battery thermal systems with an emphasis on the use of composite phase change materials. The review revealed that the hybrid strategy is performing well, machine learning and advanced optimization methods are being applied to understand the state of health of batteries. Few works are focussed on the mitigation of thermal runaway propagation serving the composite phase change materials as effective flame retardants. The current status and challenges being faced in the use of LIBs is also briefed. It is essential to develop economical integrated battery thermal management systems with parasitic power losses that are compact and safe to attract many city dwellers to adopt pure electric vehicles besides meeting the mandate of sustainable development goals. The review is an attempt to provide a ready reckoner in the area of integrated battery thermal management involving composite phase materials.

This paper presents a literature survey on the subject of voltage stability analysis of power systems. The survey describes several published methods and techniques used to determine voltage stability indices. These indices predict proximity to voltage instability and collapse problems. The Q-V and P-V curves; singular value decomposition; modal analysis; test function; reduced determinant; loading margin by multiple power flow solutions; local load margins; thevenin/load impedance; and energy function are the methods which have been decribed in the paper. The methods described are based on the original work that first proposed them. They are based on the power-flow system model, where the variation of real and reactive powers are assumed to be the main parameters driving the system to voltage instability. Some of the described methods were applied on the IEEE 30-bus power system.

Even with state of the art forecasting methods, the short-term generation of wind farms cannot be predicted with a high degree of accuracy. In a market situation, these forecasting errors lead to commercial risk through imbalance costs when advance contracting. This situation is one that needs to be addressed due to the steady increase in the amount of grid connected wind generation, combined with the rise of deregulated, market orientated electricity systems. In the presence of imbalance prices and uncertain generation, a method is required to determine the optimum level of contract energy to be sold on the advance markets. Such a method is presented here using Markov probabilities for a wind farm and demonstrates substantial reductions in the imbalance costs. The effect of market closure delays and forecasting window lengths are also shown.