Pradeep K. Sahoo

Bio: Pradeep K. Sahoo is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Desiccant & Air conditioning. The author has an hindex of 25, co-authored 52 publications receiving 1867 citations. Previous affiliations of Pradeep K. Sahoo include Botswana International University of Science and Technology & Indian Institutes of Technology.

Analysis of heat transfer augmentation and flow characteristics due to rib roughness over absorber plate of a solar air heater

Abstract: A computational analysis of heat transfer augmentation and flow characteristics due to artificial roughness in the form of ribs on a broad, heated wall of a rectangular duct for turbulent flow (Reynolds number range 3000–20,000, which is relevant in solar air heater) has been carried out. Shear stress transport k−ω turbulence model is selected by comparing the predictions of different turbulence models with experimental results available in the literature. A detailed analysis of heat transfer variation within inter rib region is done by using the selected turbulence model. The analysis shows that peak in local heat transfer coefficient occurs at the point of reattachment of the separated flow as observed experimentally. The results predict a significant enhancement of heat transfer in comparison to that for a smooth surface. There is a good matching between the predictions by SST k−ω and experimental results. In this work, nine different shapes of rib are examined using SST k−ω model and compared on the basis of heat transfer enhancement, friction characteristics and performance index considering heat transfer enhancement with the same pumping power.

Solid desiccant air conditioning – A state of the art review

Abstract: Recently, solid desiccant air conditioning system has been proposed as an alternative to the conventional vapor compression refrigeration air conditioning systems for efficient control over humidity of conditioned air especially in hot and humid areas. The solid desiccant cooling can be more favorable over the traditional vapor compression refrigeration air conditioners, because it assures more accessible, economical and cleaner air conditioning. It is still more important when it is powered by free energy sources like solar energy and waste heat with temperatures of between 60°C and 80°C. In addition, it can significantly reduce the operating cost as well as save energy. In the present paper, principle of solid desiccant cooling system is recalled and its technological applications and advancements are discussed. Through a rigorous literature review, different configurations of desiccant cooling cycles, conventional and hybrid desiccant cooling cycles, different types of mathematical models of rotary desiccant dehumidifier, performance evaluation of desiccant cooling system, technological improvement and the advantage it can offer in terms of energy and cost savings are highlighted. This paper also gives a detailed account of the general features and performance of the solid desiccant cooling system when it is powered by solar energy or industrial waste heat for regenerating the desiccant. This review is useful for making opportunities to further research of solid desiccant cooling system and its feasibility which is becoming common in the coming days.

Thermoeconomic optimization of a single effect water/LiBr vapour absorption refrigeration system

Abstract: In this paper, the thermoeconomic theory is applied to the economic optimization of a single effect water/LiBr vapour absorption refrigeration system for air-conditioning application, aimed at minimizing its overall operation and amortization cost. The mathematical and numerical techniques based optimization of thermal system is not always possible due to plant complexities. Therefore, a simplified cost minimization methodology is applied to evaluate the economic costs of all the internal flows and products of the system by formulating exergoeconomic cost equations. Once these costs are determined, the system is thermoeconomically evaluated to identify the effects of design variables on costs and enables to suggest values of design variables that would make the overall system cost effective. Finally, an approximate optimum design configuration is obtained by means of sequential local optimization of the system, carried out unit by unit. The result compares this optimum with the base case and shows percentage variations in the system's operation and amortization cost.

Exergoeconomic analysis and optimization of a cogeneration system using evolutionary programming

Abstract: Exergoeconomic analysis helps designers to find ways to improve the performance of a system in a cost effective way. Most of the conventional exergoeconomic optimisation methods are iterative in nature and require the interpretation of the designer at each iteration. In this work, a cogeneration system that produces 50 MW of electricity and 15 kg/s of saturated steam at 2.5 bar is optimized using exergoeconomic principles and evolutionary programming. The analysis shows that the product cost, cost of electricity and steam, is 9.9% lower with respect to the base case. This is achieved, however, with 10% increase in capital investment. Moreover, it is important to note that the additional investment can be paid back in 3.23 years.

Thermoeconomic evaluation and optimization of an aqua-ammonia vapour-absorption refrigeration system

Abstract: In this paper, the thermoeconomic concept is applied to the optimization of an aqua-ammonia vapour-absorption refrigeration (VAR) system—aimed at minimizing its overall product cost. The thermoeconomic concept based simplified cost minimization methodology calculates the economic costs of all the internal flows and products of the system by formulating thermoeconomic cost balances. The system is then thermoeconomically evaluated to identify the effects of design variables on costs and thereby enables to suggest values of design variables that would make the overall system cost-effective. Based on these suggestions, the optimization of the system is carried out through an iterative procedure. The results show a significant improvement in the system performance without any additional investment. Finally, sensitivity analysis is carried out to study the effect of the changes in fuel cost to the system parameters.

Review of software tools for hybrid renewable energy systems

Abstract: Hybrid energy systems are being utilized for supplying electrical energy in urban, rural and remote areas to overcome the intermittence of solar and wind resources. A hybrid renewable energy system incorporates two or more electricity generation options based on renewable energy or fossil fuel unit. The techno-economic analysis of the hybrid system is essential for the efficient utilization of renewable energy resources. Due to multiple generation systems, hybrid system analysis, is quite complex and requires to be analyzed thoroughly. This requires software tools for the design, analysis, optimization, and economic viability of the systems. In this paper, 19 softwares with their main features and current status are presented. The softwares studied are HOMER, Hybrid2, RETScreen, iHOGA, INSEL, TRNSYS, iGRHYSO, HYBRIDS, RAPSIM, SOMES, SOLSTOR, HySim, HybSim, IPSYS, HySys, Dymola/Modelica, ARES, SOLSIM, and HYBRID DESIGNER. The research work related to hybrid systems carried out using these softwares at different locations worldwide is also reviewed. The main objective of the paper is to provide the current status of these softwares to provide basic insight for a researcher to identify and utilize suitable tool for research and development studies of hybrid systems. The capabilities of different softwares are also highlighted. The limitations, availability and areas of further research have also been identified.

Exergy, exergoeconomic and environmental analyses and evolutionary algorithm based multi-objective optimization of combined cycle power plants

Abstract: A comprehensive exergy, exergoeconomic and environmental impact analysis and optimization is reported of several combined cycle power plants (CCPPs). In the first part, thermodynamic analyses based on energy and exergy of the CCPPs are performed, and the effect of supplementary firing on the natural gas-fired CCPP is investigated. The latter step includes the effect of supplementary firing on the performance of bottoming cycle and CO2 emissions, and utilizes the first and second laws of thermodynamics. In the second part, a multi-objective optimization is performed to determine the “best” design parameters, accounting for exergetic, economic and environmental factors. The optimization considers three objective functions: CCPP exergy efficiency, total cost rate of the system products and CO2 emissions of the overall plant. The environmental impact in terms of CO2 emissions is integrated with the exergoeconomic objective function as a new objective function. The results of both exergy and exergoeconomic analyses show that the largest exergy destructions occur in the CCPP combustion chamber, and that increasing the gas turbine inlet temperature decreases the CCPP cost of exergy destruction. The optimization results demonstrates that CO2 emissions are reduced by selecting the best components and using a low fuel injection rate into the combustion chamber.

Modeling of solar energy systems using artificial neural network: A comprehensive review

Abstract: The development of different solar energy (SE) systems becomes one of the most important solutions to the problem of the rapid increase in energy demand. This may be achieved by optimizing the performance of solar-based devices under some operating conditions. Intelligent system-based techniques are used to optimize the performance of such systems. In present review, an attempt has been made to scrutinize the applications of artificial neural network (ANN) as an intelligent system-based method for optimizing and the prediction of different SE devices’ performance, like solar collectors, solar assisted heat pumps, solar air and water heaters, photovoltaic/thermal (PV/T) systems, solar stills, solar cookers, and solar dryers. The commonly used artificial neural network types and architectures in literature, such as multilayer perceptron neural network, a neural network using wavelet transform, Elman neural network, and radial basis function, are also briefly discussed. Different statistical criteria that used to assess the performance of artificial neural network in modeling SE systems have been introduced. Previous studies have reported that artificial neural network is a useful technique to predict and optimize the performance of different solar energy devices. Important conclusions and suggestions for future research are also presented.

Sustainable energy systems: Role of optimization modeling techniques in power generation and supply—A review

Abstract: Electricity is conceivably the most multipurpose energy carrier in modern global economy, and therefore primarily linked to human and economic development. Energy sector reform is critical to sustainable energy development and includes reviewing and reforming subsidies, establishing credible regulatory frameworks, developing policy environments through regulatory interventions, and creating market-based approaches. Energy security has recently become an important policy driver and privatization of the electricity sector has secured energy supply and provided cheaper energy services in some countries in the short term, but has led to contrary effects elsewhere due to increasing competition, resulting in deferred investments in plant and infrastructure due to longer-term uncertainties. On the other hand global dependence on fossil fuels has led to the release of over 1100 GtCO2 into the atmosphere since the mid-19th century. Currently, energy-related GHG emissions, mainly from fossil fuel combustion for heat supply, electricity generation and transport, account for around 70% of total emissions including carbon dioxide, methane and some traces of nitrous oxide. This multitude of aspects play a role in societal debate in comparing electricity generating and supply options, such as cost, GHG emissions, radiological and toxicological exposure, occupational health and safety, employment, domestic energy security, and social impressions. Energy systems engineering provides a methodological scientific framework to arrive at realistic integrated solutions to complex energy problems, by adopting a holistic, systems-based approach, especially at decision making and planning stage. Modeling and optimization found widespread applications in the study of physical and chemical systems, production planning and scheduling systems, location and transportation problems, resource allocation in financial systems, and engineering design. This article reviews the literature on power and supply sector developments and analyzes the role of modeling and optimization in this sector as well as the future prospective of optimization modeling as a tool for sustainable energy systems.

Particle swarm optimization for redundant building cooling heating and power system

Abstract: An optimal and redundant building cooling heating and power (BCHP) system can yield economical savings, but more importantly can save energy as well as reduce the emission of pollutants. This paper presents the energy flow analysis of the conventional separation production (SP) system and the redundant BCHP system. Four decision variables (the capacity of power generation unit (PGU), the capacity of heat storage tank, the on–off coefficient of PGU and the ratio of electric cooling to cool load) to be optimized are selected in consideration of the design and the operation strategy of BCHP system. An objective function to simultaneously measure the energetic, economical and environmental benefits achieved by BCHP system in comparison to SP system is constructed and maximized. Particle swarm optimization algorithm (PSOA) is employed to search the optimal solutions. A case study of BCHP system with thermal storage unit and hybrid cooling system is presented to ascertain the feasibility and validity of the optimization method.