• Energy Research

Abstract Because of environmental issues and the depletion of fossil fuels, the world energy sector is undergoing many changes toward increased sustainability. Among the many fields of research and development, power generation from low-grade heat sources is gaining interest and the organic Rankine cycle (ORC) is seen as one of the most promising technologies for such applications. In this paper, it is proposed to perform an experimentally-validated comparison of different modelling methods for the off-design simulation of ORC-based power systems. To this end, three types of modelling paradigms (namely a constant-efficiency method, a polynomial-based method and a semi-empirical method) are compared both in terms of their fitting and extrapolation capabilities. Post-processed measurements gathered on two experimental ORC facilities are used as reference for the models calibration and evaluation. The study is first applied at a component level (i.e. each component is analysed individually) and then extended to the characterization of the entire organic Rankine cycle power systems. Benefits and limitations of each modelling method are discussed. The results show that semi-empirical models are the most reliable for simulating the off-design working conditions of ORC systems, while constant-efficiency and polynomial-based models are both demonstrating lack of accuracy and/or robustness.

Abstract Organic Rankine Cycle is an efficient and reliable technology for the thermal-to-electricity conversion of low-grade heat sources but the variability in boundary conditions often forces these systems to operate at off-design conditions. The development of reliable models for the performance prediction of organic Rankine cycle power systems under off-design conditions is therefore crucial for system-level integration and control implementation. In this paper, a mathematical model for the evaluation of the expected performance of organic Rankine cycle power units in a large range of operating conditions based on experimental data collected in a medium-size solar organic Rankine cycle power plant is presented. Two different empirical approaches for the performance prediction of heat exchangers and machines, namely, constant-efficiency and correlated-based approaches, are proposed and compared. In addition, empirical correlations based on experimental data are proposed for the preliminary assessment of the energy demanded during the start-up phase and the corresponding duration. Results demonstrate that a good achievement in terms of accuracy of the model and reliability of the simulation performance can be obtained by using a constant-efficiency approach, with average errors lower than 5% and 2.5 K for the expected net power and outlet oil temperature respectively. The use of polynomial correlations leads to a more accurate estimation of the performance parameters used for evaporator and the turbine (in particular the evaporator heat effectiveness and the isentropic and electromechanical efficiency for the turbine), which strongly affect the main output variables of the model and, at the same time, are remarkably influenced by the operating conditions. A reduction in the average error in the prediction of the net power and outlet temperature of the heat transfer fluid to about 4% and 1.5 K respectively is therefore achieved by this approach. Average errors of 18.5% and 12.5% are achieved for the start-up time and the corresponding energy absorbed, respectively. Although the results obtained in terms of accuracy could be improved, these correlations can give an initial indication about the duration and energy required during this phase.

AbstractHolzkirchen full scale dynamic experiments were conducted in the framework of IEA Annex 58 research program with the aim to obtain and apply a high quality experimental dataset for model validation of full scale buildings. A first experiment was conducted in August 2013. Two identical houses were submitted to a side by side experiment, one with blinds up, one with blinds down. That first experience lasted 42 days including an initialization period, a Randomly Ordered Logarithmic Binary Sequence of heat inputs (ROLBS), and a re-initialization followed by a free-float period. A second experiment was conducted in April 2014 in one of the two houses, with higher levels of heating power in the South oriented zones and imposed indoor temperatures in the North oriented zones. Simulations were performed with EES Engineering Equation Solver using simplified RC dynamic models. The discrepancies observed between simulated results and measured data were first explained through a deeper analysis of thermal bridges, a better assessment of solar heat gains and a better assessment of the air duct heat losses. In the second experiment, the results revealed an underestimation of the building transmission heat losses. A candidate explanation might be the air stratification which would enhance heat losses on the ceiling side. A modelization of the upper and lower room air layers was introduced. The resulting simulated indoor temperature profiles were in accordance with the measurements.A complete breakdown of heat losses and heat gains was computed for both houses, using measured temperatures as input data for the simulation.

Abstract The present paper focuses both on the thermodynamic and on the economic optimization of a small scale ORC in waste heat recovery application. A sizing model of the ORC is proposed, capable of predicting the cycle performance with different working fluids and different components sizes. The working fluids considered are R245fa, R123, n-butane, n-pentane and R1234yf and Solkatherm. Results indicate that, for the same fluid, the objective functions (economics profitability, thermodynamic efficiency) lead to different optimal working conditions in terms of evaporating temperature: the operating point for maximum power doesn’t correspond to that of the minimum specific investment cost: The economical optimum is obtained for n-butane with a specific cost of 2136 €/kW, a net output power of 4.2 kW, and an overall efficiency of 4.47%, while the thermodynamic optimum is obtained for the same fluid with an overall efficiency of 5.22%. It is also noted that the two optimizations can even lead to the selection of a different working fluid. This is mainly due to additional fluid properties that are not taken into account in the thermodynamic optimization, such as the fluid density: a lower density leads to the selection of bigger components which increases the cost and decreases the economical profitability.

Abstract Rapid deployment of health service infrastructure is underway to meet the growing needs of populations in sub-Saharan Africa, however the energy infrastructure needed to support high quality services has tended to lag. Understanding the electrical and thermal energy needs of health centers constructed with local building methods and materials and operating outside of the jurisdiction of heating, ventilation and air conditioning (HVAC) codes is complicated by a lack of appropriately scaled and configured energy system design frameworks and validation data for dynamic simulations. In this work we address this gap by linking the thermal envelope performance of health center buildings under heating and cooling loads with measured indoor air temperature, meteorological conditions, and operational electricity demand. A resistance-capacitive type energy balance model is parameterized using typical health center architectural data for sub-Saharan Africa (floor plans from Uganda and Lesotho) and heat transfer characteristics; to achieve this energy flows between HVAC equipment, internal loads, and ambient conditions are simulated on an hourly time step with indoor temperature thresholds representative of thermostat settings. A typical meteorological year dataset for Lesotho is used as a case study, validated with indoor temperature measurements and power metering at four health center sites spanning a daily patient load ranging from 15 to 450 per day over rural and urban communities. High resolution electricity measurements from smart meters installed at the clinics are used to close the energy balance and form the basis of a probabilistic method for forecasting long term hourly electricity demand in African health centers. These data and the corresponding method have relevance to energy system design for health clinics across sub-Saharan Africa, especially those featuring intermittent renewable generation. The integration of these two modeling approaches constitutes a novel tool for sizing and costing energy infrastructure to meet operational demand at health centers in both urban and rural areas of developing countries.

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Abstract A detailed mechanistic model has been developed for scroll compressors and scroll expanders with liquid flooding for application to the Liquid Flooded Ericsson Cycle. This model is based on the integration of a set of differential equations that arise from the conservation laws. The impact of the flooding liquid on the working process is also included through mixture properties as well as treatment of two-phase flow pressure drop. With the working process known, it is then possible to solve for the compressor power, total mass flow rate and other model outputs. The fine level of detail in the model allows for the investigation of the impact of design changes to the scroll machines. This model can also be readily extended to allow for the analysis of liquid flooded vapor compression refrigeration.