Following are summaries of some of our current and recent research. Learn more on our publications page.
Latent Heat Thermal Energy Storage
Thermal energy storage (TES) systems can reduce electric demand when used in conjunction with combined heat and power plants. They can also be used to integrate renewable energy sources like solar thermal with the grid. Latent heat storage systems are attractive because of their high energy storage density and energy availability at fixed temperature. They are also relatively inexpensive, especially if organic materials are used as the phase changing material. Latent heat thermal energy storage can become a viable TES technology, if a design procedure and performance modeling of phase change heat exchangers is available.
Kedar Shete, a current Ph.D. student, is working on creating design correlations for phase change storage design using a shell and tube heat exchanger system as a starting point. As an extension, we are exploring the relative importance of geometric parameters and physical properties of materials on the performance of storage devices. We are also exploring the methods of modeling natural convection with phase change. Our results are obtained through finite volume simulations of these devices and are verified by experimental results. Another part of the research focuses on extrapolating results obtained for one system to model large systems comprising of multiple units.
Melting of Phase Change Material Video 1 Video 2
Integration of Renewable Energy Sources into the Power Grid
Richard Bryce, a recent Ph.D. graduate conducted research at the National Renewable Energy Laboratory (NREL) in Golden, Colorado. He is studying how the variability of PV power generation within the UMass campus microgrid impacts the reliability of the power system. He is also interested in exploring how optimally dispatched storage might be employed to mitigate reliability issues introduced by the variability of PV power generation.
Demand Forecasting and Battery Discharge Scheduling
Akhil Soman, a recent graduate, studied electric demand forecasting and battery discharge scheduling and working to develop an algorithm that predicts demand and schedules the optimal discharge time. This research will be applied to the lithium-ion battery pack that is in the process of being installed on the UMass campus. The unit cost charged by the utility for demand changes during the day based on the systemwide demand, so using the battery to offset electricity imports during peak periods will reduce the demand charges paid by the University.
Thermodynamic Analysis of a Combined Cycle District Heating System
Recent graduate Sharan Suresh performed a thermodynamic analysis to assess performance of the UMass combined heat and power (CHP) district heating system. Energy and exergy analyses were performed based on the first and second laws of thermodynamics for power generation systems that include a 10-MW Solar combustion gas turbine, a 4-MW low-pressure steam turbine, a 2-MW high-pressure steam turbine, a 100,000 pph heat recovery steam generator (HRSG), three 125,000 pph package boilers, and auxiliary equipment. The system delivers all of the steam and nearly all the electricity to the more than 200 buildings and nearly 10 million gross square feet of building space on the Amherst campus. The exergy analysis showed that performance improvements related to the steam generation unit operations and scheduling could lead to a 4% reduction in fuel consumption and annual cost savings of close to $130,000.
Operational Planning in Combined Heat and Power Systems
Recent graduate Hariharan Gopalakrishnan, Ph.D., studied methodologies for operational planning in combined heat and power (CHP) systems, specifically the CHP and district energy system on the UMass campus. Systems like this have complex energy flow networks, due to multiple interconnected thermodynamic components like gas and steam turbines, boilers and heat recovery steam generators and also interconnection with centralized electric grids. In district energy applications, heat and power requirements vary over 24-hour periods (the planning horizon) due to changing weather conditions, time-of-day factors and consumer requirements. System thermal performance is highly dependent on ambient temperature and operating load, because component performances are nonlinear functions of these parameters. Electric grid charges are much higher for on-peak than off-peak periods, onsite fuel choices vary in prices and cheaper fuels are available only in limited quantities. In order to operate such systems in an energy efficient, cost effective way while minimizing pollutant emissions, optimal scheduling strategies need to be developed. This study using mixed-integer nonlinear programming (MINLP) formulations and actual system operation data showed that optimal scheduling can improve system efficiency by 6%, reduce cost by 11% and emissions by 14%.