Discrete cogeneration optimization with storage capacity decision support for dynamic hybrid solar combined heat and power systems in isolated rural villages

Significance Statement

Smart technology, deployed in rural village energy systems, has emerged as a prominent concept to relieve global energy poverty. It promotes the integration of renewable distributed energy resources by allowing improved data capture, energy management, and control automation. The development of new technologies and control processes, in order to bring clean energy to people living in rural off-grid areas, is needed as an alternative to paraffin and wood-fuel.

Solar cogeneration systems have the ability to attain considerably high levels of energy efficiency. These systems are designed to produce heat and electricity from the same device by recovering energy that would otherwise have been wasted making them suitable for district energy systems in off-grid areas. Solar cogeneration systems are inspiring a large number of developers to come up with packaged cogeneration systems, their emphasis being on functional controller design and scheduling optimization.

Unfortunately, control optimization for systems operating as stand-alone power packs in eco-villages often lack access to wideband wireless and cellular linkage infrastructure. Online control and optimization, therefore, becomes a challenge. Gerro Prinsloo and Robert Dobson from Stellenbosch University, South Africa, in collaboration with Andrea Mammoli from University of New Mexico, USA, focused on an integrated on-board control and optimization technique in a bid to realize load demand balancing with specific communication and cost restraints. Their work is published in Energy.

A storage optimization solution was proposed in the study and evaluated within the confines of an energy storage scenario for a rural solar microgrid. They used predicted generation and energy consumption profiles. Using this information along with other economical, physical and environmental restraints, the researchers were able to come up with a day-ahead control plan using an integrated integer linear programming technique.

The authors overlaid the discrete rural village electrical demand per hour onto the main supply contribution. Doing so, they highlighted the mismatch between peak load demand and the solar supply. It was possible to schedule the supply from a consumer point of view, but it wasn’t possible to shift produced loads to a period when excess energy was generated. Load shifting carefully took into consideration daily schedules of the villagers as not to be disruptive. Optimizing the generation schedule allowed the self-consumption and self-generation microgrid controller to reduce the effect on the consumer budget.

It was clear that a significant amount of solar energy was lost during the peak sunlight hours. This was mainly due to a limited microgrid storage capacity. The researchers, therefore, developed a storage optimization decision support system in a bid to curtail the added cost effect on the user. The system could now compare and track operating costs and storage extension capital cost. This would alert the user of billing cost versus operating cost savings that could be obtained by increasing the battery and hot water storage capacity.

Experimental results obtained by the authors indicate that incremental storage optimization can provide energy management efficiency and reduced customer bills. The developed hybrid decision support system ensured that less energy was dumped due to automated microgrid storage capacity specifications. The storage cost optimization gave approximately 66% reduction in daily microgrid liquefied petroleum gas (LPG) costs while the storage optimization posted an approximate annual financial gain of $130, as a result of reduced waste of energy.

cogeneration optimization with storage capacity decision support for dynamic hybrid solar

About the author

Andrea Mammoli is Professor of Mechanical Engineering at the University of New Mexico, and Director of the Center for Emerging Energy Technologies, an organization within the School of Engineering dedicated to research on the integration of distributed energy resources on the electricity grid through system architecture and controls. Mammoli has been active in the field of distributed energy systems since 2005, with projects including solar-assisted HVAC in commercial buildings, building-scale energy storage, distribution-level PV and battery systems, and microgrids, in the context of optimization and controls leading to better economics and enhanced resilience.

He conducts research in collaboration with the Electric Power Research Institute, Sandia National Laboratories and Lawrence Berkeley National Laboratory, among others. Mammoli obtained a Ph.D. in mechanical and materials engineering in 1995 from the university of Western Australia, and was Director’s Fellow at Los Alamos National Laboratory between 1995 and 1997 in the Energy and Process Engineering group, prior to joining UNM.

About the author

Gerro Prinsloo is a Mechatronic Engineer and PhD Engineering student at the Department of Mechanical & Mechatronic Engineering at Stellenbosch University in South Africa and the Department of Mechanical Engineering at the University of New Mexico in the USA. He specializes in the mechanical and electronic design aspects of solar thermal systems and solar electrical power generation. He received his Bachelor’s degree in Mechatronic Engineering from Stellenbosch University in 2011 and a Master’s degree in Mechatronic Engineering from Stellenbosch University in 2014. His PhD research is being conducted at the Centre for Emerging Energy Technologies (CEET) at the University of New Mexico in Albuquerque and aims to solve challenges faced by rural African villages in terms of solar cogeneration systems with smart Microgrid distribution.

This research aims to implement novel energy management principles to support the use of renewable energy technologies in rural applications. He is a member of the Solar Thermal Energy Research Group (STERG) and a Candidate Professional Engineer with the Engineering Council of South Africa (ECSA) and he continues with Smartgrid research at the CEET Mesa Del Sol Research Labs in Albuquerque.

About the author

Robert Dobson received his degree in Mechanical Engineering in 1969 and his postgraduate degree in Nuclear Engineering in 1970. He then registered as a Professional Engineer in 1973. He worked at the then Atomic Energy Board until 1980 and gained experience in the design, manufacture and testing of reactor components and systems. He then joined Kwikot LTD and gained experience in the design, manufacture and marketing of electric and solar water heaters and heat pumps. From 1985 and 1987 he was Engineering Services Manager at Kentron Pty LTD, a missile systems manufacturing company. Since 1988 he has been a Lecturer at the University of Stellenbosch. He now gives undergraduate courses in Food Engineering and Heat Transfer. He also gives postgraduate and specialist courses in Twophase Flow and Heat Transfer, and Nuclear Reactor Safety-Systems Engineering.

His research interests are in heat transfer using closed and closed-loop single and two-phase natural circulation thermosyphon-type heat pipes, and thermal management and control using heat pipes and other two-phase flow and heat transfer devices. The research focus on heat to electrical power conversion system safety and reliability enhancement using passive natural circulation systems. Over the past 15 years he has published 56 peer reviewed papers, presented 71 papers at international conferences, supervised 21 thesis projects and is at present supervising and co-supervising 6 Masters and PhD thesis projects.


Gerro Prinsloo2, Andrea Mammoli1, and Robert Dobson1. Discrete cogeneration optimization with storage capacity decision support for dynamic hybrid solar combined heat and power systems in isolated rural villages. Energy, volume 116 (2016), pages 1051-1064

Show Affiliations
  1. Centre for Renewable and Sustainable Energy Studies, Thermodynamic Research Group, Stellenbosch University, Stellenbosch, South Africa
  2. Centre for Emerging Energy Technologies, University of New Mexico, Albuquerque, USA


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