Energy and power management of hybrid renewable energy systems for remote communities

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Kaluthanthrige, Roshani
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Incorporation of renewable sources and energy storage can contribute to reduce fuel consumption in diesel generation-based remote off-grid power systems. This thesis proposes methodologies for improved management of available generating and storage resources to reduce costs and emissions and investigates the coordination of energy management with power management functions essential for stable operation of the isolated power systems. Firstly, a test system is developed considering a case of retrofitting an existing diesel power system with photovoltaic (PV) generation and battery energy storage. A sizing study conducted using HOMER software with weather and load data for Northern Canada resulted in a PV-Diesel-Battery topology with high PV penetration levels. Next, the energy management functions are developed incrementally in three steps. First, a computationally efficient energy management system (EMS) is implemented to optimize the system operation while incorporating multiple operational requirements essential to remote power systems. Then, a demand response (DR) model that requires minimal bi-directional interactions and therefore implementable without sophisticated communication infrastructure is developed and integrated with the EMS. Thirdly, a computationally efficient two-stage model predictive control process is developed to compensate for forecast uncertainties. Finally, the power management functions necessary to achieve a logical real-time operation are implemented and coordinated with the energy management functions in a hierarchical architecture. Also, an operation evaluation framework is suggested to assess the viability of the optimum operation routines under dynamic conditions. After adding PV and energy storage to an existing diesel-only system and optimizing the operation with the DR integrated EMS, over 60% cost and emission reductions are achieved for a representative summer day compared to the diesel-only operation. The cost and emission reductions achieved for a representative winter day are 31% and 11%, respectively. During the intra-day operation, the proposed uncertainty management framework navigates the system judiciously and achieves cost and emission performance closer to that is obtainable when perfect forecast information is available in a computationally efficient manner. Numerous tests verify the correct operation of the proposed power management strategies and the utility of the operation evaluation framework while demonstrating the importance of coordination of the energy and power management functions.
Energy management, Power management, Demand response, Uncertainty management, Hybrid renewable energy systems, Hierarchical control, Operation optimization, Remote power systems
R. Kaluthanthrige, A. D. Rajapakse, C. Lamothe, and F. Mosallat, “Optimal Sizing and Performance Evaluation of a Hybrid Renewable Energy System for an Off-Grid Power System in Northern Canada,” Technol. Econ. Smart Grids Sustain. Energy, vol. 4, no. 1, pp. 24–26, 2019, doi: 10.1007/s40866-019-0061-5.
R. Kaluthanthrige and A. D. Rajapakse, “Demand response integrated day-ahead energy management strategy for remote off-grid hybrid renewable energy systems,” Int. J. Electr. Power Energy Syst., vol. 129, no. February, p. 106731, 2021, doi: 10.1016/j.ijepes.2020.106731.
R. Kaluthanthrige and A. D. Rajapakse, “Evaluation of hierarchical controls to manage power, energy and daily operation of remote off-grid power systems,” Appl. Energy, vol. 299, no. June, p. 117259, 2021, doi: 10.1016/j.apenergy.2021.117259.
R. Kaluthanthrige and A. D. Rajapakse, “Two-stage framework for optimizing the operation of remote off-grid power systems under uncertainties,” Int. J. Electr. Power Energy Syst., vol. 135, p. 107553, 2022, doi:
R. Kaluthanthrige and A. D. Rajapakse, "Operational Optimization of a Remote Off-Grid Hybrid Renewable Energy System in Northern Canada," 2019 IEEE 7th International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, ON, Canada, 2019, pp. 268-273, doi: 10.1109/SEGE.2019.8859885.
R. Kaluthanthrige and A. D. Rajapakse, "Use of Probabilistic Fuzzy Inference Systems to Model Demand Response in the Off-grid Power Systems of Northern Canada," 2019 14th Conference on Industrial and Information Systems (ICIIS), Kandy, Sri Lanka, 2019, pp. 419-424, doi: 10.1109/ICIIS47346.2019.9063281.