Sustainable Energy Optimization in a Smart Microgrid

This chapter titled “Sustainable Energy Optimization in a Smart Microgrid” presented the methodology for developing a smart microgrid optimization model that can be used to determine the most financially economical combination of microgrid technologies with acceptable level of system reliability. The smart microgrid optimization model assessed various combinations of PV and wind turbine renewable generation in increments of 5 kW varying between 0 and 200 kW. Battery energy storage was also considered in combination with renewable generation in increments of 5 kWh from 0 to 200 kWh. The smart microgrid optimization model was developed in the MATLAB environment and incorporated a smart microgrid management system to achieve additional fuel savings and increased system reliability by utilizing load shedding and load deferral techniques. Microgrid power system reliability was assessed using an SMCS simulation model. The accuracy of the model was verified using the SIPSREL program developed at the University of Saskatchewan. Results indicated that the implementation of renewable generation, battery energy storage and DSM techniques can substantially reduce the lifetime operational costs of a microgrid while increasing power system reliability. Implementation of energy storage technologies to reduce fossil fuel consumption as well as to increase renewable generation penetration is an area of ongoing research, as is the application of microgrid technology to improve remote power system reliability.

[1]  M. Matos,et al.  Reliability of distribution networks with microgrids , 2005, 2005 IEEE Russia Power Tech.

[2]  R. Billinton,et al.  Capacity Expansion of Small Isolated Power Systems Using PV and Wind Energy , 2001, IEEE Power Engineering Review.

[3]  Timothy M. Weis,et al.  The utility of energy storage to improve the economics of wind–diesel power plants in Canada , 2008 .

[4]  Chris Marnay.  Lessons Learned from Microgrid Demonstrations Worldwide , 2014 .

[5]  Kankar Bhattacharya,et al.  Optimal planning and design of a renewable energy based supply system for microgrids , 2012 .

[6]  Luai M. Al-Hadhrami,et al.  Study of a solar PV–diesel–battery hybrid power system for a remotely located population near Rafha, Saudi Arabia , 2010 .

[7]  Naresh K. Sinha,et al.  Modern Control Systems , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[8]  J. Halton.  Sequential Monte Carlo , 1962, Mathematical Proceedings of the Cambridge Philosophical Society.

[9]  Syed Islam,et al.  Demand side management for remote area power supply systems incorporating solar irradiance model , 2004 .

[10]  Stanwick Rs.  Balancing the risks: Legionella pneumophila pneumonia and tap water scalds in the home. , 1986, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

[11]  B. Kroposki,et al.  Microgrid standards and technologies , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[12]  Herbert A. Sturges,et al.  The Choice of a Class Interval , 1926 .