On-line minimization of running costs, greenhouse gas emissions and the impact of distributed generation using microgrids on the electrical system

Distributed generation systems composed of non-renewable and renewable power sources is one of the best approaches for reducing greenhouse gas emissions. Nevertheless, uncontrolled integration of power sources in the distribution system may have negative effects on efficiency and working parameters. Global optimization of distributed generation in the system is not available, but microgrids arrangements make it possible to the design management systems which are able to control their working parameters and give fast responses to internal events without affecting the distribution system. This work presents a new active-power dispatch algorithm capable of adjusting microgrid generation to demand on-line in grid-connected-mode. It also reduces the greenhouse gas emissions to a minimum, and optimizes running costs of microsources. The algorithm uses a heuristic approach based on cost functions of microsources and has been tested to solve different power dispatch cost optimization problems. The results obtained are superior to those obtained by applying state-of-the-art optimization methods, in terms of global cost and emissions, system stability, and computational resources requirements. This reduction of the requirements of computational resources makes it possible to run the algorithm on-line, using an off-the-shelf programmable logic controller or microcontroller. Thus, the infrastructure requirements and new investments are reduced and the penetration of microgrids based on renewable energies is improved.

[1]  Mohammad S. Alam,et al.  Dynamic behavior of PEM fuel cell and microturbine power plants , 2007 .

[2]  J.R. Abbad,et al.  Assessment of energy distribution losses for increasing penetration of distributed generation , 2006, IEEE Transactions on Power Systems.

[3]  R.H. Lasseter,et al.  Autonomous control of microgrids , 2006, 2006 IEEE Power Engineering Society General Meeting.

[4]  Shin'ya Obara Dynamic Characteristic of a Fuel Cell Micro-Grid Using an Engine Generator to Base Load Operation * , 2008 .

[5]  J.A.P. Lopes,et al.  Defining control strategies for MicroGrids islanded operation , 2006, IEEE Transactions on Power Systems.

[6]  Robert H. Lasseter,et al.  Microgrids And Distributed Generation , 2007, Intell. Autom. Soft Comput..

[7]  Rolf D. Reitz,et al.  Multidimensional simulation of diesel engine cold start with advanced physical submodels , 2000 .

[8]  T.C. Green,et al.  Fuel consumption minimization of a microgrid , 2005, IEEE Transactions on Industry Applications.

[9]  Ian F. Roth,et al.  Incorporating externalities into a full cost approach to electric power generation life-cycle costing , 2004 .

[10]  Marcelo Godoy Simões,et al.  Electrical Model Development and Validation for Distributed Resources , 2007 .

[11]  Goran Strbac,et al.  Microgrids - Large Scale Integration of Microgeneration to Low Voltage Grids , 2006 .

[12]  Filipp Fedorov Microgrids and their operations , 2007 .

[13]  João Peças Lopes,et al.  Management of Microgrids , 2003 .

[14]  Faisal A. Mohamed,et al.  Microgrid modelling and online management , 2008 .

[15]  H.N. Koivo,et al.  System Modelling and Online Optimal Management of MicroGrid Using Multiobjective Optimization , 2007, 2007 International Conference on Clean Electrical Power.

[16]  Stephen Daniel Gurski,et al.  Cold-start effects on performance and efficiency for vehicle fuel cell systems , 2002 .

[17]  Timothy C. Green,et al.  Real-World MicroGrids-An Overview , 2007, 2007 IEEE International Conference on System of Systems Engineering.