With the increase in requirement of low-carbon economy and demand on power supply reliability from customers, more and more attention is being paid on distributed generations (DGs). As an effective means of integration of DGs to the power system, microgrid is being more of a concern. Microgrid integrates DGs, load, storage and control system into a single controllable unit, which can either operate in grid-connected mode or in isolated mode, thus provides a new way for remote rural electrification. There are still some remote rural areas in developing countries nowadays, to where the cost of delivering power from the grid is relatively high. Even if lines are constructed to deliver power from the grid, the power supply quality would be unacceptable due to long distance of power delivery. Microgrid that utilizes renewable energy resources (RES) would be a promising solution for power supply problem of these areas. The main object of this paper is to develop an optimal unit sizing methodology for remote autonomous microgrid with multiple energy sources. In order to truly reflect the value of RES, both economical and environmental objectives are considered in the optimization model in this paper. By deducting environmental benefit of RES DGs from their high initial capital cost, competitiveness of RES DGs can be greatly improved. Differing from conventional power system planning, microgrid planning should consider operation and control problem because control strategy of microgrid has a great impact on the energy contribution of different DGs. An energy dispatching strategy aiming to maximize the utilization of RES and fuel saving is proposed in the paper, and hourly simulation of one year is performed in the planning process. Case study results show that considering the environmental benefit of RES DGs will increase the proportion of wind turbine and PV with a considerable increase of environmental benefit. Although there is a slight increase in the annual total cost compared with the planning result without considering environmental benefit, the true value of RES can be better reflected. The impact of diesel fuel price and average wind speed on unit sizing of microgrid is also investigated. Results show that the increase of diesel fuel price and average wind speed leads to a decrease of proportion of diesel generator in microgrid and increase of contribution of wind and PV generation. For remote areas with a relatively high cost of diesel fuel transportation and abundant renewable energy resource, the value of microgrid utilizing renewable resources can be even raised.
[1]
F. Katiraei,et al.
Diesel Plant Sizing and Performance Analysis of a Remote Wind-Diesel Microgrid
,
2007,
2007 IEEE Power Engineering Society General Meeting.
[2]
Riccardo Poli,et al.
Particle swarm optimization
,
1995,
Swarm Intelligence.
[3]
Arash Navaeefard,et al.
Optimal sizing of distributed energy resources in microgrid considering wind energy uncertainty with respect to reliability
,
2010,
2010 IEEE International Energy Conference.
[4]
T. Logenthiran,et al.
Short term generation scheduling of a Microgrid
,
2009,
TENCON 2009 - 2009 IEEE Region 10 Conference.
[5]
H. Vahedi,et al.
Optimal unit sizing of Distributed Energy Resources in MicroGrid using genetic algorithm
,
2010,
2010 18th Iranian Conference on Electrical Engineering.
[6]
Shun Ke.
Environmental cost analysis and research of different power plants
,
2004
.
[7]
T. Logenthiran,et al.
Optimal sizing of an islanded microgrid using Evolutionary Strategy
,
2010,
2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems.
[8]
H. B. Gooi,et al.
Sizing of energy storage system for microgrids
,
2010,
2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems.
[9]
Mohammad Shahidehpour,et al.
The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee
,
1999
.
[10]
Walter G. Scott,et al.
Distributed Power Generation Planning and Evaluation
,
2000
.
[11]
Nathanael Greene,et al.
Small and Clean Is Beautiful: Exploring the Emissions of Distributed Generation and Pollution Prevention Policies
,
2000
.
[12]
G. Joos,et al.
A Stochastic Optimization Approach to Rating of Energy Storage Systems in Wind-Diesel Isolated Grids
,
2009,
IEEE Transactions on Power Systems.
[13]
Geza Joos,et al.
Energy storage system scheduling for an isolated microgrid
,
2011
.
[14]
Zhiyong Yuan,et al.
Microgrid planning and operation: Solar energy and wind energy
,
2010,
IEEE PES General Meeting.
[15]
James Kennedy,et al.
Particle swarm optimization
,
2002,
Proceedings of ICNN'95 - International Conference on Neural Networks.