Dispatch of wind-thermal power system by using aggregated outputs of virtual power plants

Usage of renewable energy sources, such as wind power, is of major importance in future power grids for economic and environmental reasons, while the intermittent and stochastic nature of such energy brings challenges to system dispatch. Application of the virtual power plant (VPP) concept is one of the most promising ways to better accommodate and utilize renewable power in the grid. Among the many issues of applying VPPs in practice, the aggregated output characteristics of a VPP containing several wind and thermal generators have not been well studied yet. In this paper, a two-phase economic dispatch model considering the aggregated outputs of VPPs is presented for wind-thermal power systems. In phase 1, outputs of VPPs are decided by the grid operator, with characteristics of such VPPs obtained by aggregating those of individual generators. Then in phase 2, a local dispatch among individual generators within each VPPis performed by its aggregator. Both of the above two phase shave linear programming formulations, and numerical tests are performed on an illustrative 3-bus system. Results show that compared with conventional economic dispatch models, our model leads to substantial improvements in wind power utilization and lower generator costs.

[1]  Rene Kamphuis,et al.  Balancing wind power fluctuations with a domestic Virtual Power Plant in Europe's First Smart Grid , 2011, 2011 IEEE Trondheim PowerTech.

[2]  William D'haeseleer,et al.  Bidding strategies for virtual power plants considering CHPs and intermittent renewables , 2015 .

[3]  K. Dielmann,et al.  Virtual power plants (VPP) - a new perspective for energy generation? , 2003, Proceedings of the 9th International Scientific and Practical Conference of Students, Post-graduates Modern Techniques and Technologies, 2003. MTT 2003..

[4]  I. Husain,et al.  Gone with the wind: innovative hydrogen/fuel cell electric vehicle infrastructure based on wind energy sources , 2005, IEEE Industry Applications Magazine.

[5]  Mohammad Shahidehpour,et al.  A probabilistic reliability evaluation of a power system including Solar/Photovoltaic cell generator , 2009, 2009 IEEE Power & Energy Society General Meeting.

[6]  Jean Kumagai Virtual power plants, real power , 2012 .

[7]  Wang Shu-xiang Action analysis of nominal power plants on energy saving and emission controlling of power industry , 2010 .

[8]  Jarosław Milewski,et al.  Virtual Power Plants - general review : structure, application and optimization , 2012 .

[9]  Zhao Yang Dong,et al.  Distributed optimal dispatch of virtual power plant based on ELM transformation , 2014 .

[10]  Zhen Wang,et al.  Control of virtual power plant in microgrids: a coordinated approach based on photovoltaic systems and controllable loads , 2015 .

[11]  S. M. Moghaddas-Tafreshi,et al.  Bidding Strategy of Virtual Power Plant for Participating in Energy and Spinning Reserve Markets—Part II: Numerical Analysis , 2011, IEEE Transactions on Power Systems.

[12]  Tianshu Bi,et al.  The utilization of large-scale renewable powers with high security and efficiency in smart grid , 2012, PES 2012.

[13]  Liu Jizhe,et al.  Review on Virtual Power Plants , 2014 .

[14]  Christof Wittwer,et al.  Decentralised optimisation of cogeneration in virtual power plants , 2010 .

[15]  Ehab F. El-Saadany,et al.  Implementing Virtual Inertia in DFIG-Based Wind Power Generation , 2013, IEEE Transactions on Power Systems.

[16]  Marija D. Ilic,et al.  Balancing wind power with virtual power plants of micro-CHPs , 2009, 2009 IEEE Bucharest PowerTech.

[17]  Wil L. Kling,et al.  Virtual power plants: An answer to increasing distributed generation , 2010, 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe).

[18]  Pierluigi Mancarella,et al.  Real-Time Demand Response From Energy Shifting in Distributed Multi-Generation , 2013, IEEE Transactions on Smart Grid.

[19]  Hongming Yang,et al.  Distributed Optimal Dispatch of Virtual Power Plant via Limited Communication , 2013, IEEE Transactions on Power Systems.

[20]  Shi You,et al.  A market-based Virtual Power Plant , 2009, 2009 International Conference on Clean Electrical Power.

[21]  Henrik W. Bindner,et al.  Utilization of Flexible Demand in a Virtual Power Plant Set-Up , 2015, IEEE Transactions on Smart Grid.

[22]  Danny Pudjianto,et al.  Virtual power plant and system integration of distributed energy resources , 2007 .

[23]  Yu Hu,et al.  Dynamic multi-stage dispatch of isolated wind–diesel power systems , 2015 .

[24]  Marco Giuntoli,et al.  Optimized Thermal and Electrical Scheduling of a Large Scale Virtual Power Plant in the Presence of Energy Storages , 2013, IEEE Transactions on Smart Grid.

[25]  Jagadeesh Pasupuleti,et al.  Self-Scheduling of Wind Power Generation with Direct Load Control Demand Response as a Virtual Power Plant , 2013 .

[26]  Mohammad Kazem Sheikh-El-Eslami,et al.  Decision making of a virtual power plant under uncertainties for bidding in a day-ahead market using point estimate method , 2013 .

[27]  S. M. Moghaddas-Tafreshi,et al.  Bidding Strategy of Virtual Power Plant for Participating in Energy and Spinning Reserve Markets—Part I: Problem Formulation , 2011, IEEE Transactions on Power Systems.

[28]  P. Asmus Microgrids, Virtual Power Plants and Our Distributed Energy Future , 2010 .