Structural Condition for Controllable Power Flow System Containing Controllable and Fluctuating Power Devices

This paper discusses a structural property for a power system to continue a safe operation under power fluctuation caused by fluctuating power sources and loads. Concerns over global climate change and gas emissions have motivated development and integration of renewable energy sources such as wind and solar to fulfill power demand. The energy generated from these sources exhibits fluctuations and uncertainty which is uncontrollable. In addition, the power fluctuations caused by power loads also have the same consequences on power system. To mitigate the effects of uncontrollable power fluctuations, a power flow control is presented which allocates power levels for controllable power sources and loads and connections between power devices. One basic function for the power flow control is to balance the generated power with the power demand. However, due to the structural limitations, i.e., the power level limitations of controllable sources and loads and the limitation of power flow channels, the power balance may not be achieved. This paper proposes two theorems about the structural conditions for a power system to have a feasible solution which achieves the power balance between power sources and power loads. The discussions in this paper will provide a solid theoretical background for designing a power flow system which proves robustness against fluctuations caused by fluctuating power devices.

[1]  Farzam Nejabatkhah,et al.  Overview of Power Management Strategies of Hybrid AC/DC Microgrid , 2015, IEEE Transactions on Power Electronics.

[2]  Sara Lumbreras,et al.  Optimal transmission network expansion planning in real-sized power systems with high renewable penetration , 2017 .

[3]  Azman Osman Lim,et al.  System design and analysis for maximum consuming power control in smart house , 2014 .

[4]  Jianxue Wang,et al.  Multi-period planning of multi-energy microgrid with multi-type uncertainties using chance constrained information gap decision method , 2020 .

[5]  P. Malbranche,et al.  Lead–acid batteries in stationary applications: competitors and new markets for large penetration of renewable energies , 2005 .

[6]  M. Ehsan,et al.  Possibilistic Evaluation of Distributed Generations Impacts on Distribution Networks , 2011, IEEE Transactions on Power Systems.

[7]  Catherine Aliana Gucciardi Garcez Distributed electricity generation in Brazil: An analysis of policy context, design and impact , 2017 .

[8]  Y Riffonneau,et al.  Optimal Power Flow Management for Grid Connected PV Systems With Batteries , 2011, IEEE Transactions on Sustainable Energy.

[9]  Rikiya Abe,et al.  Digital Grid: Communicative Electrical Grids of the Future , 2011, IEEE Trans. Smart Grid.

[10]  Takashi Matsuyama,et al.  Power Flow Coloring System Over a Nanogrid With Fluctuating Power Sources and Loads , 2017, IEEE Transactions on Industrial Informatics.

[11]  Ebrahim Farjah,et al.  Power Control and Management in a Hybrid AC/DC Microgrid , 2014, IEEE Transactions on Smart Grid.

[12]  Takashi Matsuyama,et al.  Cooperative Distributed Control Implementation of the Power Flow Coloring Over a Nano-Grid With Fluctuating Power Loads , 2017, IEEE Transactions on Smart Grid.

[13]  Il-Woo Lee,et al.  Smart home energy management system including renewable energy based on ZigBee and PLC , 2014, IEEE Transactions on Consumer Electronics.

[14]  Il-Woo Lee,et al.  PLC-based photovoltaic system management for smart home energy management system , 2014, IEEE Transactions on Consumer Electronics.

[15]  Richard Duke,et al.  DC-Bus Signaling: A Distributed Control Strategy for a Hybrid Renewable Nanogrid , 2006, IEEE Transactions on Industrial Electronics.

[16]  Paul Denholm,et al.  Evaluating the limits of solar photovoltaics (PV) in electric power systems utilizing energy storage and other enabling technologies , 2007 .

[17]  Takashi Hikihara,et al.  AC Power Routing System in Home Based on Demand and Supply Utilizing Distributed Power Sources , 2011 .

[18]  Yasuo Tan,et al.  Stability Analysis for Smart Homes Energy Management System with Delay Consideration , 2014 .

[19]  Pierluigi Mancarella,et al.  Flexible distributed multienergy generation system expansion planning under uncertainty , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[20]  Sehyun Park,et al.  Design and implementation of intelligent energy distribution management with photovoltaic system , 2012, IEEE Transactions on Consumer Electronics.