Droop Control of Distributed Electric Springs for Stabilizing Future Power Grid Matlab/Simulink Projects


This paper describes the droop control method for parallel operation of distributed electric springs for stabilizing ac power grid. It provides a methodology that has the potential of allowing reactive power controllers to work in different locations of the distribution lines of an ac power supply and for these reactive power controllers to support and stabilize the ac mains voltage levels at their respective locations on the distribution lines. The control scheme allows these reactive power controllers to have automatically adjustable voltage references according to the mains voltage levels at the locations of the distribution network. The control method can be applied to reactive power controllers embedded in smart electric loads distributed across the power grid for stabilizing and supporting the ac power supply along the distribution network. The proposed distributed deployment of electric springs is envisaged to become an emerging technology potentially useful for stabilizing power grids with substantial penetration of distributed and intermittent renewable power sources or weakly regulated ac power grid.


  1. Droop control
  2. Electric springs
  3. Smart gird
  4. Voltage regulation




Fig. 1. Single phase diagram of the experimental setup of the power grid and loads (with 3 distributed electric springs working as a group).


Fig. 2. (a) Measured root-mean-square values of the mains voltage VS1,VS2 and VS3 (b) Measured root-mean-square values of the mains voltage VS1,VS2 and VS3 from 1800 to 1440 sec (ES activated without the proposed droop control) (c) Measured root-mean-square values of the mains voltage VS1,VS2 and VS3 from 1800 to 2160 sec (ES activated with the proposed droop control).

Fig. 3. Measured average value of reactive power generated by the 3 electric springs (Qa1 ,Qa2 and Qa3 ).

Fig. 4. Measured modulation indexes of the electric springs M1,M2 and M3 .

Fig. 5. Measured average value of the critical load power PR1,PR2 and PR3 .

Fig. 6. Measured root-mean-square values of the non-critical load voltage Vo1 ,Vo2 and Vo3 .

Fig. 7. Measured average value of the non-critical load power Po1,Po2 and Po3


A control scheme has been successfully developed and implemented for a group of electric springs. It enables individual electric springs to generate their mains voltage reference values according to their installation locations in the distribution lines and to work in co-operative manner, instead of fighting against one another, therefore allowing the electric springs to work in group to maximize their reactive power compensation effects for voltage regulation. The control method also leads to more evenly distribution of load power shedding among the non-critical loads. The attractive features of the control scheme have been successfully verified in an experimental smart grid setup.

With the droop control scheme,many electric springs of small VA ratings could be embedded into non-critical loads such as electric water heaters and refrigerators to form a new generation of smart loads that are adaptive to power grid with substantial penetration of renewable energy sources of distributed and intermittent nature. If many small electric springs are deployed in the power grid in a distributed manner, their collective voltage stabilizing efforts can be added together. Because the electric springs allow these smart loads to consume power following the varying profile of intermittent renewable energy sources, they have the potential to solve the stability problems arising from the intermittent nature of renewable energy sources and ensure that the load demand will follow power generation, which is the new control paradigm for future smart grid. Since the electric appliances embedded with the electric springs can share load shedding automatically, this approach should be more consumer-friendly when compared with the on-off control of electric appliances. For example, shutting down refrigerators is intrusive and inconvenient to the consumers (and may involve consumers’ rights issues) and requires some forms of central control. Allowing many smart refrigerators to shed some load without being noticed and central control is more consumer- friendly.

The individual operations of the electric springs have previously been evaluated. The successful implementation of the droop control for 3 electric springs working as a group in a small distributed network in this study is a just a step forward to confirm that multiple electric springs can work together without ICT technology. The collective effects of electric springs and their capacity are new topics that deserve further investigations. Extensive simulation studies are needed to confirm the effectiveness of many such electric springs working together in a large-scale power system model.


[1] P. P. Varaiya, F. F. Wu, and J. W. Bialek, “Smart operation of smart grid: Risk-limiting dispatch,” Proc. IEEE, vol. 99, no. 1, pp. 40–57, 2011.

[2] D. Westermann and A. John, “Demand matching wind power generation with wide-area measurement and demand-side management,” IEEE Trans. Energy Conversion, vol. 22, no. 1, pp. 145–149, 2007.

[3] P. Palensky and D. Dietrich, “Demand side management: Demand response, intelligent energy systems, and smart loads,” IEEE Trans. Ind. Informatics, vol. 7, no. 3, pp. 381–388, 2011.

[4] A. Mohsenian-Rad, V. W. S. Wong, J. Jatskevich, R. Schober, and A. Leon-Garcia, “Autonomous demand-side management based on gametheoretic energy consumption scheduling for the future smart grid,” IEEE Trans. Smart Grid, vol. 1, no. 3, pp. 320–331, 2010.

[5] M. Parvania and M. Fotuhi-Firuzabad, “Demand response scheduling by stochastic SCUC,” IEEE Trans. Smart Grid, vol. 1, no. 1, pp. 89–98,2010.

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