Due to the increasing use of renewables into the grid connected through power converters, the rotational inertia in power systems has been reducing. Consequently the frequency response requires the activation of the so-called synthetic inertia control. The synthetic inertia control aims to inject an extra power component when the system experiences a frequency disturbance event. In this paper, it is proposed that a distributed dynamic controllers for sharing the synthetic inertia control actions between the various active power converters in the grid for the improvement of the frequency response. It is assumed that a communication structure between the synthetic inertia controllers and the local power converters is involved in the system. The convergence of the control system is reached through a game population theory and the primary frequency control has been improved. The results are validated based on simulation of a two-area test system.

Sweden is a country with abundant hydro power and has expectations to include more renewable energy sources, namely from wind power, into its electrical system. Currently, in order to improve the frequency response requirements of its electrical system, the country is considering upgrading its hydro-governors. This effort is part of maintaining the system frequency and reaction within their limits following any disturbance events. To partially compensate for increased frequency fluctuations due to an increased share of renewables on its system, the frequency response of hydro-governors should be improved. This paper proposes an innovative network control system, through a supplementary control, for the improvement of the hydro-governor's action. This supplementary control allows having more flexibility over the control action and improves the primary frequency control, and thereby the overall system frequency response. The proposed supplementary control, based on an evolutionary game theory strategy, uses remote measurements and a hierarchical dynamic adjustment of the control. Additionally, in order to guarantee an optimal response, a Simulated Annealing algorithm is combined with the supplementary control. This paper illustrates the analysis and design of the proposed methodology, and is tested on two power systems models: (i) an aggregated model that represents the frequency response of Sweden, Norway and Finland, and (ii) The Nordic 32 test system.

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