Traditional hierarchical control of the microgrid does not consider the energy storage status of a distributed hybrid energy storage system. This leads to the inconsistency of the remaining capacity of the energy storage system in the process of system operation, which is not conducive to the safe and stable operation of the system. In this paper, an improved hierarchical control strategy is proposed: the first allocation layer completes the allocation between the distribution energy storage systems considering the state of hybrid energy storage systems, and the second allocation layer realizes the allocation within the hybrid energy storage systems based on variable time constant low-pass filtering. Considering the extreme conditions of energy storage systems, the transfer current is introduced in the second allocation process. The SOC (stage of charge) of the supercapacitor is between 40% and 60%, which ensures that the supercapacitor has enough margin to respond to the power demand. An example of a 300 MW photovoltaic microgrid system in a certain area is analyzed. Compared with the traditional hierarchical control, the proposed control strategy can reduce the SOC change of a hybrid energy storage system by 9% under the same conditions, and make the supercapacitor active after power stabilization, which is helpful to the stable operation of the microgrid.

pH neutralization reaction process plays a crucial role in Waste Water Treatment Process (WWTP). Traditional PID Proportion Integral Differential, (or even advanced PID control) algorithms have poor performance on WWTP due to the strong non-linearity, large time lag, and large inertia characteristics of pH neutralization. Therefore, finding a superior control method to maintain the pH value of wastewater within the normal range will greatly help to improve the efficiency and effectiveness of wastewater treatment. The chemical reaction mechanism of pH neutralization reaction process is first analyzed, and a mechanistic model of pH neutralization reaction process is developed based on the reaction of ions during acid-alkali neutralization and the electric balance equation. Then, combining the characteristics of generalized predictive control and Model-Free Adaptive Control (MFAC), a Model-Free Adaptive Predictive Control (MFAPC) method based on compact format dynamic linearization is introduced. An Improved Model Free Adaptive PI Predictive Control algorithm (IMFAPC) with proportional (P) and integral (I) algorithms is proposed to further improve the control performance. IMFAPC is proposed on the basis of MFAPC, combining the advantages of generalized predictive control, introducing a PI module consisting of error and error sum, and predicting the PI module, making it possible to produce more accurate constraints on the control inputs, avoiding increasing errors, and improving the control effect of delayed systems at the same time. pH neutralization process simulation experimental results show that compared with the ordinary Model-Free Adaptive Control (MFAC) and MFAPC, the IMFAPC control algorithms has the best performance in terms of accuracy, overshoot, and the robustness.

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