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The utilization of a microgrid with a photovoltaic (PV) and wind generation system presents a challenge due to their voltage and power output variations. This problem is majorly addressed within the converter section of the microgrid using maximum power point tracking (MPPT) algorithms and voltage regulation strategies. This paper presents an interleaved boost converter (IBC) modeling and voltage control using a hybrid adaptive neuro-fuzzy inference system-proportional plus integral plus derivative (ANFIS-PID) controller for an off-grid microgrid. The modeling used the interleaving technique to obtain the microgrid’s transfer function (TF) and case study simulation models within MATLAB and Simulink environments. The performance of the ANFIS-PID controller, which regulates voltage in the microgrid, was compared to that of the traditional proportional integral (PI) controller. Results indicated that the hybrid ANFIS-PID controller performed better than the PI controller in terms of reduced settling time, overshoot, rise time, and the ability to address the nonlinear dynamics of the microgrid.

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In this paper, an autonomous and distributive demand-side management based on Bayesian game theory is developed and applied among users in a grid connected micro-grid with storage. To derive that strategy, an energy consumption of shiftable loads belonging to a given user is modelled as a noncooperative three-player game of incomplete information, in which each user plays against the storage unit and an opponent gathering all the other users in the micro-grid. Each player is assumed to be endowed with statistical information about its behavior and that of its opponents so that he can take actions maximizing his expected utility. Results of the proposed strategy evaluated by simulating, under MATLAB environment, a connected micro-grid with storage device evidence its efficacy when employed to manage the charging of electric vehicles.

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Synchro-phasor technology, using Phasor Measurement Unit (PMU), has improved the way power system data is collected for monitoring through state estimation. The placement of PMUs in a power system presents technical benefits, but it comes with high infrastructural costs. It is, therefore, necessary to install the minimum number of PMUs at optimal locations subject to power system observability, creating the Optimal PMU Placement Problem (OPPP). Some factors may be considered constraints in the OPPP, such as PMU outage. The main challenge with incorporating such constraints in the PMU placement problem is that the minimum number of PMUs required for system observation increases, contributing to the high infrastructural costs. This paper, therefore, proposes using a Linear Hybrid State Estimator (LHSE) that considers existing Remote Terminal Unit (RTU) measurements randomly distributed within the system and optimally placed Phasor Measurement Unit (PMU) measurements. The proposed LHSE addresses challenges associated with nonlinearity in state estimation. The LHSE is also based on the Weighted Least Absolute Value (WLAV) criterion, considered robust and able to detect and discard bad data during the estimation process. The proposed LHSE can address state estimation reliability and resiliency, specifically the PMU outage contingency, by employing existing RTU measurements and optimally placed PMU measurements based on the Artificial Bee Colony (ABC) optimization technique. The proposed approach also leverages RTU and PMU measurements to address PMU loss contingency instead of utilizing PMU measurements only as in existing studies. Three test cases (IEEE 14 Bus, IEEE 30 Bus, and IEEE 57 Bus) are considered, with the simulations performed in MATLAB using MATPOWER data. The performance of LHSE is evaluated considering PMU/RTU measurements and PMU measurements only scenarios. Both RTU/PMU measurements present a lower Normalized Cumulative Error (NCE) performance index than PMU measurements only. In case of a single PMU outage, the proposed LHSE can estimate all states based on RTU/PMU measurements instead of only PMU measurements that fail.INDEX TERMS, Linear hybrid state estimator, optimal placement, phasor measurement unit, remote terminal unit, PMU outage.