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This paper aims to propose an improved reinforcement learning-based fuzzy-PID controller for load frequency control (LFC) of an island microgrid.

To evaluate the performance of the proposed controller, three different types of controllers including optimal proportional-integral-derivative (PID) controller, optimal fuzzy PID controller and the proposed reinforcement learning-based fuzzy-PID controller are compared. Optimal PID controller and classic fuzzy-PID controller parameters are tuned using Non-dominated Sorting Genetic Algorithm-II algorithm to minimize overshoot, settling time and integral square error over a wide range of load variations. The simulations are carried out using MATLAB/SIMULINK package.

Simulation results indicated the superiority of the proposed reinforcement learning-based controller over fuzzy-PID and optimal-PID controllers in the same operational conditions.

In this paper, an improved reinforcement learning-based fuzzy-PID controller is proposed for LFC of an island microgrid. The main advantage of the reinforcement learning-based controllers is their hardiness behavior along with uncertainties and parameters variations. Also, they do not need any knowledge about the system under control; thus, they can control any large system with high nonlinearities.

With the ongoing digitalization of the construction industry (CI), situational awareness (SA) is becoming increasingly important in construction management. The purpose of this article is to identify the requirements of SA system development in the CI and to provide recommendations for the future development of SA systems.

In this exploratory multi-case research study, a literature review and five Finnish cases were used to gather the evidence on how system developers have planned SA systems and what motives and objectives were behind their development efforts. An analysis of the cases, along with a review of SA models and concepts from other sectors, was used to identify requirements and deficiencies of the SA systems developed by CI actors.

This study reveals deficiencies in the recent SA systems. The systems seemed to be based on traditional project models, in which the role of the individual as the creator and interpreter of an SA system is still significant. Major requirements and future development of the systems are related to better SA levels of perception and projection and data quality.

This study contributes to an understudied area of SA in the construction context and provides new insights into how construction companies develop their SA systems. The main study limitations are its geographically limited case selection and the limited generalizability of the results.

The research (1) shows what requirements and systemic weaknesses SA developers in the CI must consider in future development work and (2) shows developers the requirements to obtain holistic SA.

The study provides insights into the content of newly developed SA models and integrates developers' requirements into the SA theory.