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The power framework has become a vital part in the day-to-day life and exhibits a rapid development in this current era. Due to the fact of huge power utilization, the power frameworks fall under several power transmission-related concerns. Precisely, frequency deviation has generated a huge impact during power transmission; this in turn highly reduces the power system stability as well as reliability too.

To boost the system’s efficacy, this study proposes a neoteric closed loop feedback controller in which a control algorithm named correlative-elemental-curvature algorithm is introduced with a constant threshold.

With the aim of mitigating frequency deviation, a stability analysis technique called Retrofit Lyapunov’s method is deployed in the controller. This would simultaneously reduce the load disturbances along with tie-line synchronization issues faced with the prior controllers. Optimization is carried out with the aid of duelist optimization algorithm, which tunes the controller parameters thereby mitigating the complexities while designing a loop feedback controller power framework.

The efficacy of the proposed work is assessed with the aid of metrics, such as integral absolute error, accuracy and settling time. Thus, the proposed work enhances the system reliability as well as the stability by mitigating the frequency deviation related issues and guarantees reliable power transmission.

The main objective of safety instrumented systems (SISs) is to maintain a safe condition of a facility if hazardous events occur. However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).

The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).

A case study concerning a safety instrumented system implemented in the RGTE facility has shown the great applicability of the proposed approach and the results are encouraging. The results show that the selection of a good maintenance strategy allows a very significant minimization of the PFDavg, the frequency of spurious trips and Life Cycle Costs of SIS.

The maintenance strategy defined by the system designer can be modified and improved during the operational phase, in particular safety systems. It constitutes one of the least expensive investment strategies for improving SIS performances. It has allowed a considerable minimization of the SIS life cycle costs; PFDavg and the frequency of spurious trips.

With the problem of environment and energy becoming prominent, energy conservation and emission reduction have received more attention. In the using process, buildings not only have the inherent energy consumption but also have the energy consumption of equipment that is installed for improving the indoor environment. This study aims to investigate how to reduce the energy consumption of buildings through utilizing natural resources.

This paper briefly introduces three objective functions in the building energy-saving model: building energy consumption, natural lighting and natural ventilation. Genetic algorithm was used to optimize the building parameters to achieve energy conservation and comfort improvement. Then a two-story rental building was analyzed.

The genetic algorithm converged to Pareto optimal solution set after 10,000 times of iterations, which took 61024 s. The lowest energy consumption of the scheme that was selected from the 70 optimal solutions was 5580 W/(m²K), the lighting coefficient was 5.56% and Pressure Difference Pascal Hours (PDPH) was 6453 h; compared with the initial building parameters, the building energy consumption reduced by 3.40%, the lighting coefficient increased by 11.65% and PDPH increased by 9.54%.

In short, the genetic algorithm can effectively optimize the energy-saving parameters of buildings.

Political economy is a term in wide use and has been for centuries. Yet standard economic theory reduces politics to ethics or economics. This reduction is enabled by the presumption of closed choice data or given utility and cost functions. In this conceptual framework, the political vanishes into an activity of preference satisfaction according to a welfare function (ethics) or into trade (economics). To bring the political back to life within a theory of political economy requires that closed schemes of thought be replaced by open schemes. The ways in which individuals react to the indeterminacy of their subjective choice data, in innocuous small-scale settings as well as in situations of dramatic exception to constitutional rules, separates them into leaders and followers. Followership creates an opportunity for political enterprise at the social level (enterprise in rules) and at the subjective level (enterprise in visions of options, and hence preferences). At both levels the political comes to the fore of political economy as an answer to the “challenge of exception.” Much of our inspiration for this argument traces to the work of Friedrich Wieser, Carl Schmitt, and Vincent Ostrom.