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The household sector in Pakistan became the largest consumer of electricity which is responsible for more than 51% of the national consumption. The Building Energy Code of Pakistan was developed in 1990, yet the institutional setup regarding energy efficiency & conservation is inadequate. There is lack of experts and implementation of policies at national and provincial level. The study aims to explore the energy efficiency and conservation policies in Pakistan and their impact on reducing household energy consumption. The issues related to the implementation of policies across the country have been further discussed. The paper provides an overview of the energy sector and its challenges related to residential buildings. Energy policies, standards and literature related to building sector were analyzed and discussed with the experts. Moreover, suggestions and recommendations are made for the possible solutions and improvement of the existing situation.

Introduction. In an electrical power system, the output of the synchronous generators varies due to disturbances or sudden load changes. These variations in output severely affect power system stability and power quality. The synchronous generator is equipped with an automatic voltage regulator to maintain its terminal voltage at rated voltage. Several control techniques utilized to improve the response of the automatic voltage regulator system, however, proportional integral derivative (PID) controller is the most frequently used controller but its parameters require optimization. Novelty. In this paper, the chaotic sequence based on the logistic map is hybridized with particle swarm optimization to find the optimal parameters of the PID for the automatic voltage regulator system. The logistic map chaotic sequence-based initialization and global best selection enable the algorithm to escape from local minima stagnation and improve its convergence rate resulting in best optimal parameters. Purpose. The main objective of the proposed approach is to improve the transient response of the automatic voltage regulator system by minimizing the maximum overshoot, settling time, rise time, and peak time values of the terminal voltage, and eliminating the steady-state error. Methods. In the process of parameter tuning, the Chaotic particle swarm optimization technique was run several times through the proposed hybrid objective function, which accommodates the advantages of the two most commonly used objective functions with a minimum number of iterations, and an optimal PID gain value was found. The proposed algorithm is compared with current metaheuristic algorithms including conventional particle swarm optimization, improved kidney algorithm, and others. Results. For performance evaluation, the characteristics of the integral of time multiplied squared error and Zwe-Lee Gaing objective functions are combined. Furthermore, the time-domain analysis, frequency-domain analysis, and robustness analysis are carried out to show the better performance of the proposed algorithm. The result shows that automatic voltage regulator tuned with the chaotic particle swarm optimization based PID yield improvement in overshoot, settling time, and function value of 14.41 %, 37.91 %, 1.73 % over recently proposed IKA, and 43.55 %, 44.5 %, 16.67 % over conventional particle swarm optimization algorithms. The improvement in transient response further improves the automatic voltage regulator system stability for electrical power systems.

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The determination of the transient stability of an electric power system is a crucial step in power system analysis. This paper investigates the transient stability of an IEEE-9 bus system consisting of three generators and nine buses. At first, a load flow analysis is conducted in order to determine the pre-fault conditions. Secondly, fault analysis is performed to analyze post fault conditions like the fast fault clearing time and load switching in order to determine the system stability. For transient stability analysis, Euler and Runga methods are compared and applied on the frequency and rotor angle of the system to analyze the system variations under different fault conditions. The simulations were done on the Power World Simulator (PWS) software. It is concluded that Critical Fault Clearing Time (CFCT) is a very important factor in keeping the power system within the stability bounds. A slight increase in Clearing Time (CT) from the critical value causes un-synchronism.