This paper reviews the optimization strategies for the optimal simultaneous allocation of distributed generation (DG) and shunts capacitor banks (SCBs) in electrical distribution networks. These optimization strategies aim to determine the optimal size, location, and combination of DGs and SCBs to constitute a techno-economic system while satisfying the constraints and energy demand of the load. The optimization strategies explicitly reviewed include the problem formulations, optimization techniques, restrictions posed for optimization problems, decision variables, and network operating modes typically assumed while allocating the DGs and SCBs. In addition, there is an attempt to highlight the limitations of the existing literature and future research directions. This study undertakes a comprehensive review of the literature that systematically considers the simultaneous application of DGs and SCBs to advance the existing literature, which lacks such a review. Expectedly, this review will serve as a principle platform for researchers intending to explore the subject area for further improvement.

The rapid economic and population growth in developing countries, effective and efficient energy usage has turned out to be crucial due to the rising concern of depleting fossil fuels, of which, one-third of primary energy is consumed in buildings and expected to rise by 53% up to 2030. This roaring sector posing a challenge, due to 90% of people spend most of their time in buildings, requires enhanced well-being of indoor environment and living standards. Therefore, building operations require more energy because most of the energy is consumed to make the indoor environment comfortable. Consequently, there is the need of improved energy efficiency to decrease energy consumption in buildings. In relation to this, the primary challenge of building control systems is the energy consumption and comfort level are generally conflicting to each other. Therefore, an important problem of sustainable smart buildings is to effectively manage the energy consumption and comfort and attain the trade-off between the two. Thus, smart buildings are becoming a trend of future construction that facilitates intelligent control in buildings for the fulfillment of occupant’s comfort level. In this study, an intelligent multi-objective system has been developed with evolutionary multi-objective genetic algorithm (MOGA) optimization method. The corresponding case study simulation results for the effective management of users’ comfort and energy efficiency have been carried out. The case study results show the management of energy supply for each comfort parameter and maintain high comfort index achieving balance between the energy consumption and comfort level

The cyclical nature and high investment costs of the wind and photovoltaic renewable energy sources are the two critical issues seeking attention for the use of such systems in backup or isolated applications. This paper aims to present the experimental and economic analysis of a wind–photovoltaic-based hybrid direct current microgrid (DCMG) system for backup power and off-grid isolated power generation system for emergency purposes. The two distributed generating units comprising photovoltaic panels and wind generator were designed and developed for the experimental study. A lead-acid battery is also added as an energy storage system to enhance the system supply. The electric load of this system comprise of 42 DC light emitting diode (LED) lamps of 12 Watt each and a 25 Watt DC fan. The charge controller provides the control and protection features for the designed system. The complete system design and fabrication of this system have been undertaken at Mehran University of Engineering & Technology (MUET, Jamshoro, Pakistan). The compatibility of the designed system has been analysed by comparing the Levelized Cost of Energy (LCOE) with a conventional gasoline generator system of the same capacity. The capital, running and lifetime costs of DCMG are found to be 1.29, 0.15 and 0.29 times those of the gasoline generator, respectively. Moreover, it is found that per unit cost of gasoline generator is $0.3 (i.e., PKR 31.4) which is almost 3.4 times higher than that of the hybrid DCMG system. The performance and cost evaluation of the designed system indicate its broad potential to be adopted for commercialisation to meet backup power and off-grid power requirements. This study concludes that proposed DCMG system is a not only low cost, but also a pollution-free alternative option compared to the existing traditional small gasoline generator system.