The green innovations in the energy sector are smart solutions to meet the excessive power requirements through renewable energy resources (RERs). These resources have forwarded the revolutionary relief in control of carbon dioxide gaseous emissions from traditional energy resources. The use of RERs in a heuristic manner is necessary to meet the demand side management in microgrids (MGs). The pricing scheme limitations hinder the profit maximization of MG and their customers. In addition, recent pricing schemes lack mechanistic underpinning. Therefore, a dynamic electricity pricing scheme through linear regression is designed for RERs to maximize the profit of load customers (changeable and unchangeable) in MG. The demand response optimization problem is solved through the particle swarm optimization (PSO) technique. The proposed dynamic electricity pricing scheme is evaluated under two different scenarios. The simulation results verified that the proposed dynamic electricity pricing scheme sustained the profit margins and comforts for changeable and unchangeable load customers as compared to fixed electricity pricing schemes in both scenarios. Hence, the proposed dynamic electricity pricing scheme can readily be used for real microgrids (MGs) to grasp the goal for cleaner energy production.

In view of scarcity of traditional energy resources and environmental issues, renewable energy resources (RERs) are introduced to fulfill the electricity requirement of growing world. Moreover, the effective utilization of RERs to fulfill the varying electricity demands of customers can be achieved via demand response (DR). Furthermore, control techniques, decision variables and offered motivations are the ways to introduce DR into distribution network (DN). This categorization needs to be optimized to balance the supply and demand in DN. Therefore, intelligent algorithms are employed to achieve optimized DR. However, these algorithms are computationally restrained to handle the parametric load of uncertainty involved with RERs and power system. Henceforth, this paper focuses on the limitations of intelligent algorithms for DR. Furthermore, a comparative study of different intelligent algorithms for DR is discussed. Based on conclusions, quantum algorithms are recommended to optimize the computational burden for DR in future smartgrid.

Mobile applications and social networks tend to enhance the needs for high‐quality content access. To address the expeditious growing demand for data services in 5G cellular networks, it is important to develop distribution techniques and an efficient content caching, aiming to significantly reduce redundant data transmission and, thus, improve the efficiency of the networks. In modern communication systems, caching has emerged as a vital tool for reducing peak data rates. It is anticipated that energy harvesting and self‐powered small base stations are the fundamental part of next‐generation cellular networks. However, uncertainties in energy are the main reason to adopt energy efficient power control schemes to reduce SBS energy consumption and ensure the quality of services for users. Using the edge cooperative caching such as energy efficient design can also be achievable, which reduces the usage of the capacity limited SBSs backhaul and the energy consumption. To support the huge power demand of cellular network, renewable energy harvesting technologies can be leveraged. In addition to this, power supply to the infrastructures is the main challenge to the mobile network operators (MNOs) especially in terms of economic optimum, sustainability, and green energy in developing countries for the growth of cellular networks. Renewable energy–based solutions for MNOs not only reduce the overall carbon dioxide emissions but also provide numerous profits.

The growing demand for enhanced capacities, broadband services, and high transmission speeds to accommodate speech, image, multimedia, and data communication simultaneously puts a requirement for antenna to operate in multiple frequency bands. A novel compact fractal antenna based on self-similar stair-shaped fractal geometry is proposed in this paper. The fractal antenna is designed by modifying the patch antenna through the iterative process using stair-shaped fractal geometry. The third iteration results in a tri-band response, and the antenna resonate at 3.65, 4.825, and 6.325 GHz with impedance bandwidths of 75.6, 121.2, and 211.4 MHz, respectively. The antenna is designed in CST Microwave studio, and evaluated for operating bands and radiation characteristics. Prototype for the third iteration of the fractal antenna is fabricated on FR-4 substrate which is further tested for measured operating bands and radiation characteristics. The simulated and measured results show good agreement.

Purpose Antenna miniaturization, multiband operation and wider operational bandwidth are vital to achieve optimal design for modern wireless communication devices. Using fractal geometries is recognized as one of the most promising solutions to attain these characteristics. The purpose of this paper is to present a unique structure of patch antenna using hybrid fractal technique to enhance the performance characteristics for various wireless applications and to achieve better miniaturization. Design/methodology/approach In this paper, the authors propose a novel hybrid fractal antenna by combining Koch and Minkowski (K-M) fractal geometries. A microstrip patch antenna (MPA) operating at 1.8 GHz is incorporated with a novel K-M hybrid fractal geometry. The proposed fractal antenna is designed and simulated in CST Microwave studio and compared with existing Koch fractal geometry. The prototype for the third iteration of the K-M fractal antenna is then fabricated on FR-4 substrate and tested through vector network analyzer for operating band/voltage standing wave ratio. Findings The third iteration of the proposed K-M fractal geometry results in achieving a 20% size reduction as compared to an ordinary MPA for the same resonant frequency with impedance bandwidth of 16.25 MHz and a directional gain of 6.48 dB, respectively. The operating frequency of MPA also lowers down to 1.44 GHz. Originality/value Further testing for the radiation patterns in an anechoic chamber shows good agreement to those of simulated results.