Energy storage systems (ESSs) and demand-side management (DSM) strategies have significant potential in providing flexibility for renewable-based distribution networks. Therefore, combining ESSs and DSM strategies with renewable energy sources (RESs) to solve economic, operational, environmental, and power-related political issues has received special attention from power system planners around the world. In this regard, developed countries, which are pioneers in renewable technologies, have proposed various supportive policies and practices for the widespread use of ESSs and DSM strategies in the context of distribution networks. Hence, this paper performs a comprehensive review of the most recent actions taken to build the infrastructure necessary to achieve 100% renewable energy. On this basis, this paper firstly surveys the necessity of using ESSs and DSM strategies in renewable-based distribution networks. Then, the existing policies and incentive programs implemented in different countries for the development of RESs in optimal coordination with ESSs and DSM strategies are presented. The impacts of utilizing ESSs and DSM strategies in improving the economic performance of the renewable-based distribution networks are also investigated. Finally, prevalent energy management strategies, which are proposed to optimize utilization of ESSs and DSM strategies in renewable-based distribution networks, are investigated from the perspective of optimization approaches.

The topology of a distribution network can be represented by a bus injection to branch current (BIBC) matrix. It has been introduced and used for load flow analysis of distribution networks. In this paper, a method for BIBC matrix modification is developed to use in applications which require a topology change representation. Proposed method that reflects the changes in configuration in the system BIBC matrix is implemented in distribution network reconfiguration problem. With providing potential solutions for network operational and planning requirements such as necessitate changes in configurations to transfer the loads to a different substation, ease the loading of equipment, conduct planned maintenance and reduce network losses during the normal operation with renewables, storage and other uprising technologies, reconfiguration may also be useful for emergencies, accidents, attacks and weather-related disasters. The BIBC modification process provides the knowledge of possible switches to open and the direction of power flow without any need to further radiality or continuity check. The proposed method needs only initial network topology information that makes it suitable to apply on any distribution network and to use with any search method or heuristic/meta-heuristic optimization algorithm. Efficiency of the method is investigated on systems with voltage dependent and time varying loads.

In recent years, the rapid increase in the number of internet users and widespread usage of internet applications have obliged large servers and networking equipment to manage large data stack and optimize the instantaneous transmission of digital information. The COVID-19 Pandemic has also caused an increase in data exchanges and digital information generation. In order to manage large-scale data, there is a need for gigantic data centers (DCs) which are tremendous energy consumers and have relatively flexible loads that are easier to control by means of shifting in time and space. Therefore, DCs can be regarded as dispatchable loads and are considered good candidates for participating in demand side management (DSM) programs for power curve smoothing and compensation of power fluctuation in electrical power systems. In this paper, the question of why DCs should participate in DSM has been investigated rather than the technical methods used in DSM. The amount of DCs' participation energy is used by peak shaving/shifting method for power curve smoothing using actual data. The possible environmental and financial effects of it for Turkey and all the world have been carried out. The study results show that DCs' participation in DSM for Turkey decreases peak load by up to 2.18%, defers up to 34% of the installed power plants launched in 2019, and improves load and loss factors by up to 2.2% and 4.3% respectively. Additionally, global DC's participation in DSM decreases the peak point by up to 0.77% and reduces CO ₂ emission by 0.03%.

In this paper, a new conceptual design methodology for a hybrid propulsion system consisting of the battery and hydrogen fuel cells is presented based on the minimum energy consumption of the UAV. In this context, an optimization problem with non-linear constraints is constituted to determine the wing loading, aspect ratio, stall velocity, endurance velocity, battery power, fuel cell power, maximum lift coefficient, and zero-lift drag coefficient of the UAV. The solution to this optimization problem, based on the UAV’s minimum energy consumption for the endurance and cruising flight modes, is implemented by meta-heuristic algorithms: particle swarm optimization, cuckoo search algorithm, artificial bee colony, and genetic algorithm. The results of these algorithms are compared in terms of energy consumption. This article contributes to the literature on sizing fuel cell-powered small UAVs based on minimum energy consumption and comparing different metaheuristics. According to the results, the lowest power consumption of the UAV is obtained by the particle swarm optimization algorithm as 2018.63 W. Additionally, the weight ratios calculated with the parameters obtained from the sizing optimization for the UAV propulsion system components and flight stages are compared with a benchmark study in the literature. Finally, the payload weight ratio is also increased by 28.5% by sizing optimization.