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As the world's demand for sustainable and reliable energy source intensifies, the need for efficient energy storage systems has become increasingly critical to ensuring a reliable energy supply, especially given the intermittent nature of renewable sources. There exist several energy storage methods, and this paper reviews and addresses their growing requirements. In this paper, the energy storage options are subdivided according to their primary discipline, including electrical, mechanical, thermal, and chemical. Different possible options for energy storage under each discipline have been assessed and analyzed, and based on these options, a handsome discussion has been made analyzing these technologies in the hybrid mode for efficient and reliable operation, their advantages, and their limitations. Moreover, combinations of each storage element, hybrid energy storage systems (HESSs), are systems that combine the characteristics of different storage elements for fulfilling the gap between energy supply and demand. HESSs for different storage systems such as pumped hydro storage (PHS), battery bank (BB), compressed air energy storage (CAES), flywheel energy storage system (FESS), supercapacitor, superconducting magnetic coil, and hydrogen storage are reviewed to view the possibilities for hybrid storage that may help to make more stable energy systems in the future. This review of combinations of different storage elements is made based on the previous literature. Moreover, it is assessed that sodium-sulfur batteries, lithium-ion batteries, and advanced batteries are the most helpful element in HESSs, as they can be hybridized with different storage elements to fulfill electricity needs. The results also show that HESSs outperformed other storage systems and, hence, hybridizing the characteristics of different storage elements can be employed for optimizing the performance of energy storage systems. [ABSTRACT FROM AUTHOR]

The optimal PMU placement problem is placing the minimum number of PMUs in the network to ensure complete network observability. It is an NP-complete optimization problem. PMU placement based on cost and critical nodes is solved separately in the literature. This paper proposes a novel approach, a degree of centrality in the objective function, to combine the effect of both strategies to place PMUs in the power network optimally. The contingency analysis and the effect of zero-injection buses are solved to ensure the reliability of network monitoring and attain a minimum number of PMUs. Integer linear programming is used on the IEEE 7-bus, IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, and IEEE 118-bus systems to solve this problem. The results are evaluated based on two performance measures: the bus observability index (BOI) and the sum of redundancy index (SORI). On comparison, it is found that the proposed methodology has significantly improved results, i.e., a reduced number of PMUs and increased network overall observability (SORI). This methodology is more practical for implementation as it focuses on critical nodes. Along with improvement in the results, the limitations of existing indices are also discussed for future work. [ABSTRACT FROM AUTHOR]

The relentlessly depleting fossil-fuel-based energy resources worldwide have forbidden an imminent energy crisis that could severely impact the general population. This dire situation calls for the immediate exploitation of renewable energy resources to redress the balance between power consumption and generation. This manuscript confers about energy management tactics to optimize the methods of power production and consumption. Furthermore, this paper also discusses the solutions to enhance the reliability of the electrical power system. In order to elucidate the enhanced reliability of the electrical system, microgrids consisting of different energy resources, load types, and optimization techniques are comprehensively analyzed to explore the significance of energy management systems (EMSs) and demand response strategies. Subsequently, this paper discusses the role of EMS for the proper consumption of electrical power considering the advent of electric vehicles (EVs) in the energy market. The main reason to integrate EVs is the growing hazards of climate change due to carbon emissions. Moreover, this paper sheds light on the growing importance of artificial intelligence (AI) in the technological realm and its incorporation into electrical systems with the notion of strengthening existing smart grid technologies and to handle the uncertainties in load management. This paper also delineates the different methodologies to effectively mitigate the probability of facing cyber-attacks and to make the smart grids invulnerable. [ABSTRACT FROM AUTHOR]

The increasing penetration of electric vehicles (EVs) in the distribution grid has established them as a prospective resource for ancillary services. These services require adequate control strategies for prompt and efficient operation. In this study, an energy management scheme (EMS) has been proposed to employ an off-board EV smart charger to support the grid during short-term variance of renewables and reactive load onset. The scheme operates by calculating power references for the charger instantaneously. The EMS incorporates a proportional power division methodology, proposed to allocate power references to the individual EVs connected to the charger DC-bus. This methodology considers the state-of-charge and battery sizes of the EVs, and it can aggregate energy from various types of EVs. The proposed scheme is compared with another power allocation method, and the entire EMS is tested under the scenarios of power mismatch and voltage sag/swell events. The results show that the proposed scheme achieves the goal of the aggregation of EVs at the charger level to support the grid. The EMS also fulfills the objectives of voltage regulation and four-quadrant operation of the smart charger. [ABSTRACT FROM AUTHOR]

The lifespan of a battery in battery energy storage systems (BESSs) is affected by various factors such as the operating temperature of the battery, depth of discharge, and magnitudes of the charging/discharging currents supplied to or drawn from the battery. In this study, the optimal location and size of a BESS are found for voltage regulation in a distribution system while increasing the lifespan of the battery. Various factors that affect the lifespan of a battery are considered and modelled. The problem is formulated as a multi-objective optimisation problem with two-objective functions. The first objective function calculates the energy losses in the system, whereas the second objective function represents the total investment cost of the distributed generator (DG) and BESS installations. Wind and solar DGs with uncertainties in their output powers are also considered with the BESSs. An elitist non-dominated sorting genetic algorithm-II with a utopian point method is used to solve the optimisation problem. Furthermore, an IEEE 906 bus European low-voltage test feeder and eight test cases are considered for this study. The results show reduced losses and cost, improvement in the voltage profile, and extended lifespan of the batteries. [ABSTRACT FROM AUTHOR]

The present environmental and economic conditions call for the increased use of hybrid energy resources and, concurrently, recent developments in combined heat and power (CHP) systems enable their use at a domestic level. In this work, the optimal scheduling of electric and gas energy resources is achieved for a smart home (SH) which is equipped with a fuel cell-based micro-CHP system. The SH energy system has thermal and electrical loops that contain an auxiliary boiler, a battery energy storage system, and an electrical vehicle besides other typical loads. The optimal operational cost of the SH is achieved using the real coded genetic algorithm (RCGA) under various scenarios of utility tariff and availability of hybrid energy resources. The results compare different scenarios and point-out the conditions for economic operation of micro-CHP and hybrid energy systems for an SH. [ABSTRACT FROM AUTHOR]

The provision of ancillary services by electric vehicles (EVs) such as load smoothing and renewable energy (RE) compensation in the form of an aggregated storage is more regulated in the smart grid context. As such, the presence of multiple EV aggregators in the distribution network requires adept supervision by the distribution system operator (DSO). In this paper, a coordination scheme of aggregators is proposed to smoothen the load profile of distribution networks by enacting EV discharging during peak load and off-peak charging, keeping in view the EV driving requirements. A bi-level on-line interaction procedure from the DSO to the aggregators and vice versa is devised to manage the aggregators based upon their energy capacity and requirements. The aggregators employ a water-filling algorithm in a two-step EV power allocation method. The proposed scheme operation is demonstrated on an medium voltage (MV) distribution feeder located in Seoul with its actual traffic density data. The results show the achievement of peak shaving and valley filling objectives under aggregator coordination and that the EVs are completely charged before departure. The effect of various EV penetration levels and adaptivity of the scheme to RE incorporation is also verified. Furthermore, a comparison with an existing peak shaving method shows the superior performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

The modern electric power system is foreseen to have increased penetration of controllable loads under demand response programs and renewable energy resources coupled with energy storage systems which can provide virtual inertia. In this paper, the conventional model of an electric power system is appended by considering, individually and collaboratively, the role of demand response and virtual inertia for the purpose of frequency analysis and control. Most existing literature on this topic either considers one of these two roles or lacks in providing a general model of power system with demand response and virtual inertia. The proposed model is presented in general form and can include/exclude demand response and/or virtual inertia. Further, power system operator can opt the power shares from conventional, demand response, and virtual inertia loops for frequency regulation and can also evaluate the impact of other parameters such as time delays and frequency deadbands on system frequency response. The mathematical formulation of steady-state values of frequency deviation and power contribution from all resources is provided and validated by simulation results under various scenarios including a case of wind intermittency. [ABSTRACT FROM AUTHOR]