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• Recent advances in discovery and performance prediction of energy storage materials relying on ML. • An overview of the current status and dilemmas of ML databases commonly used in energy storage materials. • ML in energy storage material discovery and performance prediction: typical applications and examples. • Dilemmas to be faced in the development of ML-assisted or led energy storage materials, and corresponding prospects. Energy storage material is one of the critical materials in modern life. However, due to the difficulty of material development, the existing mainstream batteries still use the materials system developed decades ago. Machine learning (ML) is rapidly changing the paradigm of energy storage material discovery and performance prediction due to its ability to solve complex problems efficiently and automatically. Various excellent works are constantly emerging in the field of ML assisted or dominated development of energy storage material, such as exploring of new materials, studying of battery performance, investigating of battery aging mechanism. In this paper, we methodically review recent advances in discovery and performance prediction of energy storage materials relying on ML. After a brief introduction to the general workflow of ML, we provide an overview of the current status and dilemmas of ML databases commonly used in energy storage materials. The typical applications and examples of ML to the finding of novel energy storage materials and the performance forecasting of electrode and electrolyte materials. Furthermore, we explore the dilemmas that will be faced in the development of applied ML-assisted or dominated energy storage materials and propose a corresponding outlook. This review systematically summarizes the current development of ML-assisted energy storage materials research, which is expected to point the way for its further development. [ABSTRACT FROM AUTHOR]

• The self-assembly of supramolecular hydrogels and their physio-chemical properties are described. • The applications in stimuli responsiveness, energy storage and energy conversions, etc., are summarized. • For supramolecular hydrogels, none of the review papers provide comprehensive summaries of recent advancements and applications. This review article highlights the potential of supramolecular hydrogels as emerging energy materials. Supramolecular hydrogels are a class of soft materials with unique properties, such as self-healing, self-assembly, stimuli responsiveness, and biocompatibility, making them an attractive platform for various energy applications. The article discusses the definition, properties, and advantages of supramolecular hydrogels in energy materials. It further explores the recent advances in the field, such as self-healing properties, surface functionalization, and stimuli-responsive behavior. The article concludes by discussing the current challenges and future perspectives on using supramolecular hydrogels in energy materials. Overall, supramolecular hydrogels hold great potential as versatile and sustainable materials for energy storage and conversion, and further research in this area can lead to the development of novel energy solutions. [ABSTRACT FROM AUTHOR]

Recently, with the development of new energy technologies, all-electric ships (AESs) with hybrid energy storage system (HESS) are becoming a promising solution to reduce fuel consumption and emissions. However, the high maneuverability of ships during the actual navigation places higher performance requirements on the HESS, which presents a nonlinear and multi-objective challenge for the HESS design. Therefore, it is necessary to consider the coupling between HESS sizing and energy management strategy (EMS). In this paper, a self-adaptive joint optimization framework (SJOF) for marine HESS design considering load fluctuation characteristics is proposed, which can find the optimal decision solution with excellent system economic and battery life performance for AES HESS design. Based on the rain flow counting (RFC) method, a multi-objective joint optimization method considering life cycle cost (LCC) and battery degradation index (BDI) is introduced into SJOF. Besides, a novel EMS including the self-adaptive segmentation mechanism (SSM) and power allocation is proposed, which can achieve the most efficient energy scheduling. • A self-adaptive working condition classification approach is proposed. • A power allocation strategy with optimal filter matching is proposed. • A reconstruction method for obtaining optimal solution set is proposed. [ABSTRACT FROM AUTHOR]

• A novel concept of mobile energy storage is proposed in this paper. • A detailed modeling of mobile compressed air energy storage with higher dispatchability and storage capacity is presented. • In concern to routing challenges, Google map's Application Programming Interface is used to find the target location. • A new heuristic-based technique that overcomes deficiencies of traditional constraint handling methods is proposed. • The proposed framework is tested through the IEEE 33-bus and 136-bus networks with different scenarios. • Various reliability indices and operating profits are measured to demonstrate the applicability of the proposed technology. Efficient energy storage technology is one of the key elements to enhance the flexibility, economy, and security of the power system. With the continuous development of energy storage technology, containerized mobile energy storage is coming into view, which has offered promising opportunities to improve distribution network (DN) performances and grid operating factors against emergencies. This paper proposes the concept of mobile compressed air energy storage (CAES) for an electric DN. The movable air storage tanks with stored energy are transported by trucks and placed at some distribution nodes/buses to improve DN performance. To overcome routing challenges for trucks, the configuration of the grid is mapped on the urban region of the city of Sydney, Australia, using Google map's Application Programming Interface. This approach can accurately model distances between current and targeted locations, unavailability of tanks during traveling, route congestions, and fuel consumptions. A new heuristic mathematical method is proposed in this paper to convert the constraints of the mobile CAES (MCAES) model into feasible search spaces, which significantly improves the convergence quality and speed. Operating results for both stationary and mobile CAESs are presented and compared. The methodology is applied to IEEE 136-bus DN in addition to IEEE 33-bus DN to demonstrate the competence of MCAES for larger-scale grids in optimizing the total operating profit, active power loss, energy not supplied, and voltage stability index of the grid. The crucial application of the proposed model can deal with natural disasters to avoid large-scale power outages and, eventually, mitigate the power system damages. [ABSTRACT FROM AUTHOR]

• A hierarchical approach is proposed considering quartile method for optimization. • Proposed CEEMDAN-DMD can regress the energy based on pre-set energy proportion. • Proposed hierarchical allocation strategy can be used for severe power volatility. The development of renewable energy dominated power system and the integration of large-scale wind-storage energy system are inevitable trends of the future society. This paper developed a new methodology of hierarchical power allocation strategy considering wind power fluctuation. A novel idea is presented that fully considers the fluctuation and energy proportion. Based on the Quartile Method (QM) and Hampel-Savitzky Golay (HSG) strategy, a layered-based method that considers the volatility interval to effectively overcome the limitations of a single strategy caused by severe volatility interval is proposed. Then, an improved power division method based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Dynamic Mode Decomposition (DMD) is proposed where CEEMDAN is used to decompose the Intrinsic Mode Function (IMF) of the remaining fluctuations. Furthermore, according to the required setting of energy proportion, DMD strategy is used for power fitting of the hybrid energy storage system (HESS). Through experimental verification, the hierarchical strategy proposed in this paper can effectively reduce the probability of severe volatility interval or distortion interval and ensure the sequence in the ideal interval. Moreover, the proposed CEEMDAN-DMD strategy can realize the power division according to the energy proportion demand. In model verification, the volatility improvement ζλ 1 min = 85.4766%. Set the energy demand ≥ 80%, the fitting energy proportion accounts for 87.7533%, which outperforms the traditional power division method. In addition, it is demonstrated that the theoretical method proposed in this paper is reliable and promising. [ABSTRACT FROM AUTHOR]

The rapid development of renewable energy sources (RESs) facilitates the coordinated operation of different energy sources to hedge against the uncertain and non-dispatchable nature of RESs. In this paper, we propose an effective approach for ultra-short-term optimal operation of a photovoltaic-energy storage hybrid generation system (PV-ES HGS) under forecast uncertainty. First, a generic approach for modelling forecast uncertainty is designed to capture PV output characteristics in the form of scenarios. Then, stochastic model predictive control (SMPC) is utilized in the coordinated operation of PV-ES HGS for load shifting under forecast uncertainty. Finally, a PV-ES power station located in Northeast China is selected as a case study to validate the feasibility and effectiveness of the proposed method in detail. The results show that: (1) The forecast uncertainty modelling method, which incorporates adaptive kernel density estimation (KDE) and two-layer nested copula, could capture the characteristics of PV output effectively. (2) The proposed sampling procedure ensures the representativeness and temporal dependence of scenarios extracted from the joint predictive density, leading to stability and efficiency in solving the stochastic optimization problems. (3) The SMPC-based coordinated operation strategy exhibits significant superiority in load shifting performance and resistance to risks. The standard deviation of residual load (SDORL) is reduced by 17.5% on average compared to the conventional scheme. Thus, this work provides operators with guidance in the ultra-short-term optimal operation of a PV-ES HGS under forecast uncertainty. [Display omitted] • Integration of adaptive KDE and two-layer copula to model PV forecast uncertainty. • Proposal of a representative scenario generation method incorporating LH and CD. • Utilization of scenario-based SMPC to optimize ultra-short-term PV-ES HGS operation. • Identification of trade-off between load shifting performance and operational risks. [ABSTRACT FROM AUTHOR]

• A high W rec = 7.3 J/cm3 is obtained in BT-based ceramics by "high-entropy" strategy. • The highest η = 94.3 % reported so far has been achieved in BNBSCTN ceramics. • The correlation between four effects and energy storage performance is emphasized. One of the major problems in ceramic capacitors is that their limited energy storage density (W rec) and efficiency restrict the development in cutting-edge energy storage applications. In this paper, the non-equimolar ratio high-entropy ceramics are designed using the "entropy" strategy based on the traditional ferroelectric BaTiO 3. Ultimately, the superparaelectric region of BaTiO 3 is extended successfully, forming the local polymorphic distortion structure and realizing the transformation of ferroelectrics-relaxor ferroelectrics. Here, the outstanding W rec of 7.3 J/cm3, the excellent ξ of 214.71 J/kV·m2, and the highest energy storage efficiency (η = 94.3 %) in high-entropy ceramics are obtained under moderate electric fields, indicating a breakthrough progress in energy storage applications of high-entropy relaxor ferroelectrics. Additionally, our work compared performance across multiple dimensions using measurement parameters, giving readers a more comprehensive reference. [ABSTRACT FROM AUTHOR]

• Study of microgrid with energy-stored quasi-Z-source cascaded H-bridge multilevel inverter and PV system. • Development of energy management system based on model predictive control (MPC-EMS). • Results compared with proportional sharing algorithm based on SOC level (SOC-EMS). • Best results obtained from MPC-EMS. This paper presents a new energy management system (EMS) based on model predictive control (MPC) for a microgrid with solar photovoltaic (PV) power plants and a quasi-Z-source cascaded H-bridge multilevel inverter that integrates an energy storage system (ES-qZS-CHBMLI). The system comprises three modules, each with a PV power plant, quasi-impedance network, battery energy storage system (BESS), and voltage source inverter (VSI). Traditional EMS methods focus on distributing the power among the BESSs to balance their state of charge (SOC), operating in charging or discharging mode. The proposed MPC-EMS carries out a multi-objective control for an ES-qZS-CHBMLI topology, which allows an optimized BESS power distribution while meeting the system operator requirements. It prioritizes the charge of the BESS with the lowest SOC and the discharge of the BESS with the highest SOC. Thus, both modes can coexist simultaneously, while ensuring decoupled power control. The MPC-EMS proposed herein is compared with a proportional sharing algorithm based on SOC (SOC-EMS) that pursues the same objectives. The simulation results show an improvement in the control of the power delivered to the grid. The Integral Time Absolute Error, ITAE, achieved with the MPC-EMS for the active and reactive power is 20 % and 4 %, respectively, lower than that obtained with the SOC-EMS. A 1,3 % higher charge for the BESS with the lowest SOC is also registered. Furthermore, an experimental setup based on an OPAL RT-4510 unit and a dSPACE MicroLabBox prototyping unit is implemented to validate the simulation results. [ABSTRACT FROM AUTHOR]

With the development of distributed energy resources, the peer-to-peer (P2P) transactive energy market has emerged as an effective method for consuming the excess renewable energy on the end-user side. In the current research on transactive markets, distributed energy storages (DESs) have been widely applied in energy trading for transaction flexibility and system management. These small-scale energy storages have achieved a considerable momentum that, if properly harnessed, may unleash their potential for prosumers' utility maximization, reserves for renewable energy uncertainty, and transmission congestion relief. The present work reviews distributed energy storage in the transactive market, classifying and analyzing 120 papers according to their applications, algorithms, and adopted policies. This study first identifies DES functions in wholesale and transactive markets and then provides the mathematical models of DESs in various transactive market types in detail. This paper then focuses on the pricing mechanism for the DESs' contributions in the P2P transactive energy market. A transactive energy market mechanism for accommodating DESs is proposed based on the Vickrey–Clarke–Groves framework to meet incentive compatibility. The energy policies related to the promotion of DESs in electricity markets are listed and compared. Furthermore, this review highlights the possible questions and future development opportunities according to the analyzed studies. With the roles and relationships among aggregators, DES owners, and power grid determined, the benefit of participating P2P transactive market can be further improved. [Display omitted] • We analyze the application of distributed energy storage in electricity markets. • We focus on reviewing distributed energy storages in transactive energy market. • We propose a Vickrey–Clarke–Groves mechanism for accommodating energy storages. • The future development and possible questions are discussed in detail. [ABSTRACT FROM AUTHOR]

Reusable launchers have been studied under CNES contracts for more than 30 years, with early concepts such as STS-2000 or Oriflamme, more recently with very significant efforts devoted to Liquid Fly Back Boosters as with the Bargouzin project led with Tsniimash, TSTO with the Everest concept studied by Airbus-DS as prime contractor or the RFS Reusable First Stage concept of a large first stage associated to a cryotechnic second stage. These investigations, summarized in the first part of the paper, enabled CNES to identify clearly the technology requirements associated to reusability, as well as cost efficiency through detailed non-recurring costs and mission costs analysis. In parallel, CNES set in place development logic for sub-systems and equipment based on demonstrators, hardware test benches enabling maturation of technologies up to a TRL such that an actual development can be decided with limited risk. This philosophy has been applied so far to a large number of cases, such as TPTech and TPX for Hydrogen turbo pump, GGPX as demonstrator of innovative gas generator, HX demonstrator of modern cryotechnic upper stage with a dozen of different objectives (Thermal Protection, 20K Helium storage, measurements …). This virtuous approach, “learn as you test”, is currently applied in the phased approach towards scaled down reusable booster stage, whose possibility to be used as first stage of a microlaunch vehicle is under investigation. The selected technologies allow paving the way towards reusable booster stages for Ariane 6 evolutions or main reusable stage for a further generation of heavy launchers. The paper describes the logic behind this project, together with the demonstration objectives set for the various sub-systems as well as operations. [ABSTRACT FROM AUTHOR]

The Energy Act of 2020 authorizes $1 billion over five years from 2021 to 2025 to support energy storage development in the United States. In addition, the Federal Energy Regulatory Commission (FERC) Orders 841 and 2222 opened the wholesale energy markets for distributed energy resources, including energy storage. The statute and orders pave the way for novel energy storage technologies to participate in electricity markets as the qualifying facilities, thereby expanding opportunities for energy storage development. However, the existing policy, legal, and regulatory regime, including these much-welcomed newcomers, fails to recognize and support the entire spectrum of benefits that some forms of energy storage create. In this paper, we focus on Pumped Underground Storage Hydro (PUSH), a variant of pumped hydro storage (PHS), which currently provides over 90% of the world's energy storage capacity. PUSH operates with the same principle as PHS; however, it is an entirely underground variant of PHS. In addition to becoming competitive in the wholesale electricity market, PUSH facilities can be developed as community infrastructure in the postindustrial landscape, particularly in abandoned underground mines. Given federal energy law and policy development, this paper identifies how communities with abandoned mines, technically feasible for PUSH facilities and operating as municipal-owned utilities or cooperatives, can participate and take advantage of federal legislation. We further look into the implications through the lens of technical, economic, and social aspects of energy justice. We consider energy justice as a conceptual framework that seeks to explain the occurrence of injustice within energy system decisions and outcomes and how policymakers can respond to these injustices. We use it as a conceptual tool for understanding policy formulation and detailing the energy system's missing ethical and justice dimension. We argue that as a technically mature technology, PUSH facilities can act as a potential means to speed up the energy transition in the United States. The federal and state law along with utility market structures are vital in shaping the potential opportunities and barriers for energy storage facilities like PUSH. We show that although it supports PUSH development, there are gaps in the current market structure, specifically in the regulatory framework, when seen through the lens of justice and valuation of just energy services. These gaps limit the realization of utility-scale energy storage technology's potential to fully contribute to a decarbonized energy system that is more resilient and more just than the incumbent system. [ABSTRACT FROM AUTHOR]

• Supercapacitors represent a promising alternative to replace Flywheel Generators. • This paper provides the conceptual design of a Supercapacitors-based power supply for ASDEX Upgrade toroidal field coils. • Stored energy is distributed among the submodules of a MMC-like topology. • Redundancy is required to ensure reliability in case of fault of some modules. ASDEX Upgrade (AUG) electrical power is provided with three Flywheel Generators (FGs) that are charged up before the start of each plasma pulse with 15 MW for 30 minutes. The stored energy is then used to satisfy the high power needs during the pulse of up to 400 MW. The biggest FG ('EZ2') in case of a major fault could not be replaced by any other FG of such size because no comparable devices are available on the free market. Therefore, the development of an alternative energy storage with high power and energy density and fully controllable output is planned. Supercapacitors (SCs) are well known for their high specific power. The combination of this technology and a proper power converter topology such as the Modular Multilevel Converter (MMC) represent a promising alternative to be explored to replace Tokamaks FGs. The MMC topology allows a discrete-leveled output voltage and, thanks to its high cells number, it can operate continuously even in case of fault of some cells, while a FG could not. In this paper the concept of a SCs-based power supply for AUG's Toroidal Field (TF) Coils is presented, highlighting the main advantages and challenges of this project. [ABSTRACT FROM AUTHOR]

Energy storage is a cutting edge front for renewable and sustainable energy research. In fact, a massive exploitation of intermittent renewable sources, such as wind and sun, requires the introduction of effective mechanical energy storage systems. In this paper we introduce the concept of a trigenerative energy storage based on a compressed air system. The plant in study is a simplified design of the adiabatic compressed air energy storage and accumulates mechanical and thermal (both hot and cold) energy at the same time. We envisage the possibility to realize a relatively small size trigenerative compressed air energy storage to be placed close to the energy demand, according to the distributed generation paradigm. Here, we describe the plant concept and we identify all the relevant parameters influencing its thermodynamic behavior. Their effects are dissected through an accurate thermodynamic model. The most relevant technological issues, such as the guidelines for a proper choice of the compressor, expander and heat exchangers are also addressed. Our results show that T-CAES may have an interesting potential as a distributed system that combines electricity storage with heat and cooling energy production. We also show that the performances are significantly influenced by some operating and design parameters, whose feasibility in real applications must be considered. [ABSTRACT FROM AUTHOR]

• The structure and energy storage mechanism of aqueous lithium-ion batteries are systematically described. • The structure, operation mechanism, and synthesis methods of LiV 3 O 8 are introduced in detail. • The modification methods of LiV 3 O 8 are systematically reviewed for the first time. • Some views on the modification strategy are put forward, which provides a reference direction for future research. The development of new energy makes modern society have a higher requirement for energy storage systems. At the same time, traditional lithium-ion batteries have their shortcomings, such as a shortage of metal lithium resources, harsh preparation conditions, and toxic organic electrolytes. Therefore, people have gradually begun to research aqueous lithium-ion batteries (ALIBs). Aqueous electrolytes can overcome the disadvantages of traditional organic electrolytes such as low safety and high production cost. Due to high specific discharge capacity and low operating voltage, LiV 3 O 8 is considered a promising anode for ALIBs. However, inherent low conductivity and unsatisfactory cycle performance limit its further application, so it is necessary and meaningful to conduct further research on LiV 3 O 8. This paper first introduces the structure, operation mechanism, and syntheses of LiV 3 O 8. Then the modification methods to improve the performance are reviewed from coating modification, introducing conductive agent, ion doping, and nano crystallization. Finally, reasonable suggestions and perspectives for LiV 3 O 8 are put forward. [ABSTRACT FROM AUTHOR]

With the deepening of China's low-carbon energy transformation, microgrids are an essential means to promote the consumption of renewable energy. Therefore, improving the operational efficiency of microgrids is the key to promote the development of renewable energy. This paper establishes a three-layer Multi-Agent system model considering the energy storage system and power-heat load demand response based on the actual situation of China to solve the problem of microgrids energy management. In order to verify the effect of the energy storage system and demand response in microgrids, this paper designs three simulation cases, namely the underlying case, energy storage case and demand response case. In order to prove the efficiency of the proposed method, this paper applies the proposed method to solve three cases and compare the result with other meta-heuristic algorithms. The comparison results show that: (1) Multi-Agent system model can realize the collaborative optimization of 'source, grid, load, and storage.' (2) The introduction of the energy storage system and demand response in microgrids can stabilize the output of renewable energy units, promote renewable energy consumption and reduce the overall operating cost of microgrids. (3) The proposed particle swarm optimization can effectively reduce the cost and the number of iterations. • This study realizes a real-time energy management system of MG based on MAS. • This paper proves the effect of ESS and DR in MG. • This paper points out how to apply ESS and DR to MG operators. • This paper sets the stopping conditions to a chaotic process for efficiency. • Adaptive weight is added in this paper to reduce the number of iterations. [ABSTRACT FROM AUTHOR]

Abstract: In a high wind penetration scenario in electricity production, the availability of models for synthetically generating hourly wind speed data becomes increasingly important for both sizing and modeling integrated renewable systems. A methodology for generating hourly wind speed time series is presented in this paper, adopting a physical-statistical approach based on some known aggregate input data. The proposed approach, developed in a previous study by the same authors, has been here improved using a new diurnal wind speed profile function. The improved methodology is first described and validated through experimental wind speed data, comparing the results with those obtained using the basic model. Then, hourly wind speeds generated with the improved methodology are used as input data for the optimal design of grid-connected and off-grid wind power plants. For each configuration, the influence of the diurnal wind speed profile and wind regime on system sizing and its economic parameters has been evaluated. Results have shown that the diurnal variation of wind speed does not affect the size of wind turbine, but strongly influences the storage capacity of off-grid wind power plants. [Copyright &y& Elsevier]

The development of clean, renewable, and affordable energy sources such as wind or sun has become a necessity for a sustainable energy society. Consequently, it is highly required the development of energy storage systems capable of efficiently storing the energy generated by these intermittent sources. In recent years, hydrogen-based technologies have emerged as a way of mitigating the environmental footprint left by the fossil fuels-based ones. In this paper we report new insights into the performance of an environmentally friendly Acid-Base Electrochemical Flow Battery (ABEFB), using an electrolyte consisting of high NaCl concentration. Energy is obtained from the neutralization of two acid and alkaline solutions through hydrogen evolution and oxidation reactions. Different parameters such as the nature of the cationic membrane and the electrolyte concentration have been systematically evaluated. Under optimal conditions, this battery can provide a maximum power density of about 73.5 W m-2 at 215 A m−2, a coulombic efficiency of around 80%, and a round-trip efficiency of 52%. • An acid-base electrochemical flow battery with optimized core elements is presented. • The battery provides a power density of 106 W m−2 and a faradaic efficiency of 80%. • Coulombic efficiencies strongly depend on membrane thickness and H+/Na+ ratio. • Mixing the posilyte and negalyte is a strategy to rebalance the battery. [ABSTRACT FROM AUTHOR]

This paper explores the impacts of energy policies for supporting low-carbon infrastructure on the economic and financial performance of energy storage when coupled with a generator. The study sets in the UK context and the unit of analysis is the generator connected with energy storage. An analytical method is derived to assess the impact of policy schemes for low-carbon infrastructure on energy storage. The case study of energy storage systems coupled with a Small Modular nuclear Reactor (SMR) is quantitatively investigated in three scenarios: 1. SMR-only (the baseline); 2. SMR with thermal energy storage; and 3. SMR with Lithium-ion battery. For the strike price at 100 £/MWh, the net present value for scenarios 2 and 3 reduces from 562 M£ to 379 M£ and from 376 M£ to -1144 M£, respectively, when the energy storage capacity increases from 100 MWh to 1 GWh. As the net present value reduces with increased energy storage capacity (when coupled with generation), this work shows that low-carbon incentives are, unintentionally, barriers to the development of energy storage due to: (A) current generator incentives give a favourable return on investment and energy storage would diminish it; (B) energy storage cannot participate in generator only incentives. • There is a growing need to deploy energy storage infrastructures. • There is no incentive scheme specifically developed for energy storage. • Low-carbon power incentive schemes can unintendedly limit energy storage deployment. • The unintended effect is analysed analytically and numerically. • Policy recommendations are suggested to address this critical issue. [ABSTRACT FROM AUTHOR]

The development of renewable energy resources, distributed generation (DG), energy storage, and nonlinear controllable loads in distribution networks (DNs) have attracted attention towards state estimation (SE) in active distribution networks (ADNs). The energy management center (EMC) of DN is based on the results obtained from SE. ADN is intrinsically unbalanced. A two-step state estimation is applied to an unbalanced DN using a network reduction process (NRP) and a meter locating process (MLP) in this paper. Considering the shortage of measurements in DN, obtaining accurate primary information from network conditions enhances SE. Primary SE runs on the reduced network and its outputs are used as measurements to enhance total estimation (secondary SE). This method resolves the shortage of accurate measurements and elevates SE accuracy. The considered method is executed in a 37-bus unbalanced DN, and the results of the simulation are used to validate the proposed method. [ABSTRACT FROM AUTHOR]