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In the context of 'energy shortage', developing a novel energy-based power system is essential for advancing the current power system towards low-carbon solutions. As the usage duration of lithium-ion batteries for energy storage increases, the nonlinear changes in their aging process pose challenges to accurately assess their performance. This paper focuses on the study LiFeO4(LFP), used for energy storage, and explores their performance degradation mechanisms. Furthermore, it introduces common battery models and data structures and algorithms, which used for predicting the correlation between electrode materials and physical parameters, applying to state of health assessment and thermal warning. This paper also discusses the establishment of digital management system. Compared to conventional battery networks, dynamically reconfigurable battery networks can realize real-time monitoring of lithium-ion batteries, and reduce the probability of fault occurrence to an acceptably low level. [ABSTRACT FROM AUTHOR]

Integrated energy microgrids and shared energy storage have significant benefits in improving the energy utilization of the system, which is gradually becoming the current research hotspot. And the uncertainty of new energy output also significantly affects the stable and economic operation of integrated energy microgrid. So how to establish a set of integrated energy microgrids optimization operation model considering photovoltaic (PV) output uncertainty and shared energy storage is an urgent problem to be solved nowadays. Firstly, this paper introduces the framework of an integrated energy system microgrid containing a shared energy storage operator (ESO), and analyzes the scheduling method of the upper tier operator within the system as well as the economic benefits at the lower tier user end. Secondly, to address the randomness of PV output, Monte Carlo method is used to generate the scenarios, and then the scenarios are cut down by using the fast antecedent elimination technique. Then, an optimal operation model is established for micro grid operator (MGO) and user aggregator (UA), respectively, and based on the master-slave game relationship, so that the MGO is the leader and the UA is the follower, a Stackelberg game model is proposed to consider the integrated demand response of electricity and heat between the MGO and UA in the context of the participation of ESO in the auxiliary service of the UA. Finally, the proposed model is brought into a typical residential building community for simulation verification, and the results show that the model proposed in this paper can effectively balance the interests of MGOs and UAs, and realize win-win benefits for UA and ESO. [ABSTRACT FROM AUTHOR]

Along with the rapid economic development and social progress, the problem of energy and environment is becoming more and more outstanding. Therefore, it is very important to use new energy saving techniques to increase energy consumption and reduce energy consumption. In this paper, we have developed a hot water system, which is based on solar energy technology, gas-source heat pump, and phase change energy storage technology. The system was designed and constructed, and its performance was tested in various control conditions, with an emphasis on the analysis of the influence of phase change heat supply on heat storage properties. In this paper, the effect of the heat storage property is analyzed. Studies have shown that compared to a conventional tank that does not have a phase change heat storage device, the heat storage tanks equipped with phase change energy storage devices have longer discharge time, higher discharge temperature, better temperature, and better operation efficiency. In addition, the data show that flow rate control is also an important factor in optimizing the thermal storage characteristics of the system. [ABSTRACT FROM AUTHOR]

Integrating hybrid energy storage system (HESS) consisting of battery and supercapacitor provides balance over the power generation and load demand, ensuring the system's stability under transient conditions. Along with battery storage, to control its rate of charging/discharging a rate limiter (RTL) is usually employed. However, the impact of the RTL on battery storage efficiency and system performance has not been explored in the existing literature. This paper investigates the performance of a grid‐tied photovoltaic (PV) system with HESS under dynamic scenarios with different RTL values applied to the battery storage. The paper explores the simulation analysis considering transient, linear, and steady‐state conditions with varying PV generation and load demand. The simulation study shows that a lower RTL value may slow down the battery response, leading to inefficient utilization of battery storage. Alternatively, a very high RTL value will not appropriately regulate the battery current, which may lead to frequent charging and discharging and deterioration of battery life. For the proposed system, RTL with a value of 100 A/s seems appropriate, providing 1.29 Wh of energy through battery storage with an energy efficiency of 91.81% for the simulated time. The DC voltage is efficiently maintained at 400 V with a ripple factor of 0.45%. [ABSTRACT FROM AUTHOR]

Hybrid renewable energy systems (HRES) are gaining high interest in supplying electric energy for remote communities. Energy storage systems (ESS) are utilized by green autonomous HRESs to accommodate the variability of renewable resources such as wind and solar energy systems. The lack of any traditional energy source is adding a great reliability challenge which should be compensated using expensive ESS. This challenge can be avoided by using a pumped hydro energy storage system (PHES) in harmony with batteries. The PHES is an excellent option to be used in NEOM city due to the perfect topographical characteristic of this site. The minimum cost of energy and the highest reliability is used as an objective for sizing the proposed entire green HRES. Using smart grid principles (SGP) and demand‐side management (DSM) in the design and operation stages will minimize system size and cost, which can result in a significant reduction in consumer bills. As a result, this paper introduces an innovative DSM based on a dynamic tariff. The suggested DSM technique was developed utilizing a unique fuzzy logic that takes into account the present and day‐ahead ESS situations to intelligently determine the ideal tariff for the lowest cost and maximum reliability of the HRES. This paper introduces a modified grey wolf optimization (MGWO) technique to shorten convergence time while preserving the best accuracy. The suggested MGWO is assessed against 10 swarm optimization techniques. The payback period of the project is 7 years. The findings acquired from this unique program demonstrated its superiority, with conversion times reduced by 22% to 80% when compared to previous optimization procedures. Furthermore, as compared to the flat rate pricing tariff, the usage of the dynamic tariff lowered the LCOE by 53%. [ABSTRACT FROM AUTHOR]

The shared energy storage system is recognized as a promising business model for the coordinated operation of integrated energy systems (IES) to improve the utilization of energy storage and the consumption of renewable energy. As the hydrogen energy gradually receives more attention, this paper constructs the structure of a hybrid hydrogen energy storage system shared by an IES alliance in a dynamic pricing mode. A bi-level optimization model for the shared hybrid hydrogen energy storage system (SHHESS) is proposed to optimize the capacity configuration decisions and the pricing strategy jointly. The upper level determines the capacity and dynamic price of SHHESS with maximum profits and the lower level obtains the optimal operation of the IES alliance minimizing the total operation costs. The proposed model is solved by an improved PSO-GA algorithm and CPLEX solver. Finally, numerical tests are conducted in different scenarios. The results show that the hybrid energy storage system improves the daily profits of SHHESS by 70.3% and 5.44%, and reduces the renewable energy curtailment by 80.93% and 48.92% respectively compared to the battery-only and hydrogen-only systems. Additionally, the daily operation cost of the IES alliance is 35.2% lower than the individual operation scenario. The proposed model confirms the feasibility and superiority of the hybrid hydrogen energy storage system in a sharing business mode. • Design an interactive structure of a shared hybrid hydrogen energy storage system. • Propose a bi-level planning optimization framework for shared hybrid hydrogen energy storage. • The dynamic price of energy storage sharing service is optimized. • Determine the optimal operation strategy of the integrated energy system alliance. • Propose a hybrid method combining an improved PSO-GA and CPLEX optimizer. [ABSTRACT FROM AUTHOR]

This article proposed the architecture of a stand-alone photovoltaic connected system (SPVS) with energy storage. An SPVS with energy storage requires power management for various operating modes. A coordinate controller is often necessary to manage the change in control architecture depending on the operating mode. This proposed system contains a boost converter (BC) and a bidirectional switched quasi-Z-source DC-DC converter (BSQZSDC). The BC is used for two purposes. The first is extracting the maximum power from the PV. The second is to control the DC link voltage when the SPVS is not in MPPT mode; dual-loop PI controllers are used for this. The BSQZSDC is used for energy management and regulates DC link voltage when SPVS operates in MPPT mode. This paper addresses about the effective control approach that BSQZSDC used, i.e., the double-integral sliding mode control, to regulate the DC link voltage and battery current in various operating modes. Experimental results were carried out to depict that the controller reasonably achieves the control objectives and proper energy management. [ABSTRACT FROM AUTHOR]

To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency and economic viability of existing energy facilities. Among various energy storage technologies, thermocline heat storage (THS) has garnered widespread attention from researchers due to its stability and economic advantages. Currently, there are only a few review articles focusing on THS, and there is a gap in the literature regarding the optimization design of THS systems. Therefore, this paper provides a comprehensive review of the recent research progress in THS, elucidating its principles, thermal storage materials, applications, and optimization designs. The novelty of this work lies in the detailed classification and analysis of various optimization designs for THS, including tank shape, aspect ratio, inlet/outlet configuration, thermal energy storage materials arrangement, operating strategies, and numerical model optimization approaches. The limitations of existing research are also identified, and future perspectives are proposed, aiming to provide recommendations for THS research and contribute to the development and promotion of THS technology. [ABSTRACT FROM AUTHOR]

In this paper, undoped BaBi2−x−yNb2ErxYbyO9 (BBN), Er3+ doped BBN, and a series of Er3+/Yb3+ co-doped BBN ferroelectric ceramic is synthesized by the solid-state method to study the structural, dielectric, ferroelectric, and energy storage behavior of the prepared ceramic. XRD spectra revealed orthorhombic geometry and Fmmm phase group of each prepared ceramic. SEM micrograph shows dense microstructures similar to square-shaped structures. Two FTIR bands at 619 and 822 cm−1 are observed, displaying the characteristic peaks of the Aurivillius phase. Four Raman bands are detected for undoped BBN, while twelve are visible in Er3+/Yb3+ doped BBN compositions. Further, this work utilizes a comparable method to correlate Nb–O stretching frequencies with their corresponding bond lengths using Herschbach's exponential function. Temperature-dependent dielectric studies show considerable dispersion below and above maximum temperature (Tm), and the dielectric constant (εʹ) decreases with an increase in frequency. The dielectric loss (ɛʺ) curves are quite diffused, and shifts in the maxima with frequency have been observed, thus validating the relaxor behavior of all the prepared BBN compositions. The slimmer PE curves were obtained under moderate electric fields ranging from 75 to 100 kV/cm. The energy storage parameters (W, Wrec, η) are improved with increasing applied electric field. The energy storage efficiency (η) obtained for undoped, Er3+ doped, and Er3+/Yb3+ co-doped BBN ceramics are 78.25%, 83.39%, and 90.87%, respectively. The energy storage parameters revealed good temperature stability from 303 to 415 K, indicating that the synthesized material might aid in developing modern electronic equipment for energy storage applications. [ABSTRACT FROM AUTHOR]

As the global transition toward sustainable energy gains momentum, integrating electric vehicles (EVs), energy storage, and renewable energy sources has become a pivotal strategy. This paper analyses the interplay between EVs, energy storage, and renewable energy integration with Indonesia's grid as a test case. A comprehensive energy system modeling approach using PLEXOS is presented, using historical data on electricity generation, hourly demand, and renewable energy, and multiple scenarios of charging patterns and EV adoption. Through a series of scenarios, we evaluate the impact of different charging strategies and EV penetration levels on generation capacity, battery storage requirements, total system cost, renewable energy penetration, and emissions reduction. The findings reveal that optimized charging patterns and higher EV adoption rates, compared to no EVs adoption, led to substantial improvements in renewable energy utilization (+4%), emissions reduction (−12.8%), and overall system cost (−9%). While EVs contribute to reduced emissions compared to conventional vehicles, non-optimized charging behavior may lead to higher total emissions when compared to scenarios without EVs. The research also found the potential of vehicle to grid (V2G) to reduce the need for battery storage compared to zero EV (−84%), to reduce emissions significantly (−23.7%), and boost penetration of renewable energy (+10%). This research offers valuable insights for policymakers, energy planners, and stakeholders seeking to leverage the synergies between EVs and renewable energy integration to pursue a sustainable energy future for Indonesia. [ABSTRACT FROM AUTHOR]

The development of large energy systems based on renewable energy sources is accompanied by an increase in the input capacities of large grid storages. Taking into account the vector for decarbonization and maneuverability, the use of hydrogen as a fuel in the cycle of a diabatic compressed air energy storage (CAES) is a promising scientific and technical direction. This paper analyzes the key performance indicators of a compressed air energy storage in the presence and absence of thermal energy recovery within the cycle. In addition, an assessment was made of the prospects for the use of a methane-hydrogen mixture in gas turbines. At the end of the paper, a calculation of the process of plasma pyrolysis of methane is given as one of the possible methods for the production of hydrogen for use in energy purposes. [ABSTRACT FROM AUTHOR]

To achieve a more ecologically friendly energy transition by the year 2050 under the European "green" accord, hydrogen has recently gained significant scientific interest due to its efficiency as an energy carrier. This paper focuses on large-scale hydrogen production systems based on marine renewable-energy-based wind turbines and tidal turbines. The paper reviews the different technologies of hydrogen production using water electrolyzers, energy storage unit base hydrogen vectors, and fuel cells (FC). The focus is on large-scale hydrogen production systems using marine renewable energies. This study compares electrolyzers, energy storage units, and FC technologies, with the main factors considered being cost, sustainability, and efficiency. Furthermore, a review of aging models of electrolyzers and FCs based on electrical circuit models is drawn from the literature and presented, including characterization methods of the model components and the parameters extraction methods, using a dynamic current profile. In addition, industrial projects for producing hydrogen from renewable energies that have already been completed or are now in progress are examined. The paper is concluded through a summary of recent hydrogen production and energy storage advances, as well as some applications. Perspectives on enhancing the sustainability and efficiency of hydrogen production systems are also proposed and discussed. This paper provides a review of behavioral aging models of electrolyzers and FCs when integrated into hydrogen production systems, as this is crucial for their successful deployment in an ever-changing energy context. We also review the EU's potential for renewable energy analysis. In summary, this study provides valuable information for research and industry stakeholders aiming to promote a sustainable and environmentally friendly energy transition. [ABSTRACT FROM AUTHOR]

Renewable energy systems are mostly used in the world due to their inexhaustible and nonpolluting production. As a result of a large utilization of these energy sources in different areas, the electricity production rate is increasing every day. Previous studies clarified uses, modeling, configuration, energy management operation, and optimization objectives based on different energy sources. For this reason, this paper focuses on an overview of multi energy systems as renewable and conventional power sources with the integration of an energy storage system coupled to the on-off electrical network. Furthermore, a survey is done regarding global energy production, configuration energy systems, energy storage systems, power management strategies, and optimization methods based on different hybrid energy systems. Multiple optimization approaches have been implemented to reach the global best solution for the hybrid power systems. To ensure the best optimization result, it is preferable to take hybrid optimization methods into consideration. These methods have been invented recently and have proved their efficacy and performance mainly in power systems. [ABSTRACT FROM AUTHOR]

With the continuous increase in global energy demand and growing environmental awareness, the utilization of renewable energy has become a worldwide consensus. In order to address the challenges posed by the intermittent and unpredictable nature of renewable energy in distributed power distribution networks, as well as to improve the economic and operational stability of distribution systems, this paper proposes the establishment of an active distribution network capable of accommodating renewable energy. The objective is to enhance the efficiency of new energy utilization. This study investigates optimal scheduling models for energy storage technologies and economic-operation dispatching techniques in distributed power distribution networks. Additionally, it develops a comprehensive demand response model, with real-time pricing and incentive policies aiming to minimize load peak–valley differentials. The control mechanism incorporates time-of-use pricing and integrates a chaos particle swarm algorithm for a holistic approach to solution finding. By coordinating and optimizing the control of distributed power sources, energy storage systems, and flexible loads, the active distribution network achieves minimal operational costs while meeting demand-side power requirements, striving to smooth out load curves as much as possible. Case studies demonstrate significant enhancements during off-peak periods, with an approximately 60% increase in the load power overall elevation of load factors during regular periods, as well as a reduction in grid loads during evening peak hours, with a maximum decrease of nearly 65 kW. This approach mitigates grid operational pressures and user expense, effectively enhancing the stability and economic efficiency in distribution network operations. [ABSTRACT FROM AUTHOR]

This paper investigates four energy utilization scenarios with or without home‐distributed photovoltaic generation (HDPG) to reduce the generation cost and pollutant emission of the dynamic economic emission dispatch with the charging/discharging of plug‐in electric vehicles (DEED‐PEV). The first scenario considers valley filling for the charging of PEVs. The second scenario combines valley filling and peak shaving for the charging and discharging of PEVs. The third scenario adds peak shaving of HDPG to the first scenario, followed by the peak shaving with the discharging of PEVs. The fourth scenario rearranges the distribution of photovoltaic (PV) power for the third scenario, and the PV power in the afternoon is stored by a photovoltaic energy storage system (PESS) and consumed in the evening. A universal procedure is designed for the valley filling and peak shaving of the four scenarios, which is beneficial for determining the filled and shaved loads with respect to certain time intervals. An NSGA‐II method based on a modified crossover and an elimination of individuals (NSGA‐II‐MCEI) is proposed for the multiobjective optimization of DEED‐PEV. The modified crossover can improve the convergence of NSGA‐II‐MCEI, and the elimination operator can maintain the evenness of the nondominated solutions. According to experimental results, scenario 4 achieves cost savings of 95386.62 $, 85636.87 $, and 6776.85 $, respectively, for Scenarios 1, 2, and 3, and it reaches emission reductions of 27617.64 kg, 17252.71 kg, and 220.98 kg, respectively, for scenarios 1, 2, and 3. Also, scenario 4 outperforms the other three scenarios for three weather conditions such as sunny day, cloudy day, and rainy day. [ABSTRACT FROM AUTHOR]

Due to its high energy storage density, high instantaneous power, quick charging and discharging speeds, and high energy conversion efficiency, flywheel energy storage technology has emerged as a new player in the field of novel energy storage. With the wide application of flywheel energy storage system (FESS) in power systems, especially under changing grid conditions, the low‐voltage ride‐through (LVRT) problem has become an important challenge limiting their performance. In this paper, we propose a machine‐grid side coordinated control strategy based on model predictive current control (MPCC) for the insufficient LVRT capability of traditional FESS during grid faults. Excellent dynamic properties are demonstrated by the technique, which allows the grid‐side converter output current to swiftly follow the reference current instruction. The FESS's LVRT capability is increased when the grid‐side converter uses the MPCC current inner loop rather than the proportional–integral current inner loop during grid voltage dips. This greatly increases the reactive power response speed and efficiently supports the quick recovery of grid voltage. According to simulation verification carried out by Matlab/Simulink, the suggested control approach can assure the long‐term dependable operation of the FESS during voltage dips. This study can also be used as a reference for improving the FESS's LVRT capabilities in the future. [ABSTRACT FROM AUTHOR]

Demand-side flexible load resources, such as Electric Vehicles (EVs) and Air Conditioners (ACs), offer significant potential for enhancing flexibility in the power system, thereby promoting the full integration of renewable energy. To this end, this paper proposes an optimal allocation method for demand-side flexible resources to enhance renewable energy consumption. Firstly, the adjustable flexibility of these resources is modeled based on the generalized energy storage model. Secondly, we generate random scenarios for wind, solar, and load, considering variable correlations based on non-parametric probability predictions of random variables combined with Copula function sampling. Next, we establish the optimal allocation model for demand-side flexible resources, considering the simulated operation of these random scenarios. Finally, we optimize the demand-side resource transformation plan year by year based on the growth trend forecast results of renewable energy installed capacity in Jiangsu Province from 2025 to 2031. [ABSTRACT FROM AUTHOR]

This paper proposes the hybrid approach for increasing the profit of prosumers and reducing the energy cost of the residents. The hybrid method is the combination of chaotic maps and the Henry gas solubility optimization algorithm (HGSO), hence it is called chaotic Henry gas solubility optimization (CHGSO). The proposed approach is the community-based microgrid that incorporates energy storage systems (ESS), electric vehicles (EVs) and photovoltaics (PV). Both ESS and EV are conserved as alternative sources of energy. The stored EV energy is used as a power source for homes and the grid by utilizing the Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) modes. The power flow of EV/ESS is controlled depending on the rate of charging and discharging. Here, the battery degradation cost is considered. The proposed approach solves the optimization problems, like battery degradation of EV/ESS, regulation of charge/discharge and provides optimal economic benefits. The proposed approach increases the prosumer profit through encouraging EV energy transactions through incentive-based pricing. Finally, the CHGSO method is performed in MATLAB and is compared with existing methods. From the simulation analysis, it can be concluded that the cost of CHGSO method is less and the prosumer participation has increased. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of the abolition of annual net metering in Slovenia and compares the electric energy costs for the studied active user after the abolition. The article also provides an exploration of the role played by an aggregator, which serves as a central entity that enables individuals to participate in the electric energy market. An analysis of the case study of an active user was made, where an analysis was made of the measurements of household consumption and photovoltaic plant production for the year 2022. This article presents an economic analysis with and without net metering and an analysis of the aggregator involvement strategies. In addition, a battery energy storage system was also considered in the analysis. An important part of the article is the identification of the flexibility potential for shiftable loads, which enable an aggregator to acquire insight into the energy consumption profile and energy production profile of active users. The following indicators were used to compare the strategies: annual electric energy cost and the indicators including self-sufficiency, self-consumption, and grid dependency. The findings indicate that, even in the absence of annual net metering, the active user can lower their costs for electric energy with the help of an aggregator. [ABSTRACT FROM AUTHOR]

In pursuit of the "Dual Carbon Goals" and to mitigate the adverse effects of "power supply restrictions," a microgrid scheme integrating wind and solar power with hydrogen energy storage is proposed. This paper introduces the principles of system capacity configuration and establishes a mathematical model. This research offers a novel method for configuring wind and solar hydrogen storage systems called quantum-enhanced multi-objective collaboration. This work intends to address the complicated issues of achieving effective energy storage, reducing prices, and maximising renewable energy utilisation by leveraging the capabilities of quantum computing. A multi-objective capacity optimization configuration model for wind–solar–hydrogen energy storage is developed using Homer Pro software and an enhanced BAS-GA algorithm. Under off-grid operating conditions, the wind–solar–hydrogen energy storage system's capacity optimization configuration model is validated through practical examples. The results indicate that, in comparison to wind storage, solar storage, wind–solar storage, and wind–solar–diesel storage systems, the net present value and levelized cost of electricity of the wind–solar–hydrogen energy storage system decrease to 14.25 million RMB and 1.529 RMB/(kW h), respectively. The renewable energy utilization rate increases to 98.7%, and the load shedding rate decreases to 5.50%. [ABSTRACT FROM AUTHOR]

Micro-energy networks are the smallest element of integrated energy systems, and tapping into the integrated demand response potential of micro-energy networks is conducive to improving energy use efficiency and promoting the development of new energy sources on a large scale. This paper proposes a day-ahead integrated demand response strategy for micro-energy grid that takes into account the dispatchable loads. Considering the gradient use of thermal energy, a typical micro-energy grid structure including electricity, gas, medium-grade heat, low-grade heat, and cold energy is constructed, a comprehensive energy equipment model is established, and the refined scheduling models of the dispatchable loads are given. On this basis, with the operating economy of the micro-energy grid as the optimization objective, the integrated demand response strategies of tariff-type and incentive-type are proposed. Through case study analysis, it is verified that the proposed strategy can optimize the energy consumption structure of the micro-energy grid under the guidance of time-of-use tariffs, reducing the operating costs. The proposed strategy fully exploits the demand response potential of the micro-energy grid through the dispatchable loads and the multi-energy complementarity of electricity, heat, and cold, realizes the comprehensive coordination and optimization of source-network-load-storage, provides a larger peak-regulating capacity, and exhibits practical applicability in engineering. [ABSTRACT FROM AUTHOR]

Forecasts and their corresponding optimized operation plans for energy plants never match perfectly, especially if they have a horizon of several days. In this paper, we suggest a concept to cope with uncertain load forecasts by reserving a share of the energy storage system for short-term balancing. Depending on the amount of uncertainty in the load forecasts, we schedule the energy system with a specific reduced storage capacity at the day-ahead market. For the day of delivery, we examine the optimal thresholds when the remaining capacity should be used to balance differences between forecast and reality at the intraday market. With the help of a case study for a simple sector-coupled energy system with a demand for cooling, it is shown that the energy costs could be reduced by up to 10% using the optimal reserve share. The optimal reserve share depends on the forecast quality and the time series of loads and prices. Generally, the trends and qualitative results can be transferred to other systems. However, of course, an individual evaluation before the realization is recommended. [ABSTRACT FROM AUTHOR]

Recently, the implementation of software/hardware systems based on advanced artificial intelligence techniques for continuous monitoring of the electrical parameters of intelligent networks aimed at managing and controlling energy consumption has been of great interest. The contribution of this paper, starting from a recently studied DC-MG, fits into this context by proposing an intuitionistic fuzzy Takagi–Sugeno approach optimized for the energy management of isolated direct current microgrid systems consisting of a photovoltaic and a wind source. Furthermore, a lead-acid battery guarantees the stability of the DC bus while a hydrogen cell ensures the reliability of the system by avoiding blackout conditions and increasing interaction with the loads. The fuzzy rule bank, initially built using the expert's knowledge, is optimized with the aforementioned procedure, maximizing external energy and minimizing consumption. The complete scheme, modeled using MatLab/Simulink, highlighted performance comparable to fuzzy Takagi–Sugeno systems optimized using a hybrid approach based on particle swarm optimization (to structure the antecedents of the rules) and minimum batch squares (to optimize the output). [ABSTRACT FROM AUTHOR]

More and more microgrids, energy storage systems, and other emerging entities are integrated into active distribution networks. However, a microgrid is characterized by autonomous operation and privacy protection. The rapid development of equipment such as shared energy storage brings strong uncertainty to a traditional dispatcher. The observability and controllability of the distribution system decrease, and traditional regulatory methods are no longer applicable. To deal with the above challenges, a distributed collaborative operation optimization method of multilateral participants is proposed. Guided by the dynamic time-of-use electricity price, the collaborative operation of multilateral participants can be realized. Firstly, the cooperative operation architecture is established considering the dynamic time-of-use electricity price. In this architecture, the residual capacity of shared energy storage is used for arbitrage by storing electricity at low electricity prices and generating electricity at high electricity prices. Then, the optimization operation models of a microgrid alliance, shared energy storage, and an active distribution network are established. The final operation scheme and the dynamic time-of-use price of the distribution network are formulated through the cyclic iteration among the three participants. Finally, a case study is carried out to analyze the optimization effect of each participant with the proposed method. It is found that the overall interests and the interests of each participant can be taken into account effectively and the consumption of renewable energy can be promoted by the method proposed in the paper. In addition, an oscillation phenomenon is found during the distributed collaborative operation, and the strategy to eliminate the oscillation phenomenon is given. [ABSTRACT FROM AUTHOR]

The All-electric ship (AES) concept has revolutionized the maritime sector. Indeed, AES is a promising solution for modern vessels where decreasing emission pollution, suppressing fossil fuel consumption, and making economical operation are its brilliant merits. Fuel cell (FC) technology based on clean hydrogen energy sources can play a significant role in meeting these requirements in the AES platform. Because of the slow transient response of the FC, an energy storage system (ESS) is required to improve AES performance in different operation scenarios. Therefore, optimal sizing of the FC and the ESS and proper design of energy management strategy is a challenging problem. This paper proposes a systematic approach for the optimal design of hybrid FC-ESS of AES power systems. The proposed method is based on an optimization technique to determine the optimal sizing of the FCs and the ESS. Capital investment, fuel consumption, personnel electrical safety, and occupied volume of the AES power system are the main objectives. The FC size, the battery size, the scheduled output power of the FC, and the battery are the decision variables. Genetic Algorithm (GA) is used to solve the optimization problem. To validate the numerical results, the optimization problem is also solved by Mayfly Algorithm (MA) separately. To assess the feasibility of the proposed strategy, the optimal design of hybrid FC-ESS for a vessel is implemented based on the proposed method. The simulation results validate the proposed approach's sufficiency to investigate and optimize the economic, safety, and dimensional aspects of designing the FC ship's IPS. Numerical results are reported for each design aspect. Considering the minor differences of the numerical results obtained by GA and MA, the optimum points are validated by the two techniques. Using the obtained results, various perceptions can be derived from the FC ship's IPS design. For example, the IPS cost in the cases with optimum volume, weight, and safety, has 2.3%, 2.6%, and 7.3% penalties, respectively compared to the case with the minimum cost. • Fuel cell-based electrification of a fishing ship based on practical information. • Systematic approach for optimal power system design of hydrogen-powered ship. • Proposing safety objective function for integrated power system of fuel cell ship. • Fuel cell hybrid IPS optimization based on volume, mass, cost and safety. • Estimation of propulsion power demand based on ship's resistance and speed profile. [ABSTRACT FROM AUTHOR]

This paper presents a framework for the efficient design and evaluation of a standalone hybrid renewable energy system (HRES) to meet the energy requirements of a rural community in the north-eastern region of Nigeria. The proposed microgrid system incorporates solar photovoltaic, wind turbines, biomass gasifier, fuel cell, and Battery storage. The sizing of each component is determined through the utilization of real local meteorological data and the load demand over a year, employing the Levy flight-salp swarm algorithms (LF-SSA). The optimization objective is to minimize the annualized system cost (ASC) of the HRES, while also considering the reliability constraint of Loss of power supply probability (LPSP). The comparative outcomes demonstrate that the LF-SSA surpasses other examined algorithms, namely the salp swarm, genetic algorithm, and HOMER software by achieving substantial cost savings of $29033, $50796, $191771 respectively in relation to the proposed HRES. The result further shows that, the LF-SSA provides the lowest LCOE of $0.933162/kWh, in contrast to SSA at $0.947737/kWh, GA at $0.958660/kWh, and HOMER at $1.075351/kWh. Additionally, the results indicate that the implemented Energy Management System (EMS) has successfully facilitated the establishment of an environmentally friendly and cost-effective energy system. • An efficient energy storage system is essential for managing intermittent energy supply. • The fuel cell can generate DC power by combining hydrogen with oxygen. • The amount of power generated by a PV panel depends on temperature and solar radiation intensity. • Deterministic rule-based controllers operate based on pre-defined rules. • Energy Management System coordinate the flow of power between different components. [ABSTRACT FROM AUTHOR]

Most hydraulic excavators use passive power control to adjust the engine speed according to the load torque to achieve power matching, which has very limited effectiveness in energy saving. In this paper, an active power optimization control of speed closed-loop engine is proposed to improve its tracking performance for the dynamic energy-saving operating points. The inertia movement of the engine during variable speed control is analyzed to determine the kinetic energy requirements for different start and end operating points. An RBF-based neural network controller is designed based on power optimization to actively compensate the strong hysteresis of the engine speed relative to the optimal torque. The simulation and the experimental results show that the proposed control method has a much faster response for the energy-saving operating points, which reduces the energy consumption by 9.28% and 5.56% without adding any energy storage devices to the hydraulic excavator. [ABSTRACT FROM AUTHOR]

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal). Post-publication, the editor discovered suspicious changes in authorship between the original submission and the revised version of this paper. In summary, The author names Baohua Shen (new First Author) and Minghai Li (new Corresponding Author) were added to the revised paper without explanation and without exceptional approval by the journal editor, which is contrary to the journal policy on changes to authorship. The editor reached out to the authors for an explanation, but they failed to provide a satisfactory explanation to these changes. In addition, it appears that Navid Bohlooli was claiming an affiliation with Sun-Life Company, Baku, Azerbaijan. When questioned, the author was unable to provide convincing evidence of the existence and nature of this company. Overall, the editor feels that the findings of the manuscript cannot be relied upon and that the article needs to be retracted. [ABSTRACT FROM AUTHOR]

• This paper proposes a comprehensive optimization program to increase economic efficiency and improve the resiliency. • A demand response program integrated with home energy storage systems is presented to optimize energy consumption. • To modify the consumption pattern of household consumers, a real-time pricing algorithm is proposed. • A self-healing system reconfiguration program integrated with distributed energy resources is presented. • Real data of California households are considered to model the home appliances and home energy storage systems. This paper proposes a comprehensive optimization program to increase economic efficiency and improve the resiliency of the Distribution Network (DN). A Demand Response Program (DRP) integrated with Home Energy Storage Systems (HESSs) is presented to optimize the energy consumption of household consumers. Each consumer implements a Smart Home Energy Management System (SHEMS) to optimize their energy consumption according to their desired comfort and preferences. To modify the consumption pattern of household consumers, a Real-Time Pricing (RTP) algorithm is proposed to reflect the energy price of the wholesale market to the retail market and consumers. In addition, a Self-Healing System Reconfiguration (SHSR) program integrated with Distributed Energy Resources (DER), reactive power compensation equipment, and Energy Storage Systems (ESSs) is presented to manage the DN energy and restore the network loads in disruptive events. The reconfiguration operation is performed by converting the isolated part of the DN from the upstream network to several self-sufficient networked virtual microgrids without executing any switching process. Real data of California households are considered to model the home appliances and HESSs. The proposed comprehensive program is validated on the modified IEEE 123-bus feeder in normal and emergency operating conditions. [ABSTRACT FROM AUTHOR]

CaO-CaCO 3 thermochemical energy storage is a promising technology for solar energy utilization and storage. Alkaline papermaking waste (APW) from paper mills, which is mainly composed of CaCO 3. Herein, TiO 2 /MnFe 2 O 4 co-modified APW was synthesized. The energy storage capacity of TiO 2 /MnFe 2 O 4 co-modified APW was studied during CaO-CaCO 3 thermochemical energy storage cycles in a duel fixed bed reactor. TiO 2 /MnFe 2 O 4 co-modified APW mainly consists of CaO, MgO, CaTiO 3 , CaMnO 3 , and Ca 2 Fe 2 O 5. The introductions of TiO 2 and MnFe 2 O 4 significantly improve the cyclic stability and optical absorption property of APW in 30 cycles. The co-modified APW (the mass ratio for CaO:TiO 2 :MnFe 2 O 4 = 100:5:5) possesses high sintering resistance, energy storage, and optical absorption capacities in 30 cycles. The energy storage conversion and capacity of the co-modified APW are 0.72 and 2288.57 kJ/kg after 30 cycles, respectively. The optical absorptance of the co-modified APW reaches 49%, which is 9.25 times as high as that of APW. CaTiO 3 and CaMnO 3 effectively mitigate the sintering of CaO grains. CaMnO 3 and Ca 2 Fe 2 O 5 significantly increase the optical absorptance of APW. The co-modified APW possesses stronger basicity and more oxygen vacancies, which is favourable for the carbonation reaction. Thus, TiO 2 /MnFe 2 O 4 co-modified APW is a good energy storage material. • TiO 2 /MnFe 2 O 4 co-modified papermaking waste is used for CaO-CaCO 3 energy storage. • The composite mainly consists of CaO, MgO, CaTiO 3 , CaMnO 3 , and Ca 2 Fe 2 O 5. • The composite has high and stable energy storage and optical absorption capacities. • The energy storage density of the composite is 2288.57 kJ/kg after 30 cycles. • The composite has high sintering resistance, stronger basicity, and oxygen vacancy. [ABSTRACT FROM AUTHOR]

Deep Learning (DL) models, such as Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), have been widely used to predict the intermittency of wind power; however, the non-linear activation functions and backpropagation mechanisms in DL models increase computational complexity and energy consumption. This paper proposes a prediction model based on Green Learning (GL) to reduce energy consumption. The proposed GL model replaces the feature extraction of activation functions with a hybrid feature extraction approach combining categorical and numerical features. We also employ cluster centroids and quantile regression forest for classification/regression to eliminate the need for backpropagation in optimizing hyperparameters. Using Taiwan as a case study, this paper evaluates the risk of fluctuations in regional wind power generation in 2030. In simulations, the proposed GL model achieved excellent accuracy with energy consumption significantly lower than that of DL models. Our analysis also revealed that by 2030, fluctuations in wind power generation during the winter will exceed 40% of the peak supply capacity in the central region, indicating the need to enhance the resilience of regional power systems. • This is the first study to apply green learning to wind power prediction. • This study discriminated seasonal climate patterns at the regional level. • This study assessed the fluctuation risk under large-scale wind power integration. • The maximum hourly variability in wind power is projected to exceed 6,010 MWh by 2030. • We recommend the continued deployment of regional energy storage systems. [ABSTRACT FROM AUTHOR]

As the penetration of distributed renewable energy gradually increases, prosumer groups in high-altitude areas are being expanded. However, the operation of these prosumers in high-altitude areas faces numerous challenges. To address the issue, this paper proposes a double layer energy cooperation framework for high-altitude prosumer groups, considers peer aggregation and shared composite energy storage, aims to adapt to the trend of diversified energy interactions and improve the economic efficiency, maximize social welfare and ensure the continuous growth of the sharing market of prosumers operations in high altitude areas. To meet the diversified energy interaction needs of prosumers, a composite energy storage provider, an energy aggregator, and a two-stage profit clearing scheme are proposed. Furthermore, the overall benefits of the framework and the impact of profit clearing schemes on fairness under various scenarios are studied, and the comprehensive effects of the double layer energy framework are evaluated. The study results show that compared to independent operation by prosumers, under the guidance of shared electricity prices and composite energy storage providers, the economic benefits, evaluation indicators and energy storage utilization efficiency have all been improved. In addition, compared to other profit distribution modes, the two-stage profit clearing scheme proposed in this paper has higher fairness, which greatly encourages the participation of interested entities in energy cooperation. This study provides a feasible framework for energy cooperation among prosumers, and the framework's effectiveness is well-validated. [Display omitted] [ABSTRACT FROM AUTHOR]

Energy development in industrial parks promotes both industrial and inter-park economies. However, as the number of industrial parks increases and the economic level of the parks rises, energy consumption is also increasing rapidly. The rapid expansion of inter-park trading markets is accompanied by a surge in carbon emissions, making industrial parks increasingly significant contributors to carbon emissions within the industrial sector. In response to this environmental challenge, this paper proposes an integrated trading approach within industrial parks that considers carbon constraints. By implementing a spot trading method for surplus industrial energy, the goal is to mitigate the carbon emission pressure within these parks. Firstly, the paper conducts an analysis of the characteristics of combined heat and power units in industrial parks. It introduces an integrated analysis method within the target region, consolidating information from various park units to enhance flexibility in energy utilization. Secondly, an energy storage model is established. This model efficiently leverages energy storage capacity to balance fluctuations in energy supply and demand within industrial parks, thereby alleviating carbon emission pressure. Finally, the study and analysis of an industrial park in Liaoning Province were conducted using the Yalmip + Gurobi commercial software on the MATLAB platform. Compared with the traditional industrial park, the carbon dioxide emission of the industrial park is reduced by 91.49t, and the energy cost is saved by 11.2 million RMB. Numerical results from instances indicate that this method surpasses traditional trading approaches, aligning with the rigorous standards of scientific research. • An energy storage model is proposed to address the shortage of energy storage in waste heat trading in industrial parks. • A coordinated scheduling program is presented to reduce energy scheduling imbalances between multiple campuses. • The carbon-constrained energy storage device is integrated to improve the decarbonization capacity. [ABSTRACT FROM AUTHOR]

The increasing demand for renewable energy sources has led to the development of HRES that combine multiple sources of renewable energy to provide a reliable and efficient energy supply. However, renewable energy sources typically come with higher costs than conventional energy production methods. Hence, the optimal sizing of HRES is essential to prevent the oversizing of the system while ensuring a reliable supply of load demand, accommodating variations in meteorological conditions and changes in power demand. Numerous research papers addressing the optimal sizing problem are available in the literature. However, none of the mentioned studies take into account the power degradation of all renewable sources. The degradation of renewable sources, such as PV and WT, can have a significant impact on the performance of HRES. The degradation of PV panels can result in reduced efficiency and output, leading to a decrease in the overall energy production of the HRES. Similarly, WT may experience wear and tear over time, leading to reduced performance and output. The reduction in the output of renewables in the standalone system causes an increase in the loss of power supply probability (LPSP). This paper analyzes the optimal sizing of the HRES, considering the degradation of the sources. Further, analysis has also been carried out based on the number of BESS to be added to HRES to meet the derived constraints and their impact on the cost of energy as well. [Display omitted] [ABSTRACT FROM AUTHOR]

The increasing demand for renewable energy sources has led to the development of HRES that combine multiple sources of renewable energy to provide a reliable and efficient energy supply. However, renewable energy sources typically come with higher costs than conventional energy production methods. Hence, the optimal sizing of HRES is essential to prevent the oversizing of the system while ensuring a reliable supply of load demand, accommodating variations in meteorological conditions and changes in power demand. Numerous research papers addressing the optimal sizing problem are available in the literature. However, none of the mentioned studies take into account the power degradation of all renewable sources. The degradation of renewable sources, such as PV and WT, can have a significant impact on the performance of HRES. The degradation of PV panels can result in reduced efficiency and output, leading to a decrease in the overall energy production of the HRES. Similarly, WT may experience wear and tear over time, leading to reduced performance and output. The reduction in the output of renewables in the standalone system causes an increase in the loss of power supply probability (LPSP). This paper analyzes the optimal sizing of the HRES, considering the degradation of the sources. Further, analysis has also been carried out based on the number of BESS to be added to HRES to meet the derived constraints and their impact on the cost of energy as well. [Display omitted] [ABSTRACT FROM AUTHOR]

• 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]

Since a renewable energy is connected to a high-altitude integrated energy system (HAIES), challenges arise for system operation. Shared energy storage as a jointly operated energy hub for multi-integrated energy system (IES) can effectively improve the economy and flexibility of the system. This paper proposes a joint day-ahead and intra-day scheduling strategy for a HAIES considering a shared composite energy storage operator (SCESO) and profit clearing scheme. First, a HAIES structure suitable for residential, industrial, and commercial applications is built based on combined oxygen supply and integrated demand response (IDR). An SCESO is then proposed to provide multiple energy sharing services for HAIES cluster, including electricity–oxygen–hydrogen. Accordingly, HAIESs and SCESOs are aggregated to create a HAIES cluster energy sharing framework. Second, during the intra-day scheduling stage, which is based on real-time forecast data that considers multiple source–load–charge uncertainties, the flexible adjustment capabilities of each unit of the framework are used to achieve intra-day energy balance and ensure the safe operation of the framework. Furthermore, a profit clearing scheme is proposed, introducing different energy contribution quantification methods for different energy cooperation modes. Finally, day-ahead and intra-day simulation results under multiple scenarios are analyzed. The simulation results demonstrate that the framework is optimal in terms of economy, adaptability to different RE outputs and RE uncertainties, and energy storage utilization efficiency. • It proposes a new HAIES and SCESO energy cooperation framework. • An intra-day scheduling strategy for the framework is proposed. • A profit clearing scheme is constructed. [ABSTRACT FROM AUTHOR]

Liquid air energy storage (LAES) presents a promising solution to effectively manage intermittent renewable energy and optimize power grid peaking. This paper introduces a LAES system integrating LNG cold energy to flexibly manage power peaking, including intermediate energy storage, power generation using organic Rankine cycle, multi-stage direct expansion, and solar energy for heating. Aiming to maximize the electrical round-trip efficiency, a genetic algorithm is employed to optimize the operational parameters of the proposed LAES system. The results indicate that the combined design of cold energy utilization, multi-stage direct expansion and solar heating for proposed LAES system significantly improve the power performance, achieving an energy capacity of 0.125 kWh/kg LNG and an electrical round-trip efficiency of 376.7 %. The exergy losses of heat exchange equipment are far larger than mechanical equipment in the LAES system, so the optimization design of heat exchange equipment is preferred to improve the exergy performance. The proposed system achieves both high efficiency and flexibility and hence contributes to the development of liquid air energy storage systems. • LNG cold energy is used for air cooling and liquefaction. • Solar energy is used to increase the maximum temperature of direct expansions. • An outstanding electrical round-trip efficiency of 376.7 % is achieved. • Energy capacity reaches 0.125 kWh/kg LNG. • Heat exchanger equipment optimization is priority to improve exergy performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • PCM energy storage and PV/T coupled multi-source heat pump systems were combined. • The thermal performance, energy efficiency, and economy of the system were analyzed. • The performance of paraffin C17 and water as energy storage materials were compared. • The performance of six low-temperature PCMs applied to the system were analyzed. • Compared to the existing system, it saves 56 % of energy and 27.7 % of operating costs. To improve the application of renewable energy in the heating zone, as well as to address the limitations of air and water source heat pump. The study presents a PV/T (photovoltaic/thermal) coupled air–water source heat pump system integrated with phase change energy storage. A theoretical analytical model and TRNSYS simulation model of the system were developed to evaluate the thermal performance, energy efficiency and economics of the system. The performance of phase change energy storage was compared with that of water storage, and the effect of different phase change materials on the system characteristics. The results show that the coupled system achieves a seasonal performance factor of 2.3, a 56 % reduction in energy consumption, and a 27.7 % reduction in operating costs compared to a conventional gas boiler system. Comparative analysis with the water storage system showed that the system equipped with phase change materials performed well in terms of energy consumption, operating costs and heating stability. In addition, the density of the phase change material has a biased effect on the overall performance of the system. This paper can provide a reference value for the study of renewable energy heating systems in cold zone. [ABSTRACT FROM AUTHOR]

Given the stochastic nature of solar energy, integrating PV arrays with energy storage systems (ESSs) is crucial for a consistent power supply. Effective maximum power point tracking (MPPT) control is of great importance in this context. The significance lies not just in achieving high energy efficiency but also in ensuring overall system safety and reliability, as rapid and stable power tracking control alleviates power stress on ESSs. Challenging factors like parameter uncertainty from the PV array linearization process, dynamic DC bus variations induced by pulsed power loads, and sudden irradiance variation under cloudy weather, make the maximum output power of PV arrays largely dependent on the effectiveness of the control laws. Therefore, this paper presents a comparative study for MPPT control using PV-interfaced DC/DC converters. The aim is to demonstrate the advantages of employing average large-signal model-based sliding mode-type controllers in PV system integration with health-conscious objectives. A comprehensive system-level control-oriented modeling process is presented, followed by the theoretical background of three types of controllers (classical proportional–integral (PI)-type controller, μ -synthesis-based robust controller, and sliding mode controller) for practical applications. Extensive tests with real experimental data reveal sliding mode-type controllers' superiority in various integration scenarios. For example, with random solar irradiance variation over 0.5 s, they achieve a 54.75% reduction in energy loss, outperforming the commonly used PI-type counterparts. [ABSTRACT FROM AUTHOR]

In low-inertia grids, distributed energy storage systems can provide fast frequency support to improve the frequency dynamics. However, the pre-determination of locational demands for distributed energy storage systems is difficult because the classical frequency dynamic equivalent response cannot capture the dynamic characteristics of the entire system. Additionally, optimal allocation of the distributed energy storage systems required for the different buses is challenging because of nonlinear constraints that account for these locational effects. This paper develops a method to evaluate locational frequency security. By simulating the worst-case G-1 contingency, the distribution network buses that violate the limit of the maximum rate of change of frequency are determined as the installation locations of distributed energy storage systems. We then propose a feasible region-based linearization method to replace the complex nonlinear constraints. Finally, we present a two-stage robust allocation model for distributed energy storage systems that is intended to maintain locational frequency security. The validity of the proposed method is verified through case studies performed on a modified IEEE RTS-24 bus system and a modified IEEE 118 bus system. The results show that the optimally allocated distributed energy storage systems effectively reduce the frequency safety risk that originally existed due to oscillation at the distribution network buses. • A locational frequency security evaluation method after G-1 contingencies is proposed. • Considering frequency oscillations, a feasible region-based linearization method is designed. • Distributed storage systems are optimally allocated for locational frequency security. [ABSTRACT FROM AUTHOR]

• A Reference-Standard-Volume optimization method is proposed to improve CESPB. • The best aspect ratio of CESPB is 2–4 considering efficiencies and pressure drop. • The volume multiple is given at 1.1 with the highest exergy efficiency of 63.72 %. • The thermal and exergy efficiencies are increased by 2.03 % and 3.65 %, respectively. Cryogenic liquids (e.g., liquid air, liquid hydrogen, liquid carbon dioxide) have gained popularity in electricity storage due to their high energy density, no geographical constraints, and environmental friendliness. The cryogenic energy storage packed bed (CESPB) is widely employed as a cold recovery device to enhance the round-trip efficiency of cryogenic energy storage systems. Nonetheless, the cycle efficiencies of CESPB remain relatively low, with limited research investigating efficient methods for determining the design parameters. To address this, a novel optimization method named as the Reference-Standard-Volume (RSV) approach is introduced to enhance the thermodynamic performance of CESPB. In this paper, the complete optimization process of CESPB is illustrated, presenting the optimization outcomes in the view of heat and mass transfer. The findings reveal that a larger aspect ratio leads to the higher efficiencies but increased pressure drops. An optimal aspect ratio of 3 and a volume multiple of 1.1 is identified, achieving the highest exergy efficiency of 63.72 %. Meanwhile, increasing charging/discharging time enhances heat transfer in CESPB, however, it leads to an increase in external cold dissipation, which gives an optimal charging/discharging time of 3/3 h. By implementing the RSV optimization method, the percentage increase of discharging efficiency, thermal efficiency, and exergy efficiency of CESPB is 2.08 %, 2.03 %, and 3.65 %, respectively. These research outcomes offer valuable reference and guidance for future CESPB design and research. [ABSTRACT FROM AUTHOR]

Modular Gravity Energy Storage (M-GES) systems are emerging as a pivotal solution for large-scale renewable energy storage, essential for advancing green energy initiatives. This study introduces innovative capacity configuration strategies for M-GES plants, namely Equal Capacity Configuration (EC) and Double-Rate Capacity Configuration (DR), tailored to optimize energy storage efficiency and stability. Through comprehensive MATLAB/Simulink simulations, we demonstrate each configuration's distinct power characteristics and operational advantages. Our findings reveal that while the EC configuration offers enhanced power accuracy and stability, it requires a larger number of units. In contrast, the DR configuration, characterized by fewer but larger units, shows a trade-off with reduced power stability. This paper contributes significantly to the field by presenting a first-of-its-kind comparative analysis of these configurations, offering insights into their practical applications and scalability. The proposed strategies and findings lay a foundation for future research and development in gravity energy storage systems, marking a step forward in pursuing sustainable and reliable energy solutions. [Display omitted] • Two typical unit capacity configuration strategies for M-GES power plants are proposed. • The unit scheduling method of the M-GES power plant is proposed. • The coordination control method is provided for each proposed configuration strategy. • Equal capacity configuration has better power accuracy but requires more units. • Double rate configuration needs fewer but larger units and less power stability. [ABSTRACT FROM AUTHOR]

• Linear planning models of two types of compressed air energy storage are proposed. • A novel electricity-gas coupled energy hub for cascade utilization is structured. • Comparisons between energy-based and capacity-based energy storage are analyzed. Large-scale long-duration energy storage (LDES), like compressed air energy storage (CAES) and liquid air energy storage (LAES), is promising for high-penetration renewable energy consumption in the city-scale integrated energy system (IES). Due to high installation costs and challenges in decentralized control of distributed energy storage, this paper proposes an optimal planning model for an urban electricity-gas coordination hub (UEGCH) with centralized energy storage using large-scale LDES. Firstly, the UEGCH with energy cascade utilization is designed, where process-based linearized models of advanced adiabatic compressed air energy storage (AACAES) and LAES are established to make a trade-off between solving accuracy and speed. Then, a city-scale integrated electricity and gas system (IEGS) is constructed with multiple regions considering line-packing. Finally, a multi-scenario planning method is proposed based on X-means for scenario reduction, and the global optimum is obtained through linearization. Results show that compared with traditional gas storage tank (GST) in the UEGCH, the utilization of AACAES and LAES requires as little as 7 % and 0.7 % of the construction volume with lower carbon emissions and can be cost-competitive in terms of future advancement. As for different EESs, in contrast to the energy-based energy storage (EBES) (i.e., battery (BT)), the levelized cost of energy (LCOE) of the capacity-based energy storage (CBES), which includes AACAES and LAES, can be reduced by nearly 0.1 $/kWh, bringing an annual economic benefit of $ 3 million. Besides, the discharge duration of CBES can be increased to 13 h, demonstrating the application prospect in 100 % renewable consumption and islanding operation. Compared with AACAES, LAES can reach 11.67 times the energy density, with a drop of 6.11 % in operating cost. The abilities of EBES and CBES to locally consume renewables are respectively weaker and stronger than that of power-to-gas (P2G) combined with line-packing. Meanwhile, this paper further analyzes the impacts of temperature, discharge duration, renewable penetration, energy tariff, and demand on the operation and sizing of centralized energy storage. [ABSTRACT FROM AUTHOR]

In recent years, the severe environmental degradation and high levels of fossil fuel consumption linked to conventional ship energy systems have drawn attention to the advancement of alternative ship energy systems. Consequently, ship energy systems based on the use of an electrical microgrid are coming to the fore as an increasingly popular alternative solution. However, managing the energy flows within a shipboard microgrid can be highly challenging due to the multiple energy sources (including renewable energy sources) and types of loads involved. Additionally, the integration of an energy storage system has been identified as an effective solution for improving the reliability of shipboard power systems, pointing out the important role of energy storage systems in maritime microgrids and their potential to enhance the energy management process. As such, effective energy management strategies are necessary to optimize performance and ensure that the vessel's energy demands are met while minimizing fuel consumption and reducing cost and environmental impacts. This paper presents a comprehensive review of such strategies and methods recently presented in the literature associated with energy management in shipboard microgrids integrating energy storage systems and examine the different techniques that can be utilized to achieve optimal system performance. Moreover, the paper also sheds light on the future challenges and perspectives imposed by the modern shipboard microgrids operation on the energy/power management of these systems. The aim of this paper is to provide a helpful guideline for researchers and engineers conducting research in the field of electrically powered ships. [Display omitted] • A comprehensive review of EMS for electrical and hybrid ship is presented. • A comprehensive review of ESS which can be used in such ships is presented. • Technologies of ESS and their suitability to ships are discussed and commented. • Future challenges and perspectives imposed by modern SMG operation are presented. [ABSTRACT FROM AUTHOR]

Lower limb exoskeletons have garnered significant attention for their effectiveness in gait training for paraplegic patients. For patients with insufficient trunk or upper limb strength to maintain balance, employing an unpowered robotic walker with an exoskeleton for gait training is an effective approach. The energy efficiency of the actuation system is a pivotal consideration in the design of the exoskeleton–walker system due to its significant influence on the system's durability and service efficiency. The main contribution of this paper is the development of a Parallel Compliant Leg (PCL) for the exoskeleton–walker system. The PCL consists of both powered legs of the exoskeleton and a passive flexible mechanism within the walker. This integration allows for the storage and release of energy during cyclic walking, resulting in reduced system energy consumption. To enhance energy efficiency, the support force optimization of the flexible mechanism is established. Based on this optimization, a design scheme and parameter optimization for the flexible mechanism are proposed. The effectiveness of the proposed flexible mechanism is verified through simulations on a robot simulation platform. Experimental results demonstrate a remarkable 67.6% reduction in system energy consumption achieved by the optimized mechanism. [ABSTRACT FROM AUTHOR]

This research paper presents an in-depth analysis of diesel–electric power systems in offshore Platform Supply Vessels (PSVs). The main contribution is the use of real data obtained from a PSV to produce and validate computational models subsequently used to accurately calculate fuel consumption and emissions, with representative load demands, considering different configurations of non-hybrid and hybrid power systems with the addition of lithium-ion batteries to provide a reliable analysis. Power dispatch optimization had a significant impact, achieving fuel and CO 2 reductions of around 7%–12% in non-hybrid systems, depending on the generator loading limits. Hybridization and battery integration further enhanced reductions, with up to 10% improvements in fuel consumption and CO 2 emissions. Particulate matter (PM) emissions and running hours were substantially reduced, but NO x varied. Validity checks accounted for biases, and the study provided reliable assessments of trends. The differences between monthly averages and robust approaches were minimal. Overall, the strategies presented achieved reductions of up to 15% in fuel consumption and CO 2 emissions, 20% in NO x emissions, and 68% in PM emissions for the complete mission. • Analyzing Platform Supply Vessel's power system with real data and computation models. • Power dispatch optimization yields significant fuel consumption and CO 2 reductions. • Battery integration further improves fuel efficiency and CO 2 reductions. • Particulate matter emissions and running hours reduce considerably, but NO x varies. • Validity checks account for biases providing a reliable assessment of trends. [ABSTRACT FROM AUTHOR]

Developing high-efficiency solar photothermal conversion and storage (SPCS) technology is significant in solving the imbalance between the supply and demand of solar energy utilization in time and space. Aiming at the current research status in the field of SPCS, this review thoroughly examines the phase change materials and substrates in SPCS systems. It elucidates the design principles and methods of SPCS integrated composites. Comparatively, it analyzes the parameters of various types of SPCS composites in terms of photothermal conversion, thermal conductivity, energy density, and cycling stability. Additionally, the review discusses the trade-offs between each parameter to achieve the most optimal effect of SPCS. By sorting out the current status of the application of SPCS technology in solar thermal/photovoltaic, aerospace, buildings, textile, and other industries, this analysis clarifies the requirements for various latent heat, phase change temperature, and other properties under different environmental conditions. Through a comprehensive discussion of SPCS technology, this paper accurately captures the development trend of efficiently and comprehensively utilizing solar energy by analyzing existing scientific problems. It identifies bottlenecks in SPCS technology and suggests future development directions that need focused attention. The insights gained from this analysis may provide a theoretical basis for designing strategies, enhancing performance, and promoting the application of SPCS. [Display omitted] • SPCS technology show high efficiency for energy utilization and management. • SPCS can solve the imbalance in the supply and demand of solar energy utilization. • The study of the design principles and methods of SPCS is important. • SPCS system can solve the energy crisis and environmental pollution. • SPCS systems have great potential for practical water treatment in the future. [ABSTRACT FROM AUTHOR]

In recent years, liquified natural gas (LNG) cold energy utilization technology has been widely investigated due to the increasing global use of LNG. The LNG stored at −162 °C needs to be regasified. To efficiently recover the large amount of cold energy released during the regasification process of LNG with lower investment, a multi-stage Rankine cycle system combined with hydrate energy storage and seawater ice-making cycle was carried out, and the advanced exergy and exergoeconomic analysis was conducted in this paper. The Aspen HYSYS V11 was selected to establish the LNG cold energy recovery process. The result of exergy analysis shows that the exergy destruction rate and exergy efficiency of the total system are 1662.655 kW and 41.149 %, respectively. For conventional analysis results, the burner gives the highest exergy destruction and total cost rate, while considering the result of advanced exergy and exergoeconomic analysis, the condenser 2 gives the highest avoidable exergy destruction, and the turbine 1 gives the highest avoidable total cost rate. In addition, 26.49 % of exergy destruction, 31.6 % of exergy destruction cost rate and 6.59 % of investment cost rate are avoidable, which indicated the optimization potential of the proposed system. • Advanced exergy and exergoeconomic analysis of LNG cold energy recovery system is carried out. • The exergy efficiency of the total system reaches 41.149 % under real condition. • 26.49 % of exergy destruction, 31.6 % of exergy destruction cost rate and 6.59 % of investment cost rate are avoidable. • The system has good energy and economic benefits. [ABSTRACT FROM AUTHOR]