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Although several studies have been performed on energy systems, there is a gap in examining the impact of energy storage systems (ESSs) technologies on the technoeconomic design of optimal multicarrier microgrids (MCMGs), considering environmental concerns. This paper aims to address this research gap by developing an optimal technoeconomic reliability‐oriented design of MCMGs, specifically focusing on battery storage systems (BSSs) and hydrogen storage systems (HSSs). The study was applied to MCMG at an actual MCMG, using HOMER Pro software. Additionally, a reliability‐oriented sensitivity analysis is conducted to understand the effects of reliability constraints, such as desired maximum capacity shortage, on the performance of various ESS technologies. One of the main contributions is analyzing the HSS and BSS from different viewpoints, such as cost, emission, and other technical–economic features for MCMGs. The comparative test results show that if a highly reliable MCMG is desired, the BSS‐based MCMG is the more practical option in terms of technoeconomic indices. However, regardless of reliability constraints, the HSS‐based MCMGs offer better environmental conditions. The total net present cost of the HSS‐based MCMG is 1.68% higher than the BSS‐based one, while it has 17.99% less CO2 emissions, while the HSS one has 17.99% less CO2 emissions. [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]

Thermal energy is one of the most widely encountered energy forms in our daily life. To ensure efficient utilization and conversion of this energy, the balance between supply and demand needs to be maintained. For this purpose, thermal energy storage is required. There are various thermal energy storage systems available; one of the most basic is sensible thermal energy storage which includes rock thermal energy storage (RTES). This rock‐based energy storage has recently gained significant attention due to its capability to hold large amounts of thermal energy, relatively simple storage mechanism and low cost of storage medium. Accordingly, numerous studies have been conducted to elucidate the basic flow and heat transfer mechanism and to evaluate the performance of this energy storage. The major technical challenges hindering the wide adoption of this technology are the enormous pressure drop across the storage and nonoptimal heat transfer from the heat transfer fluid to the storage medium and vice versa. These issues will directly and indirectly affect the overall cost (capital, operational, and maintenance costs) of the system. To eliminate this issue and assist further development of this technology, it is crucial to compile and extract important findings from these previous studies, identify the challenge and research gap, and draw guidelines for the upcoming research and development. At the moment, this kind of compilation does not exist. Hence, this paper is prepared with the primary objective to comprehensively review the current technology and development of RTES and to propose a potential way forward based on the pain point identified. Discussion on the nontechnical aspect such as policy and regulations as well as community awareness will also be outlined and discussed. [ABSTRACT FROM AUTHOR]

In this paper, a new control strategy, along with an innovative switching pattern, is proposed for the transfer of charge from one cell to another, whether they are adjacent or nonadjacent, or even to multiple cells simultaneously. Therefore, this strategy improves the efficiency of state of charge balancing, which is critical for lithium polymer (LiPo) batteries. Unlike in previous studies, all these functions are realized with a simple structure that employs standard DC–DC buck‐boost converters, without any additional complexities. By implementing the proposed control strategy, the effects of inaccuracies in the gain of current sensors, as well as multiplicative measurement noises, are reduced. The proposed method is applied to a set of five series LiPo cells, and a comprehensive investigation is conducted to assess both its balancing algorithm and operation. The simulation results illustrate the effective balancing performance and the achievement of the desired charge transfer through the proposed approach. An experimental setup, which includes five LiPo cells with a capacity of 1530 milliampere‐hours (mAh), is used to verify the proposed method. The outcomes demonstrate that the balancing of all cells is accurately performed under different initial conditions, within an acceptable time frame. [ABSTRACT FROM AUTHOR]

The direct current (DC)‐link voltage control of the flywheel energy storage system plays an important role in realizing high‐quality grid connection. With the traditional proportional‐integral control, the DC‐link voltage cannot track its reference value quickly and smoothly when the flywheel energy storage system switches from the charging stage to other working stages. Therefore, a DC‐link voltage control strategy for the flywheel energy storage system based on active disturbance rejection control is proposed in this paper to deal with this issue. The DC‐link voltage and its differential value are considered as the state variables in this strategy. The internal and external disturbances, such as load power, switching loss, and parameter uncertainty, are regarded as an expanded state. By inputting the voltage error and the observed disturbance into the nonlinear state feedback control law, the rapidity and anti‐interference of the DC‐link voltage control are ensured under different States of Charge of the flywheel energy storage system. Then, the coefficient freezing method is used to analyze the effects of the disturbance observation bandwidth by nonlinear gain and pole position changes. The DC‐link voltage can track the reference value over a wider frequency range of disturbances. By configuring the appropriate observer structure parameters, the disturbance observation bandwidth under the nonlinear function gain variation is always higher than the expected bandwidth. The effectiveness of the proposed control strategy is verified by simulation results at last. [ABSTRACT FROM AUTHOR]

Renewable energy (RE) sources play an important role that not only reduces the pressure on fossil fuels but also produces safe and clean energy by developing the microgrid (MG) technology that fulfills the excess demand for power throughout the world. The technological development and the blessing of information and communication technology converts the MG technology to a smarter one, termed as smart grid (SG) and virtual power plant, by establishing a two‐way communication between the consumers and service provider with the aid of smart metering infrastructure, dynamic pricing scheme, energy management system, smart transmission and distribution system. The transformation of the traditional power system to SG enhances the efficiency, flexibility, resiliency, and robustness of the power system due to the increasing level of cyber security and automation. A directional pathway from conventional to smart power system has been carried out in this paper by addressing the present status of the power system, challenges during the operations, and possible solutions. Initially, the control operation of MG with RE and energy storage system has been investigated which is essential to understand the operation complexity and challenges due to the variable nature of the RE, load dynamics, and uncertainties. But the facilities of end‐user feedback, dynamic pricing scheme, cyber security, and smart metering system are not present in MG technology that hampers the proper regulation of controlling operation, generating and distributing energy as well as energy losses. The development of SG with smart technologies overcomes these problems by proper controlling of power usage. Finally, this paper provides a path to move the MG toward SG by analyzing the technical and critical challenges of smart devices, equipment integration, and their control issues and provides possible solutions to overcome the integration and control challenges for a reliable and sustainable operation. [ABSTRACT FROM AUTHOR]

The battery energy storage system (BESS) is considered as an effective way to solve the lack of power and frequency fluctuation caused by the uncertainty and the imbalance of renewable energy. Based on these, this paper proposes a mixed control strategy for the BESS. First, this paper divides the demand for frequency modulation, peak regulation, and state of charge (SOC) of the battery into different zones. Then the Kuramoto model modulates the frequency, and the self‐recovery strategy is used to optimize the SOC. Meanwhile, the proposed mixed control strategy is used to integrate frequency control, demand control, and SOC optimization. Finally, the simulation results verify the rationality of the strategy. [ABSTRACT FROM AUTHOR]

The fuel cell system (FCS) is commonly combined with an energy storage system (ESS) for enhancing the performance of the ship. Consequently, the battery ESS size and power allocation strategy are critical for the hybrid energy system. This paper focuses on designing a method to solve these two problems. First, a battery degradation model is employed to assess the ESS lifetime. Subsequently, the sizing problem and the optimal power allocation are integrated into a cost‐minimization problem, which is solved by a double‐loop optimization approach. The inside loop utilizes the battery degradation model to calculate ESS lifetime. In the outside loop, a power allocation strategy based on the hybrid Particle Swarm Optimization algorithm and Gray Wolf Optimization algorithm is presented. Finally, the power allocation strategy is extended to real‐time implementation by the equivalent consumption minimization strategy (ECMS) and an improved ECMS is proposed to make the FCS operates near the maximal efficiency point. Compared with ECMS, the operating cost reduces by 0.26%. The result indicates that the proposed method can optimize the ESS size efficiently, and the power allocation strategy can assure the stable operation of the fuel cell ship. [ABSTRACT FROM AUTHOR]

A significant amount of electricity in numerous regions worldwide is used for lighting roads, squares, and other public spaces. Renewable energy can contribute notably to electricity usage for public lighting. This paper focuses on the day‐ahead scheduling of a hybrid renewable energy system (HRES) exploiting solar–wind energy potential to meet the electrical energy needs of public lighting. The studied HRES provides electricity for a Wi‐Fi hotspot and a charging hotspot for the end users and has an energy storage system that ensures a reliable electricity supply without interruptions. The day‐ahead scheduling of the studied HRES is based on electricity generation forecasting by using a deep‐learning approach. Particularly, the long short‐term memory model is utilized, considering the fact that it is able to perceive long‐term dependencies among the time series. Moreover, the model's performance is investigated through the determination of diverse inputs: (a) historical data, (b) weather predictions, and (c) historical data with weather predictions. Multiple scenarios of energy consumption are assumed and applied to optimize the day‐ahead scheduling. A new recommendation method is proposed and applied for day‐ahead scheduling, utilizing the power forecasts to achieve optimum operation and energy savings. The results point out that the utilization of the proposed recommendation method controls loads when a shortage in power generation and battery capacity is forecasted for the day ahead, leading to significant energy savings and minimizing the power demand from the grid. [ABSTRACT FROM AUTHOR]

Packed bed thermal energy storage (PBTES) is an essential means to solve the temporal difference and continuity between energy supply and utilization in the fields of concentrating solar power, compressed‐air energy storage, and waste heat recovery. In this paper, to solve the imperfection and inaccuracy of the current energy model, a precise transient two‐dimensional multiequation model is developed. The model comprehensively considers thermal dispersion, wall effects, thermophysical property changes, and other factors. Experiments are performed to compare and validate the simulation results, and the simulation error is −4.5% to 1.9%, achieving excellent simulation accuracy. Also, the wall effect on the PBTES is observed, and the gas‐solid temperature fields exhibit an evident nonuniform oscillation distribution in the radial direction. The effects of storage tank length, thermophysical properties, particle diameter, and gas‐solid initial temperature on the heat release rate are discussed in detail. Results indicated that decreasing the tank length, increasing the gas‐solid temperature difference, and particle materials with high thermal diffusivities can increase the heat release rate, and a clear linear change was found. Particularly because a larger range of particle diameter variation is considered, the heat release rate is shown to vary nonlinearly with particle diameter, and the selection of the optimal diameter must comprehensively consider the effects of the heat capacity and the heat transfer rate. This study provides a theoretical basis for the design of thermal energy storage systems. [ABSTRACT FROM AUTHOR]

Nowadays most photovoltaic (PV) plants usually use battery energy storage technology to smooth fluctuant power, but batteries have the drawbacks of a short lifetime and environmental pollution. The existing renewable power networks have serious problems with decarbonizing electricity on the end‐user side. This paper investigates a new hybrid photovoltaic‐liquid air energy storage (PV‐LAES) system to provide solutions for the low‐carbon transition for future power and energy networks. In this article, a local PV power plant cooperates with its maximum power point tracking (MPPT)‐based boost converter, to generate low‐carbon electricity with some uncertain fluctuations. Then a zero‐emission‐air‐based LAES unit is used to absorb the surplus power from the PV plant, and also compensate power for the local load with inadequate power level. This makes the new system save a large proportion of power from main grids, which can also indirectly reduce greenhouse gas emissions. For the MW‐class PV‐LAES case, results show that the surplus renewable electricity (6.73 MWh) generates 27.12 tons of liquid air for energy backups during the day time, and then the LAES unit has a round‐trip efficiency of 47.4% that can discharge a flexible power compensation to the load in the night. Accordingly, the grid power demand reduces significantly from 12.78 to 3.33 MWh in a day. In this way, the annual power savings is estimated to be 3449.25 MWh, and the corresponding carbon emission can be reduced by 2607.63 tons. Regarding the economic performance, the PV‐LAES system presents a dynamic payback period of 9.33 years and an accumulated life‐cycle net profit of $2,260,011. Overall, the proposed PV‐LAES scheme is economically feasible from a life‐cycle perspective, and can potentially realize flexible energy interaction with local renewables to achieve an integrated low‐carbon power generation and storage system. [ABSTRACT FROM AUTHOR]

The renewable energy system integrates various power generating units, heating units, energy conversion devices, and energy storage devices, which is an effective way to improve energy efficiency and realize clean energy utilization. In this paper, a renewable energy system integrating with photovoltaic electric power generation systems, wind‐driven generators, gas‐driven generators, gas‐fired boilers, electric chillers, electric and heating energy storage devices is constructed in an isolated tourist area. Considering the complex multi‐energy flows in renewable energy systems, an energy hub with power and heat is established to concentrate and distribute electric and heating energy flow for balancing energy supply and demand in a CCHP system. Introducing the constraints of renewable energy penetration index and energy supply reliability index, a collaborative optimization framework for system configuration is constructed to minimize annual capital cost, fuel cost, and maintenance cost. The simulation results show that the model and algorithm in this paper are feasible and applicable, and the optimization scheme has good economic benefits and optimal performance, which can promote the consumption of renewable energy and reduce the surplus of electric energy and heat energy. [ABSTRACT FROM AUTHOR]

In this paper, a novel energy storage technology of a gravity‐enhanced compressed air energy storage system is proposed for the first time, aiming to support the rapid growth of solar and wind capacity. With air storage formed by the shaft well, gravity piston, and seal membrane, the proposed system could achieve constant operating pressure, high storage efficiency, and large storage capacity. Electricity charged into this system is simultaneously transformed and stored in the thermal, pressure potential, and gravitational potential forms. The operating properties of the proposed system are simulated and analyzed with the commercial software Thermoflex V29. Results show that both the storage pressure and the well radius have essential influences on the performance of the newly proposed system. The theoretical energy storage efficiency of the proposed system is in a scope of 63.58%–65.50% with a storage pressure range of 40–100 bar. Economic analysis based on the time‐of‐use price policy in China suggests that the optimum levelized cost of storage (LCOS) happens at the storage pressure of 70 bar and a well radius of 8 m. Besides, considering different plant cost factors that reflect the total investment of a power plant, the optimum LCOS is 1.09–1.26 CNY/kWh. Moreover, the specific exergy cost of the discharged electricity is assessed to be 0.51 CNY/kWh or so, which is significantly more profitable compared with the given electricity price of 1.15 CNY/kWh at off‐peak. [ABSTRACT FROM AUTHOR]

With the development of multi‐energy technology, the electric‐heat integrated energy system has become an important research direction for multi‐energy joint supply. The dynamic characteristics and energy storage capacity of heat supply network provide potential for joint dispatching of electric heating energy system. Aiming at the problem of electric‐heat joint dispatching, this paper presents an operation optimization model of electric‐heat integrated energy system considering the virtual energy storage characteristics of heat supply network. Firstly, according to the characteristics of transmission delay and user temperature fuzzy, the virtual energy storage characteristics of heat supply network are studied, and a model of the dynamic transfer of energy in the heat system was built. Then, the operation optimization model of the electric‐heat integrated energy system is established to minimize the operation cost. In order to improve the robustness of scheduling optimization results, the Monte Carlo Simulation embedded Quantum Particle Swarm Optimization algorithm is proposed to solve the model. In order to prove the validity of the proposed model, this paper selects a park (a 36 node thermal system) in the northwest region of China as a simulation case. The results show that the operation optimization method considering the virtual energy storage of heat supply network will greatly enhance the complementary potential of the electric‐heat integrated energy system and reduce the operation cost of the system. [ABSTRACT FROM AUTHOR]

High peak current for vehicle starting, recuperation of regenerative braking energy, longer battery lifespan, and more significant acceleration among others in modern transport vehicles (TVs) require increased battery size. Moreover, batteries have high energy density and low power density. Therefore, a big battery pack can weigh more, shorten its lifespan, increase vehicle total mass, and increase battery degradation costs. On the one hand, higher power energy storage systems (ESSs) such as supercapacitors, lithium‐ion capacitors, and superconducting magnetic ESSs have a lower energy density, higher power density, and greater lifespan. Thus, to satisfy the requirements of modern TVs, the combination of higher energy and higher power density can provide enhanced performance and a longer battery lifespan for these vehicles. Available research publications in the literature have addressed a similar problem. However, these publications have reported the findings separately, providing various research and conclusions. Currently, no available literature has compiled an intelligible and combined analysis for addressing hybrid ESS configurations, sizing methods, and energy management strategies to create further knowledge in this domain. There is a need to consolidate a compact and insightful knowledge toward this research direction for a more significant societal and industrial impact. This paper critically reviews the hybrid higher energy density batteries and higher power density ESSs used in TVs. It discusses the integration configurations, applications, and provides sizing methods to achieve the best hybrid energy storage systems (HESSs). Also, applied control methods are described for these HESSs such that the overall system performance matches the vehicle requirements. Lastly, it provides insights and future research direction for HESS configuration, sizing, and control. [ABSTRACT FROM AUTHOR]

Mature and inexpensive ice thermal storage was employed to replace battery bank in energy storage, and photovoltaic directly driven technology was also combined in this paper. A 3HP household air conditioning assisted with ice thermal storage was investigated in four operating conditions. First, directly driven by photovoltaic arrays, the (COP)rs were almost 6.31% than that of refrigerator driven by power grid for the instantaneous solar irradiance, and the stored cooling capacity decreased 18.63% under the intermittent influence of solar irradiance. Moreover, the (COP)r of refrigerator operating in out‐of‐box mode was about 1.38 times that of operating in ice storage mode. Next, the inevitable compress motor fluctuation, caused by instantaneous solar irradiance, was investigated by experiment and simulation. In three typical weathers, compressor fluctuating time was approximately 65.22 s, 197.05 s, and 270.48 s in full irradiance range. When the lower solar irradiance limit was optimized from 150 to 80 Wm−2, refrigerator operated stably and continuously in any weather conditions. The ice production and the (COP)r were improved by 40.91% and 12.36%, respectively. [ABSTRACT FROM AUTHOR]

With the increase in new energy power generation and the continuous augment in the penetration rate of electric vehicles, it is of crucial importance to use electric vehicles as energy storage devices to promote the consumption of new energy. Aiming at the uncertainty of electric vehicles, this paper proposes a method based on multiobjective optimization for electric vehicle‐supercapacitor hybrid energy storage system to track PV project output. The hybrid system consists of electric vehicles and supercapacitor. Electric vehicles and supercapacitors supplement the deviation of PV actual power and predicted power by charging and discharging. The electric vehicle is regarded as a nonspecific way to label a piece of equipment that can store energy. First and foremost, on the basis of traditional method of predicting PV output, a PSO‐BP prediction method based on PCA is proposed to improve the accuracy of PV output prediction. Secondarily, according to the different characteristics of electric vehicles and supercapacitors, the empirical mode decomposition (EMD) method is used to decompose the deviation that the hybrid energy storage system needs to bear with the purpose of initially allocating the energy. Furthermore, a multiobjective optimization model is established for the precise energy distribution of the hybrid energy storage system, and the NSGA‐III algorithm is used to solve it. Ultimately, the data of a domestic PV power station are used for simulation. After optimized control, the result shows that the standard deviation of the system output is reduced from 1967 to 75.77. The research in this article provides a theoretical basis for the application of electric vehicle virtual energy storage technology in the field of auxiliary new energy grid connection. [ABSTRACT FROM AUTHOR]

The efficiency of DC microgrid needs investigation from a smart grid perspective, since their spread has expected to prevail in comparison with AC counterparts. Furthermore, there is a need to address the limitations (majorly to cater the intermittency of distributed energy resources (DERs) as well as the time dependency of systematic parameters etc.) in previous model and propose a new mathematical model to evaluate system efficiency for given parameters and scenarios. The core focus of current study aims at formulation of an improved (composite) mathematical model, that is capable of bridging issues and serve as a tool to address requirements of future DC systems including microgrids (MGs) and multi‐microgrids (MMGs). This research work offers such a mathematical model that consists of 3D matrices based on newly derived set of discrete time dependent equations, which evaluates the system efficiency of residential DC‐MMGs. Each DC‐MG is embedded with intermittent DERs, storage, components (with efficiency variations), and multi‐class load (with discrete time dependency), for evaluation across worst, normal, and best scenarios. A comprehensive sensitivity analysis across various cases and respective scenarios are also presented to evaluate overall system performance. Also, the impacts of system parameters on various system variables, states, and overall system efficiency have presented in this paper. [ABSTRACT FROM AUTHOR]

This paper presents a stochastic bi‐objective model to reduce the operation cost and the carbon emission of a smart railway station along with dependent commercial buildings, according to a multi‐energy hub system's structure. The proposed energy hub system (EHS) includes a power, heating, and cooling subenergy hub. The recovered energy obtained from the regenerative braking (RB) during train deceleration is utilized to supply the load of EHS. To calculate the recovered energy, the motion of trains is simulated in MATLAB software. Furthermore, a demand response program (DRP) is integrated into the model to improve the flexibility of the EHS. Also, the uncertainty related to the photovoltaic generation and the power obtained from RB is considered. GAMS software is used to solve the bi‐objective model with the ɛ‐constraint approach. Then, to select the best possible solution, a fuzzy technique is engaged. Seven case studies are considered investigating the effect of exerting the DRP, utilizing the recovered energy, and employing the energy storage on operation cost and carbon emission. The simulation results demonstrate a significant improvement in operating cost and the carbon emission for the proposed EHS. [ABSTRACT FROM AUTHOR]

This paper studies the heat storage system's influence on a solar chimney's power production. This study considers several material types, including solid and phase change materials, at the bottom section of a solar chimney for energy storage, and evaluates their effects on the energy yield and capacity to prolong the power output during the absence of the sun. A computational fluid dynamic model using COMSOL Multiphysics is performed to carry out this work. An initial steady‐state analysis using average monthly irradiance is implemented, after which the top two solid and phase change material options are selected. Subsequently, a time‐dependent simulation using a typical summer day is carried out for the chosen storage materials. The overall performance results are comparatively assessed in terms of average temperature, power generation, and efficiency. As a result, bismuth‐led‐tin‐cadmium and magnesium chloride hexahydrate present the highest power production among the phase change materials, giving a yearly average power output of 27.46 kW and a storage temperature of about 346 K. On the other hand, sandstone offers the highest overall annual average power production, yielding 31.49 kW, and a storage temperature of 352.17 K. This material also reflects the highest yearly average energy and exergy efficiencies with 0.122% and 0.128%, respectively. [ABSTRACT FROM AUTHOR]

Over the past years, wind energy has been considered as a promising solution for clean and sustainable energy development, but wind curtailment remains a challenge to wind power development. On this basis, utilization of non‐grid‐connected wind power becomes crucial and necessary as it can mitigate wind curtailment and improve energy efficiency. This paper proposes the collaboration strategy and optimization model of wind farm‐hybrid energy storage system (WF‐HESS) for non‐grid‐connected wind power based on battery and superconducting magnetic energy storage (SMES) whose combination can effectively cope with fluctuation and intermittence of wind input. The optimization problem is simultaneously investigated by the minimization of total cost, wind curtailment magnitude, and loss of power supply probability (LPSP). The multi‐objective particle swarm optimization (MOPSO) is introduced to find available solutions, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to determine the optimal one. Results are obtained for a case study, and the effectiveness and the feasibility of proposed model are verified by a comparative analysis and a sensitivity analysis. Results analysis and discussion show that the WF‐HESS model and the application of HESS have important influence on promoting utilization of non‐grid‐connected wind power and mitigating wind curtailment. [ABSTRACT FROM AUTHOR]

The combined heat and power system (CHPS) is one important type of the integrated energy system in Northern China. Compared with the independently operated power system, the combined heat and power system (CHPS) has a great potential to improve the utilization of wind energy in virtue of the energy storage of the heating system and power‐to‐heat (P2H) devices. This paper studies the optimal operation of the CHPS equipped with the electric boiler (EB) and heat pump (HP). Comprehensive factors are considered, including P2H conversion, the thermal inertia of district heating network (DHN) and buildings, and adjustable heat loads. An equivalent model of the heating system is developed to express the direct mathematical relations between the heat source and heat loads. Redundant details of the DHN are simplified to reduce the complexity of the optimization problem. Furthermore, a self‐repair method incorporated with the real‐coded genetic algorithm (RCGA) is proposed to efficiently handle the nonlinear constraints. The effectiveness of the solving method is verified in case studies. The impacts of the EB and the HP on the CHPS are compared in details. The results show that the HP offers better performance than the EB on coal saving and improving wind power integration. [ABSTRACT FROM AUTHOR]

Abstract: This study is focused on the design of the subsea accumulators currently used to deliver a pressurized fluid whose function is to actuate safety operations on a subsea well. API 16D, whose specifications regulate the design method of a bank of accumulators, was revised, discussed, and resumed in terms of a nomogram whose engineering value is useful for designers. An additional nomogram was derived allowing to perform the verification process which is suggested by the norm, in order to verify the fulfillment of the actuations requested to the accumulators. This verification phase caught the interest of the Authors: API 16D assumes for the design that the Functional Volume Requirement (FVR) – the sum of the quantities of pressurized fluid to be delivered for different sequenced‐in‐time functions – is delivered at the Minimum Operating Pressure (MOP) requested by the last actuation. This hypothesis simplifies the design, but the result cannot fulfill the previous functions because of the pressure lack (energy content in the pressurized propelling gas) which can happen. The use of the two nomograms proposed simplifies the application of the design procedure and allow to discuss main sensitivities of the variables involved (FVRs & MOPs), evidencing which variables deserve more attention and accuracy. In particular, the use of the second nomogram permits to verify that the right volumes of fluid during the actuations are delivered above a minimum pressure level, so guaranteeing the fulfillment of the function. It is based on a thermo‐fluid‐dynamic discharge modeling of the accumulators. The paper outlines a design direction which minimizes the number of accumulators and opens the way to a different design approach, based on a fully physical discharge process description. [ABSTRACT FROM AUTHOR]