Capacity Of Storage System Research Articles

Location and Capacity Determination for Energy Storage System Involved in Compensating Voltage Sag

For the energy storage system participating in the grid voltage sag compensation service, a location and capacity determination method based on the joint compensation strategy of distributed energy storage systems and dynamic voltage restorer is proposed. Firstly, a two-layer siting and determining capacity model for distributed energy storage systems is established, with the upper layer aiming to minimize the installation cost of distributed energy storage systems and the voltage crossing cost of sensitive loads, and determine the optimal access point for energy storage system. The lower layer determines the optimal configuration capacity of the energy storage system by targeting the compensation cost of the energy storage system, the dynamic voltage restorer, and the voltage satisfaction of sensitive loads. Then, the arithmetic simulation with IEEE33 bus system shows that the proposed method can select a reasonable access point for energy storage system and reduce the configuration capacity.

Determination of the working energy capacity of the on-board energy storage system of an electric locomotive for quarry railway transport during working with a limitation of consumed power

The use of specialized rail rolling stock which is used for transporting ore from the quarry to the crushing plant at mining enterprises is analyzed here. Electric locomotives with an asynchronous traction electric drive and an on-board energy storage system are considered for use. The calculated dependencies of the electric locomotive trac-tive power were analyzed and it was established that on flat sections of the track profile, the movement is carried out with a power that does not exceed 50% of the nominal one. The movement with the nominal power is carried out on the controlled uphill during the cargo half-passage. To ensure the necessary power for movement in such areas, the use of an on-board energy storage system is proposed, which should feed the traction system while limiting the power consumed from the catenary. This happens when the voltage on the pantograph drops to a minimum level. The aim of this work is to determine the on-board energy storage system parameters during the operation of the electric locomotive with limitation of the power consumed from the traction network. Mathemati-cal models of the energy exchange processes in the electric locomotive traction system have been developed. The criteria for comparing options for calculating the parameters of the on-board energy storage system have been proposed. The criteria take into account the reduction of energy consumption during movement, the efficiency of energy storage, and the complete use of the on-board energy storage system in terms of power and working energy capacity. Based on the calculation results, it was determined that the use of an energy storage device with a power of 3,540 kW and an operating energy capacity of 63.5 kWh provides a 10% reduction in energy consumption, which is being consumed while moving along the sample section of the road. The current that can be consumed by an electric locomotive with such parameters of the on-board energy storage system is limited by 600 A.

Achieving economic efficiency in the electricity markets through internalizing negative externalities

AbstractEconomic efficiency is the ultimate goal of all markets, including the electricity market. Several technical and pecuniary restrictions known as externalities in economics literature can significantly affect the economic efficiency of the electricity market. Negative externalities resulting from the operational restrictions of generation units are inherent to electricity markets. In this paper, after reviewing the effects of externalities on the day‐ahead electricity markets' economic efficiency using a unit commitment‐based model, an innovative and theoretically efficient service‐based procedure aimed at internalizing negative externalities in the day‐ahead electricity markets is presented. In this way, a new service procured by the energy storage system to provide energy interchange possibilities in the electricity market is introduced. The proposed service uses both price and quantity adjustment methods to internalize externalities. A new discriminatory method for pricing the service and a bi‐level optimization problem for determining the capacity of the energy storage system required to provide the service are considered. The consideration of the proposed method facilitates reaching the first‐best optimal market solution by alleviating negative externalities existing in the sub‐optimal second‐best solution in the presence of generation sector operational constraints. Numerical case studies demonstrate the functioning of the proposed externalities internalization scheme.

Optimal sizing of RES and BESS in networked microgrids based on proportional peer‐to‐peer and peer‐to‐grid energy trading

AbstractNetworked microgrids emerged from the growing deployment of microgrids in the distribution network. The coordinated operation of networked microgrids offers technical and economical benefits to microgrid owners, customers, grid/utility, and other stakeholders. The optimal capacity sizing of renewable energy sources and battery energy storage systems allows microgrids to minimize costs and maximize reliability. A multi‐objective optimization problem is developed for optimal sizing in a networked microgrid consisting of four different microgrids. The annual energy costs and loss of power supply probability index are taken as objectives. Peer‐to‐peer and peer‐to‐grid energy trading approaches are employed. The peer‐to‐peer energy trading among microgrids employs the proposed “proportional trading method” via a networked microgrid manager or aggregator. The multi‐objective optimization problem formulated is solved using Multi‐Objective Particle Swarm Optimization. The individual objective optimization results for annual energy cost and loss of power supply probability are also analyzed. The proposed method decreases the interaction between the grid and the MGs, and the usage of renewable energy sources is enhanced. The capacity of battery energy storage systems is lowered by 96%, 53.2%, 48.86%, 21% for respective microgrids in networked microgrids. The results of proportional peer‐to‐peer energy trading‐based multi‐objective optimization show that trading energy among microgrids minimizes annual energy cost by 0.75% while maintaining system reliability.

Research on energy storage allocation strategy considering smoothing the fluctuation of renewable energy

Energy storage technology can effectively solve the problems caused by large-scale grid connection of renewable energy with volatility and uncertainty. Due to the high cost of the energy storage system, the research on capacity allocation of energy storage system has important theoretical and application value. In this paper, an optimization method for determining the capacity of energy storage system for smoothing the power output of renewable energy is proposed. First, based on the actual data of Ulanqab, the output characteristics of wind power and photovoltaic power generation are studied, and the K-means algorithm is used to select typical days. Then, the energy storage configuration model is built according to the objective function and constraints. Finally, genetic algorithm is used to solve the optimization model, obtain the corresponding parameters, and complete the configuration of energy storage capacity. Based on the results of renewable energy spectrum analysis, the minimum capacity of the energy storage system that meets the constraint of target power output volatility after compensation by the energy storage system can be optimized. The simulation results show that at 1 and 10 min, the flattened volatility is about 2% and 5%, while the actual penetration volatility is about 20% and 30%. The volatility of the optimized model is greatly reduced, which proves the effectiveness of the proposed strategy.

Optimal Configuration of Extreme Fast Charging Stations Integrated with Energy Storage System and Photovoltaic Panels in Distribution Networks

Extreme fast charging (XFC) for electric vehicles (EVs) has emerged recently because of the short charging period. However, the extreme high charging power of EVs at XFC stations may severely impact distribution networks. This paper addresses the estimation of the charging power demand of XFC stations and the design of multiple XFC stations with renewable energy resources in current distribution networks. First, a Monte Carlo (MC) simulation tool was created utilizing the EV arrival time and state-of-charge (SOC) distributions obtained from the dataset of vehicle travel surveys. Various impact factors are considered to obtain a realistic estimation of the charging power demand of XFC stations. Then, a method for determining the optimal energy capacity of the energy storage system (ESS), ESS rated power, and size of photovoltaic (PV) panels for multiple XFC stations in a distribution network is presented, with the goal of achieving an optimal configuration. The optimal power flow technique is applied to this optimization so that the optimal solutions meet not only the charging demand but also the operational constraints related to XFC, ESS, PV panels, and distribution networks. Simulation results of a use case indicate that the presented MC simulation can estimate approximate real-world XFC charging demand, and the optimized ESS and PV units in multiple XFC stations in the distribution network can reduce the annual total cost of XFC stations and improve the performance of the distribution network.

Определение характеристик систем хранения и генерации реагентов для морского подводного объекта с электрохимическим генератором

Autonomy of the marine submersibles is specified by the type of energy, fuel and oxidizers they use. As a rule, marine underwater objects of small displacement with a short underwater mission time are equipped with lithium-ion batteries. A number of the submersible power plants have air-independent energy, which allows using an electrochemical generator (ECG) as energy source fueled by hydrogen and applying oxygen as oxidizer. Each method of storing reagents as part of an ECG power plant has been assessed promising. Using an ECG power plant is determined by the possibility of placing on a marine underwater object the amounts of hydrogen and oxygen necessary to perform a specific underwater mission. There have been considered the issues of placing the reagents (hydrogen and oxygen) necessary for ECG functioning as part of an air-independent power plant of a marine submersible. There are given the dependencies to determine necessary reagent amounts on the submersible to perform an underwater mission. Cryogenic oxygen storage has been proved the most acceptable option for large-displacement marine underwater objects. Numerical values of the hydrogen and oxygen mass are obtained for the hypothetical ECG capacity. The possibilities of placing a balloon hydrogen storage system as the most acceptable for placement on small non-nuclear submarines and autonomous unmanned submersible apparatus are considered. Types of hydrogen tanks capable to operate in a wide range of environmental parameters at internal hydrogen pressure over 40 MPa are given. Available arrangement of tanks with hydrogen and oxygen outside the hull of an autonomous unmanned submersible is presented and the main dependencies for calculating the capacity of a balloon storage system of reagents subject to the gas properties are given.

A Dynamic Model For Poultry Supply Chain In West Java


 
 
 
 This paper analyzes the constraints on supply chain processes within the poultry industry in West Java, Indonesia after COVID-19 pandemic. During the upstream process, poultry feed costs fluctuates greatly and lacks of storage which causing feed supply constraint, the mortality rate of chickens often surpasses 5% due to several factors including stocking density. Another identified problem adversely affecting the upstream process is the inability of small-scale farmers to procure their own Grand Parent Stock (GPS) since they remain dependent upon corporations to supply it, leading to inefficiency and increased production costs. Meanwhile, in downstream processes, the lack of a cold supply chain system and adequate storage capacity presents other challenges with regard to product durability. Consumer awareness regarding the relationship between food safety and health, and shifting in consumer preferences, especially during COVID-19 pandemic is also considered as a constraint in West Java poultry supply chain. To cope with those problems, several solutions such as technology and policy were offered to improve and solve problems in the supply chain process. Technology can be a powerful tool in addressing challenges in the poultry supply chain by providing efficient, accurate, and scalable solutions. While policy play a crucial role in addressing problems in the poultry supply chain by setting standards, promoting best practices, and providing a framework for action, regulate the behavior of the actors, promote transparency and hold actors accountable for their actions. A causal loop diagram is also made to assess the relationship between technology and policy in poultry supply chain process
 
 
 
 

An Experimental Model to Manage Power Flows in Isolated Wind System for Irrigational Regime

This paper focuses on irrigational problem in isolated systems with the participation of wind power generation. Power flows in whole system are regulated basing on analyzing the relation of ambient temperature and humidity, capacity of energy storage system (ESS). It means that the higher humidity is, the less water is; the higher temperature is, the more water must be used; the lower capacity is, the lower power consumption is. An experimental model is established to describe the irrigational problem and verify the ability to regulate power flows in a system including three water pumps, Raspberry Pi board controller, a 100-W wind generator and a battery. Python application was used to designed and programmable human-machine Interface (HMI) and control relays corresponding to different operating modes by using measurement or virtual information. Control command can be created by manual or automation basing on analyzing the relation of ambient temperature and humidity, capacity of ESS. Experimental results showed the ability to regulate power flows in whole system based on the evaluation of the irrigational demand and available energy supply. It also showed the good meaning in reality to improve life time for ESS and good capability to irrigational demand. Keywords: Energy power flow, irrigational regime, isolated power grid, power-flow management, control power flow.

Numerical study on heat storage efficiency of broken rock mass under different CO2 injection conditions

The application of energy storage technology can solve the problems of randomness and volatility in the development and use of renewable energy, such as wind and solar energy, and effectively improve energy utilization. Rock heat storage is one of the primary forms of sensible heat storage. The heat storage efficiency and heat storage capacity of rock packed bed are important indicators to measure the energy storage effect of a rock energy storage system. This paper takes CO2 as the heat-carrying medium and broken granite grains as the packed bed matrix of the energy storage system. It establishes a porous medium thermal-hydraulic-mechanical coupling model of the broken rock bed. The heat injection and production process of the large-sized rock bed heat storage system is simulated using the COMSOL finite element software, and the heat storage efficiency and heat storage capacity of the broken rock bed is analyzed under different fluid injection pressures and injection temperatures. The results show that: 1) With the increase of CO2 injection pressure, the heat storage and heat production speed of the heat storage system will increase, and the heat storage rate changes from two stages of “low rise - slow decline” to four stages of “rapid increase—stability—rapid decrease—stability”; 2) With the increase of CO2 injection temperature, the maximum heat storage capacity of the rock bed heat storage system will increase. Due to the increase in the temperature gradient between CO2 and the rock bed, the heat storage and the heat production time of the heat storage system will increase, and its speed will decrease.

Guest editorial: Application of cloud energy storage systems in power systems

Guest editorial: Application of cloud energy storage systems in power systems

Optimal allocation method of hybrid energy storage capacity of multi-energy system under low-carbon background

Abstract The energy dispatching and distribution ability is improved by optimizing the configuration of hybrid energy storage capacity of multi-energy system in low-carbon background, and an optimal configuration method of hybrid energy storage capacity of multi-energy system in low-carbon background based on equilibrium control and dynamic optimization algorithm is proposed. The data structure model of hybrid energy storage capacity distribution of multi-energy system is constructed. Under the condition that the energy storage optimal allocation model based on cost analysis meets the system performance index, the energy storage optimal allocation model is established with the objective function of minimizing the cost of configuring energy storage system, and with the objective of minimizing the fluctuation of active power of distributed power sources, such as wind and light. Taking the penalty cost of wind energy storage combined output power exceeding the fluctuation limit as the objective function, low-pass filtering method is adopted to stabilize the fluctuation of new energy power, and the optimal configuration capacity of energy storage system is determined according to the allowable frequency deviation and voltage stability of the system. Balanced control and dynamic optimization algorithm are adopted to realize the optimal configuration of hybrid energy storage capacity of multi-energy system under low-carbon background by combining different wind and solar energy combinations, different sampling intervals and different number of power stations. The simulation results show that the hybrid energy storage capacity allocation of multi-energy system has strong adaptability and high environmental adaptability, which effectively improves the transient stability of power grid system and further promotes the safe and stable operation of power grid system.

Optimal Capacity and Cost Analysis of Battery Energy Storage System in Standalone Microgrid Considering Battery Lifetime

In standalone microgrids, the Battery Energy Storage System (BESS) is a popular energy storage technology. Because of renewable energy generation sources such as PV and Wind Turbine (WT), the output power of a microgrid varies greatly, which can reduce the BESS lifetime. Because the BESS has a limited lifespan and is the most expensive component in a microgrid, frequent replacement significantly increases a project’s operating costs. This paper proposes a capacity optimization method as well as a cost analysis that takes the BESS lifetime into account. The weighted Wh throughput method is used in this paper to estimate the BESS lifetime. Furthermore, the well-known Particle Swarm Optimization (PSO) algorithm is employed to maximize battery capacity while minimizing the total net present value. According to simulation results, the optimal adjusting factor of 1.761 yields the lowest total net present value of US$200,653. The optimal capacity of the BESS can significantly reduce the net present value of total operation costs throughout the project by extending its lifetime. When applied to larger power systems, the proposed strategy can further reduce total costs.

Measurement of shrinkage void and identification of solid-liquid phases in phase change materials: Ultrasound-based approach and simulated predictions

Phase change materials in thermal energy storage systems undergo solidification and melting during cyclic operations. During solidification, internal shrinkage voids are formed randomly in phase change materials due to density differences in the solid and liquid phases. These shrinkage voids can severely affect the heat transfer performance and storage capacity of thermal energy storage systems. Additionally, the containers in which phase change materials are kept are usually metallic, making them opaque. Therefore, identification of the solid–liquid phase by direct visualisation during the phase change is limited. The present work aims to develop a non-destructive ultrasonic scanning approach to detect and measure internal shrinkage voids in solid phase change materials and the solid–liquid phases during melting and perform multi-phase numerical simulations that simultaneously capture solidification/melting and the associated shrinkage/expansion. The most commonly used phase change materials, n-eicosane, and n-octadecane, are used in this study. The effectiveness of the ultrasonic technique is evaluated by measuring cavities of known sizes. Further, three cases are considered for examining and measuring the shrinkage void. Case A involves two-dimensional solidification with a surface void, while Case B and C involve three-dimensional solidification with an internal shrinkage void. The numerically obtained shrinkage cavity profile shows a maximum deviation of 7.8% with experimental results for case C. Furthermore, the developed approach is implemented to uniquely detect and identify the solid and liquid phases during melting in an opaque container.

Optimal planning of hybrid electric-hydrogen energy storage systems via multi-objective particle swarm optimization

Abstract: In recent years, hydrogen is rapidly developing because it is environmentally friendly and sustainable. In this case, hydrogen energy storage systems (HESSs) can be widely used in the distribution network. The application of hybrid electric-hydrogen energy storage systems can solve the adverse effects caused by renewable energy access to the distribution network. In order to ensure the rationality and effectiveness of energy storage systems (ESSs) configuration, economic indicators of battery energy storage systems (BESSs) and hydrogen energy storage systems, power loss, and voltage fluctuation are chosen as the fitness function in this paper. Meanwhile, multi-objective particle swarm optimization (MOPSO) is used to solve Pareto non-dominated set of energy storage systems’ optimal configuration scheme, in which the technique for order preference by similarity to ideal solution (TOPSIS) based on information entropy weight (IEW) is used select the optimal solution in Pareto non-dominated solution set. Based on the extended IEEE-33 system and IEEE-69 system, the rationality of energy storage systems configuration scheme under 20% and 35% renewable energy penetration rate is analyzed. The simulation results show that the power loss can be reduced by 7.9%–22.8% and the voltage fluctuation can be reduced by 40.0%–71% when the renewable energy penetration rate is 20% and 35% respectively in IEEE-33 and 69 nodes systems. Therefore, it can be concluded that the locations and capacities of energy storage systems obtained by multi-objective particle swarm optimization can improve the distribution network stability and economy after accessing renewable generation.

ADMM-Based Multi-Objective Control Scheme for Mitigating the Impact of High Penetration DER Integration in the Modern Distribution Systems

The high penetration of renewable energy sources in modern distribution networks poses challenges for grid voltage regulation. In this study, a multi-agent distributed voltage control strategy based on the proximal Jacobian alternating direction method of multipliers (PJ-ADMM) is proposed for distribution power systems with a high penetration of photovoltaic (PV) resources coordinated with battery energy storage systems (BESS). In this context, all active and reactive power outputs of the PV are locally optimized through smart inverters to improve the grid voltage with minimum power loss. Uncertainties associated with the solar energy generation and load demands are considered in the defined scenarios. This study consists of two phases. In the first phase, the voltage control problem is formulated as an optimization problem to regulate the voltages within an acceptable limit with fast convergence. In the second phase, a coordinated voltage control strategy for smart PV inverters and BESS is proposed to allocate the power capacity of the battery energy storage systems and the active power loss reduction. Finally, the proposed method is tested on modified IEEE 13-bus, 33-bus and 141-bus distribution systems using MATLAB/Simulink and MATPOWER. A comparison of the results of the voltage profiles with and without the control algorithm demonstrated the efficacy, robustness, and scalability of the distributed scheme for voltage improvement and optimal utilization of PV power under different scenarios.

Optimal Capacity and Cost Analysis of Hybrid Energy Storage System in Standalone DC Microgrid

Optimal Capacity and Cost Analysis of Hybrid Energy Storage System in Standalone DC Microgrid

Comprehensive Benefit Evaluation Analysis And Application Research of Energy Storage

In recent years, the penetration rate of renewable energy in the power system has increased year by year, and the allocation of energy storage is an important development trend to improve the operation stability of the grid-connected power system containing renewable energy. This paper first analyzes the basic concept and operation principle of energy storage devices, and then explains the costs and benefits of energy storage devices. Finally, the industrial park and energy storage power station are used as practical application scenarios to verify the correctness of the proposed method. The example results show that energy storage should be installed in a place where the system network loss is minimal and the reliability of power supply can be maximized, and the capacity of the energy storage system should match the load capacity of the bus bar of the installation site, so as to achieve the greatest comprehensive benefits.

Optimal Placement and Capacity of Battery Energy Storage System in Distribution Networks Integrated With PV and EVs Using Metaheuristic Algorithms

Optimal Placement and Capacity of Battery Energy Storage System in Distribution Networks Integrated With PV and EVs Using Metaheuristic Algorithms

Life Cycle Environmental Impact of Pumped Hydro Energy Storage

Pumped hydro energy storage (PHES) is one of the energy storage systems to solve intermittent renewable energy and support stable power generation of the grid. About 95% of installed capacity of the global energy storage system is contributed by PHES. Life cycle assessment (LCA) is used to analyse the environmental impact of PHES construction and operation phase in this study, and 1 MWh of electricity delivered from PHES to the power grid is set as the functional unit. The results show that the electricity power structure and electricity loss caused by the charging-discharging of PHES are the main environmental burden contributors, contributing 80 to 99% of the total environmental emissions. And environmental impacts during the construction phase is mainly due to the use of concrete, steel, and cement. In the future, as the proportion of renewable energy in the grid structure increases, the environmental impacts caused by PHES will decrease accordingly.