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The cost of Energy Storage System (ESS) for frequency regulation is difficult to calculate due to battery’s degradation when an ESS is in grid-connected operation. To solve this problem, the influence mechanism of actual operating conditions on the life degradation of Li-ion battery energy storage is analyzed. A control strategy of Li-ion ESS parti...
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Context 1
... measured data of the LiFePO4 battery (one kind of Li-ion battery) shown in Fig. 1 is given by manufac- turers. Under standard conditions, with different DOD as each charge-discharge indicator, it shows the varia- tions of the LiFePO4 battery actual capacity retention rate as the number of cycles ...
Context 2
... can be seen from Fig. 1 that the relationship be- tween battery capacity retention rate and the number of cycles is analogously parabolic. The deterioration rate of the battery is reflected in two stages. In the first stage, the battery decay rate gradually decreases, indicating that the battery tends to self-stabilize its state. In the second stage, the ...
Context 3
... parabolic. The deterioration rate of the battery is reflected in two stages. In the first stage, the battery decay rate gradually decreases, indicating that the battery tends to self-stabilize its state. In the second stage, the battery decay rate increases, indicating that the battery begins to accelerate its aging. It can also be seen from Fig. 1 that the higher the DOD value is, the faster aging rate of the battery becomes, and the fewer the cycle is. The relationship between the dis- charge depth and the cycle life is approximately expo- nential [3] and for the LiFePO4 battery it can be fitted ...
Citations
... The multiple directional charging/discharging patterns will impose great challenges on quantifying battery aging and relative capacity, especially for intermittent renewable supply, stochastic demand, start-stop/acceleration/large load changing cycles/maximum power time operation on transportation. Note that, the battery degradation data tested in experiments or provided by manufacturers (under standard testing conditions) fails to characterize the dynamic degradation feature under sophisticated application scenarios (charging by intermittent renewable, discharging for stochastic demand, etc) [82]. Furthermore, it will be more complicated when conducting economic analysis combined with off-peak grid power and stakeholders' participation willingness. ...
As an indispensable component and intermediate bridge, electrochemical battery as an indispensable component is essential for power supply reliability, stability, grid-friendly interaction, sustainability with e-transportation and building electrification. However, the lifecycle carbon intensity of electrochemical batteries is uncertain throughout lifecycle battery-related activities. In this study, a generic methodology is proposed to accurately quantify the lifecycle carbon intensity of electrochemical batteries. A cross-scale multi-stage analytic platform with inter-disciplinary and trans-disciplinary is formulated, involving battery materials (anode, cathode, electrolyte), charging/discharging behaviours, cascade battery utilization, recycling, and reproduction. A case study on a zero-energy district in subtropical Guangzhou indicates that lifetime EV battery carbon intensity is +556 kg CO2,eq/kWh for the scenario with pure fossil fuel-based grid reliance, while the minimum carbon intensity of EVs at −860 kg CO2,eq/kWh can be achieved for the solar-wind supported scenario. The grid mandatory EVs charging will slightly increase the battery carbon intensity to −617.2 kg CO2,eq/kWh, and the exclusion of embodied carbon on both solar PV and wind turbines will increase the battery carbon intensity to −583.8 kg CO2,eq/kWh. The proposed approach and formulated platform can enable synthetical and comprehensive analysis on battery sustainability, throughout integrated cross-disciplinary approaches for 2060 carbon neutrality in China.
... Limited literature have explored differentiated control modes in the context of batteries. Yan et al. [12] primarily concentrated on investigating the impact of DOD, establishing a control strategy for frequency regulation scenarios aimed at enhancing battery lifetimes. Furthermore, Karunathilake et al. [13] developed a multi-objective optimization control strategy that takes into account aging and is based on multiple features reflecting energy and power performance. ...
In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to intricate coupled conditions, this distribution strategy inevitably results in increased inconsistency and hastened system aging. This paper presents a novel differentiated power distribution strategy comprising three control variables: the rotation status, and the operating boundaries for both depth of discharge (DOD) and C-rates (C) within a control period. The proposed strategy integrates an aging cost prediction model developed to express the mapping relationship between these control variables and aging costs. Additionally, it incorporates the multi-colony particle swarm optimization (Mc-PSO) algorithm into the optimization model to minimize aging costs. The aging cost prediction model consists of three functions: predicting health features (HFs) based on the cumulative charge/discharge throughput quantity and operating boundaries, characterizing HFs as comprehensive scores, and calculating aging costs using both comprehensive scores and residual equipment value. Further, we elaborated on the engineering application process for the proposed control strategy. In the simulation scenarios, this strategy prolonged the service life by 14.62%, reduced the overall aging cost by 6.61%, and improved module consistency by 21.98%, compared with the traditional equalized distribution strategy. In summary, the proposed strategy proves effective in elongating service life, reducing overall aging costs, and increasing the benefit of energy storage systems in particular application scenarios.
... At the same time, charging at too low temperature can lead to lithium plating, which involves safety and performance issues as seen Table 9 Design requirements of lithium ion batteries [56]. Fig. 3. Percent capacity retention of a LIB at various discharge depths [60]. ...
The reliability and efficiency of the energy storage system used in electric vehicles (EVs) is very important for consumers. The use of lithium-ion batteries (LIBs) with high energy density is preferred in EVs. However, the long range user needs and security issues such as fire and explosion in LIB limit the widespread use of these batteries. This review discusses the working principle, performance and failures of LIB. It provides an overview of LIB with particular emphasis on the factors that affect their performance and the factors that cause failures. Finally, potential batteries to replace lithium batteries in EVs are evaluated. In addition, the challenges of these future batteries are discussed. In this paper, we review studies in the field of batteries used in EVs, general problems and future battery technologies. Methods related to such topics are compared in terms of their advantages, disadvantages and qualitative factors. The authors believe that EVs will be the transportation vehicle of the future such that battery systems should be developed and academic studies should be carried out. The authors think this study will contribute to the EV and will provide a perspective to designers, researchers, manufacturers and companies working in the field of batteries.
... To investigate the influences of operation cost over time, the operation cost variation factors of HPP, PVPP, and EES over time in Fig. 10 are considered to calculate the LCOE of the hybrid system in the whole life cycle. These data were obtained through fitting and regression from the following data: the PVPP average expenses by major U.S. investor-owned electric utilities from 1998 to 2022 [48], PV operation cost in Europe [49], and degradation cost rate of EES accorded with the average performance degradation rate [50]. Both the annual maintenance costs of HPP and EES increase with the increase in operation time, which are resulted from the failures and reliability of components. ...
A stochastic two-stage optimization model of a hybrid renewable energy system. • Cascaded hydro power plants are optimized to accommodate load growth. • The uncertainties including water inflows, sources, and loads, are modeled. • The installed capacities considering energy scheduling are optimized. • The construction sequences of hydro plants are analyzed with electric load growth. A R T I C L E I N F O Keywords: Cascade hydropower plant Hybrid energy system System configuration Energy scheduling Uncertainty A B S T R A C T The implementation of a large-scale energy infrastructure, relying exclusively on 100% clean and renewable sources, effectively meets the rising regional energy demands and mitigates climate change impacts stemming from fossil fuel consumption. However, challenges arise due to uncertainties in renewable energy outputs and the dynamic nature of medium-and long-term electricity demands, affecting energy supply reliability, as well as considerations of investment and economic performance. To tackle these issues, a stochastic two-stage optimization method is proposed for refining system configurations in a hybrid cascade hydro-wind-photovoltaic system with a battery. This approach includes optimizing the scheduling and management of energy production plants. Uncertainties related to water inflows, wind and solar powers, and electric demands are modeled using a scenario generation method. Temporal correlation degrees are introduced to improve the precision of Latin hypercube sampling. Addressing nonlinear aspects, the linear relaxation method, based on the McCormick envelope, deals with nonlinear elements in cascade hydro power plants. A mixed-integer linear programming approach is then used to obtain optimal solutions for the hybrid system. Results show that the proposed scenario generation method enhances computational efficiency. Cover ratios for sampling and clustering improve by 2.24% and 3.60%, respectively, and average errors of temporal correlations decrease by 0.81% for sampling and 0.52% for clustering. Key parameters like electric growth, cost parameters, and initial battery state, be considered for optimal system configurations and strategies. The levelized cost of electricity of the optimum system configurations is about 0.060$/kWh when the peak electric load is 10,000 MW. The life cycle CO 2 emission is about 9.49 kg CO 2-eq/MWh. Both electricity cost and environmental impact will have dramatic growth because of the integration of EES with large capacity when the electric load continuously increases.
... Limited literature explores differentiated control modes in the context of batteries. Yan et al. [10] primarily concentrated on investigating the impact of DOD, establishing a control strategy for 3 frequency regulation scenarios aimed at enhancing battery lifetimes. Furthermore, Karunathilakeet al. [11] developed a multi-objective optimization control strategy that takes into account aging and is based on multiple features reflecting energy and power performance. ...
In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to intricate coupled conditions, this distribution strategy inevitably results in increased inconsistency and hastened system aging. This paper presents a novel differentiated power distribution strategy comprising three control variables: the rotation status, the operating boundaries for both Depth of Discharge (DOD) and C-rates (C) within a control period. The proposed strategy integrates an aging cost prediction model developed to express the mapping relationship between these control variables and aging costs. Additionally, it incorporates the multi-colony particle swarm optimization (Mc-PSO) algorithm into the optimization model to minimize aging costs. The aging cost prediction model consists of three functions: predicting health features (HFs) based on the cumulative charge/discharge throughput quantity and operating boundaries, characterizing HFs as comprehensive scores, and calculating aging costs using both comprehensive scores and residual equipment value. Further, we elaborated on the engineering application process for the proposed control strategy. In the simulation scenarios, this strategy prolonged the service life by 14.62%, reduced the overall aging cost by 6.61%, and improved module consistency by 21.98%, compared with the traditional equalized distribution strategy. In summary, the proposed strategy proves effective in elongating service life, reducing overall aging costs, and increasing the benefit of energy storage systems in particular application scenarios.
... Cost accounting is different from financial accounting subject to legal requirements and GAAP unlike financial accounting (Yan, et al. 2018), (Z. Zhang 2018). ...
The government of Bangladesh is providing various financial incentives like reduced
tax rates, lower import duties, and export subsidies to the shipbuilding industry of the
country. Financial soundness along with a growing domestic market, competitiveness
for the international small vessel segment, availability of skilled engineers and
workers, and availability of shipbuilding cluster are necessary for the next step
development of the shipbuilding industry. The aim of this study is to explore the current
financial and cost accounting practices, identify the relationship among the variables,
and find out the significance of the factors that affect the current financial and cost
accounting practices of the shipbuilding industry of Bangladesh. Descriptive statistics,
Pearson’s product-moment correlation analysis, and a Multi-Criteria Decision Making
(MCDM)-BWM have been applied to analyze the data. The study shows that there is a
positive perception among professionals regarding the expert knowledge of qualified
accountants and the application of cost and management accounting. It also reveals
that the relationship between the ACC and QFA, IC and CFR are significantly highly
positive on the other hand the CMA and QCA, MCC and MPV are also highly and
moderately positive respectively. The result of this study suggests increasing the
qualification of financial and cost accountants so as to increase the accuracy of
financial reporting that affects the potential investors’ perception of the industry.
... In the context of the energy internet and dual carbon objectives, integrated energy systems (IES) have gained significant attention and have undergone rapid development [1][2][3]. The integrated energy system makes extensive use of renewable energy, enhances energy efficiency, and lowers carbon emissions through multi-energy coupling. ...
Extreme disasters have become increasingly common in recent years and pose significant dangers to the integrated energy system’s secure and dependable energy supply. As a vital part of an integrated energy system, the energy storage system can help with emergency rescue and recovery during major disasters. In addition, it can improve energy utilization rates and regulate fluctuations in renewable energy under normal conditions. In this study, the sizing scheme of multi-energy storage equipment in the electric–thermal–hydrogen integrated energy system is optimized; economic optimization in the regular operating scenario and resilience enhancement in extreme disaster scenarios are also considered. A refined model of multi-energy storage is constructed, and a two-layer capacity configuration optimization model is proposed. This model is further enhanced by the integration of a Markov two-state fault transmission model, which simulates equipment defects and improves system resilience. The optimization process is solved using the tabu chaotic quantum particle swarm optimization (TCQPSO) algorithm to provide reliable and accurate optimization results. The results indicate that addressing severe disaster situations in a capacity configuration fully leverages the reserve energy function of energy storage and enhances system resilience while maintaining economic efficiency; furthermore, adjusting the load loss penalty coefficients offers a more targeted approach to the balancing of the system economy and resilience. Thus, new algorithmic choices and planning strategies for future research on enhancing the resilience of integrated energy systems under extreme disaster scenarios are provided.
... For any of the BESS applications, maximizing the DOD reduces the energy storage capacity and thus increases the number of cycles. Further, the degradation factor of BESS mainly depends on its energy exchange, which, in turn, diminishes battery capacity (i.e., capacity fading) [10]. Although the ageing mechanism of batteries is complex, for optimal scheduling, parameters such as DOD and charging/discharging cycles have the most significant influence on degradation. ...
... It is considered linear with battery shelf life because it is independent of operating conditions. The annual static depreciation is expressed in (13) [10]. ...
... Because practical charging/discharging cycles are aperiodic, the dynamic deterioration becomes non-linear. Therefore, it is crucial to consider practical operating circumstances while calculating the dynamic degradation, as indicated by (14) [10]. ...
The concept of utilizing microgrids (MGs) to convert buildings into prosumers is gaining massive popularity because of its economic and environmental benefits. These pro-sumer buildings consist of renewable energy sources and usually install battery energy storage systems (BESSs) to deal with the uncertain nature of renewable energy sources. However, because of the high capital investment of BESS and the limitation of available energy, there is a need for an effective energy management strategy for prosumer buildings that maximizes the profit of building owner and increases the operating life span of BESS. In this regard, this paper proposes an improved energy management strategy (IEMS) for the prosumer building to minimize the operating cost of MG and degradation factor of BESS. Moreover, to estimate the practical operating life span of BESS, this paper utilizes a non-linear battery degradation model. In addition, a flexible load shifting (FLS) scheme is also developed and integrated into the proposed strategy to further improve its performance. The proposed strategy is tested for the real-time annual data of a grid-tied solar photovoltaic (PV) and BESS-powered AC-DC hybrid MG installed at a commercial building. Moreover, the scenario reduction technique is used to handle the uncertainty associated with generation and load demand. To validate the performance of the proposed
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trategy, the results of IEMS are compared with the well-established energy management strategies. The simulation results verify that the proposed strategy substantially increases the profit of the building owner and operating life span of BESS. Moreover, FLS enhances the performance of IEMS by further improving the financial profit of MG owner and the life span of BESS, thus making the operation of prosumer building more economical and efficient.
... The aging or degradation of a battery heavily depends on the type of use. Several studies have tried to model the degradation of the battery and understand how it affects the capacity [95,96]. However, for simplicity purposes, this study has not considered degradation. ...
This paper proposes a methodological way to compensate for the imbalance between energy generation and consumption using a battery block from electric vehicles as an energy reservoir through the well-known vehicle-to-grid system (V2G). This method is based on a simulation process developed by the authors that takes into consideration the daily fluctuations in energy consumption as well as the power level generated by an energy source, either conventional, renewable, or hybrid. This study shows that for very large electric vehicle fleets, the system is rendered non-viable, since the remaining energy in the battery block that allows the electric vehicle to be usable during the daytime avoids having to compensate for the energy grid imbalance, only allowing it to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. This method allows for predicting the optimum size of an electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance, and size of the electric vehicle fleet.
... Battery capacity is affected by the degradation the battery suffers from use; despite the aging (degradation) of a battery heavily depends on the type of use, there are some studies that have tried to modelling the degradation of the battery and how it affects to the capacity [72,73]. The degradation has not been considered in this study for simplicity; nevertheless, if the State-of-Health (SOH) of the battery is either known or estimated from a model, the capacity of the battery can be expressed in the following way: ...
The paper proposes a methodological way to compensate the imbalance between energy generation and consumption using the battery block of electric vehicles as energy reservoir through the well-known Vehicle to Grid system (V2G). The method is based on a simulation process developed by the authors that take into consideration the daily fluctuations of energy consumption as well as the power level generated by an energy source, either conventional, renewable or hybrid. The study shows that for very large electric vehicle fleet the system renders non-viable, since the remaining energy in the battery block to let the electric vehicle usable for running during daytime avoids to compensating for the energy grid imbalance, only allowing to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. The method allows predicting the optimum size of electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance and size of the electric vehicle fleet.
