Techno-economic assessment of energy storage systems using annualized life cycle cost of storage (LCCOS) and levelized cost of energy (LCOE) metrics

Mostafa, Mostafa H.; Aleem, Shady H. E. Abdel; Ali, Samia Gharib; Ali, Ziad M.; Abdelaziz, Almoataz Y.

doi:10.1016/j.est.2020.101345

Cited by 174 publications

(85 citation statements)

References 46 publications

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“…Other points that were not under the scope of this work and will be addressed in future works are the reliability evaluation of the obtained configurations via system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and other reliability indices and considering other power quality issues that affect the HC of the distribution systems. Future works will consider the allocation of multi-terminal SOPs [46] and various energy storage types [47] along with DNR for increasing the HC of the studied distribution systems while ensuring an effective protective scheme [48]. Besides, reliability will be considered in the possible works [49][50][51] to provide a reliable configuration for unbalanced large/real distribution networks.…”

Section: Discussionmentioning

confidence: 99%

Scenario-Based Network Reconfiguration and Renewable Energy Resources Integration in Large-Scale Distribution Systems Considering Parameters Uncertainty

et al. 2020

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Renewable energy integration has been recently promoted by many countries as a cleaner alternative to fossil fuels. In many research works, the optimal allocation of distributed generations (DGs) has been modeled mathematically as a DG injecting power without considering its intermittent nature. In this work, a novel probabilistic bilevel multi-objective nonlinear programming optimization problem is formulated to maximize the penetration of renewable distributed generations via distribution network reconfiguration while ensuring the thermal line and voltage limits. Moreover, solar, wind, and load uncertainties are considered in this paper to provide a more realistic mathematical programming model for the optimization problem under study. Case studies are conducted on the 16-, 59-, 69-, 83-, 415-, and 880-node distribution networks, where the 59- and 83-node distribution networks are real distribution networks in Cairo and Taiwan, respectively. The obtained results validate the effectiveness of the proposed optimization approach in maximizing the hosting capacity of DGs and power loss reduction by greater than 17% and 74%, respectively, for the studied distribution networks.

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Section: Discussionmentioning

confidence: 99%

Scenario-Based Network Reconfiguration and Renewable Energy Resources Integration in Large-Scale Distribution Systems Considering Parameters Uncertainty

et al. 2020

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“…In comparison, in the residential community microgrid dominated by renewable DERs, battery storage assets would be the only source that can set the supply curve. Levelized cost of energy (LCOE) is a general approach to model the cost of a battery storage, by averaging the life cycle costs (including capital cost, operation cost, and maintenance cost) into each hour [14]. However, it is a constant value that cannot accurately reflect the energy scarcity situations at different time periods (with respect to the availability and fluctuation of renewable DERs) and the dynamic degradation process of a battery storage through multiple charging-discharging cycles.…”

Section: Marginal Cost Model Of Battery Storage To Enable Price-drivementioning

confidence: 99%

“…( ) = 2 ⁄ ; (13) The relationship between net power dispatch (i.e., discharging minus charging) of the battery and the average DOD over a short time period of ∆ is formulated as in (14). and are the initial state of charge (SOC) and the energy of the battery for time interval ∆ .…”

Section: Tertiary Controlmentioning

confidence: 99%

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Online Cooperative Feedback Control of Residential Community Microgrids with 100% Renewable Energy

Zuo¹,

Wu²

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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The emerging of renewable distributed energy resources (DER) in the residential community opens the door to forming a residential community microgrid. However, traditional microgrid controls via the hierarchical feedforward tertiary, secondary, and primary control framework may not be effective for such residential community microgrids, because of high volatility, low inertia, and insufficiency of DERs. This paper discusses an online feedback scheme, which cooperates the three control layers in real time to improve operational stability of the microgrid. In addition, to economically dispatch scarce reserve, this paper deduces an increment cost model of battery storage assets based on their degradation costs and depth of discharges. The model is of low computational complexity, thus can be naturally embedded in the proposed online cooperative feedback control scheme to calculate marginal price in real-time. Small-signal analysis and Simulink simulation are conducted to illustrate the performances of the proposed online cooperative feedback control scheme.

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“…Renewable energy environmentally-friendly sources have proven efficient, clean, and low cost candidates to the traditional fossil fuels [1]- [5]. Several studies have been performed for evaluating the joint technical-economical long term impacts of RESs installations [6], [7]. In addition, the continual cost decrease of the RES technologies and parts have lead to intensive widespread world-widely.…”

Section: Introductionmentioning

confidence: 99%

A Differential Evolution-Based Optimized Fuzzy Logic MPPT Method for Enhancing the Maximum Power Extraction of Proton Exchange Membrane Fuel Cells

Aly

Rezk

2020

IEEE Access

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Recently, fuel cells (FCs) have found vast employment in several applications. However, unique maximum power point tracking (MPPT) exists for each set of operating condition for the efficient operation of FCs. Therefore, this paper presents a differential evolution optimization algorithm (DEOA)based optimized fuzzy-logic (OFLC) MPPT method for enhancing the maximum power extraction of FCs. The various settings for the membership functions (MFs) of the input and output variables are optimized in the proposed method. Thence, more degree-of-freedom can be employed for accurate and fast tracking of the optimal power point of the proton exchange membrane FCs (PEMFCs). Whereas, existing MPPT methods in the literature for FC applications suffer from decreased degree-of-freedom for optimizing their performance, and lack of adaptivity, which obstructs their suitability for the wide operating range of FCs. The superiority and performance effectiveness of the proposed OFLC MPPT method have been validated and compared with the most prevalent techniques in the literature. Moreover, the robustness and sensitivity of the proposed OFLC MPPT method have been tested at various step changes in the water content of membrane and various temperature changes. Moreover, the proposed design of the suggested OFLC MPPT is general and it can be implemented on low-cost microcontrollers. The results verify the superior performance of the proposed OFLC MPPT method from the accurate and fast MPPT extraction, smooth output power with low ripple, and simplicity of the design point of views. INDEX TERMS Differential Evolution Optimization Algorithm (DEOA), fuel cell (FC), fuzzy logic control (FLC), maximum power point tracking.

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Techno-economic assessment of energy storage systems using annualized life cycle cost of storage (LCCOS) and levelized cost of energy (LCOE) metrics

Cited by 174 publications

References 46 publications

Scenario-Based Network Reconfiguration and Renewable Energy Resources Integration in Large-Scale Distribution Systems Considering Parameters Uncertainty

Scenario-Based Network Reconfiguration and Renewable Energy Resources Integration in Large-Scale Distribution Systems Considering Parameters Uncertainty

Online Cooperative Feedback Control of Residential Community Microgrids with 100% Renewable Energy

A Differential Evolution-Based Optimized Fuzzy Logic MPPT Method for Enhancing the Maximum Power Extraction of Proton Exchange Membrane Fuel Cells

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