scholarly journals Optimal Configuration of Different Energy Storage Batteries for Providing Auxiliary Service and Economic Revenue

2018 ◽  
Vol 8 (12) ◽  
pp. 2633 ◽  
Author(s):  
Lijuan Chen ◽  
Tiantian Wu ◽  
Xiaohui Xu
Keyword(s):  
Life Cycle ◽  
Energy Storage ◽  
Life Cycle Cost ◽  
Demand Management ◽  
Configuration Model ◽  
Peak Shaving ◽  
The Government ◽  
Cost And Benefit Analysis ◽  
Whole Life Cycle ◽  
Auxiliary Services

Energy storage providing auxiliary service at the user-side has broad prospects in support of national polices. Three auxiliary services are selected as the application scene for energy storage participating in demand management, peak shaving and demand response. Considering the time value of funds, the user-side energy storage economy model is built. The model comprehensively considers the delayed transformation income, the government subsidy income, the auxiliary service income and the whole-life-cycle cost factor. According to the cost and benefit analysis, an energy storage optimization configuration model is proposed. The model takes maximum revenue of industrial user in energy storage’s whole-life-cycle as the objective function. Then, the Cplex solver is employed to solve the model. In addition, four indexes are utilized to evaluate the financial effect brought by the user-side energy storage. Finally, the revenue and configuration results of the four types of battery energy storage are calculated to verify the validity of the proposed model. In comparison to the value of evaluation index, planning suggestions are provided for the user-side energy storage providing different auxiliary services. Moreover, the conditions of profit and worthwhile investment are obtained through sensitivity analysis of energy storage providing peak shaving service.

scholarly journals Life Cycle Cost Assessment of Offshore Wind Farm: Kudat Malaysia Case

2021 ◽  
Vol 13 (14) ◽  
pp. 7943
Author(s):  
Shamsan Alsubal ◽  
Wesam Salah Alaloul ◽  
Eu Lim Shawn ◽  
M. S. Liew ◽  
Pavitirakumar Palaniappan ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Life Cycle ◽  
Wind Energy ◽  
Life Cycle Cost ◽  
Wind Farm ◽  
Capital Expenditure ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
The Government ◽  
Whole Life Cycle

The Government of Malaysia has set a striving target to achieve a higher usage of renewable energy (RE) in the energy mix which is currently around 2% of the country’s electricity. Yet, the government intends to increase this ratio up to 20% by the year 2025. Most of the renewable energy in Malaysia comes from hydropower and biomass sources. Meanwhile, numerous studies have been conducted to determine the feasibility of wind energy in Malaysia. Several locations were reported to be economically viable for wind energy development such as Kudat, Mersing, and Kuala Terengganu. This study presents and discusses the whole life cycle cost analysis of an offshore wind farm in Kudat, Malaysia and determines the cost drivers of offshore wind energy developments. It covers the wind data collection and analysis, breakdown of whole life cycle cost structure, and calculation of the levelized cost of energy (LCOE). Results showed that almost 67% of the total cost was incurred by the capital expenditure (CAPEX), and around 26% by operation and maintenance costs (OPEX), while decommissioning costs (DECOM) reached up to 7% of the whole life cycle costs. The LCOE was calculated and determined to be USD 127.58/MWh.

scholarly journals Predication of life cycle cost of equipment base on unbiased grey Markov models

2020 ◽  
Vol 309 ◽  
pp. 05005
Author(s):  
Yonghong Chen ◽  
Ping Hu ◽  
Dong Zhang
Keyword(s):  
Life Cycle ◽  
Markov Model ◽  
Life Cycle Cost ◽  
Prediction Accuracy ◽  
Markov Models ◽  
Grey Model ◽  
Model Accuracy ◽  
Integrated Logistics ◽  
And Control ◽  
Whole Life Cycle

Life cycle cost(LCC) is an important content of equipment integrated logistics support. While the LCC includes the whole life cycle of equipment from development, production, service and maintenance to retirement, in order to effectively manage and control the LCC and better develop integrated logistics support, it is necessary to analyze and predict it. The unbiased grey markov model(UGMM) was introduced into the LCC prediction in the paper, in order to check model accuracy, the posterior difference method(PDM) was used, also the influence by the number of state intervals in UGMM on the prediction accuracy is analyzed and studied. The result indicate that UGMM can be used to predict the LCC, also have the highest prediction accuracy comparing with unbiased grey model and grey separating model, and in order to ensure the prediction accuracy, the state interval should be divided according to the number of sequence.

Optimal Whole-Life-Cycle Planning of Battery Energy Storage for Multi-Functional Services in Power Systems

2020 ◽  
Vol 11 (4) ◽  
pp. 2077-2086 ◽  
Author(s):  
Yongxi Zhang ◽  
Yan Xu ◽  
Hongming Yang ◽  
Zhao Yang Dong ◽  
Rui Zhang
Keyword(s):  
Life Cycle ◽  
Energy Storage ◽  
Power Systems ◽  
Battery Energy Storage ◽  
Battery Energy ◽  
Whole Life Cycle
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