Factoring the Cycle Aging Cost of Batteries Participating in Electricity Markets

Xu, Bolun; Zhao, Jisheng; Zheng, Tongxin; Litvinov, Eugene; Kirschen, Daniel S.

doi:10.1109/tpwrs.2017.2733339

Cited by 292 publications

(187 citation statements)

References 33 publications

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“…For example, choosing different uncertainty sets for r-LAPB could take advantage of strong correlation among some loads. Future works also include designing approximation algorithms with optimality guarantees and exploring the benefits of controlling distributed generations [39][40][41], electric vehicles [42][43][44], energy storage [29,[45][46][47] and demand response [48][49][50][51].…”

Section: Discussionmentioning

confidence: 99%

Robust Look-ahead Three-phase Balancing of Uncertain Distribution Loads

Geng

Gupta

Xie

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Increasing penetration of highly variable components such as solar generation and electric vehicle charging loads pose significant challenges to keeping three-phase loads balanced in modern distribution systems. Failure to maintain balance across three phases would lead to asset deterioration and increasing delivery losses. Motivated by the real-world needs to automate and optimize the three-phase balancing decision making, this paper introduces a robust look-ahead optimization framework that pursues balanced phases in the presence of demand-side uncertainties. We show that look-ahead moving window optimization can reduce imbalances among phases at the cost of a limited number of phase swapping operations. Case studies quantify the improvements of the proposed methods compared with conventional deterministic phase balancing. Discussions on possible benefits of the proposed methods and extensions are presented.

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Section: Discussionmentioning

confidence: 99%

Robust Look-ahead Three-phase Balancing of Uncertain Distribution Loads

Geng

Gupta

Xie

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Sarker et al, in [20], used a MILP method, including a basic degradation model to analyse the effect of trading electricity at different power levels, but a lack of data underlying the degradation and efficiency models meant that they could not quantify the effects. Xu et al [21] also targeted electricity trading, but using a rain-flow counting method to account for degradation. While the proposed algorithm may mimic the cycle-induced degradation of a battery to a certain extent, it did not take into account inverter and peripheral component-induced losses.…”

Section: Literature Reviewmentioning

confidence: 99%

Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †

et al. 2019

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To achieve maximum profit by dispatching a battery storage system in an arbitrage operation, multiple factors must be considered. While revenue from the application is determined by the time variability of the electricity cost, the profit will be lowered by costs resulting from energy efficiency losses, as well as by battery degradation. In this paper, an optimal dispatch strategy is proposed for storage systems trading on energy arbitrage markets. The dispatch is based on a computationally-efficient implementation of a mixed-integer linear programming method, with a cost function that includes variable-energy conversion losses and a cycle-induced battery capacity fade. The parametrisation of these non-linear functions is backed by in-house laboratory tests. A detailed analysis of the proposed methods is given through case studies of different cost-inclusion scenarios, as well as battery investment-cost scenarios. An evaluation with a sample intraday market data set, collected throughout 2017 in Germany, offers a potential monthly revenue of up to 8762 EUR/MWh cap installed capacity, without accounting for the costs attributed to energy losses and battery degradation. While this is slightly above the revenue attainable in a reference application—namely, primary frequency regulation for the same sample month (7716 EUR/MWh cap installed capacity)—the situation changes if costs are considered: The optimisation reveals that losses in battery ageing and efficiency reduce the attainable profit by up to 36% for the most profitable arbitrage use case considered herein. The findings underline the significance of considering both ageing and efficiency in battery system dispatch optimisation.

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“…A shortcoming among the aforementioned papers are lack of more sophisticated modelling of degradation due to DoD. Batteries will typically have an increasing degradation rate with increasing cycling depth, and [14] shows how to represent this with a piece-wise linear model. The contributions of this paper can be summarized as follows: i) The microgrid storage coordination problem has been formulated as a multi-stage stochastic problem.…”

Section: Contributions and Organizationmentioning

confidence: 99%

Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming

Aaslid

Belsnes

Fosso

2019

2019 International Conference on Smart Energy Systems and Technologies (SEST)

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Intermittent energy sources demand temporal storages to balance generation and load, and batteries stand out as an alternative. However, the lifetime is limited, and cycling depth affects the battery degradation rate. Current stochastic multistage methods lack proper representation of battery degradation. This paper proposes a stochastic multi-stage model for optimizing battery operation in a microgrid considering battery degradation with a piece-wise linear cost function with uncertain wind power production and load. The model is solved using Stochastic Dual Dynamic Programming (SDDP) and is demonstrated on a 4-bus test case with limited import and export capacity to illustrate the battery degradation cost's impacts on the battery cycling strategy. The results show that the importance of a stochastic method is more pronounced when battery degradation is modelled.

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Factoring the Cycle Aging Cost of Batteries Participating in Electricity Markets

Cited by 292 publications

References 33 publications

Robust Look-ahead Three-phase Balancing of Uncertain Distribution Loads

Robust Look-ahead Three-phase Balancing of Uncertain Distribution Loads

Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †

Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming

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