Integrated Multiscale Design, Market Participation, and Replacement Strategies for Battery Energy Storage Systems

Sorourifar, Farshud; Zavala, Ví­ctor M.; Dowling, Alexander W.

doi:10.1109/tste.2018.2884317

Cited by 47 publications

(26 citation statements)

References 32 publications

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“…In [126], another study was performed to help different entities improve factors such as participation in the market, the degradation of BESS, and the annual replacement of BESS through realistic CAISO data. Results show that it achieved an increment of 4-5-fold in the NPV compared with the day-ahead energy market.…”

Section: Simulation Tools For Campus Microgridsmentioning

confidence: 99%

An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Muqeet¹,

Munir

Javed

et al. 2021

Energies

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The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids’ energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids’ importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids.

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Section: Simulation Tools For Campus Microgridsmentioning

confidence: 99%

An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Muqeet¹,

Munir

Javed

et al. 2021

Energies

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“…In their seminal work, Walawalkar et al [48] use mathematical optimization to estimate the maximum possible revenue from historical market data and compare energy storage technology options. This now-standard approach has been applied by many technologies including batteries [12,43,16,30,44], and concentrated solar thermal with energy storage [13,25,22,27,14]. Likewise, time-varying energy prices incentivize large energy consumers to either directly participate in wholesale markets or demand response programs.…”

Section: Introductionmentioning

confidence: 99%

Learning spatiotemporal dynamics in wholesale energy markets with dynamic mode decomposition

Elmore

Dowling

2021

Energy

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Energy markets facilitate the balancing of electricity generation (supply) and demand while ensuring non-discriminatory access. Understanding energy market dynamics is essential to improving grid efficiency and resilience and optimizing the development of new energy conversion and storage technologies. Accurate energy price forecasts are essential for many energy storage technologies to be profitable from price arbitrage. In this paper, we apply the novel spatial-temporal dimensionality reduction method of Dynamic Mode Decomposition (DMD) to forecast 6587 locational marginal prices in the California Independent System Operator (CAISO) on the Day-Ahead Market (DAM). DMD is a promising equation-free modeling technique in systems with inherent periodic tendencies in time such as financial markets and fluid dynamics. Yet we show, for the first time, that DMD cannot reliably forecast day-ahead energy prices due to the so-called standing wave problem. Instead, we find Augmented DMD (ADMD) overcomes these limitations is a fast and accurate price forecaster. We benchmark DMD, ADMD, and backcasting forecasting methods for optimal price arbitrage with an energy storage system. We find, using ADMD, a market-connected energy storage system can capture up to 92% of allowable revenues in rolling horizon simulations. Lastly, we show ADMD is up to 1000-times faster than time-series forecasting methods (i.e., ARIMA) which requires orders of magnitude less data than deep/machine learning techniques.

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“…Additionally, the perspective of BESS operators has already been discussed for different market‐based applications, such as FCR [26–28], peak shaving [29–31] and combinations of multiple applications [32–34]. Hence, many studies analyse BESS profitability for different grid‐oriented applications.…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge, no other SCOPF‐based study considers profitability of curative BESS and only few consider market‐based provision of system services. On the contrary, studies dealing with BESS profitability [26–34] do not perform detailed power system optimization.…”

Section: Introductionmentioning

confidence: 99%

Technical and economic analysis of curative actions in distribution networks utilizing battery energy storage systems

Liere-Netheler¹,

Schuldt²,

Maydell³

et al. 2021

IET Generation Trans & Dist

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Renewable energy generation curtailment increases due to more frequently occurring congestions in power system operation. Post‐contingency curative congestion management actions can reduce the necessity of renewable energy curtailment by enabling a more efficient utilization of transmission capacities. In this research, the potential of curative actions to substitute renewable energy curtailment is studied considering technical and economic criteria. Therefore, a novel pricing methodology for the market‐based provision of curative actions is introduced. The method is based on the security constraint optimal power flow technique. Simulations are carried out on a modified version of the IEEE 14‐bus network and a real‐world 110 kV distribution network. Battery energy storage systems are implemented as an exemplary technology to provide curative actions. The developed method achieves a positive power system impact by reducing operational costs and maximizing renewable energy integration. Also, novel business models for merchant‐owned battery energy storage systems are unveiled. The provision of curative actions further proves to be competitive to established battery storage applications. Additionally, results of different grid expansion scenarios of the 110 kV network reveal the need to coordinate power system planning and operation more extensively in the future.

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Integrated Multiscale Design, Market Participation, and Replacement Strategies for Battery Energy Storage Systems

Cited by 47 publications

References 32 publications

An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Learning spatiotemporal dynamics in wholesale energy markets with dynamic mode decomposition

Technical and economic analysis of curative actions in distribution networks utilizing battery energy storage systems

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