Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost

Choi, Yeonjoo; Hongseok, Kim

doi:10.3390/en9060462

Cited by 69 publications

(48 citation statements)

References 31 publications

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“…Life damage has relationship with charge and discharge frequency, depth and other factors [42], and the cost of battery life damage in the t-th dispatch period is shown as Equation (11):…”

Section: Operation and Cost Model Of Energy Storage Devicementioning

confidence: 99%

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Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

et al. 2018

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Abstract:In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM) and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP), and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL), are still imperfect, which make it difficult for the active distribution network (ADN) to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified.

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“…Life damage has relationship with charge and discharge frequency, depth and other factors [42], and the cost of battery life damage in the t-th dispatch period is shown as Equation (11):…”

Section: Operation and Cost Model Of Energy Storage Devicementioning

confidence: 99%

“…The upper and lower bounds of the charge and discharge power of the energy storage device, the SOC constraints, and the logic constraints of charge and discharge also use the common form, and detailed models and parameters can be found in [42].…”

Section: Operation and Cost Model Of Energy Storage Devicementioning

confidence: 99%

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

et al. 2018

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“…The subtlety lies in that, if the realized load happens to be a lot higher than the expected value E n m , the peak load may exceedP n m even though it could have been kept lower thanP n m . In order to avoid this subtle case, we conservatively design the algorithm by discountingP n m by γ ∈ [0, 1] so that peak load control can be done more often.P n m is then updated everyday as in (22). Let C n m be the ToU cost of day n of month m, which is simply given by:…”

Section: Year-round Operation Of Ess With Uncertain Load Profilementioning

confidence: 99%

“…Weighting factor β is the inverse of base electricity price. We use battery price quoted from the practical data [22], and the battery price per kWh is $150, and total cycle life is about 3500 cycles when battery is used with 80% depth of discharge (DoD). …”

Section: Experimental Set-upmentioning

confidence: 99%

Robust Operation of Energy Storage System with Uncertain Load Profiles

et al. 2017

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Abstract:In this paper, we propose novel techniques to reduce total cost and peak load of factories from a customer point of view. We control energy storage system (ESS) to minimize the total electricity bill under the Korea commercial and industrial (KCI) tariff, which both considers peak load and time of use (ToU). Under the KCI tariff, the average peak load, which is the maximum among all average power consumptions measured every 15 min for the past 12 months, determines the monthly base cost, and thus peak load control is extremely critical. We aim to leverage ESS for both peak load reduction based on load prediction as well as energy arbitrage exploiting ToU. However, load prediction inevitably has uncertainty, which makes ESS operation challenging with KCI tariff. To tackle it, we apply robust optimization to minimize risk in a real environment. Our approach significantly reduces the peak load by 49.9% and the total cost by 10.8% compared to the case that does not consider load uncertainty. In doing this we also consider battery degradation cost and validate the practical use of the proposed techniques.

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“…In spare spaces like warehouses, an ESS for stabilizing the fluctuation of the PV generation system or adjusting the peak load of the smart home is installed [19,20]. Although interests in ESSs are rising for the self-reliance of smart home such as zero energy house, most of them are controlled according to time schedule or used in conjunction with PV generation systems [21,22]. In addition, a Home Energy Management System (HEMS) is installed for energy reduction and efficient use of smart home [23].…”

Section: Introductionmentioning

confidence: 99%

Energy Storage System Control Algorithm by Operating Target Power to Improve Energy Sustainability of Smart Home

et al. 2018

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Abstract:As energy issues are emerging around the world, a variety of smart home technologies aimed at realizing zero energy houses are being introduced. Energy storage system (ESS) for smart home energy independence is increasingly gaining interest. However, limitations exist in that most of them are controlled according to time schedules or used in conjunction with photovoltaic (PV) generation systems. In consideration of load usage patterns and PV generation of smart home, this study proposes an ESS control algorithm that uses constant energy of energy network while making maximum use of ESS. Constant energy means that the load consumes a certain amount of power under all conditions, which translates to low variability. The proposed algorithm makes a smart home a load of energy network with low uncertainty and complexity. The simulation results show that the optimal ESS operating target power not only makes the smart home use power constantly from the energy network, but also maximizes utilization of the ESS. In addition, since the smart home is a load that uses constant energy, it has the advantage of being able to operate an efficient energy network from the viewpoint of energy providers.

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Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost

Cited by 69 publications

References 31 publications

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

Robust Operation of Energy Storage System with Uncertain Load Profiles

Energy Storage System Control Algorithm by Operating Target Power to Improve Energy Sustainability of Smart Home

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