Effect of the battery energy storage system on the time-of-use rates industrial customers

Lee, T.-Y.

doi:10.1049/ip-gtd:19941364

Cited by 15 publications

(7 citation statements)

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“…D t ≥ 0, ∀t (15) where N is the number of ESS, T is a decision horizon, D t is forecasted load demand at the t-th time interval, D t is a modified demand by ESSs at the t-th time interval, ep c j,t is a charging power of ESS-j from the grid at the t-th time interval, and ep d j,t is a discharging power of ESS-j injected to the grid at the t-th time interval.…”

Section: Peak-shavingmentioning

confidence: 99%

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Linear Formulation for Short-Term Operational Scheduling of Energy Storage Systems in Power Grids

Park

Kim

et al. 2017

Energies

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This paper presents linear programming (LP) formulations for short-term energy time-shift operational scheduling with energy storage systems (ESSs) in power grids. In particular, it is shown that the conventional nonlinear formulations for electric bill minimization, peak shaving, and load leveling can be formulated in the LP framework. New variables for the peak and off-peak values are introduced in peak shaving and load leveling model, and the historical peak value for demand charge are considered in the electric bill minimization model. The LP formulations simplify computation while maintaining the accuracy for including linear technical constraints of ESSs, such as the state-of-charge, charging/discharging efficiency, output power range, and energy limit considering the life cycle of ESS. Proposed LP formulations have been implemented and verified in practical power systems and a large-scale industrial customer using historical data.

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Section: Peak-shavingmentioning

confidence: 99%

“…Finally we can solve the peak-shaving problem using LP with the objective function (16) subject to ESS technical constraints (1)- (12) and additional constraints (14), (15), and (17).…”

Section: Peak-shavingmentioning

confidence: 99%

Linear Formulation for Short-Term Operational Scheduling of Energy Storage Systems in Power Grids

Park

Kim

et al. 2017

Energies

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“…In contrast, by owning a battery energy storage system (BESS), every customer is able to be price-elastic and demand can be changed without reduction of the customer's utility. Therefore, operation of BESS for participating in DR programs is one of the options that customer can use to reduce their electricity cost, and it has already been studied in [2][3][4]. Although performance of its application on DR programs is verified in previous studies, the economic value of BESS operation is still controversial due to the high installation costs and short life time of BESS.…”

Section: Introductionmentioning

confidence: 99%

“…For this reason, most of the previous studies on utilization of BESS to reduce energy costs under a TOU tariff has only considered demand charge reduction, thereby confining the contribution of the research to no more than the decrease in energy charges. In some studies, research on determination of an optimal BESS size [2], and its operation [3,4,10], which could also minimize energy charges along with demand charges have been conducted. However, the results appeared to be similar to the peak shaving operations since a normal demand pattern in which the peak occurs in a time period of a high rates is used, and it did not practically reflect the customer loads in reality, which may have various patterns.…”

Section: Introductionmentioning

confidence: 99%

Impact of Battery Energy Storage System Operation Strategy on Power System: An Urban Railway Load Case under a Time-of-Use Tariff

Kim

Heo²,

Park

et al. 2017

Energies

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Customer-owned battery energy storage systems (BESS) have been used to reduce electricity costs of energy storage owners (ESOs) under a time-of-use (TOU) tariff in Korea. However, the current TOU tariff can unintentionally induce customer's electricity usage to have a negative impact on power systems. This paper verifies the impact of different BESS operation strategies on power systems under a TOU tariff by analyzing the TOU tariff structure and the customer's load pattern. First, several BESS operation strategies of ESO are proposed to reduce the electricity cost. In addition, a degradation cost calculation method for lithium ion batteries is considered for the ESO to determine the optimal BESS operation strategy that maximizes both electricity cost and annual investment cost. The optimal BESS operation strategy that maximizes ESO's net benefit is illustrated by simulation using an urban railway load data from Namgwangju Station, Korea. The results show that BESS connected to urban railway loads can negative impact power system operation. This is due to the high BESS degradation costs and lack of incentive of differential rates in TOU tariff that can effectively induce proper demand response.

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“…M. S. Kandil et al simulated optimal power flow containing ESSs in the test grids and analyzed the impact on transmission congestion relief by ESSs [9]. In the customer side, operational strategies of BESS are scheduled to minimize the electric bill in [10] and [11]. Optimal allocation of distributed resources in a microgrid has been resolved in [12] and [13].…”

Section: Introductionmentioning

confidence: 99%

MILP-Based Dynamic Efficiency Scheduling Model of Battery Energy Storage Systems

Park¹,

Kim²,

Park³

2016

Journal of Electrical Engineering and Technology

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-This paper presents a methodology to determine an optimal operation schedule of a battery energy storage system (BESS) considering dynamic charging/discharging efficiencies considering the output power levels. A novel optimization problem is formulated based on the mixed integer linear programming (MILP) addressing a non-linear charging/discharging efficiency function by a stair-wise linear model. Technical constraints of BESS are also included in the MILP formulation. Test simulation results of BESS operation for the two Korean power systems show the effectiveness of the dynamic efficiency scheduling model compared to the conventional average efficiency ones.

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Effect of the battery energy storage system on the time-of-use rates industrial customers

Cited by 15 publications

References 0 publications

Linear Formulation for Short-Term Operational Scheduling of Energy Storage Systems in Power Grids

Linear Formulation for Short-Term Operational Scheduling of Energy Storage Systems in Power Grids

Impact of Battery Energy Storage System Operation Strategy on Power System: An Urban Railway Load Case under a Time-of-Use Tariff

MILP-Based Dynamic Efficiency Scheduling Model of Battery Energy Storage Systems

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