• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.305-312
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• 2014

This paper discusses real-time peak shaving algorithms for a large-scale battery energy storage system (BESS). Although several transmission and distribution functions could be implemented for diverse purposes in BESS applications, this paper focuses on a real-time peak shaving algorithm for an energy time shift, considering wind power generation. In a high wind penetration environment, the effective load levels obtained by subtracting the wind generation from the load time series at each long-term cycle time unit are needed for efficient peak shaving. However, errors can exist in the forecast load and wind generation levels, and the real-time peak shaving operation might require a method for wind generation that includes comparatively large forecasting errors. To effectively deal with the errors of wind generation forecasting, this paper proposes a real-time peak shaving algorithm for threshold value-based peak shaving that considers fuzzy wind power generation.

• 한국지능시스템학회논문지
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• 제24권2호
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• pp.141-146
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• 2014

본 논문은 Peak Shaving 알고리즘의 성능 향상을 위한 예측 부하 곡선의 생성의 한 방법을 제시한다. 여기서 논하는 Peak Shaving 알고리즘은 대용량의 배터리 에너지 저장시스템 (BESS, Battery Energy Storage System)을 위한 PMS (Power Management System)의 장주기 스케쥴링 알고리즘을 의미한다. 위의 PMS는 주로 배터리에서 에너지의 입출력을 제어하는 데에 주목적이 있다. 이를 위해서 Peak Shaving 알고리즘이 사용되는데, 여기서 예측 부하곡선과 실제 부하곡선 사이의 불확실성이 나타난다. 원활한 에너지의 충,방전을 위하여 본 논문에서는 주 단위의 표준화 방법과 계절별 부하의 특성을 고려한 예측 부하 곡선 생성 방법을 제안한다.

• 한국지능시스템학회논문지
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• 제22권6호
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• pp.754-760
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• 2012

본 논문은 MW 스케일의 배터리 에너지 저장 시스템 (BESS)을 위한 PMS (power management systems)의 장기간 스케쥴링 알고리즘의 하나로서 peak shaving 알고리즘에 대하여 설명한다. PMS의 목적은 기본적으로 배터리 모듈의 AC 입출력을 제어하는 데 있다. 1일전 부하 곡선이 제공된다는 가정 하에서, 오프라인 peak shaving 알고리즘이 적용될 수 있으나, 이 오프라인 알고리즘의 결과를 적용할 경우 부하 곡선에 존재하는 불확실성에 의하여 그 적용 결과가 실시간 운전에서는 다르게 나타날 수 있다. 본 논문에서는 PMS의 peak shaving 문제에서 부하 곡선의 불확실성을 고려하기 위하여 퍼지 LP 문제 형태로 정식화하고 그 해법과 실시간 운전 시 적용 방안에 대하여 논한다.

• 전기학회논문지
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• 제65권3호
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• pp.404-410
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• 2016

This paper proposed a program of an energy storage system(ESS) for peak shaving of high-speed railway substations The peak shaving saves cost of equipment and demand cost of the substation. To reduce the peak load, it is very important to know when the peak load appears. The past data based load profile forecasting method is easy and applicable to customers which have relatively fixed load profiles. And an optimal scheduling method of the ESS is helpful in reducing the electricity tariff and shaving the peak load efficiently. Based on these techniques, MS. NET based peak shaving program is developed. In case study, a specific daily load profile of the local substation was applied and simulated to verify performance of the proposed program.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.981-987
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• 2017

In this paper, we estimate the economic benefits of Energy Storage Systems (ESSs) for peak load shaving in an urban railway substation using the annual cost. The annual investment cost of ESSs is estimated using Net Present Value (NPV) and compared with the cost reduction of electricity by the ESS. The optimal capacities of the battery and Power Converting System (PCS) are determined for peak load shaving. The optimal capacity of the ESS and the peak load shaving is determined to maximize the profit by the ESS. The proposed method was applied to real load data in an urban railway substation, and the results show that electric power costs can be reduced. Other aspects of the ESS, such as the lifetime and unit price of the battery, are also investigated economically.

• 전기학회논문지
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• 제63권12호
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• pp.1752-1758
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• 2014

This paper evaluates economic benefits of ESS (Energy Storage System) for peak load shaving in the substation of urban railway. For this purpose, the method to determine capacities of ESS and PCS (Power Conditioning System) for peak load shaving is proposed. Then the economic benefits of those devices are evaluated using net present value method. The proposed methods are applied to actual measurements of loads in the substation of urban railway. The results show that electric power costs can be reduced and the economic benefits of ESS for peak load shaving mainly depends on the price of battery.

• 전기학회논문지
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• 제63권1호
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• pp.27-34
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• 2014

The paper proposed a sizing method of an energy storage system(ESS) for peak shaving of high-speed railway substations based on load profile patterns of substations. A lithium based battery ESS was selected since it can produce high-power at high speed that peak shaving requires, and also takes up a relatively smaller space for installation. Adequate size of the ESS, minimum capacity which can technically meet a peak shaving target, was determined by collectively considering load patterns of a target substation, characteristics of the ESS to be installed, and optimal scheduling of the ESS. In case study, a local substation was considered to demonstrate the proposed sizing method. Also economic analysis with the determined size of ESS was performed to calculate electricity cost savings of the peak shaving ESS, and to offer pay-back period and return on investment.

• 산업경영시스템학회지
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• 제43권2호
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• pp.1-13
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• 2020

There are several methods of peak-shaving, which reduces grid power demand, electricity bought from electricity utility, through lowering "demand spike" during On-Peak period. An optimization method using linear programming is proposed, which can be used to perform peak-shaving of grid power demand for grid-connected PV+ system. Proposed peak shaving method is based on the forecast data for electricity load and photovoltaic power generation. Results from proposed method are compared with those from On-Off and Real Time methods which do not need forecast data. The results also compared to those from ideal case, an optimization method which use measured data for forecast data, that is, error-free forecast data. To see the effects of forecast error 36 error scenarios are developed, which consider error types of forecast, nMAE (normalizes Mean Absolute Error) for photovoltaic power forecast and MAPE (Mean Absolute Percentage Error) for load demand forecast. And the effects of forecast error are investigated including critical error scenarios which provide worse results compared to those of other scenarios. It is shown that proposed peak shaving method are much better than On-Off and Real Time methods under almost all the scenario of forecast error. And it is also shown that the results from our method are not so bad compared to the ideal case using error-free forecast.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.337-338
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• 2015

본 논문은 BESS 기반 전력피크 대응 peak shaving 알고리즘에 대하여 설명한다. 전력망 응용에 적용되는 BESS는 다양한 C-rate (charge rate)을 갖으며, 이를 고려한 알고리즘 개발이 요구된다. 상대적으로 높은 C-rate을 갖는 BESS의 경우 단주기 응용으로 적용될 수 있으나, 보다 효과적인 활용방안은 두 가지의 이상의 목적을 위한 운용이 요구된다. 더욱이 전력피크 예측을 위한 정교한 부하예측 방법이 필요하다. 본 논문에서는 단주기 및 장주기 응용을 모두 고려하였을 때 요구되는 peak shaving 알고리즘 설계 및 Algebraic Prediction을 이용한 부하예측에 대하여 논하고자 한다.

• 전기학회논문지
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• 제63권6호
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• pp.860-865
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• 2014

This paper proposes the method for determination of the capacities of ESS (Energy Storage System) and PCS (Power Conditioning System) for the peak load shaving based on the load data in the substation of urban railway. In addition, this paper analyze the actual measurement of loads in the substation of urban railway. The load of a weekday in the substation of urban railway is high around rush hours in the morning and evening, which is different from that of a normal substation. The required capacities of ESS and PCS become larger as the amount of peak load shaving is higher, and are affected from the patterns of daily load in the substation.