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.

본 연구는 ISO19030 - 선체 및 프로펠러 성능 모니터링 방법을 실선 178 k 벌크선박에 적용한 결과에 관한 것이다. 최근 온실가 스 저감 규정 대응과 해운 경쟁력 확보를 위해 에너지 저감 솔루션을 선박에 적용하려는 시도가 증가하고 있다. 하지만 정량적으로 선박 성능을 분석하기 쉽지 않아 에너지 저감 솔루션의 평가가 쉽지 않았다. 이러한 해운 산업의 요구에 따라 2016년 ISO19030이 표준화되어 선박 성능 분석을 정량화할 수 있는 기반이 마련되었다. 하지만 ISO19030에서 제안하는 환경 보정법은 각 날씨 영향을 고려한 보정이 아닌 정수(Calm Sea) 상태에서 운항한 데이터만 분석하는 방식이다. 이러한 분석 방식은 선박의 운항 구간에 따라 데이터가 필터링 되는 편차가 심하고 정확한 환경 보정을 하지 않아 6개월 이하의 분석은 신뢰하기 어렵다. 본 연구에서는 ISO19030을 실제 3척 선박 3년 이상 장 기간 운항 데이터에 적용하였다. 적용 결과를 토대로 ISO19030 효용성과 한계점을 파악하고 ISO19030에서 제안하는 필터링 방식 대신 ISO15016의 파도 보정(STA-WAVE2)을 통해 성능 분석 방법을 개선하고자 한다.

Optimizing energy usage for maximum efficiency is an essential goal for manufacturing plants in every industrial manufacturing sector. The generation and distribution of purifying compressed air is a large expense incurred in practically all manufacturing processes. Not only is the generation and treatment expensive equipment of compressed air, but frequent maintenance and effective operation is also required. As a plant’s compressed air system is often an integral part of the production process, it needs to be reliable, efficient, and easy to be maintain. In this paper, we study to find operating method to save energy from the adsorption dryer in the process of purifying compressed air, which is required for a clean room production site in “A” company. The compressed air passes through a pressure vessel with two “towers” filled with a material such as activated alumina, silica gel, molecular sieve or other desiccant material. This desiccant material attracts the water from the compressed air via adsorption. As the water clings to the desiccant, the desiccant particle becomes saturated. Therefore, Adsorption dryer is an extremely significant facility which removes the moisture in the air 70℃ below the dew point temperature while using a lot of energy. Also, the energy consumption of the adsorption dryer can be varied by various operating conditions (time, pressure, temperature, etc). Therefore, based on existing operating experiments, we have searched operating condition to maximize energy saving by changing operating conditions of the facility. However, due to a short experiment period (from September to October), further research will be focused on considering seasonality.