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      계시별 요금제에서 ESS와 태양광발전을 고려한 최적 부하계획법 = An Optimal Load Scheduling Method Considering ESS and PV Generation Under Time-of-Use Pricing

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      https://www.riss.kr/link?id=A108723473

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      다국어 초록 (Multilingual Abstract)

      From the perspective of load planning, if the consumer has its own power generation facilities or energy storage devices, it can be somewhat complicated methodologically but can result in excellent outcomes. This paper proposes a load planning method in a time-of-use pricing environment assuming the consumer has both self-owned PV generation facilities and energy storage devices. The load is divided into fixed loads with a fixed consumption time and controllable loads with a flexible consumption time, and the controllable loads are the target of load planning. The goal of the proposed method is to minimize electricity bills while considering various realistic constraints such as precedence constraints between controllable loads. The proposed method uses mixed integer linear programming (MILP) as an optimization method and confirms its effectiveness by coding in Matlab.
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      From the perspective of load planning, if the consumer has its own power generation facilities or energy storage devices, it can be somewhat complicated methodologically but can result in excellent outcomes. This paper proposes a load planning method ...

      From the perspective of load planning, if the consumer has its own power generation facilities or energy storage devices, it can be somewhat complicated methodologically but can result in excellent outcomes. This paper proposes a load planning method in a time-of-use pricing environment assuming the consumer has both self-owned PV generation facilities and energy storage devices. The load is divided into fixed loads with a fixed consumption time and controllable loads with a flexible consumption time, and the controllable loads are the target of load planning. The goal of the proposed method is to minimize electricity bills while considering various realistic constraints such as precedence constraints between controllable loads. The proposed method uses mixed integer linear programming (MILP) as an optimization method and confirms its effectiveness by coding in Matlab.

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      참고문헌 (Reference)

      1 김광원, "태양광발전과 시간대별 차등 요금제를 고려한 배터리 최적 충전/방전 계획에 관한 연구" 한국조명.전기설비학회 34 (34): 10-15, 2020

      2 김광원, "시간대별 차등요금제에서 정수선형계획을 이용한 부하계획법" 한국조명.전기설비학회 34 (34): 17-23, 2020

      3 A. Oudalov, "Sizing and optimal operation of battery energy storage sy stem for peak shaving application" 621-625, 2007

      4 T. Remani, "Residential load scheduling with renewable generation in the smart grid: A reinforcement learning approach" 13 (13): 3283-3294, 2019

      5 M. Kumar, "Optimal load scheduling for industrial load - Analysis for a generalized industrial load model" 2019

      6 H. A. Taha, "Operations Research" Macmillan Publishing Company 25-342, 1989

      7 M. Ostadijafari, "Linearized price-responsive HVAC controller for optimal scheduling of smart building loads" 11 (11): 3131-3145, 2020

      8 J. Wang, "Intelligent demand response for industrial energy management considering thermostatically controlled loads and EVs" 15 (15): 3432-3442, 2019

      9 R. Morsali, "Demand response based day-ahead scheduling and battery sizing in microgrid management in Rural areas" 12 (12): 1651-1658, 2018

      10 N. Javaid, "An intelligent load management system with renewable energy integration for smart homes" 5 : 13587-13600, 2017

      1 김광원, "태양광발전과 시간대별 차등 요금제를 고려한 배터리 최적 충전/방전 계획에 관한 연구" 한국조명.전기설비학회 34 (34): 10-15, 2020

      2 김광원, "시간대별 차등요금제에서 정수선형계획을 이용한 부하계획법" 한국조명.전기설비학회 34 (34): 17-23, 2020

      3 A. Oudalov, "Sizing and optimal operation of battery energy storage sy stem for peak shaving application" 621-625, 2007

      4 T. Remani, "Residential load scheduling with renewable generation in the smart grid: A reinforcement learning approach" 13 (13): 3283-3294, 2019

      5 M. Kumar, "Optimal load scheduling for industrial load - Analysis for a generalized industrial load model" 2019

      6 H. A. Taha, "Operations Research" Macmillan Publishing Company 25-342, 1989

      7 M. Ostadijafari, "Linearized price-responsive HVAC controller for optimal scheduling of smart building loads" 11 (11): 3131-3145, 2020

      8 J. Wang, "Intelligent demand response for industrial energy management considering thermostatically controlled loads and EVs" 15 (15): 3432-3442, 2019

      9 R. Morsali, "Demand response based day-ahead scheduling and battery sizing in microgrid management in Rural areas" 12 (12): 1651-1658, 2018

      10 N. Javaid, "An intelligent load management system with renewable energy integration for smart homes" 5 : 13587-13600, 2017

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