• ETRI Journal
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• 제36권1호
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• pp.80-88
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• 2014

Recently, the idea of the smart grid has been gaining significant attention and has become a hot research topic. The purpose of this paper is to present a novel smart grid management scheme that uses game theory principles. In our proposed scheme, power appliances in the smart grid adaptively form groups according to the non-cooperative hedonic game model. By exploiting multi-appliance diversity, appliances in each group are dynamically scheduled in a cooperative manner. For efficient smart grid management, the proposed coopetition game approach is dynamic and flexible to adaptively respond to current system conditions. The main feature is to maximize the overall system performance while satisfying the requirements of individual appliances. Simulation results indicate that our proposed scheme achieves higher energy efficiency and better system performance than other existing schemes.

• 전자공학회논문지
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• 제53권5호
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• pp.25-36
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• 2016

스마트그리드 기술은 기존의 전력망 관리와 제어를 위해 ICT (Information and Communications Technologies)를 이용하여 전력 공급자와 소비자 간에 양방향으로 실시간 전력 정보의 교환을 통하여 에너지 효율을 극대화시키는 것을 목적으로 하고 있다. 본 논문에서는 IEEE 802.11s STDMA (Spatial Time Division Multiple Access) 기반의 다중 채널 스마트그리드의 NAN (Neighborhood Area Network) 네트워크에서 수리적 모델링에 기반한 계층 교차적 설계 기법을 이용하는 "JRS-MS" (Joint Routing and Scheduling for Multi-channel SmartGrid) 알고리즘을 제안한다. 제안 알고리즘은 다중 채널 스마트그리드 NAN 네트워크의 각 데이터 링크에서 데이터 전송량을 적절히 조절하고 동시에 플로우들 간에 간섭이 적은 고속 경로의 탐색을 수행한다. 이를 통하여 각 플로우들의 네트워크 이용률을 높여 전송률을 향상시킨다. 제안 알고리즘과 기존 제안 알고리즘인 JRS-SG (Jointly Routing and Scheduling for SmartGrid) 알고리즘 과의 비교 성능 분석을 통하여 JRS-MS 알고리즘이 다중 홉 NAN 무선 메쉬 네트워크를 경유하는 플로우들의 수가 늘어날 때 주어진 대역폭 자원을 최대로 활용하여 전송 성능을 향상 시킬 수 있음을 보였다.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• 전기학회논문지
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• 제62권10호
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• pp.1390-1396
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• 2013

The paper estimated the reasonable market price of lead-acid battery energy storage system (BESS) intended for demand management of electricity customers. As time-of-use (TOU) tariffs have extended to a larger number of customers and gaps in the peak and off-peak rates have gradually risen, deployment of BESS has been highly needed. However, immature engineering techniques, lack of field experiences and high initial investment cost have been barriers to opening up ESS markets. This paper assessed electricity cost that BESS operation could save for customers and, based on the possible cost savings, estimated reasonable prices at which BESSs could become a more prospective option for demand management of customers. Battery scheduling was optimized to maximize the electricity cost savings that BESS would possibly achieve under TOU tariffs conditions. Basic economic factors such as payback period and return on investment were calculated to determine reasonable market prices. Actual load data of 12 industrial customers were used for case studies.

• KEPCO Journal on Electric Power and Energy
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• 제6권3호
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• pp.315-319
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• 2020

The modern transportation and mobility sector is expected to encounter high penetration of Electric Vehicles (EVs) because EVs contribute to reducing the harmful emissions from fossil fuel-powered vehicles. With the prospective growth of EVs, sufficient and convenient facilities for fast charging are crucial toward satisfying the EVs' quick charging demand during their trip. Therefore, the Fast Electric Vehicle Charging Stations (FECS) will be a similar role to gas stations. In this paper, we study a charging scheduling problem for the FECS with solar photovoltaic (PV) and an Energy Storage System (ESS). We formulate an optimization problem that minimizes the operational costs of FECS. There are two cost and one revenue terms that are buying cost from main grid power, ESS degradation cost, and revenue from the charging fee of the EVs. Simulation results show that the proposed scheduling algorithm reduces the daily operational cost by effectively using solar PV and ESS.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.2135-2141
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• 2015

Power line communication (PLC) is one of the major communication technologies in smart grid since it combines good communication capability with easy and simple deployment. As a power network can be modeled as a graph, we propose a vertex coloring based slot reuse scheduling in the time division multiple access (TDMA) period for PLCs. Our objective is to minimize the number of assigned time slots, while satisfying the quality of service (QoS) requirement of each station. Since the scheduling problem is NP-hard, we propose an efficient heuristic scheduling, which consists of repeated vertex coloring and slot reuse improvement algorithms. The simulation results confirm that the proposed algorithm significantly reduces the total number of time slots.

• 한국산학기술학회논문지
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• 제13권8호
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• pp.3358-3365
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• 2012

본 논문은 전력 효율을 고려한 다이캐스팅 공정의 스케줄링 기법을 제안한다. 시프트(shift)마다 반복 작업하는 다이캐스팅 공정의 스케줄링 문제는 각 제품의 시프트별 생산량을 의사결정변수로 정의하여 용탕 효율을 최대화 시키는 선형계획법으로 표현 가능하다. 본 연구에서는 주조 공장의 전력 사용에 대한 제한 조건까지 고려하는 새로운 선형계획법 모델을 제시한다. 제안된 모델은 다이캐스팅 공정의 한 시프트가 소비하는 전력 사용량이 주어진 한계 전력량 범위를 넘지 않도록 하는 스케줄링 결과를 유도한다. 사례 연구를 통하여 제안된 모델의 우수성과 응용가능성을 검증한다. 본 논문은 스마트 그리드 환경에서 지능형 소비자로 분류되는 주조 공장이 전력 사용 제한 조건을 만족시켜야 하는 문제에 대한 기초 연구의 역할을 할 것이다.

• 전기학회논문지
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• 제62권1호
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• pp.21-28
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• 2013

The paper proposes an optimal sizing method of a customer's battery energy storage system (BESS) which aims at managing the electricity demand of the customer to minimize electricity cost under the time of use(TOU) pricing. Peak load limit of the customer and charging and discharging schedules of the BESS are optimized on annual basis to minimize annual electricity cost, which consists of peak load related basic cost and actual usage cost. The optimal scheduling is used to assess the maximum cost savings for all sets of candidate capacities of BESS. An optimal size of BESS is determined from the cost saving curves via capacity of BESS. Case study uses real data from an apartment-type factory customer and shows how the proposed method can be employed to optimally design the size of BESS for customer demand management.

• 전력전자학회논문지
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• 제19권6호
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• pp.511-521
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• 2014

This study proposes an electric vehicle (EV) smart panel board and its control method on the basis of charging scheduling. The proposed system consists of batteries, a three-phase battery charger, three single-phase inverters, transfer switches for electric power distribution, and a controller. The three-phase battery charger usually charges the batteries at midnight when electric rates are cheap and in light load. When the electric power consumption of the EV standard chargers connected to one phase of the power line is relatively large or when a blackout occurs, the electric power stored in the battery is supplied by discharging through the inverters to the EV standard chargers. As a result, the value of peak load and the charging electric power quantity supplied from a utility grid are reduced, and the current unbalance is improved. The usefulness of the proposed system is confirmed through simulations, experiments, and case studies.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.1363-1364
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• 2010

본 논문에서는 스마트 그리드 시스템에서 사용자의 전력 사용 요구를 받아 이를 효율적으로 스케줄링하는 시스템을 설계하고 그 프로토타입을 구현한다. 각 기기들이 시작가능시간, 종료시한, 시간대별 사용량 변화를 명세하는 프로파일 등을 스케줄러에 넘겨주면 스케줄러는 각 작업의 시작가능시간과 여유시간 내에서 작업들을 배치한 후 리커시브하게 서치 스페이스를 확장하여 가장 최소의 단위시간당 최대 전력 요구량을 갖는 스케줄을 찾아낸다. 비선점형 작업의 특성에 의해 스페이스 확장의 복잡도를 크게 줄일 수 있으며 최소비용 소비 스케줄 등 다양한 목표를 위해 변경될 수 있다. 구현된 시스템은 주어진 작업 집합에 대해 최대 전력 요구량을 30 % 감소시키는 스케줄을 생성한다.