• Title/Summary/Keyword: Electricity IT

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Synthesis and Evaluation of Superhydrophobic ODA/PDMS Dip Coating on PET for Liquid-Solid Contact Electrification (액체-고체 접촉대전을 위한 PET 기판 기반 ODA/PDMS 딥 코팅 제조 및 평가)

  • Park, Sunyoung;Kang, Hyungyu;Byun, Doyoung;Cho, Dae-Hyun
    • Tribology and Lubricants
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    • v.37 no.2
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    • pp.71-76
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    • 2021
  • As opposed to using fossil fuels, we need to use eco-friendly resources such as sunlight, raindrops and wind to produce electricity and combat environmental pollution. A triboelectric nanogenerator (TENG) is a device that converts mechanical energy into electricity by inducing repetitive contact and separation of two dissimilar materials. During the contact and separation processes, electron flow occurs owing to a change in electric potential of the contacting surface caused by contact electrification and electrostatic induction mechanisms. A solid-solid contact TENG is widely known, but it is possible to generate electricity via liquid-solid contact. Therefore, by designing a hydrophobic TENG, we can gather electricity from raindrop energy in a feasible manner. To fabricate the superhydrophobic surface of TENGs, we employ a dip coating technique to synthesize an octadecylamine (ODA)- and polydimethylsiloxane (PDMS)-based coating on polyethylene terephthalate (PET). The synthesized coating exhibits superhydrophobicity with a contact angle greater than 150° and generates a current of 2.2 ㎂/L while water droplets fall onto it continuously. Hence, we prepare a box-type TENG, with the ODA/PDMS coating deposited on the inside, and place a 1.5 mL water droplet into it. Resultantly, we confirm that the induced vibration causes continuous impacts between the ODA/PDMS coating and the water, generating approximately 100 pA for each impact.

Electricity forecasting model using specific time zone (특정 시간대 전력수요예측 시계열모형)

  • Shin, YiRe;Yoon, Sanghoo
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.2
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    • pp.275-284
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    • 2016
  • Accurate electricity demand forecasts is essential in reducing energy spend and preventing imbalance of the power supply. In forcasting electricity demand, we considered double seasonal Holt-Winters model and TBATS model with sliding window. We selected a specific time zone as the reference line of daily electric demand because it is least likely to be influenced by external factors. The forecasting performance have been evaluated in terms of RMSE and MAPE criteria. We used the observations ranging January 4, 2009 to December 31 for testing data. For validation data, the records has been used between January 1, 2012 and December 29, 2012.

Electricity Demand Forecasting based on Support Vector Regression (Support Vector Regression에 기반한 전력 수요 예측)

  • Lee, Hyoung-Ro;Shin, Hyun-Jung
    • IE interfaces
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    • v.24 no.4
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    • pp.351-361
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    • 2011
  • Forecasting of electricity demand have difficulty in adapting to abrupt weather changes along with a radical shift in major regional and global climates. This has lead to increasing attention to research on the immediate and accurate forecasting model. Technically, this implies that a model requires only a few input variables all of which are easily obtainable, and its predictive performance is comparable with other competing models. To meet the ends, this paper presents an energy demand forecasting model that uses the variable selection or extraction methods of data mining to select only relevant input variables, and employs support vector regression method for accurate prediction. Also, it proposes a novel performance measure for time-series prediction, shift index, followed by description on preprocessing procedure. A comparative evaluation of the proposed method with other representative data mining models such as an auto-regression model, an artificial neural network model, an ordinary support vector regression model was carried out for obtaining the forecast of monthly electricity demand from 2000 to 2008 based on data provided by Korea Energy Economics Institute. Among the models tested, the proposed method was shown promising results than others.

Measuring Efficiency of Global Electricity Companies Using Data Envelopment Analysis Model (DEA모형을 이용한 전력회사의 효율성 분석에 관한 연구)

  • Kim, Tae Ung;Jo, Sung Han
    • Environmental and Resource Economics Review
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    • v.9 no.2
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    • pp.349-371
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    • 2000
  • Data Envelopment Analysis model is a linear programming based technique for measuring the relative performance of organizational units where the presence of multiple inputs and outputs makes comparison difficult. A common measure for relative efficiency is weighted sum of outputs divided by weighted sum of inputs. DEA model allows each unit to adopt a set of weight that shows it in the most favorable light in comparison to the other unit. In this paper, we present the mathematical background and characteristics of DEA model, and give a short case study where we apply the DEA model to evaluate the relative efficiencies of 51 global electricity companies. The technical efficiency and scale efficiency are also to be investigated. Generating capacity and the number of employees are used for input data, and revenue, net profit and electricity sales are used for output data. We find that the companies with 100% relative efficiency are only 9 among 51 electricity companies. And the technical and scale efficiency of KEPCO is 98.7% and 78.89%, respectively. This means that the inefficiency of KEPCO is caused by the scale inefficiency. The analysis shows that the employees should be decreased by 15% at minimum to get the 100% efficiency. The result suggests that KEPCO needs the structural reform to improve the efficiency.

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Designing Forward Markets for Electricity using Weather Derivatives (날씨파생상품을 이용한 전기선물시장 설계)

  • Yoo, Shiyong
    • Environmental and Resource Economics Review
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    • v.15 no.2
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    • pp.319-353
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    • 2006
  • This paper shows how weather derivatives can be used to hedge against the price risk and volume risk of purchasing relatively large amounts of electricity. Our specific approach to designing new contracts for electricity is to focus on the return over a summer season rather than on the daily levels of demand and price. It is shown that correct market signals can be preserved in a contract and the associated financial risk can be offset by weather options. The advantage of combining a forward contract with a weather derivative is that the high prices on hot days or when the temperature is high reflect the underlying high cost of producing power when the load is high and that the combined contract with a weather derivative substantially reduces the volatility of the return.

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Smart Card based Framework for Electricity AMR (스마트카드 기반의 전력원격검침 프레임워크)

  • Kang, Hwan-Soo
    • The Journal of the Korea Contents Association
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    • v.9 no.7
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    • pp.121-129
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    • 2009
  • Inspection of an Electrical Meter is an action of measuring power usage to charge electricity rates and Electricity AMR(Automatic Meter Reading) is a system to automatize the action. AMR has been highlighted because it can reduce metering cost by substituting an automatic system for personnel and strengthen customer service. In this paper, we proposed and developed a smart card based AMR framework SCEMS as an alternative to other current AMR Models. This proposed SCEMS uses a java card based multi-application smart card and supports customer service such as various meter rates according to electricity consumption pattern data per household and transaction data that are accumulated in a smart card. This research can be a solution to the problems such as diversity, heterogeneity, and complexity that environmental changes will cause soon to the power supply industry.

Feasibility of using biogas in a micro turbine for supplying heating, cooling and electricity for a small rural building

  • Rajaei, Gh.;Atabi, F.;Ehyaei, M.A.
    • Advances in Energy Research
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    • v.5 no.2
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    • pp.129-145
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    • 2017
  • In this study, the use of a micro gas turbine system using biogas to supply heating, cooling and electricity loads of a rural building located in rural area around Tehran has been studied. Initially, the amount of energy needed by the farmhouse was calculated and then the number of needed microturbines was determined. Accordingly, the amount of substances entering biogas digester as well as tank volume were determined. The results of this study showed that village house loads including electrical, heating and cooling and hot water loads can be supplied by using a microturbine with a nominal power of 30 kW and $33.5m^3/day$ of biogas. Digester tank and reservoir tank volumes are $67m^3$ and $31.2m^3$, respectively. The cost of electricity produced by this system is 0.446 US$/kWh. For rural area in Iran, this system is not compatible with micro gas turbine and IC engine system use urban natural gas due to low price of natural gas in Iran, but it can be compatible by wind turbine, photovoltaic and hybrid system (wind turbine& photovoltaic) systems.

Electricity Consumption Information Transmission Protocol with ID-based Key Distribution Method (ID 기반 키 분배 기법을 활용한 전력사용량 정보 전송 프로토콜)

  • Jung, Su-Young;Kwak, Jin
    • Journal of Advanced Navigation Technology
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    • v.16 no.4
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    • pp.709-716
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    • 2012
  • Recently, smartgrid has interested in enable to existing electrical grid to supplying stably and efficient energy management. Smartgrid environment using PLC is transmit PLC module collected electricity consumption information in each house from PLC module to server. This communication process can occurred security threats such as personal information leak of consumer, electrical grid paralysis. In this paper, we propose efficient electricity consumption information transmission protocol with ID-based key distribution method for respond to security threats.

A Proposal for Inverse Demand Curve Production of Cournot Model for Application to the Electricity Market

  • Kang Dong-Joo;Oh Tae-Kyoo;Chung Koohyung;Kim Balho H.
    • KIEE International Transactions on Power Engineering
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    • v.5A no.4
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    • pp.403-411
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    • 2005
  • At present, the Cournot model is one of the most commonly used theories to analyze the gaming situation in an oligopoly type market. However, several problems exist in the successful application of this model to the electricity market. The representative one is obtaining the inverse demand curve able to be induced from the relationship between market price and demand response. In the Cournot model, each player offers their generation quantity to obtain maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect the real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears over the long-term through statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as the trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

Independent Generation System Design for the Economic Management of Electrical Charging Stations (전기충전소의 경제적 운영을 위한 독립발전 시스템 설계)

  • Seo, Jin-Gyu;Kim, Kyu-Ho;Rhee, Sang-Bong
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.2
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    • pp.222-227
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    • 2015
  • This paper presents the optimal energy generation systems for economical EVs(Electric Vehicles) charging stations located in an island area. The system includes grid electricity, diesel generator and renewable energy sources of wind turbines and PV(Photovoltaic) panels. The independent generation system is designed with data resources such as annual average wind speed, solar radiation and the grid electricity price by calculating system cost under different structures. This sensitive analysis on the varying data resources allows for the configuration of the most economical generation system for charging stations by comparing initial capital, operating cost, NPC(Net Present Cost) and COE(Cost of Energy). Depending on the increase of the grid cost, the NPC variation of the most economical system which includes renewable energy generations and grid electricity can be smaller than those of other generation systems.