• International journal of advanced smart convergence
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• v.10 no.4
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• pp.59-65
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• 2021

Electricity contributes to the development of the economy. Therefore, forecasting electricity demand plays an important role in the development of the electricity industry in particular and the economy in general. This study aims to provide a precise model for long-term electricity demand forecast in the residential sector by using three independent variables include: Population, Electricity price, Average annual income per capita; and the dependent variable is yearly electricity consumption. Based on the support of Multiple variable regression, the proposed method established a model with variables that relate to the forecast by ignoring variables that do not affect lead to forecasting errors. The proposed forecasting model was validated using historical data from Vietnam in the period 2013 and 2020. To illustrate the application of the proposed methodology, we presents a five-year demand forecast for the residential sector in Vietnam. When demand forecasts are performed using the predicted variables, the R square value measures model fit is up to 99.6% and overall accuracy (MAPE) of around 0.92% is obtained over the period 2018-2020. The proposed model indicates the population's impact on total national electricity demand.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1116-1120
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• 2014

With the shift of the energy paradigm from supply side management to demand side management, demand resource management and demand response plays an important role in the energy industry. As a consequency, a lot of researches have been done to provide a suitable demand response system. However, most of the demand response systems are based on the propriety products that cannot be modified. In this paper, we are proposing an automated demand response system using an EnerNOC provided open source code. We implemented the demand response server (VTN) and demand response client (VEN), and validated the OpenADR2.0 compliances using the open source code. We also used an Arduino microcontoller to demonstrate the communication schemes to control various devices.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.227-233
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• 2019

The study examines how business conditions, demand conditions and the role of government can influence the development of batik clusters in Pekalongan. This research is expected to be able to provide recommendations for both employers and local governments in order to help in optimizing the development of batik clusters. The research applied a quantitative research by engaging multiple regression analysis as an effort to understand the effect of the relationship between independent and dependent variables. In addition, this research was conducted in three largest batik clusters in Pekalongan, Indonesia namely batik cluster of Pasindon, Kauman, and Jenggot. These results indicate that business conditions positively affect the batik clusters development. It implies that the greater both business conditions in a cluster will lead the better the development. Indeed, the demand conditions also have an impact on the cluster development. This finding remarked that demand conditions are variable that need to be considered to development of batik cluster. Lastly, Government's role is confirmed that positively related to the Development of Batik Clusters. It implies that the more active the government's role in a cluster will have a good impact on the development of the cluster in certain area.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.110-112
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• 1992

Recently, increment of power demand is conspicuous, the necessity of demand side management is increased. here, we presented development of economic power demand controller again, we investigated the validity of peak demand control for customers and utilities.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1304-1310
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• 2015

In remote islands, due to expense of existing generation systems, installation of photovoltaic cells (PVs) and wind turbines has a chance of reducing generation costs. However, in island power systems, even short-term power fluctuations change the frequency of grids because of their small inertia constant. In order to compensate power fluctuations, the authors proposed the power consumption control of pumps which send water to tanks. The power control doesn’t affect water users’ convenience as long as tanks hold water. Based on experimental characteristics of a pump system, this paper shows methods to determine reference power consumption of the system with compensation for short-term PV fluctuations while satisfying water demand. One method uses a PI controller and the other method calculates reference power consumption from water flow reference. Simulations with a PV and a pump system are carried out to find optimum parameters and to compare the methods. Results show that both PI control method and water flow calculation method are useful for satisfying the water demand constraint. The water demand constraint has a little impact to suppression of the short-term power fluctuation in this condition.

• Journal of Information Technology Applications and Management
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• v.30 no.3
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• pp.1-13
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• 2023

Demand forecasting is a crucial task for an online retail where has to manage daily fresh foods effectively. Failing in forecasting results loss of profitability because of incompetent inventory management. This study investigated the optimal performance of different forecasting models for a very short shelf-life product. Demand data of 13 perishable items with aging of 210 days were used for analysis. Our comparison results of four methods: Trivial Identity, Seasonal Naïve, Feed-Forward and Autoregressive Recurrent Neural Networks (DeepAR) reveals that DeepAR outperforms with the lowest MAPE. This study also suggests the managerial implications by employing coefficient of variation (CV) as demand variation indicators. Three classes: Low, Medium and High variation are introduced for classify 13 products into groups. Our analysis found that DeepAR is suitable for medium and high variations, while the low group can use any methods. With this approach, the case can gain benefit of better fill-rate performance.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.36-41
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• 2016

In order to take advantage of the building as an energy demand resources, it requires automated systems that can respond to the demand response event. Load aggregator has been started business in Korea, research and development of building energy management and demand response systems that can support them has been active recently. However, the ratio of introducing automated real-time demand response systems is insufficient and the cost is also high. In this research, we developed a building energy management system and OpenADR protocol to participate in a demand response and then evaluated them in real building. OpenADR is a standard protocol for automated system through the event and reporting between load aggregator and demand-side. In addition, we also developed a web-based building control system to embrace different control systems and to reduce the peak load during demand response event. We verified that the result systems are working in a building and the reduced load is measured to confirm the demand response.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.171-178
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• 2019

Korea's shipbuilding industry is in a critical condition due to changes in the domestic and international environment. To overcome this crisis, preemptive development of products and technologies through prediction of new demand for ships is necessary. The goal of this research is to develop an artificial intelligence algorithm based on ship big data in order to predict new demand for ships. We intend to develop a big data analytics platform specialized in predicting ship demand and to utilize the forecast results of new ship demand through data analysis for planning/development of new products. By doing so, the development of sustainable new business models for equipment and equipment manufacturers will create new growth engines for shipyard and shipbuilders. Furthermore, it is expected that shipbuilders will be able to create business cases based on measurable performance, plan market-oriented products and services, and continuously achieve innovation that has high market destructive power.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.114-119
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• 2000

To estimate Agricultural water demand, many factors such as weather, type of crop, soil, cultivation method, crop coefficient and cultivation area, etc. must be considered. But it is not easy to estimate water demand in consideration of these many factors, which are variable according to a period and regional environment. So, this study provides estimation system for agricultural water demand(ESAD) in order to estimate water demand easily and accurately, calculates the present and future agricultural water demand and arranges all factors needed for water demand estimation. This study calibrates the application of estimation system for agricultural water demand with the data observed in the other Studies and analyzes agricultural water demand nationwide.

• Journal of Korean Society of Rural Planning
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• v.15 no.2
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• pp.97-110
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• 2009

The objective of this research was to develop a rural settlement demand model to analyze the determinants of settlement demand of urban residents. The point aimed at from model development was deriving stated preference of potential consumers towards rural settlement through setting a hypothetical market, and using settlement subsidy as a surrogate variable for price in the demand model. The adequate demand model deducted from hypothetical market data was derived from the basis of Hanemann's utility difference theory. In the rural settlement demand model, willingness to accept was expressed by a function of settlement subsidy. Data utilized in the analysis was collected from surveys of households nationwide. According to inferred results of the demand model, settlement subsidy had a significant influence on increasing demand for rural settlement. A significant common element was found among variables affecting demand increase through demand curve shift. The majority group of those with high rural settlement demand sought agricultural activity as their main motive, due to harsh urban environments aggravated by unstable job market conditions. Subsequently, restriction of income opportunities in rural areas does not produce an entrance barrier for potential rural settlers. Moreover, this argument could be supported by the common trend of those with high rural settlement demand generally tending to have low incomes. Due to such characteristics of concerned groups of rural settlement demand, they tended to react susceptibly to the subsidy provided by the government and local autonomous entities.