• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1821-1830
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• 2018

With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important component of home-based intelligent electricity. In this study, a multi-objective optimization model in an intelligent electricity environment is proposed based on economy and comfort. Firstly, the domestic consumer's load characteristics are analyzed, and the operating constraints of interruptible and transferable electrical appliances are defined. Then, constraints such as household electrical load, electricity habits, the correlation minimization electricity expenditure model of household appliances, and the comfort model of electricity use are integrated into multi-objective optimization. Finally, a continuous search multi-objective particle swarm algorithm is proposed to solve the optimization problem. The analysis of the corresponding example shows that the multi-objective optimization model can effectively reduce electricity costs and improve electricity use comfort.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.14-19
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• 2008

The paper presents an intelligent time series model to predict uncertain electricity market price in the deregulated industry environment. Since the price of electricity in a deregulated market is very volatile, it is difficult to estimate an accurate market price using historically observed data. The parameter of an intelligent time series model is obtained based on the simultaneous perturbation stochastic approximation (SPSA). The SPSA is flexible to use in high dimensional systems. Since prediction models have their modeling error, an error compensator is developed as compensation. The SPSA based intelligent model is applied to predict the electricity market price in the Pennsylvania-New Jersey-Maryland (PJM) electricity market.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.82-85
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• 2006

With the fast growing number of skyscrapers and large ultrahigh apartment complexes, the concerns on fire caused by electricity also grow. Among about 30,000 fires recorded annually, roughly one third of them are hewn to be caused by electricity. If one of such high and densely populated buildings or apartments catches a fire, the consequence can potentially be quite catastrophic. However, with the rapid development of the techniques in the fields of communications and computers, electric power distribution systems for such buildings and apartments have been largely digitalized in recent years. More detailed informations on the operating status are now available, which enables more sophisticated monitoring and early detection of potential fire caused by electricity. In this paper, we present an inference technique that can be used as one of the basic techniques in building intelligent distribution panel systems that can effectively monitor, prevent and detect the occurrence of fire caused by electricity. The technique can accommodate production rules in linguistic expressions on high abstraction levels. Fire finding strategies can be easily modified to provide more effective countermeasures. Simulation results show that inference capabilities and thus the capability of fire monitoring in power distribution panel systems can be significantly enhanced with our approach.

• Proceedings of the KIEE Conference
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• 2001.07e
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• pp.17-19
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• 2001

In this paper, we constitute H/W systems for the accurate control of DC servo motor. This H/W systems are designed by applying a simple genetic algorithm (SGA) to the robust $H_{\infty}$ control system and the intelligent Fuzzy control system of DC motor, respectively. To verify the effectiveness of the proposed systems, the characteristics of this systems are analysed and simulated.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.194-198
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• 2023

The current electricity networks will undergo profound changes in the years to come to be able to meet the growing demand for electricity, while minimizing the costs of consumers and producers, etc. The electricity network of tomorrow or even the intelligent « Smart Grids » network will be the convergence of two networks: the electricity network and the telecommunications network. In this context falls our work which aims to study the impact of the integration of energy decentralization into the electricity network. In this sense, we have implemented a new smart grid model where several coexisting suppliers can exchange information with consumers in real time. In addition, a new approach to energy distribution optimization has been developed. The simulation results prove the effectiveness of this approach in improving energy exchange and minimizing consumer purchase costs and line losses.

• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.19-24
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• 2014

Many people all over the world have been conducting a great deal of research to solve the problem of global warming since the great majority consider reduction of CO2 as the only solution for that. That is why the production and conservation of energy is thought to be highly crucial. while it is important to produce energy with the high efficiency, the efficient use of the energy is also important. This paper focused on the development of devices for the reducing electricity which is a primary energy source used in homes, shops, buildings, factories and so on. Also the objective of this paper is to develop the inference mechanism as the core component of the devices. Therefore, in this paper, we propose the inference algorithm for reducing the electricity consumption using SARIMA mode and present the feasibility of the procedure.

• Journal of the Korean Professional Engineers Association
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• v.42 no.6
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• pp.28-30
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• 2009

There is a proverb in Korea "Don't chase after another." It can be a right proverb in sometimes. However, usually it doesn't fit in these various society, information knowledge society. Modern society requires convergence technology. IBS (Intelligent Building System) requires knowledge of architecture field, electric field, communication field, and computation field. ITS (Intelligent Transport Systems) which is constructing in many cities requires various knowledge as engineering works, electricity, computation, communication and transportation. In the case of u-City, it requires technology of many fields as architecture, electricity, communication, engineering works, transportation, and computation. Anyone who wants to participate in u-City should study and acquire knowledge in various field. Otherwise, it must be failed because of lack of communication like as the Tower of Babel. U-City is not a portion of one field. Therefore, engineers in many fields should cooperate with each other to make u-city as the best product in the world.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.255-263
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• 2003

A multi-agent system designed to represent newly deregulated electricity markets in the USA is aimed at testing the capability of the multi-agent model to replicate the observed price behavior in the wholesale market and developing a smart business intelligence which quickly searches the optimum offer strategy responding to the change in market environments. Simulation results show that the optimum offer strategy is to withhold expensive generating units and submit relatively low offers when demand is low, regardless of firm size; the optimum offer strategy during a period of high demand is either to withhold capacity or speculate for a large firm, while it is to be a price taker a small firm: all in all, the offer pattern observed in the market is close to the optimum strategy. From the firm's perspective, the demand-side participation as well as the intense competition dramatically reduces the chance of high excess profit.

• Journal of the Korean Society of Industry Convergence
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• v.9 no.1
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• pp.79-86
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• 2006

In this study, we research and develope Intelligent Remote management controller. According to the load condition, we will apply various control techniques and plan high efficient Demand control. After development, According to the Demand Control, An electricity enterprisers will expect enlargement of equipment coefficient, elevation of back up load factor and reduction effect of equipment investment. On Customer side, They will expect reduction of electric fee, saving energy and variety of service choice.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.391-395
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• 2016

In the last few decades, global electricity consumption has dramatically increased and has become drastically fluctuating and uncertain causing blackout. Due to the unexpected peak electricity demand, we need significant electricity supply. The solutions to these problems are smart grid system which is envisioned as future power system. Smart grid system can reduce electricity peak demand and induce effective electricity consumption through various price policies, demand response (DR) control methodologies, and state-of-the-art smart equipments in order to optimize electricity resource usage in an intelligent fashion. Demand response (DR) is one of the key technologies to enable smart grid. In this paper, we propose greedy technique for demand response smart grid system. The proposed scheme focuses on minimizing electricity bills, preventing system blackout and sacrificing user convenience.