• New & Renewable Energy
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• v.4 no.1
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• pp.19-24
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• 2008

Energy environment has been changing rapidly such as high oil prices and the effectuation of UNFCCC. Oil prices have continued to rise and Dubai crude prices recorded about 90 dollars per barrel in 2007. In addition, the effectuation of UNFCCC will affect Korean economy and national energy security. Korea is the 9th $CO_2$ emissions country and takes the 1st place related to the increase rate of $CO_2$ emissions globally. Energy technology development is a key breakthrough and one of the optimal alternatives to cope with national energy security. In this study, we prioritize energy technologies in the sectors of high oil prices and UNFCCC related to ETRM for well focus R&D and efficiency of finite resources allocations. We applied to the extended method of AHP, fuzzy AHP reflecting the fuzziness of human thoughts and perception, for prioritizing the relative importance among energy technologies in ETRM for the first time as we make an energy policy in Korea.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.742-746
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• 2007

Energy environment has been changing rapidly such as high oil prices and the effectuation of UNFCCC. Oil prices have continued to rise and Dubai crude prices recorded 60 or 70 dollars per barrel in 2006. In addition, the effectuation of UNFCCC will affect Korean economy and national energy security. Korea is the 9th $CO_2$ emissions country and takes the 1st place related to the increase rate of $CO_2$ emissions globally. Energy technology development is a key breakthrough and one of the optimal alternatives to cope with national energy security. In this study, we prioritize energy technologies in the sectors of high oil prices and UNFCCC related to ETRM for well focus R&D and efficiency of finite resources allocations. We applied to the extended method of AHP, fuzzy AHP reflecting the fuzziness of human thoughts and perception, for prioritizing the relative importance among energy technologies in ETRM for the first time as we make an energy policy in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1571-1589
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• 2016

Nodes in MANETs are battery powered which makes energy an invaluable resource. In OLSR, MPRs are special nodes that are selected by other nodes to relay their data/control traffic which may lead to high energy consumption of MPR nodes. Therefore, employing energy efficient MPR selection mechanism is imperative to ensure prolonged network lifetime. However, misbehaving MPR nodes tend to preserve their energy by dropping packets of other nodes instead of forwarding them. This leads to huge energy loss and performance degradation of existing energy efficient MPR selection schemes. This paper proposes an energy efficient secure MPR selection (ES-MPR) technique that takes into account both energy and security metrics for MPR selection. It introduces the concept of 'Composite Eligibility Index' (CEI) to examine the eligibility of a node for being selected as an MPR. CEI is used in conjunction with willingness to provide distinct selection parameters for Flooding and Routing MPRs. Simulation studies reveal the efficiency of ES-MPR in selection of energy efficient secure and stable MPRs, in turn, prolonging the network operational lifetime.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.49-58
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• 2023

Renewable energy is not a new terminology. One of the fastest growing renewable energies is solar energy. The implementation of solar energy provides several advantages including the reduction of some of the environmental risks of fossil fuel consumption. This research elaborated the importance of the adaption of solar energy by developing a spatial decision support system (SDSS), while the Residential Solar Energy Adoption (RSEA) is an instantiation artifact in the form of an SDSS. As a GIS web-based application, RSEA allows stakeholders (e.g., utility companies, policymakers, service providers homeowners, and researchers) to navigate through locations on a map interactively. The maps highlight locations with high and low solar energy adoption potential that enables decision-makers (e.g., policymakers, solar firms, utility companies, and nonprofit organizations) to make decisions. A combined qualitative and quantitative methodological approach was used to evaluate the application's usability and user experience, and results affirmed the ability of the factors of utility, usefulness, and a positive user experience of the residential solar energy adoption of spatial decision support system (RSEA-SDSS). RSEA-SDSS in improving the decision-making process for potential various stakeholders, in utility, solar installations, policy making, and non-profit renewable energy domains.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.133-143
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• 2023

As drones (also known as UAV) become popular with advanced information and communication technology (ICT), they have been utilized for various fields (agriculture, architecture, and so on). However, malicious attackers with advanced drones may pose a threat to critical national infrastructures. Thus, anti-drone systems have been developed to respond to drone threats. In particular, remote identification data (R-ID)-based UAV detection and identification systems that detect and identify illegal drones with R-ID broadcasted by drones have been developed, and are widely employed worldwide. However, this R-ID-based UAV detection/identification system is vulnerable to security due to wireless broadcast characteristics. In this paper, we analyze the security vulnerabilities of DJI Aeroscope, a representative example of the R-ID-based UAV detection and identification system, and propose a replay-attack-based neutralization method using the analyzed vulnerabilities. To validate the proposed method, it is implemented as a software program, and verified against four types of attacks in real test environments. The results demonstrate that the proposed neutralization method is an effective neutralization method for R-ID-based UAV detection and identification systems.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.312-320
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• 2021

Increase in computational cost and exhaustive search can lead to more complexity and computational energy. Thus, there is need for effective and efficient scheme to reduce the complexity to achieve optimal energy utilization. This will improve the energy efficiency and enhance the proficiency in terms of the resources needed to achieve convergence. This paper primarily focuses on the development of hybrid swarm intelligence scheme for reducing the computational complexity in binary optimization. In order to reduce the complexity, both artificial bee colony (ABC) and particle swarm optimization (PSO) have been employed to effectively minimize the exhaustive search and increase convergence. First, a new approach using ABC and PSO has been proposed and developed to solve the binary optimization problem. Second, the scout for good quality food sources is accomplished through the deployment of PSO in order to optimally search and explore the best source. Extensive experimental simulations conducted have demonstrate that the proposed scheme outperforms the ABC approaches for reducing complexity and energy consumption in terms of convergence, search and error minimization performance measures.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6B
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• pp.233-248
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• 2008

Advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks (WSNs). There are numerous applications for wireless sensor networks, and security is vital for many of them. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the lack of infrastructure, all of which impose unique security challenges and make innovative approaches desirable. In this paper, we present a survey on security issues in wireless sensor networks. We address several network models for security protocols in WSNs, and explore the state of the art in research on the key distribution and management schemes, typical attacks and corresponding countermeasures, entity and message authentication protocols, security data aggregation, and privacy. In addition, we discuss some directions of future work.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.528-537
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• 2008

Primary frequency control(PFC) has the ability to regulate short period random variations of frequency during normal operation conditions and also to respond rapidly to emergencies. However, during the past decade, numerous significant sized blackouts occurred worldwide that resulted in serious economic losses. Therefore, the conclusion has been reached that the ability of the current PFC to meet an emergency is poor, and security of power systems should be improved. An alternative to enhance the PFC and thus security is to store excessive amounts of energy during off-peak load periods in efficient energy storage systems for substituting the primary control reserve. In this sense, superconducting magnetic energy storage(SMES) in combination with a static synchronous compensator(STATCOM) is capable of supplying power systems with both active and reactive powers simultaneously and very rapidly, and thus is able to enhance the security dramatically. In this paper, a new concept of PFC based on incorporating a STATCOM-SMES is presented. A complete detailed model is proposed and a new control scheme is designed, comprising an enhanced frequency control scheme, and a fully decoupled current control strategy in d-q coordinates with a novel controller to prevent dc bus capacitors voltage drift/imbalance. The performance of the proposed control schemes is validated through digital simulation carried out using MATLAB/Simulink.