• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.98-107
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• 2015

Hierarchical constraints and constraint satisfaction were analyzed in order to solve the problem of conflict detection in collaborative design. The constraints were divided into two sets: one set consisted of known constraints and the other of unknown constraints. The constraints of the two sets were detected with corresponding methods. The set of the known constraints was detected using an interval propagation algorithm, a back propagation (BP) neural network was proposed to detect the set with the unknown constraints. An immune algorithm (IA) was utilized to optimize the weights and the thresholds of the BP neural network, and the steps were designed for the optimization process. The results of the simulation indicated that the BP neural network that was optimized by IA has a better performance in terms of convergent speed and global searching ability than a genetic algorithm. The constraints were described using the eXtensible Markup Language (XML) for computers to be able to automatically recognize and establish the constraint network. The implementation of the conflict detection system was designed based on constraint satisfaction. A wind planetary gear train is taken as an example of collaborative design with a conflict detection system.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.584-587
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• 1997

In this paper, we present a transmission constraints modeling of carrier relay signal over ATM network. Since teleprotection system, which is used for protecting power transmission lines using telecommunications, has strict transmission delay constraints, it is a important problem to transmit teleprotection signals in future utilities' ATM networks when utilites' communications are integrated. Therefore, we considered the transmission constraints of carrier relay signal over ATM network and the transmission model system.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.59-61
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• 2003

This paper describes the market power evaluation of generator due to network constraints. When the specified generator must be dispatched to meet the network requirements, that generator will be able to have market power. For identifying this, we formulate optimization problem to determine whether the power system requirements can be met without the specified generator, and evaluate its possible market power exertion from the solution.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.494-499
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• 2007

In this paper, we have investigated how transmission network constraints can be modeled in an electricity market equilibrium model. Under Cournot competition assumption, a game model is set up considering transmission line capacity constraints. Based on locational marginal pricing principle, market clearing is formulated as a total consumers# benefit maximization problem, and then converted to a conventional optimal power flow (OPF) formulation with a linearized transmission model. Using market clearing formulation, best response analysis is formulated and, finally, Nash equilibrium is formulated. In order for illustration, a numerical study for a four node system with two generating firms and two loads are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1379-1397
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• 2013

We consider a system where a licensed radio spectrum is shared by multiple primary users(PUs) and secondary users(SUs). As the spectrum of interest is licensed to primary network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to PUs. For this system, we study the joint beamforming and power allocation problem via game theory in this paper. The problem is formulated as a non-cooperative beamforming and power allocation game, subject to the interference constraints of PUs as well as the peak transmission power constraints of SUs. We design a joint beamforming and power allocation algorithm for maximizing the total throughput of SUs, which is implemented by alternating iteration of minimum mean square error based decision feedback beamforming and a best response based iterative power allocation algorithm. Simulation results show that the algorithm has better performance than an existing algorithm and can converge to a locally optimal sum utility.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.215-222
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• 2013

Electrical power distribution systems are critical links between the utility and customer. In general, power distribution systems have unbalanced feeders due to the unbalanced loading. The devices that dependent on balanced three phase supply are affected by the unbalanced feeders. This necessitates the balancing of feeders. The main objective of reconfiguration is to balance the loads among the phases subject to constraints such as load flow equations, capacity and voltage constraints and to reduce the real power loss, while subject to a radial network structure in which all loads must be energized. Therefore, the distribution system reconfiguration problem has been viewed as multi-objective problem. In this paper, the hybrid heuristic algorithm has been used for reconfiguration, which is the combination of fuzzy and greedy algorithms. The purpose of the introduction of greedy is to refrain the searching for the period of phase balancing. The incorporation of fuzzy helps to take up more objectives amid phase balancing in the searching. The effectiveness of the proposed method is demonstrated through modified IEEE 33 bus and modified IEEE 125 bus radial distribution system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.12
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• pp.586-591
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• 2005

This paper presents a method of minimizing of generation cost on individual electrical power utility. The method is based on the Economic Dispatch (ED) and linear Available Transfer Capability (ATC). The economic dispatch redistributes the total load to individual units to minimize the generation cost without transmission network constraints. The proposed method is implemented using ATC calculated from Power Transfer Distribution Factor (PTDF) for the transmission network constraints. The performance of the proposed method has been tested for the IEEE-30 bus system. It has also been observed that the results of the proposed method is compared with that of optimal power flow.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.745-753
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• 2007

The wireless medium is known to be time-varying which could affect and result to a poor network's performance. As a solution, an opportunistic scheduling and power control algorithm based on IEEE 802.11 MAC protocol is proposed in this paper. The algorithm opportunistically exploits the channel condition for better network performance. Convex optimization problems were also formulated i.e. the overall transmission power of the system is minimized and the "net-utility" of he system is maximized. We have proven that an optimal transmission power vector may exist, satisfying the maximum power and SINR constraints at all receivers, thereby minimizing overall transmission power and maximizing net-utility of the system.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.257-266
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• 2012

A decode-and-forward two-way relay system benefits from orthogonal frequency division multiplexing (OFDM) and relay transmission. In this paper, we consider a decode-and-forward two-way relay system over OFDMwith two strategies: A joint subcarrier matching algorithm and a power allocation algorithm operating with a total power constraint for all subcarriers. The two strategies are studied based on average capacity using numerical analysis by uniformly allocating power constraints for each subcarrier matching group. An optimal subcarrier matching algorithm is proposed to match subcarriers in order of channel power gain for both transmission sides. Power allocation is defined based on equally distributing the capacity of each hop in each matching group. Afterward, a modified water-filling algorithm is also considered to allocate the power among all matching groups in order to increase the overall capacity of the network. Finally, Monte Carlo simulations are completed to confirm the numerical results and show the advantages of the joint subcarrier matching, power allocation and water filling algorithms, respectively.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.8
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• pp.379-384
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• 2002

In the competitive electricity market, various pricing methods are developed and practiced in many countries. Among these pricing methods, marginal loss factor(MLF) can be applied to reflect the marginal cost of network losses. For the calculation of MLF, power flow method has been used to calculate system loss deviation. However, this power flow method shows some shortcomings such as necessity of regional reference node, and absence of an ability to consider network constraints like line congestion, voltage limit, and generation output limit. The former defect might affects adversely to the equity of market participants and the latter might generate an inappropriate price signals to customers and generators. To overcome these defects, the utilization of optimal power flow(OPF) is suggested to get the system loss deviation in this paper. 30-bus system is used for the case study to compare the MLF results by the power flow and the OPF method for 24-hour dispatching and pricing, Generator payment and customer charge are compared with these two methods also. The results show that MLF by OPF reflects the power system condition more faithfully than that of by the conventional power flow method