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Optimal Allocation of Distributed Solar Photovoltaic Generation in Electrical Distribution System under Uncertainties

  • Verma, Ashu;Tyagi, Arjun;Krishan, Ram
    • Journal of Electrical Engineering and Technology
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    • v.12 no.4
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    • pp.1386-1396
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    • 2017
  • In this paper, a new approach is proposed to select the optimal sitting and sizing of distributed solar photovoltaic generation (SPVG) in a radial electrical distribution systems (EDS) considering load/generation uncertainties. Here, distributed generations (DGs) allocation problem is modeled as optimization problem with network loss based objective function under various equality and inequality constrains in an uncertain environment. A boundary power flow is utilized to address the uncertainties in load/generation forecasts. This approach facilitates the consideration of random uncertainties in forecast having no statistical history. Uncertain solar irradiance is modeled by beta distribution function (BDF). The resulted optimization problem is solved by a new Dynamic Harmony Search Algorithm (DHSA). Dynamic band width (DBW) based DHSA is proposed to enhance the search space and dynamically adjust the exploitation near the optimal solution. Proposed approach is demonstrated for two standard IEEE radial distribution systems under different scenarios.

Discrete Optimization of Plane Frame Structures Using Genetic Algorithms (유전자 알고리즘을 이용한 뼈대구조물의 이산최적화)

  • 김봉익;권중현
    • Journal of Ocean Engineering and Technology
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    • v.16 no.4
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    • pp.25-31
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    • 2002
  • This paper is to find optimum design of plane framed structures with discrete variables. Global search algorithms for this problem are Genetic Algorithms(GAs), Simulated Annealing(SA) and Shuffled Complex Evolution(SCE), and hybrid methods (GAs-SA, GAs-SCE). GAs and SA are heuristic search algorithms and effective tools which is finding global solution for discrete optimization. In particular, GAs is known as the search method to find global optimum or near global optimum. In this paper, reinforced concrete plane frames with rectangular section and steel plane frames with W-sections are used for the design of discrete optimization. These structures are designed for stress constraints. The robust and effectiveness of Genetic Algorithms are demonstrated through several examples.

A hybrid tabu-simulated annealing heuristic algorithm for optimum design of steel frames

  • Degertekin, S.O.;Hayalioglu, M.S.;Ulker, M.
    • Steel and Composite Structures
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    • v.8 no.6
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    • pp.475-490
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    • 2008
  • A hybrid tabu-simulated annealing algorithm is proposed for the optimum design of steel frames. The special character of the hybrid algorithm is that it exploits both tabu search and simulated annealing algorithms simultaneously to obtain near optimum. The objective of optimum design problem is to minimize the weight of steel frames under the actual design constraints of AISC-LRFD specification. The performance and reliability of the hybrid algorithm were compared with other algorithms such as tabu search, simulated annealing and genetic algorithm using benchmark examples. The comparisons showed that the hybrid algorithm results in lighter structures for the presented examples.

Search for broadband extended gravitational-wave emission bursts in LIGO S6 in 350-2000 Hz by GPU acceleration

  • van Putten, Maurice H.P.M.
    • The Bulletin of The Korean Astronomical Society
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    • v.42 no.1
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    • pp.37.3-37.3
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    • 2017
  • We present a novel GPU accelerated search algorithm for broadband extended gravitational-wave emission (BEGE) with better than real-time analyis of H1-L1 LIGO S6 data. It performs matched filtering with over 8 million one-second duration chirps. Parseval's Theorem is used to predict the standard deviation ${\sigma}$ of filter output, taking advantage of near-Gaussian LIGO (H1,L1)-data in the high frequency range of 350-2000 Hz. A multiple of ${\sigma}$ serves as a threshold to filter output back to the central processing unit. This algorithm attains 80% efficiency, normalized to the Fast Fourier Transform (FFT). We apply it to a blind, all-sky search for BEGE in LIGO data, such as may be produced by long gamma-ray bursts and superluminous supernovae. We report on mysterious features, that are excluded by exact simultaneous occurrance. Our results are consistent with no events within a radius of about 20 Mpc.

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Chaos Search Method for Reconfiguration Problem in Unbalanced Distribution Systems (불평형 배전계통의 선로 재구성문제를 위한 카오스 탐색법 응용)

  • Rhee, Sang-Bong;Kim, Kyu-Ho;Lee, Yu-Jeong;You, Seok-Ku
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.403-405
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    • 2003
  • In this paper, we applied a chaos search method for feeder reconfiguration problem in unbalanced distribution system. Chaos method, in optimization problem, searches the global optimal solution on the regularity of chaotic motions and more easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos search method applied to the IEEE 13 unbalanced test feeder systems, and the test results indicate that it is able to determine appropriate switching options for global optimum configuration.

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Distributed Database Design using Evolutionary Algorithms

  • Tosun, Umut
    • Journal of Communications and Networks
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    • v.16 no.4
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    • pp.430-435
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    • 2014
  • The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

Performance Analysis of Layer Pruning on Sphere Decoding in MIMO Systems

  • Karthikeyan, Madurakavi;Saraswady, D.
    • ETRI Journal
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    • v.36 no.4
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    • pp.564-571
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    • 2014
  • Sphere decoding (SD) for multiple-input and multiple-output systems is a well-recognized approach for achieving near-maximum likelihood performance with reduced complexity. SD is a tree search process, whereby a large number of nodes can be searched in an effort to find an estimation of a transmitted symbol vector. In this paper, a simple and generalized approach called layer pruning is proposed to achieve complexity reduction in SD. Pruning a layer from a search process reduces the total number of nodes in a sphere search. The symbols corresponding to the pruned layer are obtained by adopting a QRM-MLD receiver. Simulation results show that the proposed method reduces the number of nodes to be searched for decoding the transmitted symbols by maintaining negligible performance loss. The proposed technique reduces the complexity by 35% to 42% in the low and medium signal-to-noise ratio regime. To demonstrate the potential of our method, we compare the results with another well-known method - namely, probabilistic tree pruning SD.

On Near Subtraction Semigroups (Near Subtraction Semigroups에 관한 연구)

  • Yon Yong-Ho;Kim Mi-Suk;Kim Mi-Hye
    • Proceedings of the Korea Contents Association Conference
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    • 2003.05a
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    • pp.406-410
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    • 2003
  • B. M. Schein([1]) considered systems of the form (${\Phi}$; ${\circ}$,-), where ${\Phi}$ is a set of functions closed under the composition "${\circ}$" of functions and the set theoretic subtraction "-". In this structure, (${\Phi}$; ${\circ}$) is a function semigroup and (${\Phi}$;-) is a subtraction algebra in the sense of [1]. He proved that every subtraction semigroup is isomorphic to a difference semigroup of invertible functions. Also this structure is closely related to the mathematical logic, Boolean algebra, Bck-algera, etc. In this paper, we define the near subtraction semigroup as a generalization of the subtraction semigroup, and define the notions of strong for it, and then we will search the general properties of this structure, the properties of ideals, and the application of it.

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Estimating Coverage of the Web Search Services Using Near-Uniform Sampling of Web Documents (균등한 웹 문서 샘플링을 이용한 웹 검색 서비스들의 커버리지 측정)

  • Jang, Sung-Soo;Kim, Kwang-Hyun;Lee, Joon-Ho
    • The KIPS Transactions:PartD
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    • v.15D no.3
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    • pp.305-312
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    • 2008
  • Web documents with useful information are widely available on the internet and they are accessible with web search service. For this reason, web search services study better ways to collect more web documents, but have a difficulty figuring out the coverage of these web pages. This paper is intended to find ways to evaluate the current coverage assessment methods and suggest more effective coverage assessment technique that is, sampling internet web documents equally, monitoring how they are classified on web search services, in an attempt to assess both absolute and relative coverage of the web search engines. The paper also presents the comparison among Korean web search services using the suggested methods.the absolute and relative coverage was highest in Google followed by Naver and Empas. The result is expected to help estimating coverage of web search services.

Efficient and Privacy-Preserving Near-Duplicate Detection in Cloud Computing (클라우드 환경에서 검색 효율성 개선과 프라이버시를 보장하는 유사 중복 검출 기법)

  • Hahn, Changhee;Shin, Hyung June;Hur, Junbeom
    • Journal of KIISE
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    • v.44 no.10
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    • pp.1112-1123
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    • 2017
  • As content providers further offload content-centric services to the cloud, data retrieval over the cloud typically results in many redundant items because there is a prevalent near-duplication of content on the Internet. Simply fetching all data from the cloud severely degrades efficiency in terms of resource utilization and bandwidth, and data can be encrypted by multiple content providers under different keys to preserve privacy. Thus, locating near-duplicate data in a privacy-preserving way is highly dependent on the ability to deduplicate redundant search results and returns best matches without decrypting data. To this end, we propose an efficient near-duplicate detection scheme for encrypted data in the cloud. Our scheme has the following benefits. First, a single query is enough to locate near-duplicate data even if they are encrypted under different keys of multiple content providers. Second, storage, computation and communication costs are alleviated compared to existing schemes, while achieving the same level of search accuracy. Third, scalability is significantly improved as a result of a novel and efficient two-round detection to locate near-duplicate candidates over large quantities of data in the cloud. An experimental analysis with real-world data demonstrates the applicability of the proposed scheme to a practical cloud system. Last, the proposed scheme is an average of 70.6% faster than an existing scheme.