Evaluation of power system security and development of transmission pricing method

The electric power utility industry is presently undergoing a change towards the deregulated environment. This has resulted in unbundling of generation, transmission and distribution services. The introduction of competition into unbundled electricity services may lead system operation closer to its security boundaries resulting in smaller operating safety margins. The competitive environment is expected to lead to lower price rates for customers and higher efficiency for power suppliers in the long run. Under this deregulated environment, security assessment and pricing of transmission services have become important issues in power systems. This dissertation provides new methods for power system security assessment and transmission pricing. In power system security assessment, the following issues are discussed 1) The description of probabilistic methods for power system security assessment 2) The computation time of simulation methods 3) on-line security assessment for operation. A probabilistic method using Monte-Carlo simulation is proposed for power system security assessment. This method takes into account dynamic and static effects corresponding to contingencies. Two different Kohonen networks, Self-Organizing Maps and Learning Vector Quantization, are employed to speed up the probabilistic method. The combination of Kohonen networks and Monte-Carlo simulation can reduce computation time in comparison with straight Monte-Carlo simulation. A technique for security assessment employing Bayes classifier is also proposed. This method can be useful for system operators to make security decisions during on-line power system operation. This dissertation also suggests an approach for allocating transmission transaction costs based on reliability benefits in transmission services. The proposed method shows the transmission transaction cost of reliability benefits when transmission line capacities are considered. The ratio between allocation by transmission line capacity-use and allocation by reliability benefits is computed using the probability of system failure

2d Seiberg-like dualities with an adjoint matter

We consider the analogue of Kutasov-Schwimmer-Seiberg duality for two-dimensional N = (2, 2) U(k) gauge theory with one adjoint X with the superpotential Tr Xl+1 and with fundamental and anti-fundamental chiral multiplets. We give the evidences for the proposed dualities by analytically proving that the elliptic genus of dual pair coincides with each other. For some of the dual pairs flowing to the superconformal field theory, we show the nonperturbative truncation of the chiral ring. For the theory with one adjoint and N-f > k fundamental fields, we argue the theory exhibits mass gap.111Ysciescopu

Real-time response estimation of structural vibration with inverse force identification

This study aimed to develop a virtual sensing algorithm of structural vibration for the real-time identification of unmeasured information. First, certain local point vibration responses (such as displacement and acceleration) are measured using physical sensors, and the data sets are extended using a numerical model to cover the unmeasured quantities through the entire spatial domain in the real-time computation process. A modified time integrator is then proposed to synchronize the physical sensors and the numerical model using inverse dynamics. In particular, an efficient inverse force identification method is derived using implicit time integration. The second-order ordinary differential formulation and its projection-based reduced-order modeling is used to avoid two times larger degrees of freedom within the state space form. Then, the Tikhonov regularization noise-filtering algorithm is employed instead of Kalman filtering. The performance of the proposed method is investigated on both numerical and experimental testbeds under sinusoidal and random excitation loading conditions. In the experimental test, the algorithm is implemented on a single-board computer, including inverse force identification and unmeasured response prediction. The results show that the virtual sensing algorithm can accurately identify unmeasured information, forces, and displacements throughout the vibration model in real time in a very limited computing environment.Comment: 24 Pages, 15 Figures, 10 Table

Development of carbon-based adsorbent for separation of impurities such as siloxane and ammonia from land-fill gas

Land-fill gas or bio-gas is composed of large portion of methane and carbon dioxide, and small amount of impurities such as nitrogen, oxygen, hydrogen sulfide, siloxane and ammonia. These gases can be used as a gas-fuel after upgrading treatment. For the application of the land-fill gas and bio-gas as a fuel, we developed highly-performing carbon-based adsorbent which can separate siloxane and ammonia residue from these gases. It was quite necessary to consider the chemical properties of siloxane and ammonia for development of suitable adsorbent of each component. The siloxane can be polymerized in acidic or basic condition to form bulkier species which causes adsorbent deactivation and difficult regeneration. The ammonia gas is well known as basic molecules which have strong affinity to acidic species. In these reasons, we prepared neutral carbon materials by various methods for siloxane adsorption. In addition, we developed carbon-based basic ammonia-adsorbent by simple methods such as the chemical treatment of commercial activated carbon or the impregnation of organic molecules into the activated carbon. And then, adsorption-desorption isotherms and breakthrough curve of siloxane and ammonia were measured for thus synthesized adsorbents. Detail results for synthesis and the adsorption measurement of the studied adsorbents will be presented in the conference

Efficient Differential Trail Searching Algorithm for ARX Block Ciphers

In this paper, we suggest an advanced method searching for differential trails of block cipher with ARX structure. We use two techniques to optimize the automatic search algorithm of differential trails suggested by Biryukov et al. and obtain 2~3 times faster results than the previous one when implemented in block cipher SPECK

High-Precision Bootstrapping for Approximate Homomorphic Encryption by Error Variance Minimization

The Cheon-Kim-Kim-Song (CKKS) scheme (Asiacrypt\u2717) is one of the most promising homomorphic encryption (HE) schemes as it enables privacy-preserving computing over real (or complex) numbers. It is known that bootstrapping is the most challenging part of the CKKS scheme. Further, homomorphic evaluation of modular reduction is the core of the CKKS bootstrapping, but as modular reduction is not represented by the addition and multiplication of complex numbers, approximate polynomials for modular reduction should be used. The best-known techniques (Eurocrypt\u2721) use a polynomial approximation for trigonometric functions and their composition. However, all the previous methods are based on an indirect approximation, and thus it requires lots of multiplicative depth to achieve high accuracy. This paper proposes a direct polynomial approximation of modular reduction for CKKS bootstrapping, which is optimal in error variance and depth. Further, we propose an efficient algorithm, namely the lazy baby-step giant-step (BSGS) algorithm, to homomorphically evaluate the approximate polynomial, utilizing the lazy relinearization/rescaling technique. The lazy-BSGS reduces the computational complexity by half compared to the ordinary BSGS algorithm. The performance improvement for the CKKS scheme by the proposed algorithm is verified by implementation over HE libraries. The implementation results show that the proposed method has a multiplicative depth of 10 for modular reduction to achieve state-of-the-art accuracy, while the previous methods have depths of 11 to 12. Moreover, we achieve higher accuracies within a small multiplicative depth, for example, 93-bit within multiplicative depth 11

Bootstrapping on SEAL

We implement bootstrapping of RNS-CKKS on SEAL, a homomorphic encryption library released by Microsoft. And we measure the accuracy of encrypted data after bootstrapping for various parameters, which allows us to do more than thousands of homomorphic operations