The investigation of stable M/G/1 and queue with balking, characterized by a Poisson prospective arrival process and i.i.d. general (G) service periods, is being done to examine linkages between discrete maximum entropy (ME) distribution (i.e., the derived solutions resulting from the Lagrangian optimization of the proposed entropy function under prior and main constraints conditions) judgements and Markov chains. Increasing moment limitations are expected to keep exposing distinct state probability for single and many server queues with new information theoretic distributional structures. In this setting, the stationary queue length distributions (QLDs) of the queues-specifically, the generalized discrete Half Normal (GdHN) distributions-are more precisely inferred. The underlying service time distribution function and the cumulative service time distribution function both describe the M/GE/1 queue with balking (by balking, we mean the situation when customers refuse to join a queue) bearing the GdHN ME. Significant applications of queuing theory have been demonstrated to reveal the potential role of queueing techniques to energy works and other related fields. Fundamentally, the sky is open for revolutionary advancements by employing novel emerging queueing techniques in energy works and many unexplored disciplines.
Three-phase static Synchronous Series Compensators (SSSC) are being used to resolve the non-uniform loading of transmission lines in an existing interconnected system by controlling the flow of power. Implementation of a three-phase SSSC is complex owing to its intricate control structure, complex PWM techniques and its requirement of a coupling transformer to be connected to the grid. This paper presents a complete implementation of a single-phase cascaded converter topology for the SSSC. The proposed system is implemented by IGBTs based Voltage Source Converters (VSC) which consists of 5 H-bridge modules per phase connected directly in series with the line without a coupling transformer. A simplified direct voltage control system employing a PID regulator is implemented using Pulse Width Modulation (PWM) technique to control the magnitude of the injected voltage. The dynamic performance of the SSSC is investigated on PSCAD/EMTDC simulation tool in inductive operation mode and the effect of the variation of the injected voltage level on power flow is observed. For the synchronization of SSSC with the grid, SOGI-PLL is implemented which provides a better steady-state and dynamic performance. It is seen that SOGI-PLL provides accurate tracking of the grid parameters even in the presence of harmonics and distortion.
In this study, short-term load forecasting of the Gebze region in Turkey was carried out using Machine Learning-based prediction algorithms such as Artificial Neural Networks, Decision Tree, Support Vector Regression and K-Nearest Neighbor. Load demand and weather variables such as temperature, humidity, pressure and wind speed are used as input variables in the forecast models. Error metrics such as Mean Absolute Error, Mean Squared Error, Mean Absolute Percentage Error and R-squared were used to control the prediction success of the proposed algorithms and models. As a result, the predictions made with all the proposed algorithms are within reliable and acceptable ranges, and Support Vector Regression algorithm showed the best performance with an error of 1.1%.
This study investigates linear parameter varying power system stabilizer modeling and controller synthesis frameworks in single machine infinite bus power systems with synchronous generator rotor oscillations by focusing on the generator moment of inertia term. The uncertain power system stabilizer dynamics is analyzed for its fluctuating components and is formulated as a linear parameter varying model, with the measurable parameter being the generator rotor inertia term, representing the parametric and corresponding global system uncertainty. The corresponding linear parameter varying power system stabilizer plant model is utilized to synthesize respective controllers both to stabilize the actual power system stabilizer and to achieve superior transient and steady state responses for all system dynamics in the same convex hull of the generator inertia fluctuations. The controller synthesis framework used the corresponding linear fractional transformation representation to achieve the robust performance of the time-varying power system, i.e., a perfect tracking to a zero reference or a perfect disturbance rejection. The linear parameter varying power system stabilizer numerical model analysis and controller synthesis results clearly demonstrate the efficacy of the proposed framework for superior generator oscillation magnitude and duration results under dynamical parameter variations.
