No abstract

Motivated by the hunting strategies of cheetahs, this paper proposes a nature-inspired algorithm called the cheetah optimizer (CO). Cheetahs generally utilize three main strategies for hunting prey, i.e., searching, sitting-and-waiting, and attacking. These strategies are adopted in this work. Additionally, the leave the pray and go back home strategy is also incorporated in the hunting process to improve the proposed framework's population diversification, convergence performance, and robustness. We perform intensive testing over 14 shifted-rotated CEC-2005 benchmark functions to evaluate the performance of the proposed CO in comparison to state-of-the-art algorithms. Moreover, to test the power of the proposed CO algorithm over large-scale optimization problems, the CEC2010 and the CEC2013 benchmarks are considered. The proposed algorithm is also tested in solving one of the well-known and complex engineering problems, i.e., the economic load dispatch problem. For all considered problems, the results are shown to outperform those obtained using other conventional and improved algorithms. The simulation results demonstrate that the CO algorithm can successfully solve large-scale and challenging optimization problems and offers a significant advantage over different standards and improved and hybrid existing algorithms. Note that the source code of the CO algorithm is publicly available at https://www.optim-app.com/projects/co.

This paper presents a systematic procedure for partitioning smart distribution systems into supply-sufficient microgrids. Firstly, renewable distributed generations (DGs) are optimally allocated in the distribution system. A multiobjective performance index including voltage profile and energy losses indices is utilized in this problem as the objective function. Two alternative control approaches of future smart grids including on load tap changer (OLTC) control and adaptive power factor control (PFc) are assessed to maximize potential benefits and increase the penetration level of DGs. Then, optimal allocation of protection devices and energy storage systems (ESSs) for constructing supply-sufficient microgrids is presented for a feeder equipped with capacity-constrained DGs. To this end, two different optimization problems are formulated and proper indices are developed for minimizing power exchange between microgrids and minimizing generation-load imbalance within microgrids. Finally, test results of the proposed models on 33-bus IEEE radial distribution system are presented and discussed.

No abstract

Increasing penetration of distributed generation (DG), may be interesting from several points of view, but it raises important challenges about distribution system operation and planning practices. To optimal allocation of DG, which play an important role in construction of microgrids, the benefits and risks should be qualified and quantified. This paper introduces several probabilistic indices to evaluate the potential operational effects of increasing penetration of renewable DG units such as wind power and photovoltaic on rural distribution network with the aid of evaluating technical benefits and risks trade-offs. A probabilistic generation-load model is suggested to calculate these indices which combine a large number of possible operating conditions of renewable DG units with their probabilities. Temporal and annual indices of voltage profile and line flow related attributes such as Interest Voltage Rise (IVR), Risky Voltage Rise (RVR), Risky Voltage Down (RVD), Line Loss Reduction (LLR), Line Loss Increment (LLI) and Line overload flow (LOF) are introduced using probability and expected values of their occurrence. Also, to measure the overall interests and risks of installing DG, composite indices are presented. The implementation of the proposed framework in a 4-bus and IEEE 33-bus radial distribution systems shows the effectiveness of the benefits and risks assessment technique with the proposed metrics.

No abstract

Increase in doubly fed induction generator (DFIG)-based wind farms degrades the short-term frequency regulation of power systems. However, such wind farms may have large amount of kinetic energy which can be rapidly injected into the power system to support system frequency by using an appropriate supplementary control loop. This study first analyses the impacts of DFIGs and their supplementary loop on power system short-term frequency regulation. Then, the average power system frequency model is modified to include the participation of wind farms in frequency control. Moreover, a new method is proposed to derive an analytical expression for minimum frequency of a power system, as an important index of frequency regulation, after a power imbalance occurrence. This analytical expression provides a tool for better insight into frequency behaviour of power systems with high levels of wind generation. The results of the analysis are verified by simulation of the nine-bus test system, using MATLAB/SIMULINK.

No abstract