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Optimal scheduling of the conventional generating units for five dynamic test systems is percolated in this paper. When the valve point loading effect (VPE) is present, the system's fitness function becomes non-convex and nonlinear. This paper compares and contrasts among three types of wind profile formulations, namely linear, quadratic and cubic, which are used to calculate wind power from hourly wind speed to find the profile with the greatest penetration of wind power. Thereafter, the wind profiles in turns for the five test systems are used to execute dynamic economic dispatch. The optimization tool of the study was a unique hybrid algorithm created by combining the properties of the recently developed crow search algorithm (CSA) and JAYA. Results infer that maximum level of wind penetration was attained by linear wind profile and a fuel cost reduction of 8% was realized upon incorporation of the same. Also owing to its high penetration level, the least generation cost was obtained with linear wind profile when compared to quadratic and cubic ones. Furthermore, numerical results also claims that proposed hybrid CSAJAYA approach consistently yielded better quality solutions within minimum execution time without being affected by the dimension of the problem, thereby outperforming a long list of algorithms implemented for the study. [ABSTRACT FROM AUTHOR]

Demand side management (DSM) separates elastic and inelastic loads and reorganizes a distribution system's load demand model while reducing the overall cost of the operation. This is accomplished by shifting flexible loads to hours with lower utility costs per unit. In this study, a bi-level optimization technique is used to reduce the operating costs of a low voltage microgrid system that uses battery energy storage, renewable energy sources, and fossil fuel generators while running in grid-connected mode. The load model is reorganized at the first level of optimization according to the DSM involvement level. Thereafter, the restructured load demand models are taken into account, and distributed generator scheduling ideas are percolated for reducing the microgrid system's generating costs in the second level. The optimization tool for the study was a newly established hybrid swarm intelligence algorithm that has previously been utilized to solve a variety of power system optimization challenges. For various grid participation models and grid pricing schemes, both with and without taking into account DSM, the generating cost was reduced. When 10%, 20%, and 30% DSM involvement was taken into consideration, the numerical findings reveal 25%, 50%, and 70% reduction, respectively, in costs. [ABSTRACT FROM AUTHOR]

In a typical power system network, transmission losses are considered as one of the important parameters for economic operation. To concern this problem, researchers have proposed many techniques to minimize the transmission losses based on the cost benefit analysis which is associated with the optimal placement of the reactive power sources. In the present work, a novel technique, namely oppositional crow search algorithm (CSA), is proposed for Var planning by utilizing the fuzzy logic technique to determine capacitor placement positions. In this approach, fuzzy membership value is calculated based on the loss sensitivity factor of each bus of the test networks. Then, shunt capacitors placement positions are assigned to buses having the higher membership values. Once the capacitor placement positions are evaluated, the CSA and oppositional CSA are executed to obtain the optimal setting of transformer tap positions, reactive power generation of the generators, and magnitude of shunt capacitors placed at the weak nodes. The proposed method is performed on standard IEEE 30 and IEEE 57 bus networks, and the obtained results are compared with several other established methods for Var planning. From the obtained results, it is found that the proposed method shows better performance when compared to other techniques suggested in the literature in terms of reduced active power loss and system operating cost. [ABSTRACT FROM AUTHOR]

Utilities are no longer only concerned with distributing power at a low cost. Rather, utilities are focusing on lowering the hazardous chemicals discharged into the environment as a result of greater usage of traditional fossil-fuelled generators to meet rising electrical energy demand. This may be done by increasing the use of renewable energy sources (RES) to provide clean power, hence preventing fossil fuel depletion. This article evaluates the dynamic economic emission dispatch (DEED) approach for two large test systems. Two DEED approaches, the price-penalty factor (PPF) method and fractional programming (FP) method, were studied for each of the test systems, and a comparative analysis was conducted based on the balanced trade-off solution between the least amount of hazardous and toxic gases released into the environment and fuel cost. The current article provides a unique hybrid CSA-JAYA method as an optimization tool. According to numerical information acquired, FP emits fewer dangerous and poisonous compounds into the environment than the PPF technique. Because of the valve point loading effect, fitness functions are non-convex and non-linear, necessitating the use of a metaheuristic over traditional optimization methods. The proposed CSA-JAYA algorithm consistently beat a long list of algorithms in producing high-quality results. [ABSTRACT FROM AUTHOR]

This paper aims to minimize the generation cost of a low voltage (LV) grid-connected microgrid system using a novel hybrid whale optimization algorithm (WOA)- Sine cosine algorithm (SCA) optimization technique. Three different methods of electricity market prices are formulated in turns and the generation cost is evaluated for each method to sort out the best among them which yields the least generation cost of the same microgrid system. Both active and passive participation of grid are studied to acknowledge its importance. Numerical results show that the time of usage (TOU) method of electricity market pricing proved to be the most convenient and economic method for cost analysis of the system. The generation cost was at its maximum when the electricity price was a constant value. Also during the TOU method of electricity pricing, a 15% surge in the price was realized when the grid was passively participating in supplying power to the system. Figures and statistical data aids the fact that proposed hybrid WOASCA outperformed WOA in consistently providing a robust and superior quality result. [ABSTRACT FROM AUTHOR]

This paper formulates and solves a techno-economic planning problem of reactive power (VAR) in power transmission systems under loadings. The objective of the proposed research work is to minimize the combination of installation cost of reactive power sources, power losses and operational cost while satisfying technical constraints. Initially, the positions for the placement of reactive power sources are determined technically. Different cost components such as VAR generation cost, line charging cost etc. are then added in the total operating cost in a most economical way. Finally, the optimal parameter setting subjected to reactive power planning (RPP) is obtained by taking advantages of hybrid soft computing techniques. For the justification of the efficiency and efficacy of the proposed approach the entire work is simulated on two inter-regional transmission networks. To validate the robustness and ease of the soft computing techniques in RPP the responses of benchmark functions and statistical proof are provided simultaneously. [ABSTRACT FROM AUTHOR]

This paper aims to percolate energy management of microgrid systems by minimizing the generation cost of the same. Energy management of microgrid refers to the optimal sizing and scheduling of the distributed energy resources to reduce the generation cost and pollutant emission. A recently developed crow search algorithm (CSA) is implemented to execute the optimization. The proposed CSA imitates the crows' memory and tactics of hiding and chasing their food. Six renewable integrated microgrid test systems and a total of eighteen different cases are considered for this study. Various practical complexities such as valve point loading effect, combined economic–emission dispatch using price penalty factor method, modeling of the renewable energy sources and energy storage systems are taken into consideration for energy management of the microgrid systems. Results obtained are then compared to a number of different soft computing techniques such as genetic algorithm and particle swarm optimization and the likes to justify the effectiveness of the proposed algorithm. A statistical analysis, viz. Wilcoxon signed-rank test, is performed to prove the superiority of the proposed approach over the various other optimization techniques used in the paper. [ABSTRACT FROM AUTHOR]

Phasor measurement units (PMUs) are preferred for installation at weak buses in a power network. Therefore, the weak buses need to be located and the strategic locations of PMUs identified to ensure network observability. Thus, the primary aim of this work is to identify the placements of the maximum number of PMUs installed at the weak buses in the electrical network. The voltage collapse proximity indicator, line stability index, fast voltage stability index, and a new voltage stability indicator utilizing load flow measurement are used to determine the weak buses. A novel deterministic methodology based on a binary-integer linear programming model is then proposed to determine the optimal locations of PMUs. The effect of a single PMU outage considering the weak buses is also demonstrated. The effectiveness of the developed approach is tested and validated on the standard IEEE 14-, 118-, 300-, and New England 39-bus systems. The obtained results are also compared to those using different weak bus methodologies. [ABSTRACT FROM AUTHOR]