Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm

Optimal scheduling of distributed energy resources (DERs) of a low-voltage utility-connected microgrid system is studied in this paper. DERs include both dispatchable fossil-fueled generators and non-dispatchable renewable energy resources. Various real constraints associated with adjustable loads, charging/discharging limitations of battery, and the start-up/shut-down time of the dispatchable DERs are considered during the scheduling process. Adjustable loads are assumed to the residential loads which either operates throughout the day or for a particular period during the day. The impact of these loads on the generation cost of the microgrid system is studied. A novel hybrid approach considers the grey wolf optimizer (GWO), sine cosine algorithm (SCA), and crow search algorithm (CSA) to minimize the overall generation cost of the microgrid system. It has been found that the generation costs rise 50% when the residential loads were included along with the fixed loads. Active participation of the utility incurred 9–17% savings in the system generation cost compared to the cases when the microgrid was operating in islanded mode. Finally, statistical analysis has been employed to validate the proposed hybrid Modified Grey Wolf Optimization-Sine Cosine Algorithm-Crow Search Algorithm (MGWOSCACSA) over other algorithms used

An approach to solve OPF problems using a novel hybrid whale and sine cosine optimization algorithm

Nowadays, improvement in power system performance is essential to obtaine economic and technical benifits. To achieve this, optimize the large number of parameters in the system based on optimal power flow(OPF). For solving OPF problem efficiently, it needs robust and fast optimization techniques. This paper proposes the application of a newly developed hybrid Whale and Sine Cosine optimization algorithm to solve the OPF. It has been implemented for optimization of the control variables. The reduction of true power generation cost, emission, true power losses, and voltage deviation are considered as different objectives. The hybrid Whale and Sine Cosine optimization is validated by solving OPF problem with various intentions using IEEE30 bus system. To varidate the proposed technique, the results obtained from this are compared with other methods in the literature. The robustness achieved with the proposed algorithm has been analyzed for the considered OPF problem using statistical analysis and whisker plots

Solving multi-objective economic emission dispatch of a renewable integrated microgrid using latest bio-inspired algorithms

The concept of a microgrid system, when put in simple words, is a small scale generation and deployment of power to a small geographical area in order to avoid transmission losses and maintain an uninterrupted power supply. It has been a mandatory protocol to implement the available renewable energy sources (RES) in order to minimize the emission of harmful pollutants to the atmosphere from the combustion of the fossil fuels. Economic load dispatch (ELD) deals with the optimal sizing of the distributed energy resources (DERs) by minimizing the fuel costs. Emission dispatch does the optimal sizing of the DERs sources by minimizing the amount of pollutants released in the atmosphere. A multi-objective Combined Economic-Emission Dispatch (CEED) does the optimal DER sizing providing a compromised solution of minimizing both the fuel costs and pollutants emission. This paper performs all ELD, emission dispatch and CEED on an islanded and renewable-integrated microgrid separately using a recently developed novel Whale optimization Algorithm (WOA). Four various scenarios of load sharing among the DERs are studied. The results are then compared with other recently developed bio inspired algorithms to corroborate the effectiveness of the proposed technique. Further statistical analysis such as ANOVA test and Wilcoxon signed rank test are performed to prove the superiority of the proposed approach over the various other optimization techniques used. Keywords: Combined economic emission dispatch, Penalty factor, Microgrid, Symbiotic organisms search, Grey wolf optimization, Particle swarm optimization, Differential evolution, Whale optimization algorith

Intelligent Demand Side Management for Exhaustive Techno-Economic Analysis of Microgrid System

In a typical microgrid (MG) structure, the requisite of load varies from hour to hour. On the basis of the rise and fall of the load demand curve, the power system utilities fix the rate of electric power at different times of the day. This process is known as time-of-usage (TOU)-based pricing of electricity. The hourly basis load demand can be categorized into elastic hourly load demand and inelastic hourly load demand. For the duration of the peak hours, when the utility charges more, the elastic loads are shifted to low demand hours by the demand side management (DSM) to save the cost. This rebuilds the total demand model on the pillars of demand price elasticity. Keeping in view the fact that the total load in an hour in an MG structure consists of 10% to 40% of elastic loads, the paper proposes an intelligence-technique-based DSM to achieve reduction in the overall cost of using loads in an MG structure. Seven different cases are studied which cover diverse grid participation and electricity market pricing strategies, including DSM programs. The results obtained for all the MGs showcase the applicability and appropriateness of using the proposed DSM strategy in terms of cost savings

Intelligent Demand Side Management for Exhaustive Techno-Economic Analysis of Microgrid System

In a typical microgrid (MG) structure, the requisite of load varies from hour to hour. On the basis of the rise and fall of the load demand curve, the power system utilities fix the rate of electric power at different times of the day. This process is known as time-of-usage (TOU)-based pricing of electricity. The hourly basis load demand can be categorized into elastic hourly load demand and inelastic hourly load demand. For the duration of the peak hours, when the utility charges more, the elastic loads are shifted to low demand hours by the demand side management (DSM) to save the cost. This rebuilds the total demand model on the pillars of demand price elasticity. Keeping in view the fact that the total load in an hour in an MG structure consists of 10% to 40% of elastic loads, the paper proposes an intelligence-technique-based DSM to achieve reduction in the overall cost of using loads in an MG structure. Seven different cases are studied which cover diverse grid participation and electricity market pricing strategies, including DSM programs. The results obtained for all the MGs showcase the applicability and appropriateness of using the proposed DSM strategy in terms of cost savings

Effective demand response program addresing carbon constrained economic dispatch problem of a microgrid system

Electricity is produced, transferred, and delivered within a small geographic area using a constrained power distribution system called a microgrid. Such microgrids employed to guarantee that renewable energy sources (RES) are utilised to their fullest extent. Additional advantages of microgrids include reduced losses during transmission and related costs. The objectives of economic dispatch, emission dispatch, combined economic emission dispatch (CEED) founded on fractional programming (FP), and environmental constrained economic dispatch (ECED) are compared and contrasted in this study. The feasibility of a low-voltage microgrid system is examined for three situations. A novel, robust, and hybrid swarm-intelligence optimisation algorithm, based on merging the characteristics of the conventional grey-wolf optimizer (GWO), sine-cosine algorithm (SCA), and crow search algorithm (CSA), is used as a research optimisation tool. Results show that switching from a fixed pricing plan to a time-of-use (TOU) model resulted in a 15% less cost in production during the period of the research. When a portion of the microgrid customers engaged in the incentive-based demand response (IBDR) programme, further reductions in total generation costs and emissions were achieved. The peak demand was reduced by 3.5% as a result of participation in the IBDR programme, from 90 kW to 86.863 kW. and provided participants with incentives, according to numerical results

Regioselectivity of Vinyl Sulfone Based 1,3-Dipolar Cycloaddition Reactions with Sugar Azides by Computational and Experimental Studies

DFT (M06-L) calculations on the transition state for the 1,3-dipolar cycloadditions between substituted vinyl sulfones with sugar azide have been reported in conjunction with new experimental results, and the origin of reversal of regioselectivity has been revealed using a distortion/interaction model. This study provides the scientific justification for combining organic azides with two different types of vinyl sulfones for the preparation of 1,5-disubstituted 1,2,3-triazoles and 1,4-disubstituted triazolyl esters under metal-free conditions