Switching angle optimization and fault analysis of a multistring-multilevel inverter for renewable-energy-source applications

In this paper,a multistring-multilevel inverter(M-MLI)for renewable-energy-source applications has been proposed with reduced switch count and harmonics along with single-switch fault analysis for various levels.It requires only‘m+1’power switches for‘m’voltage levels.The proposed work achieves the fine-tuning of switching angles using a metaheuristic technique,i.e.the teaching-learning-based optimization algorithm(TLBOA),to mitigate the total harmonic distortion(THD)of the M-MLI.Furthermore,the proposed TLBOA has been compared with conventional modulation techniques such as equal phase(EP),half-equal phase(HEP),near-level control(NLC)and Newton-Raphson(NR)to verify the effectiveness of TLBOA for various voltage levels in terms of%voltage-THD(%V-THD),computational time and methodology.By fine-tuning the switching angles,the%V-THD is improved significantly when compared with EP,HEP,NLC and NR modulation techniques.For an 11-level single-phase M-MLI,the%V-THD using TLBOA at 0.91 modulation index(MI)is 5.051%.The lower-order harmonics,i.e.5,7,11 and 13,are eliminated to improve the power quality.Furthermore,MLIs are often prone to failure,resulting in waveform distortion.The extreme reduction in power quality impacts the load and significant damage is likely.The location of the open-circuit fault to be identified becomes more tedious under the faulty conditions with increased switch counts and voltage levels since the mathematical modelling fails to address the scenario in less computational time.Hence,the machine-learning approach,i.e.support vector machine(SVM)with Bayesian optimization,has been discussed to locate the faulty switch.Finally,the proposed M-MLI configuration has been modelled,simulated and validated using MATLAB®and Simulink®.The results of the M-MLI configuration have been verified for 7,9 and 11 levels using TLBOA along with fault analysis using the SVM approach.

Optimal cost and feasible design for gridconnected microgrid on campus area using the robust-intelligence method

In this paper,a robust optimization and sustainable investigation are undertaken to find a feasible design for a microgrid in a campus area at minimum cost.The campus microgrid needs to be optimized with further investigation,especially to reduce the cost while considering feasibility in ensuring the continuity of energy supply.A modified combination of genetic algorithm and particle swarm optimization(MGAPSO)is applied to minimize the cost while considering the feasibility of a grid-connected photovoltaic/battery/diesel system.Then,a sustainable energy-management system is also defined to analyse the characteristics of the microgrid.The optimization results show that the MGAPSO method produces a better solution with better convergence and lower costs than conventional methods.The MGAPSO optimization reduces the system cost by up to 11.99%compared with the conventional methods.In the rest of the paper,the components that have been optimized are adjusted in a realistic scheme to discuss the energy profile and allocation characteristics.Further investigation has shown that MGAPSO can optimize the campus microgrid to be self-sustained by enhancing renewable-energy utilization.

The heat-pump market in Italy:an in-depth economic study about the reasons for a still unexpressed potential

In this paper,the Italian heat-pump(HP)market is presented,with an overview over the past 10 years.In order to highlight market potential and barriers,a comparison is proposed between the economic performances of two different heating and domestic hot-water systems,air-to-water HPs and condensing boilers,based on several factors,such as energy costs,thermal loads,climatic conditions,HP-performance classes and some economic indicators such as the payback time and the interest rate.The results are presented in a parametric form,which may be profitably used for a comparative analysis with other European countries.The first part of the paper deals with the analysis of the current Italian HP market,to show its still unexpressed potential.The second part analyses the HP economic convenience with respect to the most commonly used heating technology,i.e.the gas boiler,under conditions typical of the Italian climate.The comparison is carried out in terms of two economic indicators:additional acceptable cost and net present value.The main results show that HP technology is economically competitive in most Italian climatic zones,with a strong dependence on the HP-performance class.In particular,if the best-performing class was adopted,economic gains would be guaranteed over the gas boiler,even with significant variations in the main influencing variables.Thus,the economic issue does not seem to be a limiting factor for HP technology diffusion,at least if the current incentives are maintained.Rather,some other barriers should be removed,such as the supply chain,the training of installation personnel and the final-user awareness.

A breakthrough of monitoringenergy storage in operation usingoptical fibers

The drive toward renewable-energy technologies,such as wind and solar,to help fight climate change puts a premium on ways to store and deliver power from these non-continuous energy sources.One intriguing piece in this power-management puzzle lies in supercapacitors-ultra-high-capacitance structures that can sop up,store and deliver significant amounts of charge,and that can withstand hundreds of thousands of charge-discharge cycles.But how can these closed devices be monitored in real time,to ensure that they are working at peak efficiency and to prevent potentially catastrophic failures in the renewable-power grid?