The motivation for incorporation of microgrid technology in rooftop solar photovoltaic deployment to enhance energy economics

Deployment of rooftop solar PV technology in domestic premises plays a significant role in accomplishing renewable energy transformation. Majority of domestic consumers still do not have a positive perception about adopting rooftop solar PV technology, due to its high capital cost and prolonged payback period. In this aspect, the proposed work identifies the factors causing energy deprivation in the present distribution and utilization system. To explicitly express the importance of the present work, an extensive case study based on Indian scenario has been carried out to investigate where the losses occur in the existing distribution system and how the solar power and its storage system have been ineffectively utilized. The deep investigation has thrown light on several issues that lead to the performance deterioration of PV technology. Finally, in this work, a scheme to incorporate hybrid microgrid technology in the domestic distribution network has been proposed to effectively manage the distribution system and to efficiently utilize solar power and its storage systems. The real-time electricity tariff data have been taken for cost comparison and payback period calculations to prove the effectiveness of the proposed method. A crucial comparisons have been presented based on energy saving and CO2 emission reduction strategies.publishedVersio

Incorporation of Microgrid Technology Solutions to Reduce Power Loss in a Distribution Network with Elimination of Inefficient Power Conversion Strategies

The increase in energy-efficient DC appliances and electronic gadgets has led to an upheaval in the usage of AC–DC power convertors; hence, power loss in converter devices is cumulatively increasing. Evolving microgrid technology has also become deeply integrated with the conversion process due to increased power converters in its infrastructure, significantly worsening the power loss situation. One of the practical solutions to this disturbance is to reduce conversion losses in domestic distribution systems through the optimal deployment of the battery storage system and solar PV power using microgrid technology. In this paper, a novel energy management system is developed that uses a new control algorithm, termed Inefficient Power Conversion Elimination Algorithm (IPCEA). The proposed algorithm compares the Net Transferable Power (NTP) available on the DC side with the loss rate across the converter. The converter is switched off (or disconnected from the grid and load) if the NTP is less than 20% of the converter rating to avoid low-efficiency power conversion. The solar PV system is connected to the DC bus to supply the DC loads while the AC loads are supplied from the AC source (utility power). An auxiliary battery pack is integrated to the DC side to feed DC loads during the absence of solar energy. A battery energy storage system (BESS) is deployed to manage energy distribution effectively. The power distribution is managed using a centralized microgrid controller, and the load demand is met accordingly. Thereby, the power generated by the solar PV can be utilized effectively. Microgrid technology’s effectiveness is emphasized by comparative analysis, and the achievements are discussed in detail and highlighted using a prototype model.publishedVersio

Cyber-Physical Power System (CPPS): A Review on Modelling, Simulation, and Analysis with Cyber Security Applications

Cyber-Physical System (CPS) is a new kind of digital technology that increases its attention across academia, government, and industry sectors and covers a wide range of applications like agriculture, energy, medical, transportation, etc. The traditional power systems with physical equipment as a core element are more integrated with information and communication technology, which evolves into the Cyber-Physical Power System (CPPS). The CPPS consists of a physical system tightly integrated with cyber systems (control, computing, and communication functions) and allows the two-way flows of electricity and information for enabling smart grid technologies. Even though the digital technologies monitoring and controlling the electric power grid more efficiently and reliably, the power grid is vulnerable to cybersecurity risk and involves the complex interdependency between cyber and physical systems. Analyzing and resolving the problems in CPPS needs the modelling methods and systematic investigation of a complex interaction between cyber and physical systems. The conventional way of modelling, simulation, and analysis involves the separation of physical domain and cyber domain, which is not suitable for the modern CPPS. Therefore, an integrated framework needed to analyze the practical scenario of the unification of physical and cyber systems. A comprehensive review of different modelling, simulation, and analysis methods and different types of cyber-attacks, cybersecurity measures for modern CPPS is explored in this paper. A review of different types of cyber-attack detection and mitigation control schemes for the practical power system is presented in this paper. The status of the research in CPPS around the world and a new path for recommendations and research directions for the researchers working in the CPPS are finally presented.publishedVersio

Investigation on current and prospective energy transition scenarios in indian landscape using integrated SWOT-MCDA methodology

India has ambitious goals to increase renewable energy penetration and significant progress have been made since 2017. However, the Indian energy mix is highly dominated by fossil fuels. To set India in the pathway of the energy transition, a comprehensive analysis of complex factors influencing the Indian energy sector is required. This study is put forward to delineate the current scenario of energy transition in India and to direct the energy sector towards a prospective scenario for accomplishing a smooth energy transition. A hybrid quantitative-qualitative SWOT integrated MCDA methodology is employed to accomplish the objective of this study. An extensive literature review is performed to understand and sort the various factors under each SWOT category. Fuzzy AHP methodology is utilized to convert the qualitative significance of each SWOT factor into quantitative scores through which the crucial influencing factor in the current energy transition scenario is obtained. The top three highest influencing factors include utilizing the cost-competitiveness of solar and wind energy technologies over fossil fuels, the inadequacy of manpower having specialized skillsets, and connecting households to electricity and electrifying the transportation sector. The recommendation strategies are framed and presented for prospective energy transition scenario. These strategies are assessed against the SWOT factors by using the PROMETHEE II methodology. The assessment results highlight that developing robust regulatory and policy frameworks, increasing the contribution of local energy resources, and promoting the distributed generation and grid infrastructure development are the highest scoring strategies that have a synergic effect on multiple dimensions of energy transition including political, financial and techno-economic aspects. The proposed study will be conducive to framing effective policy in the upcoming years to assist the energy transition in India.publishedVersio

Optimal Allocation/Sizing of DGs/Capacitors in Reconfigured Radial Distribution System using Quasi-Reflected Slime Mould Algorithm

Increased load demands worsen distribution system problems such as greater line losses, voltage deviation and a plethora of other concerns. This current work presents an approach stressing simultaneous optimal allocation and sizing of capacitor banks and distributed generations, as well as optimal radial distribution system (RDS) reconfiguration, to address these difficulties. The above objectives are accomplished through the maiden application of the proposed quasi-reflection-based slime mould algorithm (QRSMA). The efficacy of QRSMA is established by testing it on different benchmark functions. A new modified backward forward load flow approach is also proposed and validated by comparing its results to those obtained using MATPOWER software for IEEE 69, 85, and 118 bus RDSs. The proposed load flow technique is independent of the sequential bus numbering scheme and may be applied to any RDS network topology. The proposed QRSMA is tested on 118 bus RDS and to prove its effectiveness; its results are compared to those of other studied algorithms. The study takes into account both fixed and variable loading scenarios. A cost-benefit analysis of the strategy is also performed in order to make the methodology more realistic.publishedVersio

An Assessment of Onshore and Offshore Wind Energy Potential in India Using Moth Flame Optimization

Wind energy is one of the supremely renewable energy sources and has been widely established worldwide. Due to strong seasonal variations in the wind resource, accurate predictions of wind resource assessment and appropriate wind speed distribution models (for any location) are the significant facets for planning and commissioning wind farms. In this work, the wind characteristics and wind potential assessment of onshore, offshore, and nearshore locations of India—particularly Kayathar in Tamilnadu, the Gulf of Khambhat, and Jafrabad in Gujarat—are statistically analyzed with wind distribution methods. Further, the resource assessments are carried out using Weibull, Rayleigh, gamma, Nakagami, generalized extreme value (GEV), lognormal, inverse Gaussian, Rician, Birnbaum–Sandras, and Bimodal–Weibull distribution methods. Additionally, the advent of artificial intelligence and soft computing techniques with the moth flame optimization (MFO) method leads to superior results in solving complex problems and parameter estimations. The data analytics are carried out in the MATLAB platform, with in-house coding developed for MFO parameters estimated through optimization and other wind distribution parameters using the maximum likelihood method. The observed outcomes show that the MFO method performed well on parameter estimation. Correspondingly, wind power generation was shown to peak at the South West Monsoon periods from June to September, with mean wind speeds ranging from 9 to 12 m/s. Furthermore, the wind speed distribution method of mixed Weibull, Nakagami, and Rician methods performed well in calculating potential assessments for the targeted locations. Likewise, the Gulf of Khambhat (offshore) area has steady wind speeds ranging from 7 to 10 m/s with less turbulence intensity and the highest wind power density of 431 watts/m2. The proposed optimization method proves its potential for accurate assessment of Indian wind conditions in selected locations.publishedVersio

Selective Harmonics Elimination in Multilevel Inverter Using Bio-Inspired Intelligent Algorithms

Multilevel inverters are powerful electronic devices that are used for the conversion of DC input voltage into AC output voltage and mostly used in medium and high voltage operations. In these operations, pulse width modulation (PWM) frequency is distorted because of electromagnetic interference (EMI) and switching losses which are caused by dv/dt stress. To achieve a pure sinusoidal waveform at output of multilevel inverter is a primary purpose so that a smaller number of harmonic contents are produced. Selective harmonic elimination PWM technique is used in cascaded multilevel inverter for the mitigation of lower harmonics by solving nonlinear transcendental equations and maintains the required fundamental voltage. An objective function is derived from SHE problem to calculate switching angles. For the solution of objective function, optimization approach such as bio-inspired intelligent algorithms are used. In this paper, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Bee Algorithm (BA) are used to determine the optimum switching angles for cascaded multilevel inverters to get low total harmonic distortion (THD) in output voltage. These computed angles are analyzed in MATLAB simulation model to authenticate the results. And there will be direct comparison among these algorithms

Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns

The analysis and the assessment of interconnected photovoltaic (PV) modules under different shading conditions and various shading patterns are presented in this paper. The partial shading conditions (PSCs) due to the various factors reduce the power output of PV arrays, and its characteristics have multiple peaks due to the mismatching losses between PV panels. The principal objective of this paper is to model, analyze, simulate and evaluate the performance of PV array topologies such as series-parallel (SP), honey-comb (HC), total-cross-tied (TCT), ladder (LD) and bridge-linked (BL) under different shading patterns to produce the maximum power by reducing the mismatching losses (MLs). Along with the conventional PV array topologies, this paper also discusses the hybrid PV array topologies such as bridge-linked honey-comb (BLHC), bridge-linked total-cross-tied (BLTCT) and series-parallel total-cross-tied (SPTCT). The performance analysis of the traditional PV array topologies along with the hybrid topologies is carried out during static and dynamic shading patterns by comparing the various parameters such as the global peak (GP), local peaks (LPs), corresponding voltage and current at GP and LPs, fill factor (FF) and ML. In addition, the voltage and current equations of the HC configuration under two shading conditions are derived, which represents one of the novelties of this paper. The various parameters of the SPR-200-BLK-U PV module are used for PV modeling and simulation in MATLAB/Simulink software. Thus, the obtained results provide useful information to the researchers for healthy operation and power maximization of PV systems.publishedVersio

Reinforced Demand Side Management for Educational Institution with incorporation of User’s Comfort

Soaring energy demand and the establishment of various trends in the energy market have paved the way for developing demand-side management (DSM) from the consumer side. This paper proposes a reinforced DSM (RDSM) approach that uses an enhanced binary gray wolf optimization algorithm (EBGWO) that benefits the consumer premises with load scheduling, and peak demand reduction. To date, DSM research has been carried out for residential, commercial and industrial loads, whereas DSM approaches for educational loads have been less studied. The institution load also consumes much utility energy during peak hours, making institutional consumers pay a high amount of cost for energy consumption during peak hours. The proposed objective is to reduce the total electricity cost and to improve the operating efficiency of the entire load profile at an educational institution. The proposed architecture integrates the solar PV (SPV) generation that supplies the user-comfort loads during peak operating hours. User comfort is determined with a metric termed the user comfort index (UCI). The novelty of the proposed work is highlighted by modeling a separate class of loads for temperature-controlled air conditioners (AC), supplying the user comfort loads from SPV generation and determining user comfort with percentage UCI. The improved transfer function used in the proposed EBGWO algorithm performs faster in optimizing nonlinear objective problems. The electricity price in the peak hours is high compared to the offpeak hours. The proposed EBGWO algorithm shift and schedules the loads from the peak hours to off-peak hours, and incorporating SPV in satisfying the user comfort loads aids in reducing the power consumption from the utility during peak hours. Thus, the proposed EBGWO algorithm greatly helps the consumer side decrease the peak-to-average ratio (PAR), improve user comfort significantly, reduce the peak demand, and save the institution’s electricity cost by USD 653.046.publishedVersio