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Increased investment of a photovoltaic (PV) array makes it essential for the client to attain better results from the PV system. The nonlinearity of the PV array and the revolution and rotation of the earth require the appliance of maximum power point tracking (MPPT) to the system. Accordingly, grid connected PV systems have turn out to be renowned, because they do not require battery back-ups to accomplish MPPT. Stand-alone systems could also attain MPPT; however, they require appropriate battery back-ups for this function.

This survey intends to formulate a review on the PV-based microgrid (MG) systems. Here, the literature analyses on diverse techniques associated with PV-based MG systems. It reviews 65 research papers and states the significant analysis. Initially, the analysis depicts various controllers that are contributed in different papers. Subsequently, the analysis also focuses on various features such as PV capacity and inverter topology, and it also analyses the renewable grid source that are exploited in each paper. Furthermore, this paper provides the detailed study regarding the chronological review and performance achievements in each contribution. Finally, it extends the various research issues which can be useful for the researchers to accomplish further research on PV-based MG systems.

This paper has presented a detailed review on PV-based MG systems that were enumerated in the above sections. Here, various controllers along with their better achievements were analyzed and described. From the review, it was known that several PV-based MG systems were really at the point for enabling better power output and conversion efficiency. In conclusion, this paper reviewed about 65 research papers and declared the significant analysis. Initially, the analysis also focused on various controller classifications in PV-based MG systems that were reviewed in this paper. Subsequently, the analysis also focused on various features, such as PV capacity and inverter topology. The analysis also reviewed the performance achievements and renewable gird source that were exploited in PV-based MG systems. At last, this paper has presented various research issues which can be useful for the researchers to accomplish further research on the features of PV-based MG systems.

This paper presents a brief analysis of PV-based MG systems. This is the first work that uses PV-based MG systems for better regulation of MPPT.

The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) system.

The idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, respectively.

From the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA system.

Compared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input–output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.

This paper aims to introduce the quasi impedance source inverter (qZSI)-based static compensator (STATCOM), which is incorporated into the hybrid distributed power generation system for enhancement of power quality. The distributed power generation system includes the photovoltaic (PV), wind energy conversion system (WECS) and battery energy storage system.

The WECS is used by the self-excited induction generator (SEIG) and the flywheel energy storage system (FESS). To regulate its terminal voltage and frequency, the SEIG requires adjustable volt-ampere reactive (VAR). A combination of a STATCOM and a fixed condenser bank usually serves to satisfy the VAR demand. The maximum correntropy criterion-based adaptive filter technique (AFT) is proposed to control the qZSI-STATCOM and to guarantee that the voltage at the SEIG terminal is harmonic-free while providing non-linear three-phase and single-phase loads.

The coordinated operation of the suggested voltage control and flywheel control systems ensures that load voltage and frequency are retained in their respective values at very low harmonic distortions regardless of wind speed and load variation. The simulation and experimental studies are carried out under different load conditions to validate the efficiencies of the PV-assisted STATCOM.

To improve system stability and minimize total costs, extra load current sensors can also be avoided. This paper proposes to control the SEIG terminal voltage and harmonic elimination in the standalone WECS systems using maximum correntropy criterion-based AFT with a fuzzy logic controller.

Currently, more renewable energy resources with advanced technology levels are incorporated in the electric power networks. Under this circumstance, the attainment of optimal economic dispatch is very much essential by the power system as the system requires more power generation cost and also has a great demand for electrical energy. Therefore, one of the primary difficulties in the power system is lowering the cost of power generation, which includes both economic and environmental costs. This study/paper aims to introduce a meta-heuristic algorithm, which offers an solution to the combined economic and emission dispatch (CEED).

A novel algorithm termed Levy-based glowworm swarm optimization (LGSO) is proposed in this work, and it provides an excellent solution to the combined economic and emission dispatch (CEED) difficulties by specifying the generation of the optimal renewable energy systems (RES). Moreover, in hybrid renewable energy systems, the proposed scheme is extended by connecting the wind turbine because the thermal power plant could not control the aforementioned costs. In terms of economic cost, emission cost and transmission loss, the suggested CEED model outperforms other conventional schemes genetic algorithm, Grey wolf optimization, whale optimization algorithm (WOA), dragonfly algorithm (DA) and glowworm swarm optimization (GSO) and demonstrates its efficiency.

According to the results, the suggested model for Iteration 20 was outperformed GSO, DA and WOA by 23.46%, 97.33% and 93.33%, respectively. For Iteration 40, the proposed LGSO was 60%, 99.73% and 97.06% better than GSO, DA and WOA methods, respectively. The proposed model for Iteration 60 was 71.50% better than GSO, 96.56% better than DA and 95.25% better than WOA. As a result, the proposed LGSO was shown to be superior to other existing techniques with respect to the least cost and loss.

This research introduces the latest optimization algorithm known as LGSO to provide an excellent solution to the CEED difficulties by specifying the generation of the optimal RES. To the best of the authors’ knowledge, this is the first work that utilizes LGSO-based optimization for providing an excellent solution to the CEED difficulties by specifying the generation of the optimal RES.

Introduction: Artificial intelligence (AI) and digitisation offer substantial human potential and profit margins, making them promising retail solutions. Retail leaders have successfully integrated comprehensive uses into their daily operations, while competitors heavily invest in new projects. The Indian retail sector is undergoing a significant transformation, which can be attributed to factors such as growing income, demographic characteristics, and enhanced consumerism, as well as the rapid development of new technologies such as digitisation and AI, which is changing both consumers’ and retailers’ buying behaviour.

Purpose: This study aims to determine the influence of AI on elements that drive digitisation in the retailing sector, as well as the factors that lead to organised retailers adopting digitisation and its impact on their business.

Methodology: The study employs a standardised questionnaire distributed to organised stores via an online link, and the data are analysed with SmartPLS software 3.0.

Finding: The retail sector is driven by elements that promote digitalisation in food and groceries retailing, such as simplicity of operation, adoption of digital payment, quicker internet connection, retailer consumer interface, and the involvement of AI.

Research implication: AI has significant consequences for retailing, which serves as the interface between marketers and customers.

Theoretical implication: The study’s findings reflect the perspectives of retailers, store managers, and entrepreneurs on how digitalisation and AI are crucial for the creation and growth of long-term competitive advantages in retail.

Within the growing study of transnational entrepreneurial practice, existing conceptualisation of diaspora entrepreneurship has often lacked engagement with the particularities of the diaspora condition. This paper seeks to advance theoretical understanding and empirical study of diaspora entrepreneurship through identifying the processes that generate diaspora entrepreneurship across economic, social and political spheres.

To analyse the relationship between the development of venture activity and diaspora (re)production, in depth, qualitative biographical analysis was undertaken with UK-based diaspora entrepreneurs embedded within the particular contexts of the Sri Lankan Tamil and Kurdish diasporas. Skilled and active diaspora entrepreneurs were purposively selected from these extreme case contexts to explore their entrepreneurial agency within and across the business, social and political realms.

Results identified key dimensions shaping the development of diaspora entrepreneurship. These comprised the role of diaspora context in shaping opportunity frameworks and the mobilisation of available resources, and how venture activity served to sustain collective diaspora identity and address diaspora interests. These findings are used to produce an analytical model of the generation of diaspora entrepreneurship to serve as a basis for discussing how heterogeneous and hybrid entrepreneurial strategies emerge from and shape the evolving diaspora context.

By placing the reproduction of social collectivity centre-stage, this paper identifies the particularities of diaspora entrepreneurship as a form of transnational entrepreneurship. This recognizes the significance of a contextualised understanding of entrepreneurial diversity within wider processes of diaspora development, which has important implications for policy and practice development in homeland and settlement areas.

Predictive current control (PCC) of three-to-five-phase direct matrix converters (DMCs) is computationally expensive. For this reason, this study aims to consider a reduced number of switching states of DMC in PCC algorithm to predict the control objectives, such as output current control and input reactive power control.

The switching sequences which yield the voltage vectors of variable amplitude at a constant frequency in space are considered for the prediction and optimization step of PCC algorithm. For the selected voltage vectors, the phase angles of the output vectors are independent on the phase angles of the input vectors. In a three-to-five-phase DMC, there are 243 valid switching states. Among the switching states, only 91 states are considered using the aforementioned concept of variable amplitude output at a constant frequency. This reduced number of switching states simplifies the computational complexity of MPC based current control of three-to-five-phase DMC.

The computational complexity of the proposed PCC based DMC is lower than the all 243 vectors based PCC. The current total harmonic distortion, transient current response and input reactive power control for the simplified 91 vector based PCC are similar to the all 243 vectors based PCC.

A reduced number of switching sequence is considered for the prediction and optimization step of PCC algorithm. Hence, PCC algorithm can be sampled at a high frequency in real-time applications. Then, the performance of the PCC will be improved.

A crucial aspect of supply chain management (SCM) is the formulation of lean supply chain management (LSCM). In this sense, the key practices are extended towards the LSCM settings as alternative strategies and several frameworks were developed to help companies to make choices based on production disruption. Studies in this field have focussed mainly on SCM. Although manufacturing businesses recognise the necessity of effective SCM, but little study has been done on manufacturing LSCM. The behaviour and the potential for significant impacts on sustainable performance (SP) in manufacturing companies can vary with time and variations for approaches of the LSCM key practices. This chapter, therefore, focusses on main practices for LSCM on the basis of evaluations of experts in the Malaysian manufacturing sector in order to achieve SP in manufacturing companies. The aim of this chapter is to identify the key practices in LSCM on SP. Hence, this chapter reviewed 172 articles published from 2015 to 2019, used the methodology for SLR with three main steps: literature review planning, reviewing, and reporting. As a result, there are evidence that the key practices for LSCM used in previous studies are (1) customer relationship management, (2) supplier relationship management, (3) just in time manufacturing, (4) waste reduction, (5) cost reduction, and (6) minimise inventory level. In manufacturing industries, LSCM is more complex. Insights on the causing issues and SP are provided. Finally, this chapter contributes to SCM and literature on sustainability and has managerial implications for companies to improve SP more effectively.

The researchers and policy makers worldwide have proposed many ideas for smart cities and homes in urban areas. The extensive work done for urban smart homes neglects the unique constraints of homes at remote mountain tops and deserts and rural village homes. The purpose of this paper is to propose a smart energy management system for a self-sustained home of any type situated in any geographical location with the availability of renewable energy sources like solar, etc. The purpose is mainly to highlight the importance and advantages of direct current (DC) homes with DC loads rather than a conventional alternating current (AC) home with both AC and DC loads. An attempt has been made to evolve a multi-agent coordinated control for the low voltage direct current (LVDC) smart home system.

LVDC supply systems with in situ power generation are providing an efficient solution for the energy needs of a DC smart home. The individual sub-systems of the LVDC system have their unique functions and priorities and hence require both coordinated and independent control. The entire DC smart home system is modeled in the Matlab and codes are implemented for each agent of the home. LVDC grid is operating either in battery connected mode or utility grid-connected mode, and the DC link voltage is held constant in both the cases. Energy imported from the utility grid is minimized by load shedding during the rectifier mode of the bidirectional converter. In addition, load shedding is also done when the battery is discharging to increase the discharge time of the battery. Load shedding is done on the basis of a fixed priority of loads. A 48 s simulation is performed on the Matlab model to bring out the 24-hour operation of the proposed system. Various modes are simulated and the corresponding actions of the agents are tested.

A new control strategy with agents for each sub-system of the LVDC system is presented. Each individual agent works in tandem with other agents and meets its own control imperatives without compromising the requirements of the overall system. Unlike the centralized control system, the proposed control strategy is a distributed control system. The control algorithm for each of the agents is developed, and the pseudo code is presented. The results of the simulation of the proposed scheme are presented to confirm the usefulness of the new control approach.

The multi-agent concept for an energy management system is less addressed and thus its potential for efficient home energy management is presented. The proposed multi-agent strategy for a complete DC smart home with exclusive DC loads is not done earlier and is reported for the first time. The success of this strategy can be extended to other DC micro-grid systems like telecom power systems, ships, aircraft, datacentres, server rooms, residential complexes and commercial malls.

This paper aims to provide a detailed review of various cutting fluids (CFs).

Friction and wear are inevitable in machine parts in motion. The industrial sector uses various kinds of lubricants, which include engine oils, CFs, hydraulic fluids, greases, etc. to control friction and wear. The main purpose of using CF is to remove heat produced during machining and to reduce cutting forces, tool wear and energy associated with it. Thus, it increases the productivity and quality of the manufacturing process. But more than 80% of the CFs used in the industries now are mineral oil-based. These mineral oils and additives are highly undesirable because of their toxicity, nonbiodegradability, pollution and ecological problems. Hence, these petroleum-based oils in the lubrication system can be substituted with alternatives such as vegetable-based CF. Several studies are being conducted in the field of eco-friendly CFs. Because of the variance in fatty acid profile and availability, the selection of vegetable oils (VOs) is another problem faced nowadays. The present study is focused on bio-based oils and many eco-friendly additives. Various machining processes and comparisons relating to the same have also been made. The aim is to minimize the use of mineral oil and thereby introduce sustainability in production.

In this present study, bio-based oils, additives and various characteristic behavior of them in machining are being discussed. The VOs are found to be a potential base oil for industrial CFs.

This paper describes the importance of sustainable CFs.