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In this paper, we describe a comparative analysis of a bus route scheduling problem as part of timetable trips. We consider the current uptake of electric buses as a viable public transportation option that will eventually phase out the diesel-engine-based buses. We note that, with the increasing number of electric buses, the complexity related to the scheduling also increases, especially stemming from the charging requirement and the dedicated infrastructure behind it. The aim of our comparative study is to highlight the brevity with which a multi-agent-system-based scheduling method can be helpful as compared to the classical mixed-integer linear-programming-based approach. The multi-agent approach we design is centralized with asymmetric communication between the master agent, the bus agent, and the depot agent, which makes it possible to solve the multi-depot scheduling problem in almost real time as opposed to the classical optimizer, which sees a multi-depot problem as a combinatorial heuristic NP-hard problem, which, for large system cases, can be computationally inefficient to solve. We test the efficacy of the multi-agent algorithm and also compare the same with the MILP objective designed in harmony with the multi-agent system. We test the comparisons first on a small network and then extend the scheduling application to real data extracted from the public transport of the Maltese Islands., peer-reviewed

In this paper, a new hybrid TSA-PSO algorithm is proposed that combines tunicate swarm algorithm (TSA) with the particle swarm optimization (PSO) technique for efficient maximum power extraction from a photovoltaic (PV) system subjected to partial shading conditions (PSCs). The performance of the proposed algorithm was enhanced by incorporating the PSO algorithm, which improves the exploitation capability of TSA. The response of the proposed TSA-PSO-based MPPT was investigated by performing a detailed comparative study with other recently published MPPT algorithms, such as tunicate swarm algorithm (TSA), particle swarm optimization (PSO), grey wolf optimization (GWO), flower pollination algorithm (FPA), and perturb and observe (P&O). A quantitative and qualitative analysis was carried out based on three distinct partial shading conditions. It was observed that the proposed TSA-PSO technique had remarkable success in locating the maximum power point and had quick convergence at the global maximum power point. The presented TSA-PSO MPPT algorithm achieved a PV tracking efficiency of 97.64%. Furthermore, two nonparametric tests, Friedman ranking and Wilcoxon rank-sum, were also employed to validate the effectiveness of the proposed TSA-PSO MPPT method., peer-reviewed

Widespread Photovoltaics (PVs), which are seen by a distribution network (or an isolated microgrid) as a constant power injecting source, can be detrimental to the frequency stability of the network. To assist in frequency regulation and response, the constant current control for a Distributed Energy Resource is substantially modified to provide inertial response within the low voltage network. PVs that deploy inertial control require an additional storage in order to cater to the demand supply balance. This approach is feasible for large scale PVs, however, rooftop PVs possess limited flexibility for additional storage. This paper studies case of a low-voltage networked microgrid with an appreciable PV penetration, in the presence of a diesel generator (DG) as a separate bus. A coordinated control for PV is designed in this paper, which can help in the transition in between the grid-forming mode to the grid-following modes (with the inertial control loop acting as the Phase locked loop), with the help of an auxiliary DC link voltage based control which is designed in a way that does not require any switching action.

Insular grids are fragile owing to lower inertia and the absence of interconnection with other grids. With the increasing penetration of non-dispatchable renewable energy sources, the vulnerability of such insular grids increases further. The government of India has proposed several projects to improve the photovoltaic systems (PV) penetration in the Andaman and Nicobar Islands’ grid. This paper investigates joint stochastic scheduling of energy and reserve generation for insular grids fed from diesel and gas-based generators, PV, and battery energy storage systems (BESS). The proposed stochastic scheduling model considers a wide range of probabilistic forecast scenarios instead of a deterministic model that assumes a single-point forecast. Hence, it provides an optimal solution that is technically feasible for a wide range of PV power forecast scenarios. The striking feature of the model developed in this work is the inclusion of stochastic constraints that represent (i) the coordination between PV and BESS, (ii) reserve constraints, (iii) battery charging/discharging limit constraints, and (iv) non-anticipatory constraints that ensure technical viability of scheduling decisions. The proposed model is validated on the dataset for South Andaman Island. Results reveal the applicability and feasibility of the proposed stochastic dispatch model for different generation mix scenarios., peer-reviewed

Parameter estimation of photovoltaic modules is an essential step to observe, analyze, and optimize the performance of solar power systems. An efficient optimization approach is needed to obtain the finest value of unknown parameters. Herewith, this article proposes a novel opposition-based tunicate swarm algorithm for parameter estimation. The proposed algorithm is developed based on the exploration and exploitation components of the tunicate swarm algorithm. The opposition-based learning mechanism is employed to improve the diversification of the search space to provide a precise solution. The parameters of three types of photovoltaic modules (two polycrystalline and one monocrystalline) are estimated using the proposed algorithm. The estimated parameters show good agreement with the measured data for three modules at different irradiance levels. Performance of the developed opposition-based tunicate swarm algorithm is compared with other predefined algorithms in terms of robustness, statistical, and convergence analysis. The root mean square error values are minimum ( 6.83×10−4 , 2.06×10−4 , and 4.48×10−6 ) compared to the tunicate swarm algorithm and other predefined algorithms. Proposed algorithm decreases the function cost by 30.11%, 97.65%, and 99.80% for the SS2018 module, SolarexMSX-60 module, and Leibold solar module, respectively, as compared to the basic tunicate swarm algorithm. The statistical results and convergence speed depicts the outstanding performance of the anticipated approach. Furthermore, the Friedman ranking tests confirm the competence and reliability of the developed approach., This work was supported in part by the European Commission H2020 TWINNING Joint Universal activities for Mediterranean PV integration Excellence (JUMP2Excel) Project under Grant 810809., peer-reviewed

Photovoltaic systems (PVs) are promising low-carbon technologies playing a major role 9 in the electricity business. In terms of voltage variation and feeder usage capacity, high PV penetra- 10 tion levels have significant technical implications for grid stability, particularly in Low Voltage (LV) 11 networks. This paper presents a comprehensive PV integration analysis on real-life residential LV 12 networks in Malta using recorded smart metering data. The methodology framework and tools de- 13 veloped are highlighted through step by step results on their usefulness. First, at the substation 14 level, an LV network with seven LV feeders is analyzed using Monte Carlo simulations and 15 OpenDSS. Then, Cumulative Distribution Functions (CDFs) are extracted to establish the likeli- 16 hood of LV network challenges. Afterwards, 95 multi-feeder analysis assesses impact assessment 17 on the first occurrence of LV network challenges and predominant issues. Finally, a Regression 18 Analysis Tool, considering the regression's standard error, is built for seven feeder characteristics to 19 predict impacts. The stochastic processes reveal strong relationships with feeder characteristics that 20 are helpful for network planning and operations. However, the Maltese grid currently has less than 21 20% PV penetration at any LV feeder. Hence significant technological hurdles are absent., In Press, accepted for publication in March 2022

Climate change and environmental pollution are partly driven by fossil fuel emissions of hazardous chemicals like CO2. Due to years of exploitation, fossil fuel natural resources have been drastically decreased. The following data show the necessity for research on the technological and socioeconomic possibilities of converting energy systems and elements of the transportation system to renewable energy. This article proposes supplying an entire region with RES while considering cost and environmental efficiencies. The subject study also showed the need to research correlations between collective heating, transport systems with high V2G energy storage capacity, and power systems to optimize the total energy market. Moreover, the aforesaid reasons suggest that a new model of the power system, different from the standard producer-recipient paradigm, is needed. This research was quantitative and qualitative. Agent-based modeling, underpinned by qualitative research, was used in quantitative analysis. Renewable energy systems are more cost- and environmentally-competitive, according to study. Integration of community heating and transport systems with the energy system reduces primary energy consumption and carbon dioxide emissions, improving system efficiency. Research shows that reducing energy consumption helps transition a conventional energy system into a RES system., In Press. Accepted for Publication

Energy independence or even a single household plays an important role nowadays. Another essential aspect of the energy generation process is environmental friendliness and cost competitiveness. With new renewable energy technologies, a sustainable energy transition is possible. In this paper, we present aspects related to sustainable energy transformation. The simulation considered the Maltese energy system regarding the growth and dominance of photovoltaic energy in the electricity market. The analysis results show a significant advantage of a system with a high penetration of photovoltaics over a conventional method using fossil fuels. Due to the substantial dominance of solar PV in the simulations, Malta’s electricity cost could be reduced threefold. In contrast, CO2 emissions were reduced by 40% and the energy independence of Malta’s electricity sector was increased by around 60%. Furthermore, the paper recommends the direction of further research in the field of the Maltese energy system., In Press. Accepted for Publication with Gold Open Access in Economics and Sociology Journal

Η Πρώτη Μεσογειακή Έκθεση Αξιολόγησης (MAR1) που εκπονήθηκε από το ανεξάρτητο δίκτυο Εμπειρογνωμόνων της Μεσογείου για το Κλίμα και την Περιβαλλοντική Αλλαγή (MedECC), το οποίο ιδρύθηκε το 2015, έχει τώρα δημοσιευθεί. Η MAR1 αξιολογεί τη βέλτιστη διαθέσιμη επιστημονική γνώση σχετικά με την κλιματική και περιβαλλοντική αλλαγή και τους συναφείς κινδύνους στη λεκάνη της Μεσογείου, προκειμένου να την καταστήσει προσιτή στους υπεύθυνους χάραξης πολιτικής, τους ενδιαφερόμενους φορείς και τους πολίτες. Η έκθεση περιλαμβάνει τη Σύνοψη για τους Υπεύθυνους Χάραξης Πολιτικής (SPM), η οποία περιλαμβάνει τα βασικά μηνύματα της MAR1. Η έκθεση συντάχθηκε από 190 επιστήμονες από 25 χώρες, οι οποίοι συνέβαλαν με την ατομική τους ιδιότητα και χωρίς οικονομική αποζημίωση. Η Γραμματεία της Σύμβασης UNEP/MAP - Barcelona, μέσω του Περιφερειακού Κέντρου Δραστηριοτήτων Plan Bleu, και η Γραμματεία της Ένωσης για τη Μεσόγειο (UfM) συνεργάζονται για να υποστηρίξουν το MedECC και να συμβάλουν στην καθιέρωση μιας ορθής και διαφανούς επιστημονικής διαδικασίας αξιολόγησης.

This paper entails the activities carried out within the H2020 JUMP2Excel (Joint Universal Activities for Mediterranean PV Integration Excellence) TWINNING project and delineates the research carried out within it. The project aim has been to steadily set in the PV research, its related technology and electricity integration. This has been achieved through a programme of actions coordinated by MCAST Energy together with a group of top world leading research institutions, United Kingdom (UK), The University of Manchester (UNIMAN); Spain, Centro Nacional de Energia Renovables (CENER) and France Commissariat a l' Energie Atomique et aux Energies Alternatives (CEA), which provided access to extensive network and contacts in the field. By enhancing the quality and quantity of the research output, JUMP2Excel project helped in improving the success rate of MCAST Energy group in grant applications, developing network of excellence and international recognition. To realise these objectives, JUMP2Excel project focused precisely on knowledge transfer through the mechanisms of staff exchange and internships, rese, including poster presentation