This paper formulates a maximum power point tracking (MPPT) technique that accurately tracks the maximum power point of photovoltaic (PV), which undergoes simultaneous or independent sudden changes in load resistance and irradiance. The proposed algorithm is fundamentally divided into three parts; current and voltage perturbation algorithm (IPA/VPA), perturbation step-size reduction algorithm (PSSRA) and a deviation avoidance loop. The use of dual perturbation parameters using IPA and VPA ensures high tracking speed. PSSRA iteratively reduces the perturbation step-size of IPA and VPA and helps in reducing the power oscillations around MPP. Finally, a deviation avoidance loop is developed to detect a change in irradiance by examining the sign of the slope of the two power curves, namely P-V and P-I. The algorithm compares the per unit change in voltage and current of PV, to determine a simultaneous change in both irradiance and load resistance. The proposed algorithm is compared with two recently developed MPPT algorithms. The results show that the proposed technique can track the MPP with high speed and low steady-state oscillations and does not deviate from the MPP tracking path regardless of fast changes in irradiance and load resistance.

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.

The frequency stability of a power system is of paramount importance, as a fast frequency swings in the system can lead to oscillatory instability, and thereby blackouts. A grid-connected microgrid, that can operate in the islanded mode can also possess such deteriorating effect due to the higher share of converter-based sources. In this paper, a coordinated frequency control within a distribution network is discussed, with a higher share of Photovoltaics (PV). The main objective of this paper is to test the grid-forming capabilities of PVs, without the requirement of an energy storage in the network. The tests were carried out with the help of the Typhoon Hardware-in-the-loop (HIL) platform using a real Cypriot network feeder. The real-time results confirm the efficacy of the PV as a grid-forming inverter, provided it has sufficient input (irradiance) to provide for the loads within the system of interest. The grid-forming PV also possesses the capability of reconnection with the utility grid through a synchronizer switch that requires minimal communication, makes the overall control independent of any other power source, subject to certain irradiance and loading conditions.