Water canal networks that are widely used for irrigation are an equally good source of micropower generation to be fed to the nearby areas. A practical example of such a system is the micro-hydro generation at Renala Khurd Pakistan integrated with the national grid known as hydro–grid configuration. Apart from the rare Renala Khurd hydro generation example, solar photovoltaic generation integrated with a mainstream network, i.e., solar PV-Grid configuration, is widely used. The integrated operation of combinations of primary distributed generation sources has different operational attributes in terms of economics and reliability that are needed to be quantified before installation. So far, various combinations of primary distributed generation sources have been simulated and their accumulative impact on project economics and reliability have been reported. A detailed economic and reliability assessment of various configurations is needed for sustainable and cost-effective configuration selection. This study proposes a trigeneration combination of solar–hydro–grid with an optimal sizing scheme to reduce the solar system sizing and grid operational cost. A genetic algorithm based optimal sizing formulation is developed using fixed hydro and variable solar and grid systems with a number of pre-defined constraints. The hydro–grid, solar–grid, and grid–hydro–solar configurations are simulated in HOMER Pro software to analyze the economic impact, and to undertake reliability assessments under various configurations of the project. Finally, optimal values of the genetic algorithm are provided to the HOMER Pro software search space for simulating the grid–hydro–solar configuration. It was revealed that the net present cost (NPC) of hydro-to-grid configuration was 23% lower than the grid–hydro–solar configuration, whereas the NPC of grid–hydro–solar without optimal sizing was 40% lower than the solar–grid configuration, and the NPC of grid–solar–hydro with the genetic algorithm was 36% lower than the hydro–grid configuration, 50.90% lower than solar–grid–hydro without the genetic algorithm, and 17.1% lower than the grid–solar configuration, thus proving utilization of trigeneration sources integration to be a feasible solution for areas where canal hydropower is available.

Due to global environmental impacts, the electric vehicle (EV) adoption rate is increasing. However, unlike conventional petrol vehicles, EVs take a considerable time to charge. EVs on the road with different battery charging statuses and driving demographics may cause uncertain peak time arrivals at charging stations. Battery-swappable charging stations are a quick and easier way to replace uncharged batteries with charged ones. However, charging due to uncertain EV arrival causes higher charging profiles posing load to the grid, management of charged and discharged batteries, and peak time charging tariffs. These challenges hinder the wide operation of battery-swappable charging stations. Nevertheless, a pre-assessment of peak hours using EV demographics can reduce congestion. In recent literature surveys for battery-swappable charging stations, spot congestion has not been given much attention, which has a direct influence on the sizing and operation of battery-swappable charging stations. This research study is focused on estimating peak time events using a novel integrated techno-economic assessment framework. A fuzzy-based parametric assessment tool is developed that identifies the factors that influence higher congestion events. Based on the peak event assessment, grid, and solar PV-based generation is optimized using mixed integer linear programming. In the final step, an environment analysis of a swappable charging station is performed. Furthermore, the results achieved using the proposed framework for battery-swappable charging stations (BSCSs) were compared with fast-charging (FC) stations. FC can economically perform well if integrated with solar PV systems; however, the capital cost is 80% greater than the BSCSs designed under the proposed framework. The operational cost of BSCSs is 39% higher than FC stations as they use 29% higher grid units than FC stations due to night operations under congestion.

Modular Multilevel Converter (MMC) is widely known as one of the most promising topologies for high power medium voltage application. However, MMC is still limited when it comes to Variable Speed Drive (VSD) applications. The reasons behind this is the large fluctuations in the submodules capacitor voltages during low-speed constant torque operation. Thus, the feasibility of sensor-less vector control of MMC based variable speed drive is considered as a difficult task. This paper proposes a novel speed observer for MMC-based VSD suitable for low-speed operation. Speed estimation is carried out by using the stator currents and the input voltages. A discrete model where the rotor parameters do not change during a short sampling time is considered. An extensive simulation is carried out for verifying the closed loop operation of the proposed speed sensor -less MMC-based VSD.