Hassan Abbas Khan

Solar photovoltaic (PV) generation is recognized as a clean and sustainable energy source, with typical module lifespans exceeding 25 yrs. However, the environmental impacts across the lifecycle of PV systems, including manufacturing, transportation, installation, operation, and decommissioning, can be significant and vary across deployments. Due to the absence of a consistent framework for calculating energy payback time (EPBT), significant variations have been reported in the literature, with reported values ranging from as low as 1.45 yrs to exceeding a decade, which limits the inter-comparability of PV deployments for sustainability assessments. To address these limitations, this paper presents a standardized framework for calculating EPBT, defined as the time required for a PV system to generate the same amount of energy that was used to manufacture, transport, install, operate, and decommission the system. The framework is tested on empirical data from a 42.2 kWp polycrystalline silicon system, along with a comparative analysis to assess how EPBT varies with multiple PV technologies, such as mono-crystalline silicon, copper indium selenide, and cadmium telluride, keeping site location and regional conditions consistent. This work supports PV stakeholders in reducing EPBT through informed technology selection, enabling “greener” PV deployments.

Reliable telecommunication tower operation is paramount for sustainable cities as it ensures uninterrupted communication, supports economic growth, facilitates smart city applications, and enables emergency response. This study evaluates the reliability and economic aspects of three hybrid system configurations aimed at providing an uninterrupted power supply to base transceiver stations (BTS) during power outages. A framework is developed to optimize power operation and assess the operational costs of these configurations. A case study is conducted to examine the effectiveness of the optimization framework. The study evaluates the system size and costs of solar PV, hydrogen fuel cell, and battery energy storage systems. The results demonstrate that system architecture combining a utility grid with battery energy storage and solar PV offers the most cost-effective option. The system architecture, incorporating a utility grid with battery energy storage and hydrogen fuel cells, provides the highest reliability. Per-day operating cost of the solar PV-based architecture is 40.3% lower than that of the architecture with a hydrogen fuel cell system and 35.8% lower than the system architecture of utility grid and battery storage. This study contributes to the integration of renewable power sources and optimization framework, enhancing energy supply and promoting society’s long-term well-being.

The operation of smart buildings (with solar, storage and suitable power routing infrastructure) can be optimized with the addition of parking stations for electric vehicles (EVs) with vehicle-to-everything (V2X) operations including vehicle-to-vehicle (V2V), vehicle-to-building (V2B) and vehicle-to-grid (V2G) operations. In this paper, a multi-objective optimization framework is proposed for the smart charging and discharging of EVs along with the maximization of revenue and savings of smart building (prosumers with solar power, a battery storage system and a parking station) and non-primary/ordinary buildings (consumers of electricity without solar power, a battery storage system and parking station). A mixed-integer linear program is developed to maximize the profits of smart buildings that have bilateral contracts with non-primary buildings. The optimized charging and discharging (V2X) of EVs at affordable rates utilizing solar power and a battery storage system in the smart building helps to manage the EV load during on-peak hours and prevent utility congestion. The results indicate that in addition to the 4–9% daily electricity cost reductions for non-primary buildings, a smart building can achieve up to 60% of the daily profits. Further, EVs can save 50–69% in charging costs while performing V2X operations.

Grid-connected rooftop and ground-mounted solar photovoltaics (PV) systems have gained attraction globally in recent years due to (a) reduced PV module prices, (b) maturing inverter technology, and (c) incentives through feed-in tariff (FiT) or net metering. The large penetration of grid-connected PVs coupled with nonlinear loads and bidirectional power flows impacts grid voltage levels and total harmonic distortion (THD) at the low-voltage (LV) distribution feeder. In this study, LV power quality issues with significant nonlinear loads were evaluated at the point of common coupling (PCC). Various cases of PV penetration (0 to 100%) were evaluated for practical feeder data in a weak grid environment and tested at the radial modified IEEE-34 bus system to evaluate total harmonic distortion in the current (THD_i) and voltage (THD_v) at PCC along with the seasonal variations. Results showed lower active, reactive, and apparent power losses of 1.9, 2.6, and 3.3%, respectively, with 50% solar PV penetration in the LV network as the voltage profile of the LV network was significantly improved compared to the base case of no solar. Further, with 50% PV penetration, THD_i and THD_v at PCC were noted as 10.2 and 5.2%, respectively, which is within the IEEE benchmarks at LV.

In this study, modelling, implementation, and control of a hybrid renewables‐based, scalable DC microgrid using multi‐input multi‐output dual active half‐bridge (DAHB) converter is presented. The proposed microgrid architecture exhibits superiority and enhanced functionality in comparison to the existing conventional architectures in terms of the reduced number of converters for each resource integration, modularity, scalability, and bidirectional power flow capability, and local maximum power point tracking for each renewable resource. The proposed architecture is significant in terms that only a single converter is responsible for the whole operation of the DC microgrid. A dual half active bridge acts as a central hub for power processing while multiple renewable energy resources can be integrated through isolated input and output ports. The proposed microgrid is analysed for power flow, and the control scheme for different voltage and power‐sharing scenarios is designed. The proposed architecture of the microgrid is simulated on the Power‐SIM simulator, and a simplified hardware prototype is implemented in the laboratory with satisfactory results.

Solar photovoltaic (PV) direct current (DC) microgrids have gained significant popularity during the last decade for low cost and sustainable rural electrification. Various system architectures have been practically deployed, however, their assessment concerning system sizing, losses, and operational efficiency is not readily available in the literature. Therefore, in this research work, a mathematical framework for the comparative analysis of various architectures of solar photovoltaic-based DC microgrids for rural applications is presented. The compared architectures mainly include (a) central generation and central storage architecture, (b) central generation and distributed storage architecture, (c) distributed generation and central storage architecture, and (d) distributed generation and distributed storage architecture. Each architecture is evaluated for losses, including distribution losses and power electronic conversion losses, for typical power delivery from source end to the load end in the custom village settings. Newton–Raphson method modified for DC power flow was used for distribution loss analysis, while power electronic converter loss modeling along with the Matlab curve-fitting tool was used for the evaluation of power electronic losses. Based upon the loss analysis, a framework for DC microgrid components (PV and battery) sizing was presented and also applied to the various architectures under consideration. The case study results show that distributed generation and distributed storage architecture with typical usage diversity of 40% is the most feasible architecture from both system sizing and operational cost perspectives and is 13% more efficient from central generation and central storage architecture for a typical village of 40 houses. The presented framework and the analysis results will be useful in selecting an optimal DC microgrid architecture for future rural electrification implementations.