The installation of photovoltaic (PV) system for electrical power generation has gained a substantial interest in the power system for clean and green energy. However, having the intermittent characteristics of photovoltaic, its integration with the power system may cause certain uncertainties (voltage fluctuations, harmonics in output waveforms, etc.) leading towards reliability and stability issues. In PV systems, the power electronics play a significant role in energy harvesting and integration of grid-friendly power systems. Therefore, the reliability, efficiency, and cost-effectiveness of power converters are of main concern in the system design and are mainly dependent on the applied control strategy. This review article presents a comprehensive review on the grid-connected PV systems. A wide spectrum of different classifications and configurations of grid-connected inverters is presented. Different multi-level inverter topologies along with the modulation techniques are classified into many types and are elaborated in detail. Moreover, different control reference frames used in inverters are presented. In addition, different control strategies applied to inverters are discussed and a concise summary of the related literature review is presented in tabulated form. Finally, the scope of the research is briefly discussed.

To improve energy efficiency and reduce pollution emissions of ports with electricity and hydrogen substitution, this paper proposes a collaborative scheduling method of port integrated energy and container logistics considering electric and hydrogen-powered transport. By analyzing the coupling relationship between energy production and consumption in a port that deploys electric and hydrogen-powered transport, the scheduling optimization models of the port integrated energy system (PIES) and the port container logistic system (PCLS) are collaboratively established and rendered as a mixed-integer bi-level programming model. Moreover, to simplify the complexity of PCLS scheduling which involves the allocation and operation of each type of container logistics equipment, an assembly line of port container logistics (ALPCL) model based on flexible job-shop scheduling (FJSS) is further constructed. Then, a distributed algorithm based on the Benders decomposition (BD) embedded with an improved non-dominated sorting genetic (INSGA-II) is designed to realize optimal dispatch with limited data exchange and great solution efficiency. The results of case studies demonstrate the effectiveness of the proposed method for economic and environmental benefits, including a reduction in scheduling costs and pollution emissions. This method can also achieve co-improvement of energy and logistics efficiency

Water is a precious resource for agriculture and most of the land is irrigated by tube wells. Diesel engines and electricity-operated pumps are widely used to fulfill irrigation water requirements; such conventional systems are inefficient and costly. With rising concerns about global warming, it is important to choose renewable energy source. In this study, SPVWPS has been optimally designed considering the water requirement, solar resources, tilt angle and orientation, losses in both systems and performance ratio. A PVSyst and SoSiT simulation tools were used to perform simulation analysis of the designed solar photovoltaic WPS. After designing and performance analysis, farmers were interviewed during fieldwork to assess socioeconomic impacts. In the result section, performance of PV system is analyzed at various tilt angles and it is established that system installed at a 15° tilt angle is more efficient. The annual PV array virtual energy at MPP of designed photovoltaic system is 33342 kWh and the annual energy available to operate the WPS is 23502 kWh. Module array mismatch and ohmic wiring losses are 374.16 kWh and 298.83 kWh, respectively. The total annual water demand of the selected site is 80769 m³ and designed SPWPS pumped 75054 m³ of water, supplying 92.93% of the irrigation demand. The normalized values of the effective energy, system losses, collection losses and unused energy in the SPVWP system are 2.6 kW/kWp/day, 0.69 kW/kWp/day, 0.72 kW/kWp/day and 0.48 kW/kWp/day, respectively. The annual average performance ratio of the proposed system is 74.62%. The results of the interviews showed that 70% of farmers are extremely satisfied with the performance of SPVWPS and 84% of farmers indicated that they did not incur any operating costs. The unit cost of the SPWPS is 0.17 €/kWh, which is 56.41% and 19.04% less expensive than the cost of diesel and grid electricity.

Hybrid AC/DC microgrid architecture is emerging as an interesting and attractive approach since it combines the prominent benefits of both AC and DC networks. In Hybrid Microgrids (HMGs), AC and DC networks are interconnected with each other through power converters. Therefore, power converters play a very important role in HMG operation, as their functionality is not only limited to interconnection but also provides power flow control and improves the power quality through different ancillary services. Moreover, due to intermittency of Renewable Energy Resources (RESs), synchronization, load variation, availability of both AC and DC networks, etc., the controllability of the power converters, power management, and protection become very complex in HMG. This paper initially provides a comprehensive review of different interconnection methods and then presents an overview of different control strategies for HMG and Inter-Linking Converters (ILCs). Moreover, power management in different operating modes, including mode transition, is discussed in detail. This paper also provides a critical assessment of the available protection challenges of HMG. Finally, a comprehensive review of different available protection schemes and devices is provided.

The access of photovoltaics can reduce the carbon emissions of the integrated energy system and can also improve the economics of terminal energy supply, but the uncertainty of photovoltaic output also brings greater challenges to the optimal operation of the system. This paper focuses on coordinated optimization for the multiple energy systems in consideration of demand response. Latin hypercube sampling and the K-means algorithm are used to generate acceptable scenarios to deal with the photovoltaic uncertainty. Demand response based on Time-of-Use (TOU) electricity price is employed to realize the peak load shifting, and in consequence to improve the system operation. The optimization objective is to minimize the operational cost, subject to the constraints of electric grids, natural gas grids, and hot water pipeline grids. Due to the nonconvex constraints of these grids, the constraints are relaxed by means of the mixed integer linear programming approach, and the whole problem is established as a mixed integer linear programming model. Case studies show that demand response in each energy system and the coordinated optimization between the multiple energy systems can reduce the operational cost of the whole system. Even though the photovoltaic uncertainty results in a higher operational cost, the system has a more reliable operating point.