Developing integrated energy systems have been considered a feasible pathway to renewable-powered energy systems. The power to hydrogen technology is recognised as a promising method to enhance the economics of integrated energy systems and help reduce renewable curtailments. However, oxygen-enriched gas, which is the by-product of power to hydrogen processes (electrolysation), has not been fully utilised yet. It can be purified to produce medical oxygen at a low cost and may further increase the economics of integrated energy systems. Particularly, at this very moment, the consideration of the combined production of hydrogen and medical oxygen also has the potential to relieve the shortage of medical oxygen due to the outbreak of the 2019 novel coronavirus (COVID-19). This study proposes a model for the operation of integrated energy systems that consider the combined production of hydrogen and medical oxygen. This model is formulated as a convex mixed-integer optimisation problem that balances the electricity, heat and hydrogen demands every hour in a 24-hour period and balances oxygen demand on a daily basis. A test case of Taizhou City has been studied and results show that the combined production of hydrogen and medical oxygen improves the integrated energy system economics.

With the rapid development of renewable energy sources (RESs), adopting power-to-gas to improve the penetration of RESs is promising. This study designs a grid-forming application for the fuel cell/electrolyser (FC/ELZ) system to supply the frequency support for the grid as well as the voltage source. The detailed control methods including the DC, AC voltage controls and the power synchronisation control are designed for the FC/ELZ system so that it can operate independently without any other energy sources. Several simulation results are provided to demonstrate the effectiveness of the designed grid-forming application of the FC/ELZ system.

This study presents the performance of a novel hybrid islanding detection method for multi-single-phase photovoltaic (PV) inverters based on the combination of four active methods and three passive methods. Although islanding detection in PV multi-inverter systems has been widely researched, most islanding studies are focused on three-phase inverters, rather than single-phase ones. In this study, different active and passive methods are used to detect the islanding of four paralleled single-phase PV inverters. By combining those methods synergistically, it reduces their weakness of each method, while combining their advantages. The novelty of the proposed system methodology consists of four paralleled single-phase inverters equipped with four different active methods, namely active frequency drift, Sandia frequency shift (SFS), sliding mode frequency shift, and Sandia voltage shift triggered by a block composed of three passive methods: voltage frequency protection, rate of change of frequency, and DC-link. This novel hybrid system is studied under different detailed scenarios, where it shows its performance and characteristics.

The energy produced by bifacial photovoltaic (PV) arrays can be augmented via albedo enhancements. However, the value of the additional energy must outweigh the costs for such modifications to be economically viable. In this work, the electrical performance and economic value of six 13 kWp crystalline-silicon (c-Si) PV arrays with distinct configurations are evaluated. The system designs include horizontal single axis trackers (HSAT) and 25° fixed-tilt structures, monofacial and bifacial PV panels, and low and high ground albedo. The value of the system designs is assessed using onsite electrical measurements and spot prices from the Nord Pool electricity market. We find that HSAT systems increase the annual value factor (VF) by 4% and decrease levelized cost of energy (LCOE) by 3.5 EUR/MWh relative to fixed-tilt systems. The use of bifacial panels can increase the VF by 1% and decrease LCOE by 4.0 EUR/MWh. However, a negligible VF increase and modest LCOE decrease was found in systems with bifacial panels and ground albedo enhancements. Although our results show that albedo enhancements result in lower LCOE than designs without, the uncertainty in upfront and ongoing costs of altering the ground in utility-scale PV parks makes the solution presently unadvisable.

In order to better schedule distributed energy resources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the distribution network when a power outage occurs. The scheduling coefficient is defined to quantify the rationality of each scheduling resource. Based on this index, this study establishes an optimal scheduling model, which consists of three objectives. The non-dominated sorting genetic algorithm-II is applied to search this multi-objective optimal recovery solution in this study. Then, the modified IEEE 39-node system is used as the case study to verify the feasibility of the proposed model and the test results prove the effectiveness and efficiency of the proposed model.