This paper addresses the problem of output feedback control for high voltage direct current (HVDC) systems based on voltage source converters (VSC). Specifically, the system under study consists of two power grids and two VSC stations connected via a long HVDC cable. The primary goal of this paper is to propose a different approach for the online estimation of the grid voltage placed at a great distance from the control unit which is considered generally known, moreover the proposed technique aims to online estimation of the grid pulsation and the HVDC cable states, generally considered available. A nonlinear observer is intended to address these concerns. Only the line current measurements are used to estimate all state variables. Furthermore, utilizing the estimation offered by the proposed observer, an output feedback control strategy is formulated, using the backstepping design technique, to meet the three control objectives: (i) tight output voltage regulation of the HVDC cable; (ii) ensuring a perfect power quality at both sides of the HVDC system; (iii) regulation of the active power at the inverter station. The high effectiveness of the proposed output feedback controller’s performance is highlighted via a semi-experimental platform that includes a Processor In the Loop (PIL) on the embedded board eZdsp. Extra numerical simulations show that The proposed output feedback performance enjoys additional robustness properties and meets all control objectives.

The successful integration of renewable energy resources into the power grid hinges on the development of energy storage technologies that are both cost-effective and reliable. These storage technologies, capable of storing energy for durations longer than 10 hours, play a crucial role in mitigating the variability inherent in wind and solar-dominant power systems. To shed light on this matter, a transparent, least-cost macro energy model with user-defined constraints has been utilized for a case study of California. The model addresses all included technologies, solving for both hourly dispatch and installed capacities. Real-world historical demand and hourly weather data have been utilized to do this analysis. A novel approach has been introduced to assess the significance of long-duration energy storage technologies (LDS) in terms of their energy and power capacity. This method explores the contributions of pumped hydropower storage (PHS), compressed air energy storage (CAES), and power-to-gas-to-power (PGP) storage toward minimizing the overall balance of system cost. Historical electricity demand, hourly weather data, and current technology costs are used to investigate high-level implications for California’s power system options. Increasing the storage capacity of each technology from 1 to 10 hours results in 29.6%, 14.4%, and 7.5% cost reduction for PHS, CAES, and PGP cases respectively. However, in studied simulations, maximum availability (maximum) of pumped hydropower storage reduces the balance of system costs by 72.3% followed by CAES (60.6%) and PGP (48.6%) and suggests that pumped hydropower storage in combination with CAES/PGP could play an important role in California’s electricity system, provided that suitable sites can be identified and constructed at reasonable costs.