The impact of grid-connected PV power plants (GCPPP) operation on the grid entails mandatory provision and conformable execution of futuristic grid-codes (GC) by GCPPP stakeholders. While standard GC-compliant reactive power injection occurs in the advent of voltage drops at the point of common coupling (PCC), weather-dependent active power delivery should also coincide. Hence, it is essential to derive the PV inverter current reference set-points meticulously and confine its current range. This paper proposes a novel control strategy for realization of enhanced LVRT operation in three-phase single-stage GCPPPs. The control scheme encompasses the following features: (a) PCC negative-sequence current reference set-points determination from its positive-sequence counterpart; as well as the analytical determination of PCC voltage sequence components, (b) GC-compliant reactive power injection, without causing second-order harmonic oscillations in the delivered active power to the grid during asymmetrical PCC faults, (c) utilization of a current limiter for immaculate regulation of the PV array output power. Simulation results reflect on the developed control scheme’s effectiveness in significantly improving GCPPP LVRT operation for a wide range of operating conditions.

Switch‐model power electronic inverters are heavily deployed as the main technology in enabling flow of variable DC power into the AC grid. Various distributed energy system (DES) architectures have been designed depending on many attributes including size and application of the installed system. The reliability of the power electronic interfaces (PEI), i.e. inverters is critical in all these architectures. Recent studies demonstrate enhanced operation of a PEI can be reached by optimum adjustment of its controller parameters. While conventional tuning methods are mostly based on trial and error, their optimum performance can be achieved for primarily first‐order systems. For systems with increasing number of PEIs or more complexity, application of these tuning methods becomes challenging and expensive. Thus, considering the operational performance of DES, a controller self‐tuning methodology has been presented for PEIs with particle swarm optimisation capability. The optimal parameters for both kW‐scale and multi‐megawatt PV systems’ inverters are determined via a time‐domain performance objective function. Typical PV system performances are presented for step changes and dynamic weather conditions. Effectiveness of the controller self‐tuning methodology has been demonstrated via the reduction of transient energy, when the system is subjected to dynamic changes and disturbances.

Power electronic interfaces (PEIs) play a significant role in integrating distributed energy sources (DER) into the electric power grid. In fact, as solution to grid integration of photovoltaic arrays, voltage source inverters (VSI) are widely utilized as the PEI entity. The VSI is controlled by a set of proportional-integral (PI) controllers, which require optimal tuning in order to guarantee smooth of PV-system is exposed to severe meteorological conditions e.g. Sudden cloud covers. Hence, developing a practical robust tuning method for optimizing the PV-inverter set of controllers i.e. The DC-link voltage controller, the reactive power controller, and the decoupled current controller becomes of paramount importance. This paper employs a computational intelligence (CI) approach to optimally tune these controllers based on online operation performance of the PV-System. The CI approach used effectually used for searching the inverter's PI controllers' parameters is the particle swarm optimization (PSO). The simulation results conclude the superiority of this approach in comparison to conventional inverter PI controller tuning methods, enhancing the PV-System transient and steady-state step-response over a wide operating range of irradiance.

The scope of this paper composes of data collection and synthesis, system design, cost analysis, demonstration and grid-connected operation of diesel-gensets, forming a proposed microgrid. The solar resource in Clemson was analyzed through historical data. From the findings, the microgrid component sizing was designed so as to supply the campus with sufficient energy for two-day islanding event. Eventually, for operational performance analysis case study, a microgrid is formed from inertial prime mover gensets for Clemson University to be connected to the western main campus substation in order to support the critical loads. Parallel generator unit connection enables support of critical load during islanding-mode of operation. Results indicate autonomous operation of 1.8MW generator-based microgrid under various scenarios including load sharing, load and droop variations, gensets disconnection and grid islanding modes.

Series FACTS devices have been successfully used for many years in order to enhance the stability and loadability of high voltage transmission networks. The principle is to compensate the inductive voltage drop in the line by an inserted capacitive voltage or in other words to reduce the effective reactance of the transmission line to enhance available transfer capability (ATC) in the network. ATC accurately reflects the physical realities of the transmission network, all system conditions, uses, and limits in a consistent manner. It depends on other parameters namely total transfer capability (TTC), capacity benefit margin (CBM), transmission reliability margin (TRM), and existing transmission commitments (ETC) that are described in this study thoroughly. This paper investigates the optimized use of FACTS devices and mainly thyristor controlled series capacitor (TCSC) to improve ATC and maximize total transfer capability generally defined as the maximum power transfer transaction between a specific power-seller and a power-buyer in a two area designed power system. The case study has been implemented on a 13-bus multi-machine test system using PowerWorld Simulator version 12.0. Furthermore, static linear analysis methods have been taken into account in calculating ATC and the impact on various factors has been defined clearly.