Future Challenges and Mitigation Methods for High Photovoltaic Penetration: A Survey

: Integration of high volume (high penetration) of photovoltaic (PV) generation with power grids consequently leads to some technical challenges that are mainly due to the intermittent nature of solar energy, the volume of data involved in the smart grid architecture, and the impact power electronic-based smart inverters. These challenges include reverse power flow, voltage fluctuations, power quality issues, dynamic stability, big data challenges and others. This paper investigates the existing challenges with the current level of PV penetration and looks into the challenges with high PV penetration in future scenarios such as smart cities, transactive energy, proliferation of plug-in hybrid electric vehicles (PHEVs), possible eclipse events, big data issues and environmental impacts. Within the context of these future scenarios, this paper reviewed the existing solutions and provides insights to new and future solutions that could be explored to ultimately address these issues and improve the smart grid’s security, reliability and resilienc

Towards transactive energy systems: An analysis on current trends

This paper presents a comprehensive analysis on the latest advances in transactive energy systems. The main contribution of this work is centered on the definition of transactive energy concepts and how such systems can be implemented in the smart grid paradigm. The analyzed works have been categorized into three lines of research: (i) transactive network management; (ii) transactive control; and (iii) peer-to-peer markets. It has been found that most of the current approaches for transactive energy are available as a model, lacking the real implementation to have a complete validation. For that purpose, both scientific and practical aspects of transactive energy should be studied in parallel, implementing adequate simulation platforms and tools to scrutiny the results.This work has received funding from the European Union's Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No. 771066) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2019.info:eu-repo/semantics/publishedVersio

Utilization of Distributed Generation in Power System Peak Hour Load Shedding Reduction

An approach to utilize Distributed Generation (DG) to minimize the total load shedding by analyzing the power system in Transactive energy framework is proposed. An algorithm to optimize power system in forward and spot markets to maximize an electric utility’s profit by optimizing purchase of power from DG is developed. The proposed algorithm is a multi-objective optimization with the main objective to maximize a utility’s profit by minimizing overall cost of production, load shedding, and purchase of power from distributed generators. This work also proposes a method to price power in forward and spot markets using existing LMP techniques. Transactive accounting has been performed to quantify the consumer payments in both markets. The algorithm is tested in two test systems; a 6-bus system and modified IEEE 14-bus system. The results show that by investing in DG, utility benefits from profit increase, load shedding reduction, and transmission line loading improvement

Power System Digital Twins and Real-Time Simulations in Modern Grids

Power systems are in a state of constant change with new hardware, software and applications affecting their planning, operation, and maintenance. Power system control centers are also evolving through new technologies and functionalities to adapt to current needs. System control rooms have moved from fully manual to automated operations, from analog to digital, and have become an embedded and complex information, communication, computation and control system. Digital twins are virtual representations of physical systems, assets and/or processes. They are enabled through software, hardware and data integration, and allow real-time monitoring, controlling, prediction, optimization, and improved decision-making. Consequently, digital twins arise as a technology capable of incorporating existing control systems along with new ones to collect, classify, store, retrieve and disseminate data for the future generation of control centers. Power system digital twins (PSDTs) can uplift how data from power grids and their equipment is processed, providing operators new ways to visualize and understand the information. Nevertheless, complexity and size of modern power systems narrow the scope a current digital twin can have. Furthermore, the services provided are limited to only certain phenomena and/or applications. This thesis addresses the need for a flexible and versatile solution that is also robust and adaptable for monitoring, operating and planning future power systems. The modular design for implementation of the next generation of PSDTs is proposed based on grid applications and/or services they can provide. From a modeling perspective, this thesis also distinguishes how real-time simulations enable the design, development, and operation of a PSDT. First, the need for enhanced power system modeling and simulation techniques is established. Moreover, the necessity of expanding to a more complete and varied open-source library of power system models is identified. The thesis continues by designing, developing, and testing models of inverter-based resources that can be used by the industry and researchers when developing PSDTs. Furthermore, the first-of-its-kind synthetic grid with a longitudinal structure, the S-NEM2300-bus benchmark model, based on the Australian National Electricity Market is created. The synthetic grid is, finally, used to illustrate the first steps towards implementing a practical PSDT