Future Power System Control Research Articles

Perspectives on Future Power System Control Centers for Energy Transition

Today's power systems are seeing a paradigm shift under the energy transition, sparkled by the electrification of demand, digitalisation of systems, and an increasing share of decarbonated power generation. Most of these changes have a direct impact on their control centers, forcing them to handle weather-based energy resources, new interconnections with neighbouring transmission networks, more markets, active distribution networks, micro-grids, and greater amounts of available data. Unfortunately, these changes have translated during the past decade to small, incremental changes, mostly centered on hardware, software, and human factors. We assert that more transformative changes are needed, especially regarding humancentered design approaches, to enable control room operators to manage the future power system. This paper discusses the evolution of operators towards continuous operation planners, monitoring complex time horizons thanks to adequate real-time automation. Reviewing upcoming challenges as well as emerging technologies for power systems, we present our vision of a new evolutionary architecture for control centers, both at backend and frontend levels. We propose a unified hypervision scheme based on structured decision-making concepts, providing operators with proactive, collaborative, and effective decision support.

Siamese recurrent neural networks for the robust classification of grid disturbances in transmission power systems considering unknown events

The automated identification and localisation of grid disturbances is a major research area and key technology for the monitoring and control of future power systems. Current recognition systems rely on sufficient training data and are very error-prone to disturbance events, which are unseen during training. This study introduces a robust Siamese recurrent neural network using attention-based embedding functions to simultaneously identify and locate disturbances from synchrophasor data. Additionally, a novel double-sigmoid classifier is introduced for reliable differentiation between known and unknown disturbance types and locations. Different models are evaluated within an open-set classification problem for a generic power transmission system considering different unknown disturbance events. A detailed analysis of the results is provided and classification results are compared with a state-of-the-art open-set classifier.

Two-level agent-based scheduling for a cluster of heating systems

The ongoing decentralization of the electrical power system encompasses the installation of residential electrical loads and generators, such as electro-thermal heating devices. Clusters of these devices in combination with thermal storage can play a significant role in future power system control as they introduce load and generation flexibility into the system. Hence, control concepts which are attractive for both power system level and end user side are required. This work proposes a novel decentralized scheduling approach for electro-thermal heating devices based on a multi-agent system architecture. As a major novelty, the approach addresses both of the aforementioned appeals on two levels without central control. First, local planning with individual objectives is performed. Second, the heating devices cooperate to find the combination of local plans serving best a given energy system objective. This approach is fully decentralized and has a strong end user involvement. The performance of the proposed approach related to end user and system level objectives is compared to that of centralized approaches. Simulation results show that the new method can successfully satisfy end user objectives and provide energy fluctuation balancing. Finally, drawbacks compared to centralized scheduling are analyzed.

Compensating active power imbalances in power system with large-scale wind power penetration

Large-scale wind power penetration can affect the supply continuity in the power system. This is a matter of high priority to investigate, as more regulating reserves and specified control strategies for generation control are required in the future power system with even more high wind power penetration. This paper evaluates the impact of large-scale wind power integration on future power systems. An active power balance control methodology is used for compensating the power imbalances between the demand and the generation in real time, caused by wind power forecast errors. The methodology for the balance power control of future power systems with large-scale wind power integration is described and exemplified considering the generation and power exchange capacities in 2020 for Danish power system.

Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems

Recently, the academic and industrial literature has coalesced around an enhanced vision of the electric power grid that is intelligent, responsive, dynamic, adaptive and flexible. One particularly emphasized “smart-grid” property is that of resilience where healthy regions of the grid continue to operate while disrupted and perturbed regions bring themselves back to normal operation. Multi-agent systems have recently been proposed as a key enabling technology for such a resilient control scheme. While the power system literature has often addressed multi-agent systems, many of these works did not have resilience as the central design intention. This paper now has a two-fold purpose. First, it seeks to identify a set of multi-agent system design principles for resilient coordination and control of future power systems. To that end, it draws upon an axiomatic design for large flexible engineering systems model which was recently used in the development of resilience measures. From this quantitative model, a set of design principles are easily distilled. Second, the paper assesses the adherence of existing multi-agent system implementations with respect to these design principles. The paper concludes that while many multi-agent systems have been developed for power grids, they have been primarily intended as the decentralization of a particular decision-making/control algorithm. Thus many of the works make only limited contributions to power grid resilience.

English

2 ABSTRACT: Plug in Hybrid Electric Vehicles (PHEVs) charging and discharging, renewable energy resource generation and utilization is most important in future power system control. Proper integration of these energy sources gives solution to the challenges. In this paper Mixed Integer Linear Programming (MILP) was proposed for plug in Hybrid Electric Vehicles charging and discharging in a charging station. Charging station consists of Photo Voltaic (PV) system with practical constraints, power balance constraints, battery charging and discharging constraints are considered. The results proposed that the proposed algorithm minimize the charging cost of PHEVs and optimal power flow for the grid connected PHEVs systems. Likewise, PHEVs owners could yield more profit by discharging their vehicles to the grid in addition to having preferred charge in the departure time.