Grid Friendly Operation of a PV-Storage System with Profit Maximization and Reliability Enhancement

IEEE Trans. Power Syst.

Kolios

et al. 2022

Self Cite

“…[4]. Problem P O (w) is non-convex, and hence challenging to solve due to the presence of the non-convex constraints (1c), (5d) and (12).…”

Section: B Constraints 1) Power Flow Constraintsmentioning

confidence: 99%

“…2) Relaxation of the ESS power losses: The non-convex constraint in (12) is relaxed to the convex constraint:…”

Section: A Convexifying Problem P O (W)mentioning

confidence: 99%

See 1 more Smart Citation

Energy Management and Control of Photovoltaic and Storage Systems in Active Distribution Grids

IEEE Trans. Power Syst.

Kolios

et al. 2022

Self Cite

“…Peak shaving applications are investigated in [4]- [5] for planning purposes, to examine the location, sizing and costbenefit of the ESSs. In addition, peak shaving services provided to distribution grids using BESSs are proposed in [6]- [11] for operational purposes using optimization methods. These services are provided by minimizing the daily peak power [6]- [9] or the square of the power drawn from the feeder [10].…”

Section: Introductionmentioning

confidence: 99%

Energy Management and Control of a Flywheel Storage System for Peak Shaving Applications

Charalampous

et al. 2021

IEEE Trans. Smart Grid

Self Cite

Peak shaving applications provided by energy storage systems enhance the utilization of existing grid infrastructure to accommodate the increased penetration of renewable energy sources. This work investigates the provision of peak shaving services from a flywheel energy storage system installed in a transformer substation. A lexicographic optimization scheme is formulated to define the flywheel power set-points by minimizing the transformer power limit violations and the flywheel energy losses. Convex functions that represent the flywheel power losses and its maximum power are derived and integrated in the proposed scheme. A two-level hierarchical control framework is introduced to operate the transformer-flywheel-system in a way that handles prediction errors and modelling inaccuracies. At the higher level, a model predictive controller is developed that solves the lexicographic optimization scheme using linear programming. At the lower-level, a secondary controller corrects the power set-points of the model predictive controller using realtime measurements. A software platform has been developed for integrating the proposed controllers in an experimental setup to test their effectiveness in a realistic testbed setting, and the flywheel system characteristics are experimentally identified. Simulation and experimental results validate and verify the modelling, identification, control and operation of a real flywheel system for peak shaving services.

“…Peak shaving applications are investigated in [3]- [5] for planning purposes, to examine the location, sizing and the cost-benefit of the ESSs in distribution feeders. Optimization methods to provide peak shaving services are proposed in [6]- [9]. The methods proposed in [6]- [7] aim to reduce the peak load of the feeder for the next day by scheduling the charging/discharging of a battery energy storage system (BESS).…”

Section: Introductionmentioning

confidence: 99%

Modelling and energy management of a flywheel storage system for peak shaving applications

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Charalampous

et al. 2020

Self Cite

Peak shaving applications provided by energy storage systems are sustainable solutions for enhancing the existing capacity of distribution feeders and transformers in order to maintain their safe and reliable operation under an increased penetration of renewable energy sources and load demand growth. This work investigates the integration of a flywheel energy storage system installed in a feeder of a distribution network to provide peak shaving services. An empirical model is defined to determine the energy losses of a prototype flywheel system using an experimental setup. Furthermore, a multiobjective optimization scheme is proposed to minimize the flywheel energy losses along with the violated peak power of the feeder. Three different objective functions for applying peak shaving are presented and their efficiency is investigated in the simulation results. Finally, the impact of the flywheel energy losses on the peak shaving application of the distribution feeder is examined using a prototype and a commercial-grade flywheel energy storage system.