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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. ; © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Citation for published version (IEEE format): L. Tziovani, L. Hadjidemetriou, C. Charalampous, S. Timotheou and E. Kyriakides, " Modelling and energy management of a flywheel storage system for peak shaving applications," 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Delft, Netherlands, 2020, pp. 1-5. This work is supported in part by the European Regional Development Fund and the Republic of Cyprus through the Research and Innovation Foundation (Project: INTEGRATED/0916/0035), and in part by European Union's Horizon 2020 research and innovation programme under ...

Energy storage providing auxiliary service at the user-side has broad prospects in support of national polices. Three auxiliary services are selected as the application scene for energy storage participating in demand management, peak shaving and demand response. Considering the time value of funds, the user-side energy storage economy model is built. The model comprehensively considers the delayed transformation income, the government subsidy income, the auxiliary service income and the whole-life-cycle cost factor. According to the cost and benefit analysis, an energy storage optimization configuration model is proposed. The model takes maximum revenue of industrial user in energy storage&rsquo ; s whole-life-cycle as the objective function. Then, the Cplex solver is employed to solve the model. In addition, four indexes are utilized to evaluate the financial effect brought by the user-side energy storage. Finally, the revenue and configuration results of the four types of battery energy storage are calculated to verify the validity of the proposed model. In comparison to the value of evaluation index, planning suggestions are provided for the user-side energy storage providing different auxiliary services. Moreover, the conditions of profit and worthwhile investment are obtained through sensitivity analysis of energy storage providing peak shaving service.

Unlike traditional methods of electricity generation such as thermal power, renewable energy sources like wind power exhibit characteristics of randomness and volatility, leading to unstable power generation. With the continuous increase in grid-connected capacity of renewable energy sources like wind power, the demand for grid peak shaving is on the rise, highlighting the issue of inadequate peak shaving capacity in China's power system. As a primary source for peak shaving in the country, thermal power units incur significant revenue losses when participating in deep peak shaving, and under the current mechanism, they cannot obtain sufficient compensation for deep peak shaving. In response to these issues, the paper proposes a method for compensating thermal power units for deep peak shaving. Firstly, considering the reduced efficiency of thermal power units during low-load operation, a cost model for the operation of thermal power units is established. Secondly, building upon the existing compensated peak shaving baseline, a method for compensating thermal power units for deep peak shaving is introduced. Finally, using a simulation of a local power grid in Liaoning Province as an example, an analysis of the compensation for thermal power peak shaving and overall profits under the existing mechanism and the proposed mechanism is conducted. The results obtained validate the rationality and effectiveness of the method proposed in the paper, offering insights for the development of a compensation mechanism for thermal power deep peak shaving.

What China committed in the Paris Agreement encourages the penetration of renewable energy in power grid. To consume more renewable energy, coal-fired units undertake the most part of peak shaving task and are usually operated at a low-load level during off-peak hours. However, deep peak shaving has harmed the benefits of thermal power plants and also brought about environmental problems. To improve the peak-shaving capacity and operation efficiency of coal-fired units, the government encourages the flexibility retrofits for coal-fired units. In this paper, peak-shaving related cost functions are proposed for the multi-angle economic analysis of coal-fired unit with plasma ignition (UPI) and oil injection (UOI), respectively. First, the operation characteristic is analyzed for three stages of peak shaving, and then the peak-shaving costs related to these three stages are proposed in terms of the coal consumption cost, wear-and-tear cost, combustion-supporting cost, and environmental cost. Afterwards, a peak-shaving cost-based economic dispatch model is presented with consideration of the curtailed wind penalty, and an environmental efficiency index is defined to evaluate the environmental benefits. Finally, in the case study, quantitative economy analysis is performed from the aspects of thermal power plants, wind power plants, and the environment separately, and the simulation results indicate that UPI has better peak-shaving economy and environmental efficiency than UOI.