A review on the virtual power plant: Components and operation systems

© 2016 IEEE. Due to the high penetration of Distributed Generations (DGs) in the network and the presently involving competition in all electrical energy markets, Virtual Power Plant (VPP) as a new concept has come into view, with the intention of dealing with the increasing number of DGs in the system and handling effectively the competition in the electricity markets. This paper reviews the VPP in terms of components and operation systems. VPP fundamentally is composed of a number of DGs including conventional dispatchable power plants and intermittent generating units along with possible flexible loads and storage units. In this paper, these components are described in an all-inclusive manner, and some of the most important ones are pointed out. In addition, the most important anticipated outcomes of the two types of VPP, Commercial VPP (CVPP) and Technical VPP (TVPP), are presented in detail. Furthermore, the important literature associated with Combined Heat and Power (CHP) based VPP, VPP components and modeling, VPP with Demand Response (DR), VPP bidding strategy, and participation of VPP in electricity markets are briefly classified and discussed in this paper

Resiliency assessment of the distribution system considering smart homes equipped with electrical energy storage, distributed generation and plug-in hybrid electric vehicles

This paper presents a novel method for resiliency assessment of the distribution system considering smart homes' arbitrage strategies in the day-ahead and real-time markets. The main contribution of this paper is that the impacts of smart homes' arbitrage strategy on the resilient operation of the distribution system are explored. The optimal commitment of smart homes in external shock conditions is another contribution of this paper. An arbitrage index is proposed to explore the impacts of this process on the system costs and resiliency of the system. A two-level optimization process is proposed for day-ahead and real-time markets. At the first stage of the first level, the optimal bidding strategies of smart homes are estimated for the day-ahead market. Then, the database is updated and the optimal bidding strategies of smart homes for real-time horizon are assessed in the second stage of the first level problem. At the first stage of the second level problem, the optimal day-ahead scheduling of the distribution system is performed considering the arbitrage and resiliency indices. At the second stage of the second level, the distribution system optimal scheduling is carried out for the real-time horizon. Finally, at the third stage of the second level, if an external shock is detected, the optimization process determines the optimal dispatch of system resources. The proposed method is assessed for the 33-bus and 123-bus IEEE test systems. The proposed framework reduced the expected values of aggregated costs of 33-bus and 123-bus systems by about 62.14 % and 32.06 % for the real-time horizon concerning the cases in which the smart homes performed arbitrage strategies. Furthermore, the average values of the locational marginal price of 33-bus and 123-bus systems were reduced by about 59.38 % and 63.98 % concerning the case that the proposed method was not implemented.© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Evaluation of renewable energy technologies and their potential for technical integration and cost-effective use within the U.S. energy sector

pre-printEnergy demands, environmental impacts of energy conversion, and the depletion of fossil; fuels are constant topics of discussion in the energy industry. Renewable energy technologies; have been proposed for many years to address these concerns. However, the transformation; from traditional methods of power generation, usually based on fossil fuels, to power generation; based on renewable resources presents many challenges associated with emerging, or; less established, technologies. This paper examines the role of renewable energy in the U.S.; and its potential to meet current and future energy needs in a way that is technically and; economically sound. Renewable energy technologies, ranging from well-developed and established; to new and emerging technologies, are presented in terms of their technical potential,; current state of the technology, potential for further growth, and economic potential. While; renewable energy sources are abundant across the U.S., issues of dispatchability, variability,; scalability, energy storage, geographic limitations, and investment costs are critical in determining; future progress. The analysis in this paper can be used to guide the integration; of renewable energy systems toward becoming a larger share of energy production

Spatiotemporal Splitting of Distribution Networks into Self-Healing Resilient Microgrids using an Adjustable Interval Optimization

The distribution networks can convincingly break down into small-scale self-controllable areas, namely microgrids to substitute microgrids arrangements for effectively coping with any perturbations. To achieve these targets, this paper examines a novel spatiotemporal algorithm to split the existing network into a set of self-healing microgrids. The main intention in the grid-tied state is to maximize the microgrids profit while equilibrating load and generation at the islanded state by sectionalizing on-fault area, executing resources rescheduling, network reconfiguration and load shedding when the main grid is interrupted. The proposed problem is formulated as an exact computationally efficient mixed integer linear programming problem relying on the column & constraint generation framework and an adjustable interval optimization is envisaged to make the microgrids less susceptible against renewables variability. Finally, the effectiveness of the proposed model is adequately assured by performing a realistic case study.© 2020 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.fi=vertaisarvioitu|en=peerReviewed

PHOTOVOLTAIC PRODUCTION MANAGEMENT IN STOCHASTIC OPTIMIZED MICROGRIDS

The microgrids are composed of small scale fueled generation capacities, renewable energy sources, storage energy systems, controllable loads, and autonomously can connect or disconnect from the mains supply. The microgrids can operate connected to the upstream main grid, or in an islanded operation mode following a large perturbation in the upstream grid. The microgrid analyzed in this paper is composed of a photovoltaic system, a thermal engine, an electrochemical storage system, critical and interruptible loads. As backup generation is considered a classical generation engine and a small scale storage unit. The autonomous switching between grid-connected and islanding operation modes can occur, under an excess/deficit of generation and function of the electricity market price. The paper deals with an optimization model for minimizing the microgrid operation costs under intermittent generation and variable demand function of microgrid operation constrains. The optimization model is tested on a 24 hours horizon. The gridconnected optimized operation accounts also the exchanged power with the upstream grid function of the electricity price within the public network