The Experts below are selected from a list of 153 Experts worldwide ranked by ideXlab platform

Enrico Zio - One of the best experts on this subject based on the ideXlab platform.

  • Self-adaptable hierarchical clustering analysis and differential evolution for optimal integration of Renewable Distributed Generation
    Applied Energy, 2014
    Co-Authors: Rodrigo Mena, Martin Hennebel, Enrico Zio
    Abstract:

    In a previous paper, we have introduced a simulation and optimization framework for the integration of Renewable generators into an electrical distribution network. The framework searches for the optimal size and location of the Distributed Renewable Generation units (DG). Uncertainties in Renewable resources availability, components failure and repair events, loads and grid power supply are incorpo- rated. A Monte Carlo simulation–optimal power flow (MCS–OPF) computational model is used to gener- ate scenarios of the uncertain variables and evaluate the network electric performance with respect to the expected value of the global cost (ECG). The framework is quite general and complete, but at the expenses of large computational times for the analysis of real systems. In this respect, the work of the present paper addresses the issue and introduces a purposely tailored, original technique for reducing the computational efforts of the analysis. The originality of the proposed approach lies in the develop- ment of a new search engine for performing the minimization of the ECG, which embeds hierarchical clustering analysis (HCA) within a differential evolution (DE) search scheme to identify groups of similar individuals in the DE population and, then, ECG is calculated for selected representative individuals of the groups only, thus reducing the number of objective function evaluations. For exemplification, the frame- work is applied to a distribution network derived from the IEEE 13 nodes test feeder. The results show that the newly proposed hierarchical clustering differential evolution (HCDE) MCS–OPF framework is effective in finding optimal DG-integrated network configurations with reduced computational efforts.

  • A risk-based simulation and multi-objective optimization framework for the integration of Distributed Renewable Generation and storage
    Renewable and Sustainable Energy Reviews, 2014
    Co-Authors: Rodrigo Mena, Martin Hennebel, Carlos Ruiz, Enrico Zio
    Abstract:

    We present a simulation and multi-objective optimization framework for the integration of Renewable generators and storage devices into an electrical distribution network. The framework searches for the optimal size and location of the Distributed Renewable Generation units (DG). Uncertainties in Renewable resources availability, components failure and repair events, loads and grid power supply are incorporated. A Monte Carlo simulation – optimal power flow (MCS-OPF) computational model is used to generate scenarios of the uncertain variables and evaluate the network electric performance. As a response to the need of monitoring and controlling the risk associated to the performance of the optimal DG-integrated network, we introduce the conditional value-at-risk (CVaR) measure into the framework. Multi-objective optimization (MOO) is done with respect to the minimization of the expectations of the global cost (C g) and energy not supplied (ENS) combined with their respective CVaR values. The multi-objective optimization is performed by the fast non-dominated sorting genetic algorithm NSGA-II. For exemplification, the framework is applied to a distribution network derived from the IEEE 13 nodes test feeder. The results show that the MOO MCS-OPF framework is effective in finding an optimal DG-integrated network considering multiple sources of uncertainties. In addition, from the perspective of decision making, introducing the CVaR as a measure of risk enables the evaluation of trade-offs between optimal expected performances and risks.

Noboru Yamada - One of the best experts on this subject based on the ideXlab platform.

  • Distributed Renewable Generation and storage system sizing based on smart dispatch of microgrids
    Energies, 2016
    Co-Authors: Raji Atia, Noboru Yamada
    Abstract:

    This paper considers the contribution of independent owners (IOs) operating within microgrids (MGs) toward green power Generation in deregulated energy markets. An optimization scheme is introduced for sizing Distributed Renewable Generation (DRG) and a Distributed energy storage system (DESS) based on a novel energy management system (EMS) that accounts for demand response (DR), DESS dispatch and performance degradation, dynamic pricing environments, power distribution loss and irregular Renewable Generation. The proposed EMS utilizes an iterative Newton-Raphson linear programming algorithm that schedules resources in order to minimize the objective function, to deal with the complicated nonlinear nature of the problem and to enable efficient long-term assessments. The EMS is used to evaluate candidate solutions that are generated by a genetic algorithm (GA) to determine the optimal combination of DRG and DESS. A case study for IEEE 34-bus distribution MG in Okinawa, Japan, is used for testing the algorithm and analyzing the potential for IO/MG investments and their strategies.

Juan C. Vasquez - One of the best experts on this subject based on the ideXlab platform.

  • Centralized Control Architecture for Coordination of Distributed Renewable Generation and Energy Storage in Islanded AC Microgrids
    IEEE Transactions on Power Electronics, 2017
    Co-Authors: Nelson L. Diaz, Adriana Carolina Luna, Juan C. Vasquez
    Abstract:

    The coordinated operation of Distributed energy re- sources such as storage and Generation units and also loads is re- quired for the reliable operation of an islandedmicrogrid. Since in islanded microgrids the storage units are commonlyresponsible for regulating the voltage amplitude and frequency in the local power system, the coordination should consider safe operating limits for the stored energy, which prevents fast degradation or dam- age to the storage units. This paper proposes a centralized con- trol architecture, applicable for local area power systems such as a small-scale microgrid. The centralized architecture is based on three supervisory control tasks which consider: active power cur- tailment of Generation for avoiding overcharge of the storage units, load shedding actions for preventing deep discharge of the stor- age units, and equalization of the state of charge (SoC) among Distributed storage systems for avoiding uneven degradation. The proposed equalizationmethod has proved to be effective for equal- izing the SoC of Distributed energy storage systems and for en- suring uniform charge/discharge ratios regardless of differences in the capacity of the storage units. Additionally, the strategy is com- plemented with an optimal scheduling of load connection, which minimizes the connection and disconnection cycles of the loads within a time horizon of 24 h. The proposed architecture is veri- fied experimentally in a lab-scale prototype of a microgrid, which has real communication between the microgrid and the central controller.

Marcelo G Molina - One of the best experts on this subject based on the ideXlab platform.

  • energy storage and power electronics technologies a strong combination to empower the transformation to the smart grid
    Proceedings of the IEEE, 2017
    Co-Authors: Marcelo G Molina
    Abstract:

    The electric power industry is facing unprecedented transformations and challenges with the implementation of the smart grids. This new grid paradigm has arisen to build a flexible electric power system that better coordinates energy resources and loads aiming at efficiently delivering sustainable, economic and secure electricity supplies. As a part of the smart grids (SGs), microgrids (MGs) have been developed to exploit the full benefits from the integration of Distributed energy resources, especially Distributed Renewable Generation based on variable and intermittent sources, such as wind and solar. Nevertheless, meeting all these goal requires the implementation of innovative energy storage technologies integrated with high efficiency and very fast response electronic power conditioning systems to interface with the electrical grid. Power electronics systems play a key role in regulating the raw energy from energy storage systems (ESSs) and connecting to the electrical grid. Hence, this paper performs a comprehensive analysis of major technologies in electrical energy storage systems and their electronic interface for applications in smart grids. The work provides a complete study of the technology profile of both energy storage and power electronics suitable for applications in the evolving grid.

Tony Ahfock - One of the best experts on this subject based on the ideXlab platform.

  • the current state of Distributed Renewable Generation challenges of interconnection and opportunities for energy conversion based dc microgrids
    Journal of Cleaner Production, 2020
    Co-Authors: Shahid Ullah, Ahmed M A Haidar, Paul Hoole, Hushairi Zen, Tony Ahfock
    Abstract:

    Abstract As Distributed Renewable energy sources (RES) continue to expand, the necessity arises for more robust coordination approaches and conversion techniques to tackle the challenges introduced by uncertainties in Renewable Generation. Increasing concerns about energy efficiency and power grid security, such as the significant number of conversion stages for energy production from Renewable resources and the bidirectional power flow in the distribution system, have attracted attention to the topic. The presented comprehensive review in this paper discusses the merits and weaknesses of different integration strategies as supported by the literature review. In particular, the focus is placed on the challenges of interconnection and opportunities for direct current (DC) systems. The ultimate objective of this paper is to explore the most important power grid-wide effects due to the expected Renewable energy expansion and to gain insights on the availability characteristics of DC microgrids to facilitate their integration with the power grid. The idea behind this is to establish inferences that energy conversion based DC microgrids can be a possible solution to mitigate the negative effect of Renewable energy expansion. This is accomplished by systematically reviewing studies on power grid integration as well as providing technical analysis of the resulting outcomes in relation to the general impact of Renewable energy production, and then, conducting a comparative study on Renewable energy conversion based DC and alternating current (AC) systems. The types of bus topologies and control of DC distribution systems are also intensively reviewed and discussed. Moreover, the protection design considerations, control classifications and standards of DC microgrids are highlighted to explore the future research trends to be undertaken. The review concluded that the impact of interconnection on power grid can be eliminated through the use of intelligent control with advance communication technologies and the implementation of DC microgrids powered by sustainable resources in the distribution system.