Power and Energy Student Summit 2019: 9 – 11 July 2019 Otto von Guericke University Magdeburg ; Conference Program

The book includes a short description of the conference program of the "Power and Energy Student Summit 2019". The conference, which is orgaized for students in the area of electric power systems, covers topics such as renewable energy, high voltage technology, grid control and network planning, power quality, HVDC and FACTS as well as protection technology. Besides the overview of the conference venue, activites and the time schedule, the book includes all papers presented at the conference

Transient stability assessment of hybrid distributed generation using computational intelligence approaches

Includes bibliographical references.Due to increasing integration of new technologies into the grid such as hybrid electric vehicles, distributed generations, power electronic interface circuits, advanced controllers etc., the present power system network is now more complex than in the past. Consequently, the recent rate of blackouts recorded in some parts of the world indicates that the power system is stressed. The real time/online monitoring and prediction of stability limit is needed to prevent future blackouts. In the last decade, Distributed Generators (DGs) among other technologies have received increasing attention. This is because DGs have the capability to meet peak demand, reduce losses, due to proximity to consumers and produce clean energy and thus reduce the production of CO₂. More benefits can be obtained when two or more DGs are combined together to form what is known as Hybrid Distributed Generation (HDG). The challenge with hybrid distributed generation (HDG) powered by intermittent renewable energy sources such as solar PV, wind turbine and small hydro power is that the system is more vulnerable to instabilities compared to single renewable energy source DG. This is because of the intermittent nature of the renewable energy sources and the complex interaction between the DGs and the distribution network. Due to the complexity and the stress level of the present power system network, real time/online monitoring and prediction of stability limits is becoming an essential and important part of present day control centres. Up to now, research on the impact of HDG on the transient stability is very limited. Generally, to perform transient stability assessment, an analytical approach is often used. The analytical approach requires a large volume of data, detailed mathematical equations and the understanding of the dynamics of the system. Due to the unavailability of accurate mathematical equations for most dynamic systems, and given the large volume of data required, the analytical method is inadequate and time consuming. Moreover, it requires long simulation time to assess the stability limits of the system. Therefore, the analytical approach is inadequate to handle real time operation of power system. In order to carry out real time transient stability assessment under an increasing nonlinear and time varying dynamics, fast scalable and dynamic algorithms are required. Transient Stability Assessment Of Hybrid Distributed Generation Using Computational Intelligence Approaches These algorithms must be able to perform advanced monitoring, decision making, forecasting, control and optimization. Computational Intelligence (CI) based algorithm such as neural networks coupled with Wide Area Monitoring System (WAMS) such as Phasor Measurement Unit (PMUs) have been shown to successfully model non-linear dynamics and predict stability limits in real time. To cope with the shortcoming of the analytical approach, a computational intelligence method based on Artificial Neural Networks (ANNs) was developed in this thesis to assess transient stability in real time. Appropriate data related to the hybrid generation (i.e., Solar PV, wind generator, small hydropower) were generated using the analytical approach for the training and testing of the ANN models. In addition, PMUs integrated in Real Time Digital Simulator (RTDS) were used to gather data for the real time training of the ANNs and the prediction of the Critical Clearing Time (CCT)

Optimal Control of Hybrid Systems and Renewable Energies

This book is a collection of papers covering various aspects of the optimal control of power and energy production from renewable resources (wind, PV, biomass, hydrogen, etc.). In particular, attention is focused both on the optimal control of new technologies and on their integration in buildings, microgrids, and energy markets. The examples presented in this book are among the most promising technologies for satisfying an increasing share of thermal and electrical demands with renewable sources: from solar cooling plants to offshore wind generation; hybrid plants, combining traditional and renewable sources, are also considered, as well as traditional and innovative storage systems. Innovative solutions for transportation systems are also explored for both railway infrastructures and advanced light rail vehicles. The optimization and control of new solutions for the power network are addressed in detail: specifically, special attention is paid to microgrids as new paradigms for distribution networks, but also in other applications (e.g., shipboards). Finally, optimization and simulation models within SCADA and energy management systems are considered. This book is intended for engineers, researchers, and practitioners that work in the field of energy, smart grid, renewable resources, and their optimization and control

Energy, a continuing bibliography with indexes. Issue 33

This bibliography lists 1211 reports, articles, and other documents introduced into the NASA scientific and technical information system from January 1, 1981 through March 31, 1981

Cascading Outages Detection and Mitigation Tool to Prevent Major Blackouts

Due to a rise of deregulated electric market and deterioration of aged power system infrastructure, it become more difficult to deal with the grid operating contingencies. Several major blackouts in the last two decades has brought utilities to focus on development of Wide Area Monitoring, Protection and Control (WAMPAC) systems. Availability of common measurement time reference as the fundamental requirement of WAMPAC system is attained by introducing the Phasor Measurement Units, or PMUs that are taking synchronized measurements using the GPS clock signal. The PMUs can calculate time-synchronized phasor values of voltage and currents, frequency and rate of change of frequency. Such measurements, alternatively called synchrophasors, can be utilized in several applications including disturbance and islanding detection, and control schemes. In this dissertation, an integrated synchrophasor-based scheme is proposed to detect, mitigate and prevent cascading outages and severe blackouts. This integrated scheme consists of several modules. First, a fault detector based on electromechanical wave oscillations at buses equipped with PMUs is proposed. Second, a system-wide vulnerability index analysis module based on voltage and current synchrophasor measurements is proposed. Third, an islanding prediction module which utilizes an offline islanding database and an online pattern recognition neural network is proposed. Finally, as the last resort to interrupt series of cascade outages, a controlled islanding module is developed which uses spectral clustering algorithm along with power system state variable and generator coherency information

Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems

The transition to 100% renewable energy in the future is one of the most important ways of achieving "carbon peaking and carbon neutrality" and of reducing the adverse effects of climate change. In this process, the safe, stable and economical operation of renewable energy generation systems, represented by hydro-, wind and solar power, is particularly important, and has naturally become a key concern for researchers and engineers. Therefore, this book focuses on the fundamental and applied research on the modeling, control, monitoring and diagnosis of renewable energy generation systems, especially hydropower energy systems, and aims to provide some theoretical reference for researchers, power generation departments or government agencies

Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on the Energy Internet, blockchain technology and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

Investigation on the Benefits of Safety Margin Improvement in CANDU Nuclear Power Plant Using an FPGA-based Shutdown System

The relationship between response time and safety margin of CANadian Deuterium Uranium (CANDU) nuclear power plant (NPP) is investigated in this thesis. Implementation of safety shutdown system using Field Programmable Gate Array (FPGA) is explored. The fast data processing capability of FPGAs shortens the response time of CANDU shutdown systems (SDS) such that the impact of accident transient can be reduced. The safety margin, which is closely related to the reactor behavior in the event of an accident, is improved as a result of such a faster shutdown process. Theoretical analysis based on neutron dynamic theory is carried out to establish the fact that a faster shutdown process can mitigate accidental consequences. To provide more realistic test cases from a thermalhydraulic perspective, an industry grade simulation tool known as CATHENA is used to generate comparable accident-shutdown transients for different SDS response times. Results from both verification methods explicitly prove the feasibility of improving the safety margin via faster shutdown process. To demonstrate this concept, a prototype of the proposed faster SDS is constructed. The trip logic of CANDU shutdown system No.1 (SDS1) is converted into a digital hardware design and implemented within chosen FPGA platform. The functionality of the FPGA-based SDS1 is implemented, and the response times are tested and compared to those of the existing CANDU SDS1. The achieved 10.5 ms response time of the FPGA-based SDS1 is again applied to the CATHENA simulation process to quantitatively present the 26.98% improvement in the safety margin. To investigate potential improvement in safety margin by using FPGA technology, hardware-in-the-loop (HIL) simulation is performed by connecting the FPGA-based SDS1 to an NPP training simulator. The 6.26% improvement in safety margin has been verified, based on which a 10% potential power upgrade is discussed as another benefit of applying FPGA technology to CANDU NPPs

IEA ECES Annex 31 Final Report - Energy Storage with Energy Efficient Buildings and Districts: Optimization and Automation

At present, the energy requirements in buildings are majorly met from non-renewable sources where the contribution of renewable sources is still in its initial stage. Meeting the peak energy demand by non-renewable energy sources is highly expensive for the utility companies and it critically influences the environment through GHG emissions. In addition, renewable energy sources are inherently intermittent in nature. Therefore, to make both renewable and nonrenewable energy sources more efficient in building/district applications, they should be integrated with energy storage systems. Nevertheless, determination of the optimal operation and integration of energy storage with buildings/districts are not straightforward. The real strength of integrating energy storage technologies with buildings/districts is stalled by the high computational demand (or even lack of) tools and optimization techniques. Annex 31 aims to resolve this gap by critically addressing the challenges in integrating energy storage systems in buildings/districts from the perspective of design, development of simplified modeling tools and optimization techniques