Stochastic simulation of power systems with integrated intermittent renewable resources

Reliability and economic evaluation of power system with renewables: A review

Guest Editorial: Situational awareness of integrated energy systems

Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions

It was a great pleasure to welcome all the participants from different countries to the 2020 International Conference on Smart Grid and Energy Engineering in Guilin, China during November 13-15, 2020. This three-day conference was organized by AEIC Academic Exchange Information Centre and co-organized by GUANGZHOU Computer Society. SGEE 2020 is to bring together innovative academics and industrial experts in the field of Smart Grid and Energy Engineering to a common forum. The primary goal of the conference is to promote research and developmental activities in Smart Grid and Energy Engineering and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Smart Grid and Energy Engineering and related areas.The conference model was divided into two sessions, including oral presentations and keynote speeches. In the first part, some scholars, whose submissions were selected as the excellent papers, were given 15 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches.In this conference, we are greatly honored to have invited Prof. Om P. Malik from University of Calgary, Canada to serve as our Conference Chairmen. During the conference, we were pleased to invite six distinguished experts to present their insightful speeches. The first keynote speaker, Prof. Z.Y. Dong, The University of New South Wales, Australia, held a speech on Promoting Renewable Energy with Virtual Power Plants. In this talk, the energy market rules which provides opportunities for VPP development were presented, together with methodologies on smart energy management for VPP applications. Prof. Juan Yu from Chongqing University, China, talked about Data-driven Methods for Operational Reliability Assessment of Power Systems Integrated with High-penetration Renewables. Her speech focusing on the computational efficiency of the operational reliability assessment in power systems that contain high penetration renewables, this presentation lays a theoretical foundation to support practical applications of an online high-accuracy operational reliability assessment. Prof. Alberto Borghetti, University of Bologna, Italy, shared a speech on his specialty related to Scheduling problems in local energy communities. This presentation is aimed to describe some models that could be useful for the operation of energy communities and distribution networks where trading between neighbors becomes significant. A/Prof. Farhad Shahnia, Murdoch University, Australia, made an insightful speech on Recent and Future Research on Microgrid Clusters. This talk briefly introduced the progress of research in this field around the world and Australia, and also discussed some of the technical challenges associated with interconnection of neighbouring microgrids as a key step to improve their survivability in the course of unexpected imbalances between the demand and the available generation from intermittent renewable resources. Prof. Xinyu Chen, Huazhong University of Science and Technology, China, delivered a speech: Towards Higher Penetration of Renewable Challenge and Opportunities. This talk focused on deepen the understanding of how the environmental regulations and low carbon polices influence the operation, planning and markets for power systems in different counties. As the last keynote speaker, Prof. Shouxiang Wang from Tianjin University, China. His research area: microgrid, smart distribution system, uncertainty analysis of power system.We are glad to share with you that we received lots of submissions from the conference and we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewed them. These papers feature following topics but are not limited to: Smart Grid Information Engineering, Electric Drive and Applications, Renewable Energy, Energy Efficiency and other related topics. All the papers have been through rigorous review and process to meet the requirements of International publication standard.We are really grateful to the International/ National advisory committee, keynote speakers, session chairs, organising committee members, student volunteers and administrative assistance of the management section of University, including accounts section, digital media and publication house. Also, we are thankful to all the authors for contributing a large number of papers in the conference, because of which the conference became a story of success. It was the quality of their presentations and their passion to communicate with the other participants that really make this conference series a great success.The Organizing Committee of SGEE 2020List of Committee member are available in this pdf.

Power system is one of the most complex systems ever designed. Determining its reliability is therefore a demanding process, which is mostly dealt with in a way that partial problems are stated and solved. A reliability method of loss of load expectation is selected and improved and the model of conventional power system is considered as a standpoint. Reliability of the initial conventional power system is evaluated. Then, the conventional power system is changed, where one conventional power plant is abandoned and new wind power plants stand to its place. The reliability of the initial and the changed power system is calculated and compared. Discussion shows the problems of decreased reliability of the power system with increasing the percentage of wind power plants within the power system replacing conventional plants, if not enough reserve is added to the power system at the same time. The other related problems are discussed in addition, to show that the problem is very complex and one cannot only consider a limited number of influencing parameters when deciding on power system configurations.

The micro-grid concept has recently gained increasing attention for power system operators to increase the operational effectiveness and provide a more reliable, sustainable and economic power system. To ensure the autonomous power supply when disconnected from the bulk power system, energy storage system (ESS) options as well as demand side flexibility can be used to provide the local balance between time-varying production and consumption in a micro-grid structure. In this study, the demand side flexibility via thermostatically controllable appliances (TCAs)-based direct load control (DLC) strategies and common ESSs-based bi-directional energy flow possibility is considered for the economic operation of a micro-grid. Different case studies are conducted for validating the effectiveness of the proposed structure.

The planning of electrical power systems in remote island areas poses a few challenges, such as requiring many load centers, various energy sources, and certain geographical conditions, which leads to inefficiencies in energy production. For this reason, it is necessary to plan an electrical transmission system to efficiently transfer the power between load centers. Previous research has found that the completion of the most economical power system will be achieved in 2050 on the condition that the Ambon, Seram, Haruku, and Saparua (Ambon-SHS) systems are interconnected in 2025. Providing complementary support, this paper conducts a power system analysis to assess the proposed interconnection system in Maluku Island, which has several islands, small load centers, and local renewable energy resources. The power system analysis was performed using DIgSILENT PowerFactory and was carried out every 5 years of the system planning period until 2050. The results show that the design of the obtained transmission system meets the standard security criteria, which include thermal loading and voltage, being under both normal and N-1 contingency conditions, a short-circuit current, voltage stability, frequency stability, and transient stability. Finally, this paper demonstrates that the proposed plan is economically and technically feasible.

The load frequency control (LFC) problem in interconnected multiarea power systems is facing more challenges due to increasing uncertainties caused by the penetration of intermittent renewable energy resources, random changes in load patterns, uncertainties in system parameters and unmodeled system dynamics, leading to a compromised reliability of power systems and increasing the risk of power outages. In responding to this problem, this paper proposes a decentralized disturbance observer-based sliding mode LFC scheme for multiarea interlinked power systems with external disturbances. First, a reduced power system order is constructed by lumping disturbances from tie-line power deviations, load variations and the output power from renewable energy resources. The disturbance observer is then designed to estimate the lumped disturbance, which is further utilized to construct a novel integral-based sliding surface. The necessary and sufficient conditions to determine the tuning parameters of the sliding surface are then formulated in terms of linear matrix inequalities (LMIs), thus guaranteeing that the resultant sliding mode dynamics meet the <i>H</i>_&#x221E; performance requirements. The sliding mode controller is then synthesized to drive the system trajectories onto the predesigned sliding surface in finite time in the presence of a lumped disturbance. From a practical perspective, the merit of the proposed control method minimizes the impact of the lumped disturbance on the system frequency, which has not been considered to date in sliding mode LFC design. Numerical simulations are illustrated to validate the effectiveness of the proposed LFC strategy and verify its advantages over other approaches.

This work deals with assessing the reliability of wind energy sources incorporated into a microgrid system to increase grid stability. As the share of power generated from wind energy continues to increase due to environmental concerns and to reduce carbon footprints, the case study proposed is designing an effective wind energy system for a smart building environment to reduce the burden on the grid. Incorporating wind energy systems into grid-connected buildings increases the reliability of the microgrid system for smart building environments. Applying smart techniques with integrated automation in the built environment can play a key role in decreasing peak demand for load development in smart cities. This can also enhance the overall efficiency of power grids, reduce waste, and enable the effective use of energy resources. Furthermore, researchers are finding new ways to collect energy from renewable sources and power-built environments due to dwindling fossil fuel resources and increased environmental awareness. The analysis of wind-connected power systems has been initiated to satisfy the increasing demand for reliable supply systems by consumers. This has prompted the use of wind energy systems with controlled techniques to enhance the reliability of power systems and reduce carbon footprints generated by fossil fuel-based power systems. Therefore, the main purpose of this work is to understand the economic prospects of wind energy sources for smart building environments, reliability analysis of wind energy sources-based power systems, reduce carbon footprints, and balance power demand through wind energy systems. The Progressive Wind Model Taylor-Sequence Proliferation (PWMTSP) and Innovative Six Parameters Based Progressive Beta Creative Model (ISPBPBCM) approaches are proposed to understand the reliability of wind energy-based power systems in smart building environments. The work also provides an economic analysis of the proposed low-cost wind power system with different capacities for residential consumers in selected geographic location. Eight cases are considered for the proposed effective wind energy system for smart building environments ranging from 2 MW to 32 MW. Hence, the economic analysis of the proposed systems is discussed for residential users. All eight cases are eco-friendly and reduce carbon emissions as these generated units from wind energy sources need not be purchased from fossil fuel-based plants, which increases the reliability of the proposed system. The expected energy not supplied (EENS) in the planned work increases as wind power capacity increases. Loss of load expectation (LOLE), loss of load probability (LOLP), and failure rate all decrease with the installation of more wind power systems. Moreover, it can be seen that mean time to repair (MTTR) improves when wind energy capacity rises incrementally from 2 MW to 32 MW. The proposed method is anticipated to be adaptable to various types of wind energy systems where dependability is a crucial component of system design and scalable to large wind integrated power systems.

The ionizing radiation exposure to crew on current and future space missions can significantly increase their health risks for cancers, degenerative diseases, and other acute and late effects. A common approach for estimating risk to crew is by completing stochastic (e.g., Monte Carlo) or deterministic particle transport simulations. Within the simulated environment, a small fraction of the particle histories tracked will interact with the astronaut or detector, particularly for larger spacecraft such as the International Space Station, Tiangong Space Station or Lunar Gateway. These simulations can be computationally intensive as they require a very large number of particle histories to achieve a low statistical uncertainty. Variance reduction techniques are applied to simulations to reduce the computational time of the simulation while maintaining the same (or less) statistical uncertainty. The variance reduction technique developed herein involves applying a directional source bias to an isotropic radiation field, such as galactic cosmic rays, to reduce the quantity of particles that have a low probability of interacting with the astronaut or detector. A custom application has been developed utilizing the Geant4 Toolkit that computes the trajectories and energies of particles in three dimensions in the International Space Station using the Monte Carlo method. The results demonstrate the impact of our variance reduction technique on effective dose equivalence depending on: primary and secondary particle type (proton, neutron, photon, heavy ion, etc.), geometric volumes and spacecraft materials. Our variance reduction technique can be tuned by the user to optimize the simulation time depending on their objectives and enables rapid testing of different shield configurations and materials. This variance reduction technique is implemented easily using several input parameters for boundary conditions. Recommended values are presented for rapid implementation in simulations.

The impact of variable renewable energy resources on power system reliability

Synergistic effect of complementary cleaner energy sources on controllable emission from hybrid power systems in optimal power flow framework

Foreword . Preface . Acknowledgements . 1 Energy and Electricity . 1.1 The World Energy Scene. 1.2 The Environmental Impact of Energy Use. 1.3 Generating Electricity. 1.4 The Electrical Power System. References. 2 Features of Conventional and Renewable Generation . 2.1 Introduction. 2.2 Conventional Sources: Coal, Gas and Nuclear. 2.3 Hydroelectric Power. 2.4 Wind Power. 2.5 PV and Solar Thermal Electricity. 2.6 Tidal Power. 2.7 Wave Power. 2.8 Biomass. 2.9 Summary of Power Generation Characteristics. 2.10 Combining Sources. References. 3 Power Balance/ Frequency Control . 3.1 Introduction. 3.2 Electricity Demand. 3.3 Power Governing. 3.4 Dynamic Frequency Control of Large Systems. 3.5 Impact of Renewable Generation on Frequency Control and Reliability. 3.6 Frequency Response Services from Renewables. 3.7 Frequency Control Modelling. 3.8 Energy Storage. References. Other Useful Reading. 4 Electrical Power Generation and Conditioning . 4.1 The Conversion of Renewable Energy into Electrical Form. 4.2 The Synchronous Generator. 4.3 The Transformer. 4.4 The Asynchronous Generator. 4.5 Power Electronics. 4.6 Applications to Renewable Energy Generators. References. 5 Power System Analysis . 5.1 Introduction. 5.2 The Transmission System. 5.3 Voltage Control. 5.4 Power Flow in an Individual Section of Line. 5.5 Reactive Power Management. 5.6 Load Flow and Power System Simulation. 5.7 Faults and Protection. 5.8 Time Varying and Dynamic Simulations. 5.9 Reliability Analysis. References. 6 Renewable Energy Generation in Power Systems . 6.1 Distributed Generation. 6.2 Voltage Effects. 6.3 Thermal Limits. 6.4 Other Embedded Generation Issues. 6.5 Islanding. 6.6 Fault Ride-through. 6.7 Generator and Converter Characteristics. References. 7 Power System Economics and the Electricity Market . 7.1 Introduction. 7.2 The Costs of Electricity Generation. 7.3 Economic Optimization in Power Systems. 7.4 External Costs. 7.5 Effects of Embedded Generation. 7.6 Support Mechanisms for Renewable Energy. 7.7 Electricity Trading. References. 8 The Future - Towards a Sustainable Electricity Supply System . 8.1 Introduction. 8.2 The Future of Wind Power. 8.3 The Future of Solar Power. 8.4 The Future of Biofuels. 8.5 The Future of Hydro and Marine Power. 8.6 Distributed Generation and the Shape of Future Networks. 8.7 Conclusions. References. Appendix: Basic Electric Power Engineering Concepts . A.1 Introduction. A.2 Generators and Consumers of Energy. A.3 Why AC?. A.4 AC Waveforms. A.5 Response of Circuit Components to AC. A.6 Phasors. A.7 Phasor Addition. A.8 Rectangular Notation. A.9 Reactance and Impedance. A.10 Power in AC Circuits. A.11 Reactive Power. A.12 Complex Power. A.13 Conservation of Active and Reactive Power. A.14 Effects of Reactive Power Flow - Power Factor Correction. A.15 Three-phase AC. A.16 The Thevenin Equivalent Circuit. Reference. Index.

The enhancement of economic sustainability and the reduction of greenhouse gas (GHG) emissions are becoming more relevant in power system planning. Thus, renewable energy sources (RESs) have been widely used as clean energy for their lower generation costs and environmentally friendly characteristics. However, the strong random uncertainties from both the demand and generation sides make planning an economic, reliable, and ecological power system more complicated. Thus, this paper considers a variety of resources and technologies and presents a coordinated planning model including energy storage systems (ESSs) and grid network expansion, considering the trustworthiness of demand-side response (DR). First, the size of a single ESS was considered as its size has a close effect on maintenance costs and ultimately affects the total operating cost of the system. Second, it evaluates the influence of the trustworthiness of DR. Third, multiple resources and technologies were included in this high-penetration renewable energy integrated power system, such as ESSs, networks, DR technology, and GHG reduction technology. Finally, this model optimizes the decision variables such as the single size and location of ESSs and the operation parameters such as thermal generation costs, loss load costs, renewable energy curtailment costs, and GHG emission costs. Since the problem scale is very large not only due to the presence of various devices but also both binary and continuous variables considered simultaneously, we reformulate this model by decomposition. Then, we transform it into a master problem (MP) and a dual sub-problem (SP). Finally, the proposed method is applied to a modified IEEE 24-bus test system. The results show computational effectiveness and provide a helpful method in planning low-carbon electricity power systems.

In the power system of the future, reliability will play an important role. This reliability is influenced by different developments like the increase in electricity consumption and the use of renewable and distributed generation. It is important to have a good insight into the reliability performance of the system. With probabilistic methods, the reliability of the power system can be analyzed and decisions can be made to maintain the high reliability level that we demand. This paper gives an overview of the different developments in power systems and describes how these developments influence the reliability of the future power system. The possibilities to implement these developments into the probabilistic reliability analysis in network planning and operational planning are discussed. By use of an example, the possibilities and challenges of probabilistic methods in operational planning are illustrated.