Advances in Integrated Energy Systems Design, Control and Optimization

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (30 April 2017) | Viewed by 74206

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Guest Editor
Department of Electronic Engineering, Technical University of Catalonia, Barcelona, Spain
Interests: microgrids; renewable energy systems; neuroscience-based artificial intelligence; digital twins; cybersecurity
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Special Issue Information

Dear Colleagues,

In the face of climate change and resource scarcity, energy supply systems are on the verge of a major transformation, which mainly includes the introduction of new components and their integration into the existing infrastructures, new network configurations and reliable topologies, optimal design and novel operation schemes, and new incentives and business models. This revolution is affecting the current paradigm and demanding that energy systems be integrated into multi-carrier energy hubs. It is greatly increasing the interactions between today’s energy systems at various scales (ranging from the multinational, national, community scales down to the building level) and future intelligent energy systems, which are able to incorporate an increasing amount of often fluctuating, renewable energy sources (RESs). It is also increases the need for the integration of energy storage options into the energy mix, not only to reduce the need for increased peak generation capacity, but also to enhance grid reliability and support higher penetration of RESs. Moreover, this transformation is accommodating active participation of end-users as responsive prosumers at different scales, which in turn help to reduce energy costs to all consumers, increase reliability of service and mitigate carbon footprints. However, this plan of action necessitates regulatory frameworks, strategic incentives and business models for efficient deployment. This Special Issue will cover these promising and dynamic areas of research and development, and will allow gathering of contributions in design, control and optimization of integrated energy systems. This Special Issue also seeks papers to report advances in any aspect of these developments. The manuscripts should be unpublished and report significant advancement.

Prof. Dr. Josep M. Guerrero,
Dr. Amjad Anvari-Moghaddam
Guest Editors

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Keywords

  • Integrated Energy systems designs, monitoring and supervisory control
  • Multi-carrier energy hubs
  • Energy internet
  • Hierarchical control applications
  • Optimization Techniques
  • Risk modeling and management
  • Energy efficiency and sustainable development
  • Business models, markets and regulatory frameworks

Published Papers (10 papers)

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Editorial

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150 KiB  
Editorial
Special Issue on Advances in Integrated Energy Systems Design, Control and Optimization
by Amjad Anvari-Moghaddam and Josep M. Guerrero
Appl. Sci. 2017, 7(7), 727; https://doi.org/10.3390/app7070727 - 16 Jul 2017
Cited by 1 | Viewed by 3651
Abstract
In the face of climate change and resource scarcity, energy supply systems are on the verge of a major transformation, which mainly includes the introduction of new components and their integration into the existing infrastructures, new network configurations and reliable topologies, optimal design [...] Read more.
In the face of climate change and resource scarcity, energy supply systems are on the verge of a major transformation, which mainly includes the introduction of new components and their integration into the existing infrastructures, new network configurations and reliable topologies, optimal design and novel operation schemes, and new incentives and business models. This revolution is affecting the current paradigm and demanding that energy systems be integrated into multi-carrier energy hubs [1]. [...] Full article

Research

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1570 KiB  
Article
Frequency Regulation of Power Systems with Self-Triggered Control under the Consideration of Communication Costs
by Zhiqin Zhu, Jian Sun, Guanqiu Qi, Yi Chai and Yinong Chen
Appl. Sci. 2017, 7(7), 688; https://doi.org/10.3390/app7070688 - 04 Jul 2017
Cited by 20 | Viewed by 4138
Abstract
In control systems of power grids, conveying observations to controllers and obtaining control outputs depend greatly on communication and computation resources. Particularly for large-scale systems, the costs of computation and communication (cyber costs) should not be neglected. This paper proposes a self-triggered frequency [...] Read more.
In control systems of power grids, conveying observations to controllers and obtaining control outputs depend greatly on communication and computation resources. Particularly for large-scale systems, the costs of computation and communication (cyber costs) should not be neglected. This paper proposes a self-triggered frequency control system for a power grid to reduce communication costs. An equation for obtaining the triggering time is derived, and an approximation method is proposed to reduce the computation cost of triggering time. In addition, the communication cost of frequency triggering is measured quantitatively and proportionally. The defined cost function considers both physical cost (electricity transmission cost) and communication cost (control signal transmission cost). The upper bound of cost is estimated. According to the estimated upper bound of cost, parameters of the controller are investigated by using the proposed optimization algorithm to guarantee the high performance of the system. Finally, the proposed self-triggered power system is simulated to verify its efficiency and effectiveness. Full article
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2527 KiB  
Article
Multi-Objective Optimization of Voltage-Stability Based on Congestion Management for Integrating Wind Power into the Electricity Market
by Jin-Woo Choi and Mun-Kyeom Kim
Appl. Sci. 2017, 7(6), 573; https://doi.org/10.3390/app7060573 - 02 Jun 2017
Cited by 9 | Viewed by 4622
Abstract
This paper proposes voltage-stability based on congestion management (CM) for electricity market environments and considers the incorporation of wind farms into systems as well. A probabilistic voltage-stability constrained optimal power flow (P-VSCOPF) is formulated to maximize both social welfare and voltage stability. To [...] Read more.
This paper proposes voltage-stability based on congestion management (CM) for electricity market environments and considers the incorporation of wind farms into systems as well. A probabilistic voltage-stability constrained optimal power flow (P-VSCOPF) is formulated to maximize both social welfare and voltage stability. To reflect the probabilistic influence of CM in the presence of wind farms on voltage stability, Monte Carlo simulations (MCS) are used to analyze both the system load and the wind speed from their probability distribution functions. A multi-objective particle-swarm optimization (MOPSO) algorithm is implemented to solve the P-VSCOPF problem. A contingency analysis based on the voltage stability index (VSI) for line outages is employed to find the vulnerable line of congestion in power systems. The congestion distribution factor (CDF) is also used to find the optimal location of a wind farm in CM. The optimal pricing expression, which is obtained, with respect to preserving voltage stability, by calculating both the locational marginal prices (LMPs) and the nodal congestion prices (NCPs), is demonstrated in terms of congestion solutions. Simultaneously, the voltage stability margin (VSM) is considered within the CM framework. The proposed approach is implemented on a modified IEEE 24-bus system, and the results obtained are compared with the results of other optimal power flow methods. Full article
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4203 KiB  
Article
Coordination of EVs Participation for Load Frequency Control in Isolated Microgrids
by Mostafa Vahedipour-Dahraie, Homa Rashidizaheh-Kermani, Hamid Reza Najafi, Amjad Anvari-Moghaddam and Josep M. Guerrero
Appl. Sci. 2017, 7(6), 539; https://doi.org/10.3390/app7060539 - 24 May 2017
Cited by 44 | Viewed by 5052
Abstract
Increasing the penetration levels of renewable energy sources (RESs) in microgrids (MGs) may lead to frequency instability issues due to intermittent nature of RESs and low inertia of MG generating units. On the other hand, presence of electric vehicles (EVs), as new high-electricity- [...] Read more.
Increasing the penetration levels of renewable energy sources (RESs) in microgrids (MGs) may lead to frequency instability issues due to intermittent nature of RESs and low inertia of MG generating units. On the other hand, presence of electric vehicles (EVs), as new high-electricity- consuming appliances, can be a good opportunity to contribute in mitigating the frequency deviations and help the system stability. This paper proposes an optimal charging/discharging scheduling of EVs with the goal of improving frequency stability of MG during autonomous operating condition. To this end, an efficient approach is applied to reschedule the generating units considering the EVs owners’ behaviors. An EV power controller (EVPC) is also designed to determine charge and discharge process of EVs based on the forecasted day-ahead load and renewable generation profiles. The performance of the proposed strategy is tested in different operating scenarios and compared to those from non-optimized methodologies. Numerical simulations indicate that the MG performance improves considerably in terms of economy and stability using the proposed strategy. Full article
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5336 KiB  
Article
Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids
by Mostafa Vahedipour-Dahraie, Hamid Reza Najafi, Amjad Anvari-Moghaddam and Josep M. Guerrero
Appl. Sci. 2017, 7(4), 378; https://doi.org/10.3390/app7040378 - 11 Apr 2017
Cited by 50 | Viewed by 5257
Abstract
In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits [...] Read more.
In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits in response to energy price changes and get incentives in return. In this paper, we study the effect of various time-based rate (TBR) programs on the stochastic day-ahead energy and reserve scheduling in residential islanded microgrids (MGs). An effective approach is presented to schedule both energy and reserve in presence of renewable energy resources (RESs) and electric vehicles (EVs). An economic model of responsive load is also proposed on the basis of elasticity factor to model the behavior of customers participating in various DR programs. A two-stage stochastic programming model is developed accordingly to minimize the expected cost of MG under different TBR programs. To verify the effectiveness and applicability of the proposed approach, a number of simulations are performed under different scenarios using real data; and the impact of TBR-DR actions on energy and reserve scheduling are studied and compared subsequently. Full article
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1768 KiB  
Article
Optimal Scheduling of Industrial Task-Continuous Load Management for Smart Power Utilization
by Jidong Wang, Kaijie Fang, Jiaqiang Dai, Yuhao Yang and Yue Zhou
Appl. Sci. 2017, 7(3), 281; https://doi.org/10.3390/app7030281 - 14 Mar 2017
Cited by 3 | Viewed by 4491
Abstract
In the context of climate change and energy crisis around the world, an increasing amount of attention has been paid to developing clean energy and improving energy efficiency. The penetration of distributed generation (DG) is increasing rapidly on the user’s side of an [...] Read more.
In the context of climate change and energy crisis around the world, an increasing amount of attention has been paid to developing clean energy and improving energy efficiency. The penetration of distributed generation (DG) is increasing rapidly on the user’s side of an increasingly intelligent power system. This paper proposes an optimization method for industrial task-continuous load management in which distributed generation (including photovoltaic systems and wind generation) and energy storage devices are both considered. To begin with, a model of distributed generation and an energy storage device are built. Then, subject to various constraints, an operation optimization problem is formulated to maximize user profit, renewable energy efficiency, and the local consumption of distributed generation. Finally, the effectiveness of the method is verified by comparing user profit under different power modes. Full article
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3613 KiB  
Article
Electrical Energy Forecasting and Optimal Allocation of ESS in a Hybrid Wind-Diesel Power System
by Hai Lan, He Yin, Shuli Wen, Ying-Yi Hong, David C. Yu and Lijun Zhang
Appl. Sci. 2017, 7(2), 155; https://doi.org/10.3390/app7020155 - 14 Feb 2017
Cited by 15 | Viewed by 5019
Abstract
Due to the increasingly serious energy crisis and environmental pollution problem, traditional fossil energy is gradually being replaced by renewable energy in recent years. However, the introduction of renewable energy into power systems will lead to large voltage fluctuations and high capital costs. [...] Read more.
Due to the increasingly serious energy crisis and environmental pollution problem, traditional fossil energy is gradually being replaced by renewable energy in recent years. However, the introduction of renewable energy into power systems will lead to large voltage fluctuations and high capital costs. To solve these problems, an energy storage system (ESS) is employed into a power system to reduce total costs and greenhouse gas emissions. Hence, this paper proposes a two-stage method based on a back-propagation neural network (BPNN) and hybrid multi-objective particle swarm optimization (HMOPSO) to determine the optimal placements and sizes of ESSs in a transmission system. Owing to the uncertainties of renewable energy, a BPNN is utilized to forecast the outputs of the wind power and load demand based on historic data in the city of Madison, USA. Furthermore, power-voltage (P-V) sensitivity analysis is conducted in this paper to improve the converge speed of the proposed algorithm, and continuous wind distribution is discretized by a three-point estimation method. The Institute of Electrical and Electronic Engineers (IEEE) 30-bus system is adopted to perform case studies. The simulation results of each case clearly demonstrate the necessity for optimal storage allocation and the efficiency of the proposed method. Full article
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1145 KiB  
Article
Development of a Simulation Framework for Analyzing Security of Supply in Integrated Gas and Electric Power Systems
by Kwabena Addo Pambour, Burcin Cakir Erdener, Ricardo Bolado-Lavin and Gerard P. J. Dijkema
Appl. Sci. 2017, 7(1), 47; https://doi.org/10.3390/app7010047 - 05 Jan 2017
Cited by 37 | Viewed by 7470
Abstract
Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the [...] Read more.
Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consists of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to liquefied natural gas (LNG) terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly. Full article
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2324 KiB  
Article
Development of a Sequential Restoration Strategy Based on the Enhanced Dijkstra Algorithm for Korean Power Systems
by Bokyung Goo, Solyoung Jung and Jin Hur
Appl. Sci. 2016, 6(12), 435; https://doi.org/10.3390/app6120435 - 15 Dec 2016
Cited by 6 | Viewed by 4608
Abstract
When a blackout occurs, it is important to reduce the time for power system restoration to minimize damage. For fast restoration, it is important to reduce taking time for the selection of generators, transmission lines and transformers. In addition, it is essential that [...] Read more.
When a blackout occurs, it is important to reduce the time for power system restoration to minimize damage. For fast restoration, it is important to reduce taking time for the selection of generators, transmission lines and transformers. In addition, it is essential that a determination of a generator start-up sequence (GSS) be made to restore the power system. In this paper, we propose the optimal selection of black start units through the generator start-up sequence (GSS) to minimize the restoration time using generator characteristic data and the enhanced Dijkstra algorithm. For each restoration step, the sequence selected for the next start unit is recalculated to reflect the system conditions. The proposed method is verified by the empirical Korean power systems. Full article
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Review

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3873 KiB  
Review
Virtual Inertia: Current Trends and Future Directions
by Ujjwol Tamrakar, Dipesh Shrestha, Manisha Maharjan, Bishnu P. Bhattarai, Timothy M. Hansen and Reinaldo Tonkoski
Appl. Sci. 2017, 7(7), 654; https://doi.org/10.3390/app7070654 - 26 Jun 2017
Cited by 454 | Viewed by 28154
Abstract
The modern power system is progressing from a synchronous machine-based system towards an inverter-dominated system, with large-scale penetration of renewable energy sources (RESs) like wind and photovoltaics. RES units today represent a major share of the generation, and the traditional approach of integrating [...] Read more.
The modern power system is progressing from a synchronous machine-based system towards an inverter-dominated system, with large-scale penetration of renewable energy sources (RESs) like wind and photovoltaics. RES units today represent a major share of the generation, and the traditional approach of integrating them as grid following units can lead to frequency instability. Many researchers have pointed towards using inverters with virtual inertia control algorithms so that they appear as synchronous generators to the grid, maintaining and enhancing system stability. This paper presents a literature review of the current state-of-the-art of virtual inertia implementation techniques, and explores potential research directions and challenges. The major virtual inertia topologies are compared and classified. Through literature review and simulations of some selected topologies it has been shown that similar inertial response can be achieved by relating the parameters of these topologies through time constants and inertia constants, although the exact frequency dynamics may vary slightly. The suitability of a topology depends on system control architecture and desired level of detail in replication of the dynamics of synchronous generators. A discussion on the challenges and research directions points out several research needs, especially for systems level integration of virtual inertia systems. Full article
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