Microgrids and Virtual Power Plants

Inhaltsverzeichnis

1. Frontmatter

2. Holistic Data-Driven Approach for Sizing and Energy Management of an Urban Islanded Microgrid

   Xue Feng, Yan Xu

   Abstract

   This chapter presents a data-driven approach for optimal sizing and operation of islanded microgrids within an urban context. The study employs a building-level urban islanded microgrid as a testbed for case studies. A randomized learning model is introduced for supply and demand forecasting, and based on these results, a data-driven approach is employed to generate uncertainty scenarios characterizing uncertain supply and demand characteristics. Optimal sizing is conducted considering operational constraints to determine the sizes of different components, particularly the energy storage system and distributed generators, with a focus on minimizing capital and operational costs. A two-stage coordinated energy management strategy is used to minimize operating costs while meeting various system constraints.

3. Probabilistic Microgrid Investment Planning with Integrated Game-Theoretic Demand Response Management

   Soheil Mohseni, Alan C. Brent

   Abstract

   This Chapter presents an innovative modelling framework for advancing integrated metaheuristic-based energy planning optimization, with a focus on resilient, renewable community microgrids. The study brings attention to a critical aspect of long-term sustainable energy system planning by illuminating biases intrinsic to consumer preference-based demand response projections. Central to the framework is the emphasis on market-driven sectoral flexibility procurement, achieved through sealed-bid auctions, thereby optimizing social welfare, improving demand response capacity liquidity, and promoting sectoral stability. To this end, the integration of game theory is highlighted as a means to leverage demand-side flexibility for community-level clean energy projects. Further, navigating the uncertainties stemming from non-dispatchable sources and smart grid interventions, the Chapter advocates for a comprehensive evaluation involving holistic uncertainty-aware models for renewable system planning. In this context, a novel probabilistic investment planning framework is introduced, which incorporates climatological, demand, and price uncertainties within a stochastic microgrid sizing model integrated with demand response solutions. The significance of this framework lies in its capacity to address gaps in uncertainty-aware methodologies and the integration of operational and investment planning. By synergizing intricate modelling with practical implementation considerations, the Chapter establishes a guiding framework that not only enriches scholarly deduction, but also aids practical, sustainable energy decision-making. The efficacy of the approach is substantiated through numerical simulations of a case study in Aotearoa New Zealand, to validate the applicability of the results.

4. Design and Modelling of Microgrids Operated at Constant Frequency and with a Power Level of Megawatts

   Daming Zhang

   Abstract

   Hardware prototyping of large-scale autonomous microgrids is costly and dangerous. To reduce such risks, this chapter adopts a fixed-time-step multi-rate modelling in Matlab/Simulink to reduce the differences between modelling and hardware implementation. For a comparison purpose, single-rate modelling has also been conducted. Furthermore, phasor-domain analytical solutions of the voltages at each bus in the microgrid have also been sought and are compared with results from both single-rate and multi-rate modelling. The chapter will demonstrate that the results from multi-rate modelling are closer to those from phasor-domain analysis. Moreover, the influence of DC link voltage on the real and reactive power tracing for each inverter will be demonstrated.

5. Design, Sizing, and Simulation of a DC Microgrid for Real Implementation

   Mojgan Hojabri

   Abstract

   In recent years, DC microgrids have grown in popularity because of their improved efficiency, increased reliability, and simplified control and management when compared to AC microgrids. Moreover, the number of DC appliances is increasing for residential applications. Thus, determining the best DC voltage for them is the key question. The current DC microgrid technology achieves high efficiency by utilizing sub-systems and renewable energy sources such as wind turbines, solar panels, etc. while allowing charge controllers to facilitate maximum power point tracking. In addition, energy storage systems, which help to mitigate power intermittency caused by the deployment of renewables, are an essential part of microgrid systems. Therefore, finding the ideal DC voltage level for DC home appliances is one of the goals of this chapter. Additionally, a thorough discussion of the sizing requirements for photovoltaic and storage systems for self-sufficient homes will be held. Lastly, a model for a small DC microgrid that will be installed later in a pilot region will be designed and simulated in the MATLAB/Simulink environment. The obtained simulation results show that the suggested DC microgrid is operationally feasible.

6. Microgrid Control Assessment Using Advanced Hardware in the Loop Technologies

   Sharara Rehimi, Hassan Bevrani, Chiyori T. Urabe, Takeyoshi Kato

   Abstract

   This chapter explores the assessment of microgrid control using advanced hardware-in-the-loop technologies. It provides an introduction to hardware-in-the-loop technologies and their applications, including virtual hardware-in-the-loop, controller hardware-in-the-loop, and power hardware-in-the-loop. The chapter highlights the significance of hardware-in-the-loop assessment for assessing microgrid control units and discusses the challenges and issues involved in hardware-in-the-loop testing. It also examines the relevant IEEE standards and grid codes for microgrid testing. Furthermore, the chapter reviews the advancements in microgrid testing with hardware-in-the-loop and presents a step-by-step implementation of a microgrid using hardware-in-the-loop technology. It covers the important components of a microgrid, the difference between switching and average components, and the integration of battery energy storage systems, photovoltaic power plants, and diesel generators. The chapter provides examples of creating a simple microgrid and a fully functional terrestrial microgrid model. It also discusses microgrid model optimization and explores new trends and topics, such as ensuring cybersecurity in microgrids and the integration of electric vehicles. Additionally, the chapter delves into the use of grid-forming converters in microgrids.

7. Stability and Control of Hybrid AC/DC Microgrids

   Arash Vahidnia, Moudud Ahmed Masum, Lasantha Meegahapola

   Abstract

   Hybrid AC/DC microgrids are considered as viable solutions to reduce energy conversion losses in microgrids. However, hybrid AC/DC microgrids are susceptible to stability issues during high penetration of dynamic loads (e.g., induction machines). The non-linear dynamics of induction machines, result in sustained voltage/frequency oscillations following disturbances in the microgrid, which is a major challenge for stable operation of the hybrid AC/DC microgrid. This issue is even more severe when the hybrid AC/DC microgrid is operated at autonomous mode. The PEC based energy storage systems (ESSs) are used as an effective solution for power balancing in the microgrid; hence with the fast response of the PEC, microgrid voltage/frequency could be stabilised rapidly. This chapter discusses the stability and control aspects of hybrid AC/DC microgrids to address the drawbacks of these systems. A supplementary power oscillation damping controller for the ESS is demonstrated for damping the low-frequency oscillations (LFOs) in the microgrid. Furthermore, the dynamic characteristics of the loads in the microgrid can change constantly which requires re-tuning of the pod controller. This is addressed by an adaptive neuro-fuzzy inference system (ANFIS) based POD controller which has been shown to be more effective due to its ability to adjust the gain based on the frequency deviation, and handling more non-linearity in the system dynamics. Furthermore, this chapter presents a hybrid AC/DC microgrid architecture incorporating a central energy storage system with a coordinated control strategy between the central ESS and the inter-linking converter (ILC) to maintain the stable operation of the microgird.

8. Quantifying Transient Dynamics for Microgrid’s Inverter-Based Resources

   Touria El Mezyani, Farzad Ferdowsi, Mohammad Seyedi, Chris S. Edrington

   Abstract

   Power converters are becoming increasingly important in power systems due to the high penetration of inverter-based resources. Converters are used to implement control strategies and to interface different subsystems (e.g., distributed energy resources, loads, batteries, etc.) that produce, store, or consume electrical energy. They are suitable for microgrids because they provide fast operation and the ability to implement control algorithms at the primary and secondary levels. This chapter studies the complexity associated with the emergence of new complex dynamics in power systems that arise with the high penetration of inverter-based resources. Complexity manifests as bifurcation, oscillation, instability, and chaos, which traditional Models or data-based prediction, such as machine learning, cannot predict. It is mainly due to power electronics nonlinearity, coupling between these components, different feedbacks such as control, and human and environmental feedbacks. Complexity quantification is crucial to modern microgrids with high penetration of inverter-based resources as it allows them to indicate the system's vulnerability, instability, and hidden problems. In this chapter, two complexity metrics are investigated and computed using the permutation entropy approach and ordinal pattern technique, and approximate entropy. Various case studies are conducted on simulated data from noise-coupled buck converters, two parallel-connected buck converters, and solid-state transformers integrated into a microgrid.

9. Machine Learning and Internet-of-Things Solutions for Microgrid Resilient Operation

   Chun-Lien Su, Seyed Hossein Rouhani, Mahmoud Elsisi, Zulfiqar Ali, Hoang Le Quang Nhat, Muhammad Sadiq

   Abstract

   Microgrids inherently have lower inertia in comparison with the power system due to the high penetration of renewable generation sources. On the other hand, the lower spring reserve, high dynamic loads, and inherent volatility of renewable generation sources have demanded real-time control of them. The development of intelligent electrical devices, communication infrastructure, and Internet-of-Things (IoT) technology has enhanced real-time microgrid operation. In contrast, they have exposed the smart microgrid to cyber malicious activities. Cyber attackers try to disrupt the microgrid operation by manipulating the sensors, control center, communication infrastructure, and intelligent electrical devices, leading to decreasing power quality, cascading instability, and, finally, blackout. The effect of a cyber-attack in a standalone microgrid will be more distractive. Given the advantages inherent in these technologies, this chapter conducts an extensive examination of their integration into the management, control, and upkeep of both onshore and offshore microgrids. It provides a detailed account of the communication infrastructure within microgrids and identifies potential vulnerabilities. The chapter then elucidates methods for detecting cyber-attacks, placing a particular emphasis on machine learning, IoT, and Digital Twins. Subsequently, the chapter delves into the convergence of these technologies with maritime microgrids. It expounds upon how these advancements render maritime microgrids susceptible to cyber threats and emphasizes the instrumental role of machine learning in fortifying their cyber resilience. Furthermore, the chapter explores the application of IoT and Digital Twins, combined with machine learning, to enhance the maintenance and operational resilience of maritime microgrids. Finally, the chapter addresses the technical challenges faced by smart seaports and offers resilient operational solutions to mitigate potential disruptions.

10. Deep Learning-Based Microgrid Protection

    Muhammad Uzair, Li Li, Syed Basit Ali Bukhari

    Abstract

    Microgrids are rapidly gaining popularity as a reliable solution for localized power generation and distribution. However, ensuring microgrids' reliable operation and protection remains a critical challenge. Traditional protection methods often fail to address the complexities of microgrids, such as integrating renewable energy sources and multiple interconnected systems. This chapter introduces a unique microgrid protection system based on tunable-Q wavelet transform and multi-layered long short-term memory-based deep learning. Besides accurately detecting and classifying the faults, the system can also determine the specific phase affected by the fault, enabling prompt and targeted responses. A tunable-Q wavelet transform is employed to obtain unique patterns from three-phase current signals, and a multi-layered long short-term memory-based deep learning network is applied for fault identification and classification. Accurate fault detection ensures a quick response to faults, minimizing downtime and maximizing microgrid reliability. Secondly, fault classification enables the system to distinguish between different types of faults, which aids in implementing appropriate mitigation strategies. Lastly, the faulted phase identification capability allows for targeted interventions, streamlining maintenance efforts and reducing costs. The performance of the protection system is evaluated on a simulated microgrid model. The results demonstrate the system's ability to accurately detect faults, classify them with high precision, and identify the faulted phase correctly. These findings highlight the potential of deep learning-based microgrid protection as an effective and efficient solution for enhancing microgrids' reliability and operational efficiency.

11. Cyber-Attacks Detection and Mitigation in Microgrids

    Himani Modi, Mohit Kachhwaha, Deepak Fulwani

    Abstract

    Introducing distributed communication and control in DC microgrids significantly improves the overall performance of the system. However, these developments also raise the possibility of malicious attacks. Denial-of-service (DoS) attacks and false data injection (FDI) attacks are the most common cyber-attacks. DoS attacks disrupt data availability, and FDI attacks tamper with data integrity, which is perilous for the DC microgrid system. These attacks have the potential to create a detrimental effect on the DC microgrid's sensors, actuators, and communication channels. The combination of DoS and FDI attacks on the actuator signal can have a severe impact, endangering the secure functioning of DC microgrid and potentially destabilizing the entire system. To address these concerns, this chapter introduces an attack detection and mitigation method for mixed FDI and DoS attacks. This detection mechanism uses a state-machine-based technique with a dynamic signature function. The dynamic function constantly compares the actual signal of the actuator with its estimated signal. A Linear Unknown Input Functional Observer (LUIFO) can mitigate mixed attacks and provide an estimated actuator signal to the signature function. This detection and mitigation method ascertain the security and stable functioning of the DC microgrid system. The MATLAB simulation results on four distributed generators-based DC microgrid demonstrate the performance of the methods.

12. Peer-To-Peer Trading Among Microgrid Prosumers in Local Energy Markets

    Ziqing Zhu, Siqi Bu, Qian Hu

    Abstract

    This chapter investigates the transformative potential of Peer-to-Peer (P2P) trading in local energy markets, emphasizing the role of distributed energy resources in facilitating efficient market operations and fostering sustainable energy practices. The text first provides a foundational understanding of local energy markets, highlighting their definition and significance, and introduces the emergent concept of P2P energy trading among prosumers, with a focus on the microgrid and nanogrid levels. It underscores the advantages of such trading, including improved energy efficiency, enhanced grid reliability, and the promotion of renewable energy sources. Further, the chapter delves into the specifics of P2P ancillary service trading, with particular attention to frequency regulation support among microgrid and nanogrid prosumers, exploring its operational benefits and contribution to grid stability. Advancing the discussion, the text introduces a novel aspect of P2P markets—the carbon emission auction trading within local energy spheres. This section probes the theoretical and practical implications of integrating carbon emission considerations into energy trading and examines the market mechanisms through which microgrid prosumers might interact within this innovative paradigm. The chapter is structured into two principal sections. The first addresses P2P energy and ancillary service trading among nanogrid prosumers within a microgrid setting, focusing on real-time market operations for energy balancing and frequency regulation. The second section examines the interconnections between P2P energy, ancillary service, and carbon emission quota trading among multiple microgrid prosumers, presenting advanced modeling techniques and algorithms such as the multi-agent deep deterministic policy gradient for strategy optimization and risk mitigation. The chapter concludes with a synthesis of the explored concepts, reinforcing the significance of P2P trading in advancing the decarbonization of local energy markets and its potential for incentivizing the adoption of green technologies. It offers insights into the market structures, strategic behaviors of prosumers, and the envisioned impact on the overarching energy landscape.

13. Embedding Regulatory Frameworks in Microgrids Management

    Helena Martín, Jordi de la Hoz

    Abstract

    This chapter demonstrates the key importance of embedding the regulatory framework in the microgrid models, for either their optimal sizing and/or management or for its technoeconomic assessment. Using a case study focused on a basic microgrid for domestic self-consumption, a conceptual regulatory framework is embedded in the model for its energy management optimization. The obtained results are compared to those stemming from disregarding regulatory constraints, as is frequently observed in the literature, which leads to significantly inaccurate results.

14. Virtual Power Plant Participation in Australian Wholesale Electricity Markets

    Julius Susanto

    Abstract

    Over the last decade, Australia has witnessed unprecedented growth in its distributed energy resource (DER) installed capacity base, growing from around 3 GW in 2013 to nearly 19 GW in 2023. Alongside this massive expansion in DER capacity has come the opportunity for DER to be aggregated to form virtual power plants (VPP) that can be coordinated and controlled by a central operator. By harnessing DER at scale, VPPs can interact with wholesale electricity markets either (i) directly through energy and ancillary services trading or (ii) indirectly by flexibly adjusting imports and exports in response to market prices. This chapter provides a review of how VPPs currently participate in wholesale electricity markets in Australia, and how they could participate in the future.

15. Interconnected Microgrid Clusters Through Various Provisional Power Exchange Links

    S. M. Ferdous, Farhad Shahnia, G. M. Shafiullah

    Abstract

    A standalone microgrid in a remote area may frequently experience overloading due to lack of sufficient power generation and/or renewable-based over generation causing unacceptable voltage and frequency deviation, which in turn lead the microgrid to operate with less resiliency and reliability. Conventionally, such problems are alleviated by load shedding or renewable curtailment. Alternatively, such autonomously operating microgrid clusters in a certain geographical area can be provisionally connected to each other to enable power exchange among them to address the problems of overloading or overgeneration more efficiently and cost-effective way. The power exchange link among the microgrids can be of different types such as a three-phase ac, a single-phase ac, or a dc-link. Power electronic converters are required to interconnect such power exchange networks to the three-phase ac microgrids and control the power-sharing amongst them. Such arrangement is also essential to interconnect microgrid clusters to each other with proper isolation while maintaining autonomy if they are operating in different standards. In this chapter, the topologies, and structures of various forms of power exchange links are investigated and an appropriate framework is established under which power exchange will take place. This approach is a decentralized control mechanism to facilitate power-sharing amongst the converters of the neighboring microgrids without any data communication, that can be implemented at the primary level based on the localized measurements. The dynamic performance of the control mechanism for all the topologies is illustrated through simulation studies in PSIM® to verify that such overloading or overgeneration situations can be effectively alleviated through proper frequency regulation. The chapter also presents a comparative analysis of the topologies in terms of stability and sensitivity.

16. Cooperative and Transactive Integration of Multiple Microgrids

    Nelson L. Díaz, Jan L. Díaz, Yuly V. García, Adriana C. Luna

    Abstract

    The constant changes in electrical grids, such as the incorporation of distributed generators and the integration of microgrids, have resulted in various alterations in the way the power system functions. To address these changes, recent years have witnessed ongoing research into the concept of transactive energy. Here, the conventional operation of the electrical power system, historically characterized by unidirectional energy flow from bulk generation through the transmission and distribution systems to end-users, has experienced shifts due to the evolving dynamics of generation and demand, in which energy can be shared or transacted among many energy prosumers. This chapter presents an overview, from management to hardware, of the operation and requirements for effective energy transactions between prosumers. Game theory is introduced and explored as one of the most promising market topologies used in Transactive Energy. A real-life optimization problem, along with its Python code, is provided in the chapter. Additionally, a perspective on hardware requirements for enabling energy transactions between multiple microgrids is presented by exploring the multi-terminal converter. The topologies, control, and configuration are discussed, highlighting the advantages of using Voltage Source Converters interconnected through a common DC link.

17. Practical Aspects of Pre-engineering Design of Clustered Microgrids

    Alexandre Nassif

    Abstract

    Although microgrids are a popular research topic, design objectives of a real-life project are probably the largest uncertainty faced by planning engineers. Most real microgrid systems, i.e., those not built exclusively as a demonstration project, have as a primary goal increasing the reliability to be afforded to customers within the microgrid boundary, as well as resilience to ensure the microgrid can maintain its supply even for very long duration outages caused by high-impact-low-probability events. A secondary goal is oftentimes increasing the share of renewable energy produced and consumed by the microgrid loads, both under blue sky and black sky operation. As a result, the load serving capability of the microgrid operating under different fractions of renewable energy is another aspect of interest. Whether operating in blue sky or black sky mode, each microgrid operation must result in a stable state and the microgrid must maintain safe and reliable operation. These objectives apply to single microgrids as well as to networked (clustered) microgrids, where more than one microgrid form a cluster that can have each microgrid operating individually or a microgrid cluster operating as a networked system. Design aspects go beyond the planning phase, and consider designing the operation modes, the clustering approach, and impacts therein. Several aspects of power quality must be analysed to ensure design parameters are addressed. Only with this foundation, a clustered microgrid is expected to engage seamless transition and continue operating in both grid-tied as well as in off-grid condition uneventfully. Oftentimes this creates a focal point on protection and control. It is expected the microgrid can either have a single scheme that enables the dual operation mode, including transition, or to have practical means to quickly switch settings groups if the philosophy calls for more than one. This chapter provides an overview of several engineering aspects of two networked island microgrids.

18. Military Microgrids with Renewable Energy and 5G Communication

    Ali Mehrizi-Sani, Jeffery H. Reed, Chen-Ching Liu

    Abstract

    Military installations fit the widely accepted definition of an electrical microgrid very closely: they are geographically and electrically well-defined, need to be capable of operating in grid-connected and islanded modes, and can operate as a single entity when presented to the grid. The independent operation of a microgrid from the national grid can significantly enhance the resiliency, cybersecurity, and physical security of the nation’s military bases. As a niche application of microgrids, several military base microgrids have been deployed in recent years. Renewable-based microgrids can help the military reduce its petroleum use, potentially saving $8–$20 billion over the next two decades. However, renewables-based microgrids require stringent control and protection facilities. Considering the large number of entities that need to be coordinated and controlled together, the control of assets within a microgrid typically becomes a distributed control problem—in distributed control, different assets communicate and coordinate with each other to optimally utilize the resources. This is where 5G communication networks can induce a paradigm shift. 5G has been identified by the United States Department of Defense as a critical strategic technology. A 5G-based technology platform is attractive from economic and security perspectives for military microgrids. 5G can address security while containing cost; 5G provides different layers of security, such as device-radio network security, device-core network security, device-service network security, and intra-network security. Even though 5G needs to be customized to meet power grid-specific requirements, baseline 5G features and designs are still significantly used. This chapter discusses the challenges and opportunities related to a renewable-based 5G-enabled microgrid for military installations.