Mycorrhizal Networks (MNs) facilitate the exchange of resources including energy, water, nutrients, and information between trees and plants in forest ecosystems. This work explored MNs as an inspiration for new market models in transactive energy networks, which similarly involve exchanges of energy and information between buildings in local communities. Specific insights from the literature on the structure and function of MNs were translated into an energy model with the aim of addressing challenges associated with the proliferation of distributed energy resources (DERs) at the grid edge and the incorporation of DER aggregations into wholesale energy markets. First, a systematic review of bio-inspired computing interventions applied to microgrids and their interactions with modern energy markets established a technical knowledge base within the context of distributed electrical systems. Second, a bio-inspired design process built on this knowledge base to yield a structural and functional blueprint for a computational mycorrhizal energy market simulation. Lastly, that computational model was implemented and simulated on a blockchain-compatible, multi-agent software platform to determine the effect that mycorrhizal strategies have on transactive energy market performance. The structural translation of a mapped ectomycorrhizal network of Douglas-firs in Oregon, USA called the 'wood-wide web' created an effective framework for the organization of a novel mycorrhizal energy market model that enabled participating buildings to redistribute percentages of their energy assets on different competing exchanges throughout a series of week-long simulations. No significant changes in functional performance –- as determined by economic, technical, and ecological metrics – were observed when the mycorrhizal results were compared to those of a baseline transactive energy community without periodic energy asset redistribution. Still, the model itself is determined to be a useful tool for further exploration of innovative, automated strategies for DER integration into modern energy market structures and electrical infrastructure in the age of Web3, especially as new science emerges to better explain trigger and feedback mechanisms for carbon exchange through MNs and how mycorrhizae adapt to changes in the environment. This dissertation concludes with a brief discussion of policy implications and an analysis applying the ecological principles of robustness, biodiversity, and altruism to the collective energy future of the human species. / Doctor of Philosophy / Beneath the forest floor, a network of fungi connects trees and plants and allows them to exchange energy and other resources. This dissertation compares this mycorrhizal network (mycorrhiza = fungus + root) to a group of solar-powered buildings generating energy and exchanging it in a local community marketplace (transactive energy markets). In the analogy, the buildings become the plants, the solar panels become the leaves, and the electrical grid represents the mycorrhizal network. Trees and plants produce their own energy through photosynthesis and then send large portions of it down to the roots, where they can trade it or send it to neighbors via the mycorrhizal network. Similarly, transactive energy markets are designed to allow buildings to sell the energy they produce on-site to neighbors, usually at better rates. This helps address a major infrastructure challenge that is arising with more people adding roof-top solar to their homes. The grid that powers our buildings is old now and it was designed to send power from a central power plant out to its edges where most homes and businesses are located. When too many homes produce solar power at the same time, there is nowhere for it to go, and it can easily overload the grid leading to fires, equipment failures, and power outages. Mycorrhizal networks solve this problem in part through local energy balancing driven by cooperative feedback patterns that have evolved over millennia to sustain forest ecosystems. This work applies scientific findings on the structure and function of mycorrhizal networks (MNs) to energy simulation methods in order to better understand the potential for building bio-inspired energy infrastructure in local communities. Specifically, the mapped structure of a MN of douglas-fir trees in Oregon, USA was adapted into a digital transactive energy market (TEM) model. This adaptation process revealed that a single building can connect to many TEMs simultaneously and that the number of connections can change over time just as symbiotic connections between organisms grow, decay, and adapt to a changing environment. The behavior of MNs in terms of when those connections are added and subtracted informed the functionality of the TEM model, which adds connections when community energy levels are high and subtracts connections when energy levels are low. The resulting 'mycorrhizal' model of the TEM was able to change how much energy each connected household traded on it by changing the number of connections (more connections mean more energy and vice versa). Though the functional performance of the mycorrhizal TEM did not change significantly from that of a typical TEM when they were the context of decentralized computer networks (blockchains) and distributed artificial intelligence. A concluding discussion addresses ways in which elements of this new model could transform energy distribution in communities and improve the resilience of local energy systems in the face of a changing climate.

Recently, due to the increasing adoption of distributed energy resource (DER) technologies including battery energy storage (BES) and electric vehicle (EV) systems, bidirectional power converters are becoming more popular. These converters are broadly utilized as interface devices and provide a bidirectional power flow in applications where the primary power supply can both supply and receive energy. A dc capacitor, called the dc-link, is an important component of such bidirectional converters. For a wide range of applications, the converter is required to control the dc-link voltage. Commonly, a proportional-integrating (PI) controller is used by the dc capacitor voltage controller to generate a set-point for the inner current controller. This approach tightly regulates the dc-link voltage to a given value. The research presented in this dissertation shows that such an approach compromises the stability margins of the converter for reverse power flow and weak grid conditions. It is shown that by allowing a small variation of dc capacitor voltage in proportion to the amount of power flowing through the converter, the stability and robustness margins are improved. This approach also simplifies the design process and can be applied to both dc/dc and dc/ac (single-phase and three-phase) converters. Moreover, it grants an inherent power sharing capability when multiple converters share the same dc-link terminals; removing the need to a communication link between parallel converters. The proposed controller is equipped with a current limiting mechanism to protect the converter during low-voltage/over-current transients. Detailed analyses, simulations, comparisons, and experimental results are included to illustrate the effectiveness of the proposed control approach. To mathematically establish the properties of the proposed method in a single-phase dc/ac application, this dissertation also derives a new and systematic modeling approach for a grid-connected bidirectional single-phase inverter controlled in stationary frame. Implementing the control system in the stationary frame has advantages over rotating frame. However, the combination of dc and ac state variables and nonlinearities make its stability analysis challenging. In the proposed model, an imaginary subsystem is properly generated and augmented to allow a full transformation to a synchronous rotating frame. The proposed modeling strategy is modular and has a closed form which facilitates further extensions. It is successfully used to demonstrate enhanced stability margins of the proposed controller.

[pt] Nos últimos anos tem se verificado um papel mais ativo do pequeno consumidor com relação ao uso da energia elétrica. O acesso mais facilitado às tecnologias de geração distribuída, principalmente produção local fotovoltaica em telhados de residências e também às novas gerações de medidores inteligentes, despertou o interesse de pequenos consumidores para gerar sua própria energia, reduzindo sua fatura com a distribuidora e também sua dependência da rede de distribuição. Nesse contexto, o objetivo da dissertação é avaliar, com base em medições inteligentes reais, o impacto nas faturas de consumidores residenciais causado pela introdução de uma Tarifa de Uso do Sistema de Distribuição, em reais/quilowatt, aplicada sobre a demanda máxima registrada. A opção pelo tema buscou atender lacunas na bibliografia nacional por tratar-se de um assunto inovador, não só no Brasil, e que está sendo estudado em diversos países no mundo simultaneamente. A metodologia pode ser dividida, basicamente, em quatro fases: (i) Apuração da receita de referência; (ii) Cálculo das tarifas de distribuição nas modalidades horária e em reais/quilowatt; (iii) Cálculo e avaliação das receitas obtidas pela aplicação das tarifas às medições dos clusters de estudo; e (iv) Cálculo e avaliação das receitas obtidas pela aplicação das tarifas às medições dos clusters de estudo, considerando geração fotovoltaica distribuída. Os resultados permitiram identificar os perfis de consumo que seriam mais impactados pela introdução de uma tarifação sobre a demanda e também os efeitos resultantes da instalação de painéis solares nas residências, assim demonstrar que essa modalidade de tarifação, ao refletir os custos da atividade de distribuição de energia, propicia estabilidade das tarifas e evita subsídios cruzados. / [en] In recent years there has been a more active role of small consumers in relation to the use of electricity. The easier access to distributed generation technologies, mainly local photovoltaic production in residential roofs and also the new generations of intelligent meters, has brought the interest of small consumers to generate their own energy, reducing their invoice with the distributor and also their dependence on the distribution network. In this context, the objective of this dissertation is to evaluate, based on real smart measurements, the impact on the invoices of residential customers caused by the introduction of a demand charge, in real/kilowatt, applied on the registered maximum demand. The option for the theme sought to address gaps in the national bibliography because it is an innovative subject, not only in Brazil, and which is being studied in several countries simultaneously. The methodology can be divided into basically four phases: (i) Calculation of the reference revenue; (ii) Calculation of distribution tariffs: hourly and based in real/kilowatt; (iii) Calculation and evaluation of the revenues obtained by applying the tariffs to the measurements from the clusters to be studied; and (iv) Calculation and evaluation of the revenues obtained by applying the tariffs to the measurements from the clusters to be studied, considering distributed photovoltaic generation. The results allowed to identify the consumption profiles, whether they would be more impacted by the introduction of a demand charge and the impacts caused by the installation of solar panels by the residences as well as demonstrating that this type of charge, reflecting the costs of distribution, provides tariff stability and avoids cross subsidies.

Les réseaux électriques actuels connaîtront un profond changement dans les années à venir. La nouvelle génération est le Smart Grid (SG) ou le réseau électrique intelligent qui se caractérise par une couche d'information et de communication qui permet aux différents composants du réseau de communiquer. Il doit considérer tous les aspects du réseau électrique, le rendant plus intelligent et flexible. Cette notion est présentée comme une réponse à l'évolution du marché de l'électricité, visant à gérer l’augmentation de la demande tout en assurant une meilleure qualité de service et plus de sécurité.Premièrement, nous présentons une formulation de programmation linéaire mixte en entier pour optimiser les systèmes de production et de consommation d'énergie dans une maison intelligente avec un déploiement efficace de plusieurs ressources énergétiques distribuées. Ensuite, à travers la conception d'expériences avec la méthode de Taguchi, divers scénarios sont introduits en faisant varier des facteurs significatifs. Par la suite, une technique heuristique est proposée pour résoudre le problème de la gestion de l'énergie résidentielle en trouvant la solution optimale globale pendant plusieurs jours consécutifs avec une réduction significative du temps d'exécution.Deuxièmement, un modèle de gestion de l'énergie est assuré grâce à des modèles mathématiques pour optimiser l’utilisation du réseau, des ressources énergétiques renouvelables, des véhicules électriques et de la batterie, ainsi que pour différents types d'appareils thermiques et électriques. Une méthode de solution exacte est mise en œuvre pour réduire le coût de l'électricité dans une maison intelligente et pour trouver des modes de fonctionnement de différentes charges. Ensuite, un algorithme d'optimisation math-heuristique est proposé pour résoudre le problème avec un temps de simulation étendu.Enfin, nous étudions le problème de gestion de l'énergie dans un microréseau constitué de plusieurs maisons intelligentes. Chacune d'elles dépose de ressources énergétiques renouvelables, d’un véhicule électrique et d’appareils intelligents. Les ressources d'énergie renouvelable injectent l’excès de l'énergie dans un système de stockage d'énergie partagé. Un modèle mathématique linéaire mixte en entier pour la gestion d'énergie est proposé pour réduire le coût total de fonctionnement du microréseau. Des comparaisons avec des scénarios conventionnels où chaque maison intelligente possède son propre système de stockage d'énergie sont effectuées pour démontrer l’efficacité de la démarche proposée. / The current electricity grids will experience a profound change in the coming years. The new generation is the Smart Grid (SG) which is characterized by information and communication layer enabling the communication between the different components of the grid. It needs to consider all sides of power grid, making it more intelligent and flexible. This notion is presented as an answer to changes in the electricity market, aiming to manage the increased demand while ensuring a better quality of service and more safety.First, we present a mixed integer linear programming formulation to optimize the energy production and consumption systems in a smart home with an effective deployment of several distributed energy resources. Then through the design of experiments with the Taguchi method, diverse scenarios are introduced by varying significant factors. Afterward, a heuristic technique is proposed to solve the problem of residential energy management by finding the global optimum solution for many consecutive days with significant reduction of execution time.Second, an energy management model is proposed thanks to mathematical models to optimize the grid, renewable energy resources, battery and electric vehicles are presented as well as for different type of thermal and electrical appliances. An exact solution method is implemented to reduce the electricity cost in a smart home and find out operation modes of different loads. Then a math-heuristic optimization algorithm is proposed to solve the problem with extended simulation time horizon.Finally, we study a microgrid energy management problem which comprises multiple smart homes. Each of them owns renewable energy resources, one electric vehicle and smart appliances. The renewable energy resources inject the excess energy in the shared energy storage system. An optimized energy management model using mixed integer linear programming is proposed to reduce the total electricity cost in the microgrid. Comparisons with conventional scenarios where each smart home has its individual small energy storage system without sharing energy with their neighbors are done to ensure that the proposed formulation is well efficient.

The European policy focus on smart grids implies their development as an indispensable part of the future power system. However, the definition of a smart grid is broad and vague, and the actual implementation of a smart grid can differ significantly, depending on the stakeholders involved.This work aims to inform policy makers, the electricity industry and researchers about stakeholder interests and the technical complexities involved by presenting smart grids via a techno-institutional framework. This framework takes account of the technical nature of the electricity transport and supply service as well as the institutional nature of electricity markets, stakeholder perspectives and sector regulation. In addition, this work presents potential revenues resulting from flexibility management in smart grids and proposes a way forward for smart grids and flexibility management in Europe. / <p>QC 20170925</p>

No description available.

<p dir="ltr">Distributed energy resources (DERs), such as rooftop solar generation and energy storage systems, are becoming more prevalent in distribution systems. DERs are connected to the distribution system via power electronic converters, introducing faster dynamics in the system. Understanding the system dynamics under a high penetration of inverter-based DERs is critical for power system researchers and practitioners, driving the development of modeling techniques and simulation software. Aiming to reduce computational complexity, existing tools and techniques often employ various approximations. Meanwhile, modern advancements in computational hardware capabilities provide opportunities to include the faster time-scale dynamics. To address this, the primary objective of this thesis is to develop an open-source Python simulation package, Dynamic Simulation using Sparse Tableau Approach in Python, DynaSTPy (pronounced “dynasty”), capable of capturing the dynamics of all components in a distribution feeder. The distribution feeder is modeled as a system of Differential-Algebraic Equations (DAEs). Further, each component in the feeder is modeled based on the Sparse Tableau Approach (STA), which involves the representation of component model equations using sparse matrices, facilitating a systematic procedure to model the components and construct the system DAEs. In sinusoidal steady state, the DAEs can be represented in phasor form, extending the approach to perform power flow analysis of distribution feeders.</p>

Recently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten years in anticipation of the tremendous increase in the penetration of Distributed Generation (DG) in distribution system. This work proposes new IDMs that rely on transient and distributed behaviors to improve integrity and performance of DGs while maintaining multi-DG islanding detection capability. In this thesis, the following questions have been addressed: How to utilize the transient behavior arising from an islanding condition to improve detectability and robust performance of IDMs in a distributive manner? How to reduce the negative stability impact of the well-known Sandia Frequency Shift (SFS) IDM while maintaining its islanding detection capability? How to incorporate the perturbations provided by each of DGs in such a way that the negative interference of different IDMs is minimized without the need of any type of communication among the different DGs? It is shown that the proposed techniques are local, scalable and robust against different loading conditions and topology changes. Also, the proposed techniques can successfully distinguish an islanding condition from other disturbances that may occur in power system networks. This work improves the efficiency, reliability and safety of integrated DGs, which presents a necessary advance toward making electric power grids a smart grid.

由於石化能源的蘊藏量有限，各國政府目前以能源的安全供給與環保的使用做為主要的能源政策，經過各國公部門與私部門多年來的努力，許多替代能源的技術雖然開始商品化，但實際上對於傳統石化能源依賴度的減少，仍舊有限。反觀節能技術雖然表面上不如屬於”開源”概念的再生能源響亮，但技術的成熟度與產業化對於減少石化能源依賴的貢獻度並不亞於開源的效果，尤其許多發展中的國家短期內勢必無法負擔新的再生能源技術所要付出的昂貴能源費用，能源管理服務業所能提供的節能效果，可以同時解決能源效率低落所造成的浪費以及環境的衝擊。 而能源管理服務業重點在於節能，歐洲與日本市場無論是民眾或是政府在開發替代能源與節約能源的議題上之成果有目共睹，但反觀耗能最高的美國、發展中的中國，節能議題相對來講更形重要，這與台灣的狀況相當類似，因此本研究期望經由法制政策面、產業面以及智慧財產佈局狀況，探討美國與中國之能源管理服務業之現況，並與台灣本身能源管理服務業之發展做比較，提出能源管理服務業未來發展上的建議。 1. 能源管理服務業不宜將有限資源過分集中於發展太陽能與風力發電技術 2. 以美國市場為鏡，以中國大陸能源管理市場為目標 3. 積極從事中國大陸能源管理服務業相關技術之專利佈局 4. ”中央能源管理服務系統”概念的導入-節能減排的技術與服務的創新 5. 發展能源管理服務業住宅之應用 6. 創新的融資模式 7. 人員的培訓與教育 / Due to the limited deposits of fusil energy, the safety and environment protection of energy use ate the most two crucial issues among the countries. After decades of development, alternative energy commercialization successfully started in developed countries. Nevertheless, it’s still not material enough comparing to the energy consumption now days. However, the effect of the energy efficiency technologies is far more practical for developing countries that do not have enough budget for alternative renewable energy research and development. With effective energy management, the Energy Service Companies (ESCOs) can reduce significantly the waste of energy and the influence to the environment while mitigate the impact of the economical growth of emerging countries. ESCOs profit from the energy conservation of their clients by enhance the energy efficiency in various categories including utilities, government, industrial and commercial sectors. According to present study, European countries and Japan in Asia have already developed outstanding environmental friendly policies both in public and private sectors. On the other hand, highly energy consumption country like United States and rapidly growing China just started to deal with this global warming problem and hopefully can still maintain the economy growth at the same time. Undoubtedly, we face the same issue here in Taiwan. As a result, this study is trying to gather and analyze information about ESCO industry in United States, China and Taiwan from three aspects, governmental policies, industry environment and intellectual property strategies to conclude as well as raise opinion and suggestion about the future development of ESCOs. This study concludes in following opinion and suggestion, 1. ESCOs shouldn’t emphasize all their resources to conduct Solar and Wind power technologies instead of energy efficiency technologies. 2. Learn the track of ESCOs in United States and focus on the market in China. 3. Aggressively develop intellectual property strategies about ESCO related subjects in China. 4. Introduce the concept of “Centralized Energy Management System” and encourage innovation of law carbon discharge and high efficiency technologies. 5. Develop ESCO model in residential application. 6. Develop creative fund raising tools for ESCOs. 7. Invest in education and training program related to ESCO industry.