太陽光発電が導入された配電系統における蓄電池の最適計画・制御手法に関する研究

早大学位記番号:新8188早稲田大

Reinforcement Learning Based Cooperative P2P Energy Trading between DC Nanogrid Clusters with Wind and PV Energy Resources

In order to replace fossil fuels with the use of renewable energy resources, unbalanced resource production of intermittent wind and photovoltaic (PV) power is a critical issue for peer-to-peer (P2P) power trading. To resolve this problem, a reinforcement learning (RL) technique is introduced in this paper. For RL, graph convolutional network (GCN) and bi-directional long short-term memory (Bi-LSTM) network are jointly applied to P2P power trading between nanogrid clusters based on cooperative game theory. The flexible and reliable DC nanogrid is suitable to integrate renewable energy for distribution system. Each local nanogrid cluster takes the position of prosumer, focusing on power production and consumption simultaneously. For the power management of nanogrid clusters, multi-objective optimization is applied to each local nanogrid cluster with the Internet of Things (IoT) technology. Charging/discharging of electric vehicle (EV) is performed considering the intermittent characteristics of wind and PV power production. RL algorithms, such as deep Q-learning network (DQN), deep recurrent Q-learning network (DRQN), Bi-DRQN, proximal policy optimization (PPO), GCN-DQN, GCN-DRQN, GCN-Bi-DRQN, and GCN-PPO, are used for simulations. Consequently, the cooperative P2P power trading system maximizes the profit utilizing the time of use (ToU) tariff-based electricity cost and system marginal price (SMP), and minimizes the amount of grid power consumption. Power management of nanogrid clusters with P2P power trading is simulated on the distribution test feeder in real-time and proposed GCN-PPO technique reduces the electricity cost of nanogrid clusters by 36.7%.Comment: 22 pages, 8 figures, to be submitted to Applied Energy of Elsevie

Smart Energy Management for Smart Grids

This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book

Power Management of Nanogrid Cluster with P2P Electricity Trading Based on Future Trends of Load Demand and PV Power Production

This paper presents the power management of the nanogrid clusters assisted by a novel peer-to-peer(P2P) electricity trading. In our work, unbalance of power consumption among clusters is mitigated by the proposed P2P trading method. For power management of individual clusters, multi-objective optimization simultaneously minimizing total power consumption, portion of grid power consumption, and total delay incurred by scheduling is attempted. A renewable power source photovoltaic(PV) system is adopted for each cluster as a secondary source. The temporal surplus of self-supply PV power of a cluster can be sold through P2P trading to another cluster (s) experiencing temporal power shortage. The cluster in temporal shortage of electric power buys the PV power to reduce peak load and total delay. In P2P trading, a cooperative game model is used for buyers and sellers to maximize their welfare. To increase P2P trading efficiency, future trends of load demand and PV power production are considered for power management of each cluster to resolve instantaneous unbalance between load demand and PV power production. To this end, a gated recurrent unit network is used to forecast future load demand and future PV power production. Simulations verify the effectiveness of the proposed P2P trading for nanogrid clusters.Comment: This article is submitted for publication in Sustainable Cities and Societ

日射量予測を考慮した太陽光発電コミュニティにおけるエネルギーシェアリングに関する研究

The power sector plays an important role in energy conservation and emission reduction. Renewable energy, especially solar PV, has been growing steadily in recent years. The development of solar energy can not only reduce the use of fossil energy, but also increase the energy self-sufficiency rate. After the implementation of the FiT system in 2011, there has been an explosive growth in the import of solar PV. However, solar power generation exhibits unstable output characteristics as it is affected by weather conditions. Large-scale introduction can affect the stability of the grid. Therefore, this study considers the unstable weather conditions (mainly, solar radiation) and proposes the concept of energy sharing to increase the chances of local energy self-consumption and renewable energy penetration in the future. At the same time, we aim to explore the interactions between smart grids, smart buildings, and distributed energy storage to achieve better energy management practices.北九州市立大

Optimal coordination of energy sources for microgrid incorporating concepts of locational marginal pricing and energy storage

This research aims to coordinate energy sources for standalone microgrid (MG), incorporating locational marginal pricing (LMP) and energy storage. Two approaches are suggested for the optimal energy management of MG. First, the energy management of a standalone MG is performed utilising the concept of LMP. The objective is to minimise the average LMP to reduce network congestion and power loss costs. Second, energy management is performed using a dual-stage energy management approach. A BESS model is formulated considering charging and discharging characteristics and utilised in this research for dual-stage energy management. The impact of the battery state of charge (SOC) is assessed in the optimal day-ahead operation. An incremental cost factor is included with battery SOC when calculating the system operating cost. A new binary jellyfish search algorithm (BJSA) is developed to solve energy management problems. The suggested BJSA technique is implemented in solving the optimal energy management of MG considering LMP. The simulations of the suggested approach are conducted on the IEEE 14 and 30-bus test systems. Results show that the BJSA technique is more consistent than the binary particle swarm optimisation (BPSO) technique in determining the optimal solution. In addition, the BJSA technique is employed to solve the dual-stage energy management of MG considering BESS. The proposed approach is simulated on the IEEE 14 and 30-bus systems. Results also show that the BJSA technique is superior to the BPSO technique in minimising the operating cost in real-time economic dispatch (ED). The performance of the BJSA and BPSO techniques is exactly similar to the UC schedule with and without BESS considering the IEEE 30-bus system, like the IEEE 14-bus system. The BJSA technique minimises operating costs by up to 5% over the BPSO technique for the UC schedule with power loss. Operating costs are reduced by up to 5% using the BJSA technique rather than the BPSO technique for real-time ED with BESS. However, the BPSO technique is inconsistent and fails to obtain the same results for the IEEE 30-bus system. Overall, the findings confirm the superiority of the suggested BJSA technique and the suggested optimisation approaches in optimising the energy management of MG

Electric Mobility: Smart Transportation in Smart Cities

2014 - 2015One of the mega trends over the past century has been humanity’s move towards cities. Public Administration and Municipalities are facing a challenging task, to harmonize a sustainable urban development offering to people in city the best living conditions. Smart cities are now considered a winning urban strategy able to increase the quality of life by using technology in urban space, both improving the environmental quality and delivering better services to the citizens. Mobility is a key element to support this new approach in the growth of the cities. In fact, transport produces several negative impacts and problems for the quality of life in cities, such as, pollution, traffic and congestion. Therefore, Sustainable Mobility is one of the most promising topics in smart city, as it could produce high benefits for the quality of life of almost all the city stakeholders. The boldest and imminent challenge awaiting mobility in smart cities is the introduction of the electricity as energy vector instead of fossil fuels, concerning both the collective and the private transports. Electric public transport include electric city buses, trolleybuses, trams (or light rail), passenger trains and rapid transit (metro/subways/undergrounds, etc.). Even though railway systems are the most energy efficient than other transport modes, the enhancement of energy efficiency is an important issue to reduce their contributions to climate change further as well as to save and enlarge competition advantages involved. One key means for improving energy efficiency is to deploy advanced systems and innovative technologies. Additionally, electrification of the private road transport has emerged as a trend to support energy efficiency and CO2 emissions reduction targets. According to the International Energy Agency, in order to limit average global temperature increases to 2°C - the critical threshold that scientists say will prevent dangerous climate change -, by 2050, 21% of carbon reductions must come from the transport sector. Full electric vehicles (EVs) use electric motor and battery energy for propulsion, which has higher efficiency and lower operating cost compared to the conventional internal combustion engine vehicle. Today, there are more than 20 models offered by different brands covering different range of sizes, styles, prices and powertrains to suit the wider range of consumers as possible. The continuous development of lithium ion battery and of fast charging technology will be the major facilitators for EVs roll out in the very near future. However, the present EVs industry meets many technical limitations, such as high initial price, long battery recharge time, limited charging facilities and driving range. Although it is desirable a fast development from the start of electric mobility, its impact on the existing power grid must be assessed beforehand to see if it is necessary prior an adjustment of power infrastructure or/and the introduction of new services in the power grid. In fact, the interconnection of EVs on the power grid for charging their batteries potentially introduces negative impacts on grid operation: uncontrolled charging can significantly increase average load in the existing power systems, with problems in terms of reliability and overloads. If uncontrolled EV charging is added to the system, this can have effects both at the distribution and at the generation level. Controlled or smart charging will allow a much greater number of cars in the cities, avoiding local overload and allowing a faster EVs penetration without requiring an imminent improvement of the electricity generating and grid capacity. Smart charging might also allow load balancing both at sub-station and at the grid level, particularly with charging at peak wind supply times. This kind of use of EV battery capacity for storing electric energy may ease the integration of large scale intermittent electricity sources such as renewable energy sources. The proposed PhD Dissertation is developed in the context just described, mainly focusing the attention on the impact that electric mobility will have on the power systems and the effectiveness of solutions aimed to increase the reliability and resilience in the smart grid. In particular, it is addressed a scenario analysis regarding the electric vehicles charging management and some innovative solutions to increase energy efficiency in electrified transport systems. The first chapter emphasizes on the key aspects related to the sustainable mobility in the smart cities of the future. It provides a brief overview on the transport sector energy consumption expected in the next years. In particular, the chapter shows the significant contribution that the electrification of urban transport may provide to the sustainable mobility, and the serious concerns related to its impact on existing power systems. Chapter 2 proposes a solution method for an optimal generation rescheduling and load-shedding (GRLS) problem in microgrids in order to determine a stable equilibrium state following unexpected outages of generation or sudden increase in demand. The chapter mainly focuses on the mathematical formulation of the GRLS problem and the proposed solution algorithm. Finally, simulations results carried out by using a real case study data are presented and discussed. In Chapter 3, a simple and effective methodology is proposed to analyze data acquired during the fulfillment of the COSMO research project, and to identify typical load pattern for the EVs charging. The chapter also presents a novel scheduling problem formulation, flattening the demand load profile and minimizing the EVs charging costs, according to the electricity prices during the day. Finally, some simulations results are discussed, showing the effectiveness of the proposed methodology. Chapter 4 introduces some innovative solutions for energy efficiency in urban railway systems focusing, in particular, on energy storage systems and eco-drive operations in metro networks. The mathematical formulation of these optimization problems and the proposed solution algorithms are illustrated and discussed. The obtained results are part of the activity carried out in the SFERE research project. Finally, Chapter 5 ends the Dissertation with some concluding remarks and further developments of the proposed research activity. [edited by author]Una delle grandi tendenze nel corso del secolo scorso è stata la concentrazione della popolazione nelle città. Attualmente, le Pubbliche Amministrazioni e i Comuni si trovano ad affrontare un compito impegnativo per armonizzare uno sviluppo urbano sostenibile e offrire agli abitanti delle città le migliori condizioni di vita. Le smart cities sono ormai considerate una strategia urbana vincente in grado di aumentare la qualità della vita utilizzando la tecnologia, sia per il miglioramento della qualità ambientale che per fornire servizi migliori ai cittadini. A tale scopo, la mobilità risulta essere un elemento chiave per sostenere questo nuovo approccio nella crescita delle città. Infatti, i sistemi di trasporto urbano producono diversi effetti negativi sulla qualità della vita urbana, come ad esempio, inquinamento, traffico e congestione. Pertanto, la mobilità sostenibile è uno degli argomenti più interessanti per le smart cities, in quanto in grado produrre elevati benefici per la qualità della vita di quasi tutte le parti interessate degli agglomerati urbani. La sfida più audace e imminente per la mobilità nelle smart cities del futuro è l'introduzione dell'elettricità come vettore energetico al posto dei combustibili fossili, per quanto riguarda sia il trasporto collettivo che quello privato. I mezzi per il trasporto pubblico comprendono autobus elettrici, filobus, tram, treni passeggeri e trasporto rapido (metropolitane, etc.). Anche se i sistemi di trasporto su ferro sono più efficienti rispetto ad altri modi di trasporto, l’incremento dell'efficienza energetica è un tema importante per ridurre ulteriormente il loro contributo alle emissioni inquinanti e al consumo di energia. Le più promettenti soluzioni per migliorarne l'efficienza energetica consistono nell’implementazione di sistemi avanzati per il recupero dell’energia di frenata e tecnologie di controllo innovative. D’altro canto, l'elettrificazione del trasporto individuale su strada è emersa come una tendenza finalizzata a sostenere gli obiettivi di efficienza energetica e di riduzione delle emissioni di CO2. Secondo l'Agenzia Internazionale per l'Energia, al fine di limitare, entro il 2050, l'aumento della temperatura media globale a 2 °C - la soglia critica che gli scienziati suggeriscono di non superare per evitare pericolosi cambiamenti climatici -, il 21% delle riduzioni di biossido di carbonio deve provenire dal settore trasporti. I veicoli elettrici (EV) utilizzano un motore elettrico e l'energia accumulata nelle batterie per la propulsione, in modo da avere una maggiore efficienza e minori costi operativi rispetto ai veicoli convenzionali con motore a combustione interna. Oggi, esistono in commercio più di 20 modelli offerti da diverse case produttrici che coprono una ampia gamma di modelli che differiscono per dimensione, stile, prezzo e motorizzazione in modo da soddisfare il maggior numero di consumatori possibile. Il continuo sviluppo delle batterie al litio e delle tecnologie di ricarica rapida saranno i principali fattori abilitanti per la diffusione degli EV in un futuro molto prossimo. Tuttavia, l'attuale industria dei veicoli elettrici incontra molte limitazioni tecnico-economiche, come elevati costi, autonomia e tempi di ricarica della batteria, capillarità delle infrastrutture di ricarica. Sebbene sia auspicabile un rapido sviluppo della mobilità elettrica, il suo impatto sulla rete elettrica esistente deve essere investigato a fondo per verificare la necessità di potenziamenti delle infrastrutture e/o l'introduzione di nuovi servizi nella rete elettrica. Infatti, l'interconnessione dei veicoli elettrici con la rete di distribuzione dell’energia necessaria per la ricarica delle batterie può causare effetti negativi sul normale funzionamento del sistema elettrico: una ricarica degli EV non controllata può aumentare significativamente il carico medio negli impianti esistenti, introducendo problemi di affidabilità e sovraccarico. La ricarica intelligente o controllata degli EV consente, invece, di gestire un numero molto maggiore di autovetture elettriche nelle città, riducendo le possibilità di sovraccarico locale e di velocizzare la penetrazione della mobilità elettrica senza che rendere necessari imminenti potenziamenti dei sistemi di produzione di energia elettrica e incrementi della capacità di rete. La ricarica intelligente, inoltre, può anche influire sul bilanciamento del carico sia a livello della sottostazione elettrica che a livello di rete di distribuzione, in particolare quando si verificano molte sessioni di ricarica nelle ore di punta. Infatti, l’utilizzo della capacità della batteria degli EV per l’accumulo di energia elettrica può facilitare l'integrazione su larga scala delle fonti di energia non programmabili, come quelle rinnovabili. Il lavoro di tesi si sviluppa nel contesto di riferimento appena descritto, focalizzando l'attenzione soprattutto sull'impatto che la mobilità elettrica ha sui sistemi elettrici e sull'efficacia di nuove soluzioni finalizzate all’incremento dell'affidabilità nelle smart grids. In particolare, viene proposta un'analisi di scenario per quanto riguarda la gestione intelligente delle ricariche dei veicoli elettrici e alcune soluzioni innovative per aumentare l'efficienza energetica nei sistemi di trasporto elettrificati. Il primo capitolo sottolinea gli aspetti chiave relativi alla mobilità sostenibile nelle smart cities del futuro e fornisce una breve panoramica sul consumo energetico del settore trasporti previsto nel prossimo futuro. In particolare, vengono evidenziate da un lato il significativo contributo che l'elettrificazione dei trasporti urbani può fornire alla causa della mobilità sostenibile, e dall’altro, le gravi preoccupazioni legate all’impatto sui sistemi elettrici esistenti di un notevole incremento della domanda. Il Capitolo 2 propone un metodo per la soluzione del problema congiunto di scheduling dei generatori e load shedding (GRLS) all’interno di microgrids portando in conto l’incertezza sia sulla domanda che lato generazione. Il fine è determinare un nuovo stato di equilibrio stabile in seguito a guasti, riduzione della generazione da fonte rinnovabile o improvviso aumento della domanda. Il capitolo si concentra principalmente sulla formulazione matematica del problema GRLS e sull'algoritmo di soluzione proposto. Infine, sono presentati e commentati i risultati di simulazione basati su un caso studio reale. Nel Capitolo 3, è proposta una metodologia semplice ed efficace per identificare profili di carico tipico relativi alla ricarica di veicoli elettrici: in particolare, l’analisi condotta si basa sull’analisi dei dati acquisiti durante lo svolgimento del progetto di ricerca COSMO. Il capitolo, inoltre, introduce una formulazione matematica del problema dello scheduling delle ricariche dei veicoli elettrici, che garantisce un appiattimento del profilo di carico e riduce allo stesso tempo il costo della ricarica per gli utenti. Infine, sono commentati i risultati delle simulazioni eseguite dimostrando l'efficacia della metodologia proposta. Il Capitolo 4 introduce alcune soluzioni innovative per l'efficienza energetica nei sistemi di trasporto urbani: l’attenzione viene posta, in particolare, sui sistemi di accumulo dell’energia e sulla condotta di guida Eco-Drive in reti metropolitane. In dettaglio, nel capitolo, vengono introdotti e commentati la formulazione matematica dei problemi di ottimizzazione proposti e i rispettivi algoritmi di soluzione. I risultati ottenuti fanno parte delle attività svolte nell’ambito del progetto di ricerca SFERE. Infine, il Capitolo 5 conclude la tesi con alcune osservazioni finali e con i possibili sviluppi dell'attività di ricerca proposta. [a cura dell'autore]XIV n.s

Energy storage for complementary services in grid-tied PV systems

The continuous increase in penetration of renewable-based power plants together with the intermittent and variable nature of those natural resources have made grid stability issues a major concern, imposing limitations to higher penetration rates. Energy Storage Systems (ESS) have arise as an enabling technology capable of providing PV/ESS configurations with additional capabilities, as such as ancillary or complementary services. This work presents a complete analysis of three difierent complementary services (Maximum Power Ramp Rate limitations, Power Clipping and Peak Shaving). Additionally two different PV/ESS configurations are analysed. For that purpose, three different power converter interfaces between PV and ESS were tested. The results obtained from those tests, showing the performance of the aforementioned complementary services, are presented in this thesis. Moreover, the experimental validation of a PV/ESS, which consists of a full bridge based partial power converter as power interface between PV system and ESS, is also presented in this document. This document also includes two different ESS sizing strategies, each for an specific complementary service. These sizing strategies rely on a prediction of a year of PV power generation obtained from annual measurements of irradiance and temperature. In both cases, the resulting power prediction is contrasted against a desired power profile

Renewable energy challenges and opportunities. The prospect of adopting a new policy and legal paradigm in Ghana

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonGlobal consumption of fossil fuels has wreaked havoc on the environment through anthropogenic greenhouse gas emissions. Meeting the ever-increasing demand for energy and limiting its impact on the environment are the two intertwined issues that confront the world. Against this backdrop, national and international stakeholders have been called to transition to renewable energy (RE) to provide energy security and stem climate change. As such, governments around the world have been formulating legal and policy frameworks to encourage the deployment of RE along with technological innovations. However, poor legal frameworks and policies, insufficient financial support, and incentives have rendered the adoption of RE technologies, especially in developing countries, woefully inadequate and Ghana is no exception. In Ghana, various legal and policy frameworks have been deployed for the development of hydro and non-hydro RE. However, the contribution of non-hydro RE (solar and wind) to the country's electricity generation mix is paltry due to various challenges. The research uses desktop analysis, empirical research, and comparative analysis to critically examine the existing Renewable Energy Act, 2011 (Act 832) and policies on RE in Ghana to ascertain the extent to which they effectively address energy security challenges. The results reveal many challenges as follows: a general poor implementation of the provisions of the Act, poor funding, obsolete grid network, transmission and distribution losses, and bureaucratic processes in licence acquisition to be responsible for the paltry diffusion of non-hydro RE in Ghana whose share was 0.3% in 2020. The research recommends that the government of Ghana (GoG) reviews the existing Renewable Energy Act, policies, and regulatory frameworks currently in operation to address deployment constraints. The thesis concludes by calling on the GoG to focus on specific legal and policy frameworks that would promote solar photovoltaic deployment as the country is endowed with abundant solar energy

Contributions à l'amélioration de la performance statique des réseaux T & D intégrés en présence des REDs

Avec la croissance des nouvelles technologies émergentes dans les réseaux de distribution, tels que les éoliennes, les panneaux solaires, les véhicules électriques et les sources de génération distribuées, la nécessité d'étudier simultanément les réseaux de transmission et de distribution (T&D) et leurs interactions bilatérales ne peut plus être négligée. Une forte pénétration des sources d'énergie renouvelable, naturellement stochastiques, peut inverser le flux d'énergie, ce qui ne rentre pas dans le paradigme d’un écoulement de puissance à flux descendant qui caractérise les systèmes d'alimentation conventionnels. Par conséquent, les méthodes d'étude de réseaux telles que le fux de puissance optimal (Optimal Power Flow), l'engagement des groupes de production (unit commitment) et l'analyse de la stabilité doivent être revisitées. Cette thèse propose l'application de systèmes de stockage d'énergie sur batterie (BESS) dans un cadre intégré de T&D minimisant les impacts négatifs des énergies renouvelables insérées dans le réseau de distribution ou chez le client. Les BESS peuvent être interprétés comme des équipements flexibles supplémentaires, contrôlés à distance et/ou localement, qui absorbent ou libèrent des puissances actives et réactives et améliorent l'efficacité globale du système T&D au complet du point de vue de la stabilité et de la performance dynamique. Selon la pratique courante, les études des systèmes T&D intégrés peuvent être classées en sous-groupes d’études dynamiques vs stationnaires ou en sous-groupes d’études de cooptimisation vs co-simulation. Suivant la même approche, l’analyse à l’état d’équilibre est d’abord lancée par un nouvel outil d’allocation optimisée stochastique de BESS (VSCSOBA) à contrainte de stabilité de tension. L'outil d'optimisation développé basé sur GAMS à deux niveaux prend en compte les BESS et des modèles détaillés de ressources énergétiques distribuées stochastiques tout en minimisant principalement les pertes de puissance active, mais les écarts de tension, les coûts de délestage, l'augmentation de la capacité de charge (chargeabilité ou « loadbility ») ainsi que la réduction de la vulnérabilité sont aussi des fonctions objectives qui ont été considérées. L’applicabilité de l’outil proposé a été confirmée sur des cas d’utilisation basés sur des réseaux T&D benchmark de l’IEEE comportant des centaines de variables et contraintes. Dans la partie suivante, l'architecture du framework de co-simulation, ainsi que les différents acteurs clés qui y participent seront examinés. Les objectifs de cette partie sont les suivants : développer, simuler et résoudre des équations algébriques de chaque niveau indépendamment, à l'aide de simulateurs bien connus, spécifiques à un domaine (c’est-à-dire, transport vs distribution), tout en assurant une interface externe pour l'échange de données. L'outil d'interface devrait établir une connexion de partage de données robuste, fiable et bilatérale entre deux niveaux de système. Les idées et les méthodologies proposées seront discutées. Pour completer cette étude, La commutation optimale de réseaux de transport (Optimal Transmission Switching) en tant que nouvelle méthode de réduction des coûts d'exploitation est considérée d'un point de vue de la sécurité, en assument ou non la présence des BESS. De toute évidence, l'OTS est un moyen efficace (tout comme la référence de tension ou le contrôle des références de puissances P-Q) qui s’avère nécessaire dans le cadre T&D intégré, tel que nous le démontrons à travers divers cas d'utilisation. Pour ce faire, afin de préserver la sécurité des systèmes de transport d'électricité contre les attaques ou les catastrophes naturelles telles que les ouragans et les pannes, un problème OTS stochastique orienté vulnérabilité (VO-SOTS) est également introduit dans cette thèse tout en considérant l'incertitude des charges via une approche par échantillonage de scénarios respectant la distribution statistique des incertitudes.With the growing trend of emerging new technologies in distribution networks, such as wind turbines, solar panels, electric vehicles, and distributed generations, the need for simultaneously studying Transmission & Distribution (T&D) networks and their bilateral interactions cannot be overlooked anymore. High penetration of naturally stochastic renewable energy sources may reverse the energy flow which does not fit in the top-down energy transfer paradigm of conventional power systems. Consequently, network study methods such as optimal power flow, unit commitment, and static stability analysis need to be revised. This thesis proposes application of battery energy storage systems (BESS) within integrated T&D framework minimizing the adverse impacts of renewable energy resources. The BESSs can be interpreted as additional flexible equipment, remotely and/or locally controlled, which absorb or release both active and reactive powers and improve the overall efficiency of the complete T&D system from both steady-state and dynamic viewpoints. As a common practice, the integrated T&D framework studies are categorized into either dynamic and steady-state subcases or co-optimization framework and co-simulation framework. Following the same approach, the steady-state analysis is first initiated by a novel voltage stability constrained stochastic optimal BESS allocation (VSC-SOBA) tool. The developed bi-level GAMS-based optimization tool takes into account BESSs and detailed models of stochastic distributed energy resources while minimizing active power losses, voltage deviation, load shedding costs, increasing loadability, and vulnerability mitigation are objective functions. The applicability of proposed tool has been confirmed over large IEEE recognized T&D benchmarks with hundreds of variables and constraints. In the next part, the architecture of co-simulation framework and different key players will be investigated. The objectives of this part are set as: developing, simulating, and solving differential and algebraic equations of each level independently, using existing well-known domain-specific simulators, while externally-interfaced for exchanging data. The interface tool should stablish a robust, reliable, and bilateral data sharing connection between two levels of system. The ideas and proposed methodologies will be discussed. To complete this study, optimal transmission switching (OTS) as a new method for reduction of operation costs is next considered from a security point of view. It is shown clearly that OTS is an effective mean (just like voltage reference or P-Q reference control), which is necessary in the integrated T&D framework to make it useful in dealing with various emerging use cases. To do so without impeding the security of power transmission systems against attacks or natural disasters such as hurricane and outages, a vulnerability oriented stochastic OTS (VO-SOTS) problem is also introduced in this thesis, while considering the loads uncertainty via a scenario-based approach