A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of renewable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co-optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system

Enhancement of flexibility in multi-energy microgrids considering voltage and congestion improvement: Robust thermal comfort against reserve calls

In recent years, multi-energy microgrid (MEM) has gained increasing interest, which could use clean and efficient electro-thermal resources, multi-energy storages (MESs) and demand response potential to improve the flexibility of MEM. However, maximizing the flexibility potential of MEM and alongside managing the electrical parameters (EPs) is a challenging modeling problem. In this paper, a probabilistic nonlinear model is presented to maximize the flexibility with all the power grid constraints taking into account EPs constraints using power flow. To this end, voltage profile and congestion improvement, robust thermal comfort provision during reserve call and MESs utilization are the key properties of the proposed model. The outcome of suggested model ensures sustainability in the MEM performance, which is an essential feature in modern smart cities. The presented model is applied to a distribution network in the UK and results illustrate how equipment scheduling and demand response leads to observe the EPs limitation and maximizes MEM flexibility. The achieved results show a decrease in MEM revenue (decrease of 34% and 24% without and with reserve commitment, respectively) and in contrast, a significant increase in flexibility compared to non-compliance with EPs constraints

Co-optimizing High and Low Voltage Systems: Bi-Level vs. Single-Level Approach

This paper presents a bi-level optimization framework applied to optimize system performance with (i) increasing presence of distributed energy resources (DER) at the low-voltage level, and (ii) variable wind power generation at the high-voltage level. The paper investigates various system configurations with increasing presence of microgrids, with active devices. System simulations quantify system performance in terms of cost, first using the traditional single-level optimization framework, and second using the proposed bi-level framework. Comparisons between the system with traditional, passive distribution systems and with microgrids are also presented, with results again quantified via the interconnected system operating costs. Results show that at low levels of DER and microgrid penetration, traditional (single-level) system optimization algorithms perform adequately as compared to the proposed bi-level optimization framework. However, as DER and microgrid penetration increase, the traditional single-level framework does not accurately capture the full system benefits of distributed technologies. The results demonstrate that new optimization algorithms, such as the proposed bi-level framework, will be required if the benefits of DER are to be accurately quantified in the evolving power system

Computational Enhancement for Day-Ahead Energy Scheduling with Sparse Neural Network-based Battery Degradation Model

Battery energy storage systems (BESS) play a pivotal role in future power systems as they contribute to achiev-ing the net-zero carbon emission objectives. The BESS systems, predominantly employing lithium-ion batteries, have been exten-sively deployed. The degradation of these batteries significantly affects system efficiency. Deep neural networks can accurately quantify the battery degradation, however, the model complexity hinders their applications in energy scheduling for various power systems at different scales. To address this issue, this paper pre-sents a novel approach, introducing a linearized sparse neural network-based battery degradation model (SNNBD), specifically tailored to quantify battery degradation based on the scheduled BESS daily operational profiles. By leveraging sparse neural networks, this approach achieves accurate degradation predic-tion while substantially reducing the complexity associated with a dense neural network model. The computational burden of inte-grating battery degradation into day-ahead energy scheduling is thus substantially alleviated. Case studies, conducted on both microgrids and bulk power grids, demonstrated the efficiency and suitability of the proposed SNNBD-integrated scheduling model that can effectively address battery degradation concerns while optimizing day-ahead energy scheduling operations

EcoBlock: Grid Impacts, Scaling, and Resilience

Widespread deployment of EcoBlocks has the potential to transform today's electricity system into one that is more resilient, flexible, efficient and sustainable. In this vision, the system will consist of self- su cient, renewable-powered, block-scale entities that can deliberately adjust their net power exchange and can optimize performance, maintain stability, support each other, or disconnect entirely from the grid as needed. This report is intended as an independent analysis of the potential relationships, both constructive and adverse, between EcoBlocks and the grid

Towards realization of an Energy Internet: Designing distributed energy systems using game-theoretic approach

Distributed energy systems play a significant role in the integration of renewable energy technologies. The Energy Internet links a fleet of distributed energy systems to each other and with the grid. Interactions between the distributed energy systems via information sharing could significantly enhance the efficiency of their real-time operation. However, privacy and security concerns hinder such interactions. A game-theoretic approach can help in this regard, and enable consideration of some of these factors when maintaining interactions between energy systems. Although a game-theoretic approach is used to understand energy systems\u27 operation, such complex interactions between the energy systems are not considered at the early design phase, leading to many practical problems, and often leading to suboptimal designs. The present study introduces a game-theoretic approach that enables consideration of complex interactions among energy systems at the early design phase. Three different architectures are considered in the study, i.e., energy eystem prior to grid (ESPG), fully cooperative (FCS), and non-cooperative (NCS) scenarios, in which each distributed energy system is taken as an agent. A novel distributed optimization algorithm is developed for both FCS and NCS. The study reveals that FCS and NCS reduce the cost, respectively, by 30% and 15% compared to ESPG. In addition to cost reduction, there is a significant change in the energy system design when moving from FCS to NCS scenarios, clearly indicating the requirement for a scenario that lies between NCS and FCS. This will lead to reducing design costs while maintaining privacy

Flexibility services for distribution network operation

On the way towards a low carbon electricity system, flexibility has become one of the main sources for achieving it. Flexibility can be understood as the ability of a power system to cope with the variability and uncertainty of demand and supply. Both the generation-side and the demand-side can provide it. This research is focused on the role of the demand-side flexibility for providing a service to the distribution system operator, who manages the medium and low-voltage network. By activating this flexibility from the demand-side to the distribution network operator, the latter can avoid or mitigate congestions in the network and prevent grid reinforcement. This thesis starts with analyzing the current state of the art in the field of local electricity markets, setting the baseline for flexibility products in power systems. As a result of the previous analysis, the definition of flexibility is developed more specifically, considering the flexible assets to be controlled, the final client using this flexibility and the time horizon for this flexibility provision. Following the previous step, an aggregated flexibility forecast model is developed, considering a flexibility portfolio based on different flexible assets such as electric vehicles, water boilers, and electric space heaters. The signal is then modeled under a system-oriented approach for providing a service to the distribution network operator under the operation timeline on a day-ahead basis. The flexibility required by the distribution network operator is then calculated through an optimization problem, considering the flexibility activation costs and the network power flow constraints. Finally, since this scenario aims to lower the environmental impacts of the power system, its sustainability is assessed with the life-cycle assessment, considering the entire life cycle and evaluating it in terms of greenhouse gas emissions. This approach enhances the analysis of the potential role of flexibility in the power system, quantifying whether, in all cases, there is a reduction of emissions when shifting the consumption from peak hours to non-peak hours.En el camí cap a un sistema elèctric amb baixes emissions de carboni, la flexibilitat s'ha convertit en una de les principals fonts per aconseguir-ho. La flexibilitat es pot entendre com la capacitat d'un sistema de reaccionar davant la variabilitat i la incertesa provocades per la demanda i la generació. Tant la part de la generació com el costat de la demanda tenen actius per a poder proporcionar-ho. La recerca presentada en aquest manuscrit està enfocada en el paper de la flexibilitat oferta per la demanda, per a proporcionar un servei a l'operador del sistema de distribució, que gestiona les xarxes de mitja i baixa tensió. Gràcies a l'activació de la flexibilitat de la demanda, l'operador de les xarxes de distribució pot evitar o mitigar la congestió de la xarxa i evitar-ne les inversions per a reforçar-la, així com el seu impacte ambiental. Aquesta tesi comença amb l'anàlisi de l'estat de l'art en el camp dels mercats d'electricitat locals, establint-ne la línia base per a la definició dels productes de flexibilitat en els sistemes elèctrics. Com a resultat de l'estudi anterior, la definició de flexibilitat es desenvolupa més específicament, considerant els actius flexibles que han de controlar-se, el client final que utilitza aquesta flexibilitat i l'horitzó temporal per a aquesta disposició de flexibilitat. A continuació es desenvolupa un model de predicció de flexibilitat agregada, considerant una cartera de flexibilitat basada en diferents actius flexibles, com ara vehicles elèctrics, calderes d'aigua i escalfadors elèctrics, gestionats per la figura de l’agregador. El senyal es modela sota un enfocament orientat al sistema per proporcionar un servei a l'operador de la xarxa de distribució, per un horitzó temporal corresponent a l'operació de la xarxa de mitja i baixa tensió. El resultat és un model de la flexibilitat que pot oferir l’agregador. Una vegada desenvolupat el model de flexibilitat pel costat de l’agregador, la tesi s’enfoca al càlcul de la flexibilitat requerida per l’operador de la xarxa de distribució. Això es desenvolupa mitjançant un problema d'optimització, tenint en compte els costos d'activació de la flexibilitat, la localització dels punts on s’injectarà la flexibilitat i les restriccions de flux de potència de la xarxa de distribució. Finalment, atès que aquest escenari pretén reduir l'impacte mediambiental del sistema elèctric, la seva sostenibilitat s'avalua considerant tot el cicle de vida de les tecnologies que hi participen, i avaluant-la en termes d'emissions de gasos d'efecte d'hivernacle. L'ús d'aquest enfocament millora l'anàlisi del potencial paper de la flexibilitat en el sistema elèctric, quantificant si, en tots els casos, hi ha una reducció de les emissions traslladant el consum de les hores punta a hores vall.Postprint (published version

A Peer-to-Peer Energy Trading Framework in Distribution Systems Considering Network Constraints

With the widespread adoption of Renewable Energy Sources (RESs) in low-voltage distribution systems, opportunities for energy trading among peers have emerged. In particular, the advent of distributed ledgers and blockchain technologies has catalyzed the application of Peer-to-Peer (P2P) economic concepts in decentralized, small-scale energy trading. This paper focuses on the critical physical layer aspects of transactions within the context of P2P energy trading, with a specific emphasis on addressing network constraints. Key challenges include maintaining margins for over/under voltage, voltage balance, and preventing congestion, all of which must be upheld during P2P energy exchanges. To address these challenges, we propose a novel analytical approach tailored to distribution networks. Furthermore, we introduce the Block Double Auction (BDA) mechanism as the P2P market mechanism for determining the acceptance or rejection of P2P transactions. The effectiveness of our proposed method is validated using the IEEE 33-node distribution test system, demonstrating its robust capabilities.Comment: 10 pages, 8 fig