Sustainable distribution network planning considering multi-energy systems and plug-in electric vehicles parking lots

Entre todos os recursos associados à evolução das redes elétricas para o conceito de smart grid, os sistemas de multi-energia e os veículos eléctricos do tipo plug-in (PEV) são dois dos principais tópicos de investigação hoje em dia. Embora estes recursos possam acarretar uma maior incerteza para o sistema de energia, as suas capacidades de demanda/armazenamento flexível de energia podem melhorar a operacionalidade do sistema como um todo. Quando o conceito de sistemas de multi-energia e os parques de estacionamento com estações de carregamento para os PEVs são combinados no sistema de distribuição, a demanda pode variar significativamente. Sendo a demanda de energia uma importante informação no processo de planeamento, é essencial estimar de precisa essa demanda. Deste modo, três níveis padrão de carga podem ser extraídos tendo em conta a substituição da procura entre carriers de energia, a demanda associada ao carregamento dos PEVs, e presença de parques de estacionamento com estações de carregamento no sistema. A presença de PEVs num sistema multi-energia obriga a outros requisitos (por exemplo, um sistema de alimentação) que devem ser fornecidos pelo sistema, incluindo as estações de carregamento. A componente elétrica dos PEVs dificulta a tarefa ao operador do sistema na tentativa de encontrar a melhor solução para fornecer os serviços necessários e utilizar o potencial dos PEVs num sistema multi-energia. Contudo, o comportamento sociotécnico dos utilizadores de PEVs torna difícil ao operador do sistema a potencial gestão das fontes de energia associada às baterias. Desta forma, este estudo visa providenciar uma solução para os novos problemas que irão ocorrer no planeamento do sistema. Nesta tese, vários aspetos da integração de PEVs num sistema multi-energia são estudados. Primeiro, um programa de resposta à demanda é proposto para o sistema multi-energia com tecnologias do lado da procura que possibilitem alternar entre fornecedores de serviços. Em seguida, é realizado um estudo abrangente sobre as questões relativas à modelação dos PEVs no sistema, incluindo a modelação das incertezas, as preferências dos proprietários dos veículos, o nível de carregamento dos PEV e a sua interação com a rede. Posteriormente é proposta a melhor estratégia para a participação no mercado de energia e reserva. A alocação na rede e os possíveis efeitos subjacentes são também estudados nesta tese, incluindo o modelo dos PEVs e dos parques de estacionamento com estações de carregamento nesse sistema de multi-energia.Among all resources introduced by the evolution of smart grid, multi-energy systems and plugin electric vehicles are the two main challenges in research topics. Although, these resources bring new levels of uncertainties to the system, their capabilities as flexible demand or stochastic generation can enhance the operability of system. When the concept of multienergy systems and plug-in electric vehicles (PEV) parking lots are merged in a distribution system, the demand estimation may vary significantly. As the main feed of planning process, it is critical to estimate the most accurate amount of required demand. Therefore, three stages of load pattern should be extracted taking into account the demand substitution between energy carriers, demand affected by home-charging PEVs, and parking lot presence in system. The presence of PEVs in a multi-energy system oblige other requirements (i.e. fueling system) that should be provided in the system, including charging stations. However, the electric base of PEVs adds to the responsibilities of the system operator to think about the best solution to provide the required services for PEVs and utilize their potentials in a multi-energy concept. However, the socio-technical behavior of PEV users makes it difficult for the system operator to be able to manage the potential sources of PEV batteries. As a result, this study tries to raise the solution to new problems that will occur for the system planners and operators by the future components of the system. In this thesis, various aspects of integrating PEVs in a multi-energy system is studied.Firstly, a carrier-based demand response program is proposed for the multi-energy system with the technologies on the demand side to switch between the carriers for providing their services. Then, a comprehensive study on the issues regarding the modeling of the PEVs in the system are conducted including modeling their uncertain traffic behavior, modeling the preferences of vehicle owners on the required charging, modeling the PEV parking lot behavior and its interactions with the network. After that the best strategy and framework for participating the PEVs energy in the energy and reserve market is proposed. The allocation of the parking lot in the network and the possible effects it will have on the network constraints is studied. Finally, the derived model of the PEVs and the parking lot is added to the multi-energy system model with multi-energy demand

Optimal dispatch of uncertain energy resources

The future of the electric grid requires advanced control technologies to reliably integrate high level of renewable generation and residential and small commercial distributed energy resources (DERs). Flexible loads are known as a vital component of future power systems with the potential to boost the overall system efficiency. Recent work has expanded the role of flexible and controllable energy resources, such as energy storage and dispatchable demand, to regulate power imbalances and stabilize grid frequency. This leads to the DER aggregators to develop concepts such as the virtual energy storage system (VESS). VESSs aggregate the flexible loads and energy resources and dispatch them akin to a grid-scale battery to provide flexibility to the system operator. Since the level of flexibility from aggregated DERs is uncertain and time varying, the VESSs’ dispatch can be challenging. To optimally dispatch uncertain, energy-constrained reserves, model predictive control offers a viable tool to develop an appropriate trade-off between closed-loop performance and robustness of the dispatch. To improve the system operation, flexible VESSs can be formulated probabilistically and can be realized with chance-constrained model predictive control. The large-scale deployment of flexible loads needs to carefully consider the existing regulation schemes in power systems, i.e., generator droop control. In this work first, we investigate the complex nature of system-wide frequency stability from time-delays in actuation of dispatchable loads. Then, we studied the robustness and performance trade-offs in receding horizon control with uncertain energy resources. The uncertainty studied herein is associated with estimating the capacity of and the estimated state of charge from an aggregation of DERs. The concept of uncertain flexible resources in markets leads to maximizing capacity bids or control authority which leads to dynamic capacity saturation (DCS) of flexible resources. We show there exists a sensitive trade-off between robustness of the optimized dispatch and closed-loop system performance and sacrificing some robustness in the dispatch of the uncertain energy capacity can significantly improve system performance. We proposed and formulated a risk-based chance constrained MPC (RB-CC-MPC) to co-optimize the operational risk of prematurely saturating the virtual energy storage system against deviating generators from their scheduled set-point. On a fast minutely timescale, the RB-CC-MPC coordinates energy-constrained virtual resources to minimize unscheduled participation of ramp-rate limited generators for balancing variability from renewable generation, while taking into account grid conditions. We show under the proposed method it is possible to improve the performance of the controller over conventional distributionally robust methods by more than 20%. Moreover, a hardware-in-the-loop (HIL) simulation of a cyber-physical system consisting of packetized energy management (PEM) enabled DERs, flexible VESSs and transmission grid is developed in this work. A predictive, energy-constrained dispatch of aggregated PEM-enabled DERs is formulated, implemented, and validated on the HIL cyber-physical platform. The experimental results demonstrate that the existing control schemes, such as AGC, dispatch VESSs without regard to their energy state, which leads to unexpected capacity saturation. By accounting for the energy states of VESSs, model-predictive control (MPC) can optimally dispatch conventional generators and VESSs to overcome disturbances while avoiding undesired capacity saturation. The results show the improvement in dynamics by using MPC over conventional AGC and droop for a system with energy-constrained resources

An improved methodology for the hierarchical coordination of PEV Charging

This paper proposes an improved methodology for the hierarchical coordination of daily Plug-in Electric Vehicle (PEV) charging. The aim is to limit the power supplied by the primary distribution transformer (PDT) while minimizing the energy costs of the aggregators. This methodology consists of an iterative optimization of the total aggregated power at the PDT level, considering the local power constraints of the aggregators and the PEVs with a reduced number of decision variables and constraints which only depend on the number of time intervals. Moreover, it defines the energy boundaries of the optimization problem in each iteration through a proposed method for simulating early charging and delayed charging, considering the power constraints of the aggregators. Otherwise, it evenly distributes the total power among the aggregators, and the local power of each aggregator among the PEVs, maximizing the feasible region of the optimization problem. The proposed methodology is applied to two case studies. The uncertainties related to the charging scenarios are considered by means of Monte-Carlo simulations. The results obtained show that the total power profile is effectively limited, while the profits of the aggregators are not significantly affected by the coordinated approach that is expected to be performed by the Distribution System Operator (DSO). Additionally, to demonstrate the reduction of the impact of PEV charging on the distribution system, the voltage profile, the transformer loss of life and the power and energy losses are reported.Fil: Sanchez, Angel Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Coria Pantano, Gustavo Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Romero Quete, Andrés Arturo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Rivera, Sergio Raúl. Universidad Nacional de Colombia; Colombi

Energy Management of Prosumer Communities

The penetration of distributed generation, energy storages and smart loads has resulted in the emergence of prosumers: entities capable of adjusting their electricity production and consumption in order to meet environmental goals and to participate profitably in the available electricity markets. Significant untapped potential remains in the exploitation and coordination of small and medium-sized distributed energy resources. However, such resources usually have a primary purpose, which imposes constraints on the exploitation of the resource; for example, the primary purpose of an electric vehicle battery is for driving, so the battery could be used as temporary storage for excess photovoltaic energy only if the vehicle is available for driving when the owner expects it to be. The aggregation of several distributed energy resources is a solution for coping with the unavailability of one resource. Solutions are needed for managing the electricity production and consumption characteristics of diverse distributed energy resources in order to obtain prosumers with more generic capabilities and services for electricity production, storage, and consumption. This collection of articles studies such prosumers and the emergence of prosumer communities. Demand response-capable smart loads, battery storages and photovoltaic generation resources are forecasted and optimized to ensure energy-efficient and, in some cases, profitable operation of the resources

Demand response performance and uncertainty: A systematic literature review

The present review has been carried out, resorting to the PRISMA methodology, analyzing 218 published articles. A comprehensive analysis has been conducted regarding the consumer's role in the energy market. Moreover, the methods used to address demand response uncertainty and the strategies used to enhance performance and motivate participation have been reviewed. The authors find that participants will be willing to change their consumption pattern and behavior given that they have a complete awareness of the market environment, seeking the optimal decision. The authors also find that a contextual solution, giving the right signals according to the different behaviors and to the different types of participants in the DR event, can improve the performance of consumers' participation, providing a reliable response. DR is a mean of demand-side management, so both these concepts are addressed in the present paper. Finally, the pathways for future research are discussed.This article is a result of the project RETINA (NORTE-01-0145- FEDER-000062), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). We also acknowledge the work facilities and equipment provided by GECAD research center (UIDB/00760/2020) to the project team, and grants CEECIND/02887/2017 and SFRH/BD/144200/2019.info:eu-repo/semantics/publishedVersio

A multistage stochastic modelling framework for the optimal operation of DER aggregators under multidimensional uncertainty using stochastic dual dynamic programming

The emerging paradigm shift towards the Smart Grid concept, has vigorously encouraged the broad deployment of distributed energy resources (DER), such as energy storage (ES) and flexible demand (FD) and renewable micro-generators, in the energy system. In deregulated power systems, the deployment of flexibility pertaining to ES and FD is associated with their efficient integration in the electricity market. However, significant participation barriers have triggered the introduction of distributed energy resources (DER) aggregators in electricity markets, which settle the necessary framework for the market realisation of their promising operational flexibility potential. The significant number and diversity of resources pertaining to the DER aggregator portfolio, combined with multiple stochastic components affecting its optimal operation demonstrate a high-dimensional stochastic problem. Existing literature focusing on the problem of the optimal operation of DER aggregators exhibits significant limitations, since two-stage stochastic formulations are adopted. In this context, this thesis proposes, analyses and evaluates a novel multistage stochastic model, where multidimensional stochasticity is efficiently considered. Suitable dimensionality reduction and decomposition techniques have been deployed to tackle the computational issues stemming from the high dimensionality of the problem. Stochastic Dual Dynamic programming (SDDP) is deployed to alleviate computational tractability problems. Autoregressive models (AR) are employed to articulate temporal and cross-variable dependencies among the stochastic variables. Two novel extensions of the traditional SDDP algorithm, where linear (i.e. AR) models are integrated in the solution process and enhance solution quality, are proposed. A simulation framework for the validation and assessment of the proposed extended SDDP models, which compares them against scenario tree formulations with different structural characteristics, is presented. Case studies demonstrate that the extended SDDP models achieve a better trade-off between solution efficiency and computational performance. Additionally, results highlight the value of strategic positioning of the DER aggregator portfolio, when limited renewable generation is available. Finally, the effect of strategic decision-making based on less accurate information is shown to be intensified when the aggregator manages a more flexible portfolio.Open Acces

Flexibility Provisions from Energy Hubs for Sustainable Energy Systems

Power systems have some inherent level of flexibility built into the system, to meet the continuous mismatches between the supply and demand. Variability and uncertainty are not new to power systems as loads change over time and generators can fail in unpredictable manners. Penetration of renewable resources and plug in electric vehicles (PEVs) can make this mismatch even more difficult to meet and new flexibility resources will be needed to supplement the flexibility capabilities of the existing system. There are many options to provide flexibility at the distribution system level, but their potential have not been fully utilized. This thesis addresses some of the pertinent issues relating to flexibility provisions from energy hubs. In the first research problem, an electric vehicle charging facility (EVCF) is transformed to operate as a smart energy hub in order to build its flexibility provision. The EVCF demand mostly occurs during the evening, coinciding with the peak demand, and has no flexibility because of the short stay of PEVs at the charging facility. From the system planner’s and operator’s point of view, such transformation of the EVCF presents a new source of flexibility to the distribution system, which could alleviate network stress and defer upgrades, and the transformation to a smart energy hub will also reduce the EVCF’s operating costs through improved energy management. A generic and novel framework is proposed to optimally design and plan an EVCF as a smart energy hub that controls the energy flow between the renewables-based generation units, the battery energy storage system (BESS), the external grid, and local consumption. The proposed framework is based on a bottom-up approach to design and planning of an EVCF, incorporating a detailed representation of vehicle mobility statistics to estimate the charging load profile, and then integrating all dimensions of planning, such as technical feasibility assessment, economics, and distribution system operations impact assessment. The thesis further presents a new mathematical model to design an EVCF with distributed energy resources (DERs) to provide flexibility services in wind integrated power grids. Two different ownership structures of the EVCF and the wind generation facility (WGF) are presented and analyzed for the first time. The DER options considered for the EVCF design are solar photovoltaic (PV) units and BESS. The effects of wind power uncertainty on power system operations are mitigated through the designed EVCF with DERs via the upward and downward flexibility provisions. Monte Carlo simulations are used to simulate the uncertainties in PV and wind generation, and market price. In the third research problem, residential loads are transformed to residential energy hubs (REHs) to develop an inherent flexibility in their portfolios, and hence offer a wide range of benefits to the power grid, such as peak reduction, congestion relief and capacity deferral. A generic and novel framework is proposed, to simultaneously determine the optimal penetration of REHs in distribution systems and the optimal incentives to be remunerated by the local distribution company (LDC) to residential customers for flexibility provisions, considering economic benefits of both parties. The proposed framework models the relationship between the participation of residential customers in transforming their houses to REHs and the incentives to be offered by the LDC. A new concept of unloaded and loaded states of REHs is also introduced for quantifying the power availability of REHs, from which power flexibility can be provided considering the penetration of REHs in the system