Smart Grid as a Service: A Discussion on Design Issues

Smart grid allows the integration of distributed renewable energy resources into the conventional electricity distribution power grid such that the goals of reduction in power cost and in environment pollution can be met through an intelligent and efficient matching between power generators and power loads. Currently, this rapidly developing infrastructure is not as “smart” as it should be because of the lack of a flexible, scalable, and adaptive structure. As a solution, this work proposes smart grid as a service (SGaaS), which not only allows a smart grid to be composed out of basic services, but also allows power users to choose between different services based on their own requirements. The two important issues of service-level agreements and composition of services are also addressed in this work. Finally, we give the details of how SGaaS can be implemented using a FIPA-compliant JADE multiagent system

Desenvolvimento de um modelo de programação linear inteira mista para o problema do gerenciamento energético de microrredes

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2015Esta tese apresenta um modelo matemático para o problema de Gerenciamento Energético (GE) de uma Microrrede (MG) por meio de um modelo matemático de Programação Linear Inteira Mista. No problema do GE, o objetivo é determinar uma política de operação que minimiza, ao longo de um horizonte de planejamento, o custo de operação, sujeito às restrições técnicas e econômicas. Propõe-se um modelo detalhado para a microturbina (MT) e Célula a Combustível (CC), nas quais as restrições associadas a fatores como a rampas de partida e desligamento, mínimo tempo de operação ou inatividade, limites de geração, e várias peculiaridades que não foram devidamente considerados na literatura são estudadas. Outra importante contribuição desta tese é a modelagem de um sistema de armazenamento de energia específico para o problema GE da MG, a bateria de íons de lítio, comparando-se as várias modelagens encontradas na literatura. O modelo proposto também considera uma representação detalhada das demandas críticas, deslocáveis e com possibilidade de descontinuação, juntamente com um novo conceito de demanda difusas, que são aspectos importantes no conceito de MG. Para analisar a modelagem proposta, uma MG é utilizada juntamente com uma MT, uma CC, uma bateria, geradores eólicos e fotovoltaicos, demandas críticas e controláveis, com a opção de operar conectada ou ilhada à rede principal. Os casos de estudo são separados em três grandes grupos para se verificar as peculiaridades do GE da MG, a modelagem de cada Recurso Energético Distribuído (RED) e a modelagem da demanda controlável. Os resultados indicam que o modelo é adequado para o GE da MG.Abstract : This thesis presents a mathematical model for the Energy Management (EM) problem of a Microgrid (MG) by means of a Mixed Integer Linear Programming (MILP) approach. In the EM problem, the objective is to determine a generation and a controllable load demand schedule that minimizes, over a planning horizon, the operation cost subject to economical and technical constraints. It is proposed a detail modelling for Microturbines (MTs) and Fuel Cells (FCs), where the constraints associated with such factors as the ramps, minimum up and downtime, generation limits, and various peculiarities that have not been adequately considered in literature. Other important contribution of this thesis is the modelling of a specific energy storage system to the MG EM problem, the lithium-ion battery, comparing various approaches. The proposed model also considers a detailed representation of critical, reschedulable and curtailable loads, along with a new concept of diffuse loads, which could be important elements in the MG concept. To analyses the proposed modelling, a MG is used along with a MT, a FC, a battery, wind and photovoltaic generators, with the critical and controllable load demands, connected or island to the main grid. The study cases are divided into three big groups to verify the peculiarities of the MG EM, each Distributed Energy Resource (DER) and controllable load demand modelling. The results indicate that the model is adequate for the MG EM

A novel power management and control design framework for resilient operation of microgrids

This thesis concerns the investigation of the integration of the microgrid, a form of future electric grids, with renewable energy sources, and electric vehicles. It presents an innovative modular tri-level hierarchical management and control design framework for the future grid as a radical departure from the ‘centralised’ paradigm in conventional systems, by capturing and exploiting the unique characteristics of a host of new actors in the energy arena - renewable energy sources, storage systems and electric vehicles. The formulation of the tri-level hierarchical management and control design framework involves a new perspective on the problem description of the power management of EVs within a microgrid, with the consideration of, among others, the bi-directional energy flow between storage and renewable sources. The chronological structure of the tri-level hierarchical management operation facilitates a modular power management and control framework from three levels: Microgrid Operator (MGO), Charging Station Operator (CSO), and Electric Vehicle Operator (EVO). At the top level is the MGO that handles long-term decisions of balancing the power flow between the Distributed Generators (DGs) and the electrical demand for a restructure realistic microgrid model. Optimal scheduling operation of the DGs and EVs is used within the MGO to minimise the total combined operating and emission costs of a hybrid microgrid including the unit commitment strategy. The results have convincingly revealed that discharging EVs could reduce the total cost of the microgrid operation. At the middle level is the CSO that manages medium-term decisions of centralising the operation of aggregated EVs connected to the bus-bar of the microgrid. An energy management concept of charging or discharging the power of EVs in different situations includes the impacts of frequency and voltage deviation on the system, which is developed upon the MGO model above. Comprehensive case studies show that the EVs can act as a regulator of the microgrid, and can control their participating role by discharging active or reactive power in mitigating frequency and/or voltage deviations. Finally, at the low level is the EVO that handles the short-term decisions of decentralising the functioning of an EV and essential power interfacing circuitry, as well as the generation of low-level switching functions. EVO level is a novel Power and Energy Management System (PEMS), which is further structured into three modular, hierarchical processes: Energy Management Shell (EMS), Power Management Shell (PMS), and Power Electronic Shell (PES). The shells operate chronologically with a different object and a different period term. Controlling the power electronics interfacing circuitry is an essential part of the integration of EVs into the microgrid within the EMS. A modified, multi-level, H-bridge cascade inverter without the use of a main (bulky) inductor is proposed to achieve good performance, high power density, and high efficiency. The proposed inverter can operate with multiple energy resources connected in series to create a synergized energy system. In addition, the integration of EVs into a simulated microgrid environment via a modified multi-level architecture with a novel method of Space Vector Modulation (SVM) by the PES is implemented and validated experimentally. The results from the SVM implementation demonstrate a viable alternative switching scheme for high-performance inverters in EV applications. The comprehensive simulation results from the MGO and CSO models, together with the experimental results at the EVO level, not only validate the distinctive functionality of each layer within a novel synergy to harness multiple energy resources, but also serve to provide compelling evidence for the potential of the proposed energy management and control framework in the design of future electric grids. The design framework provides an essential design to for grid modernisation

Adaptive model predictive control of renewable energy-based micro-grid.

Doctoral Degree. University of KwaZulu-Natal, Durban.Energy sector is facing a shift from a fossil-fuel energy system to a modern energy system focused on renewable energy and electric transport systems. New control algorithms are required to deal with the intermittent, stochastic, and distributed nature of the generation and with the new patterns of consumption. Firstly, this study proposes an adaptive model-based receding horizon control technique to address the issues associated with the energy management system (EMS) in micro-grid operations. The essential objective of the EMS is to balance power generation and demand through energy storage for optimal operation of the renewable energy-based micro-grid. At each sampling point, the proposed control system compares the expected power produced by the renewable generators with the expected load demand and determines the scheduling of the different energy storage devices and generators for the next few hours. The control technique solves the optimization problem in order to minimize or determines the minimum running cost of the overall micro-grid operations, while satisfying the demand and taking into account technical and physical constraints. Micro-grid, as any other systems are subject to disturbances during their normal operation. Hence, the power generated by the renewable energy sources (RESs) and the demanded power are the main disturbances acting on the micro-grid. As renewable sources are used for the generation, their time-varying nature, their difficulty in predicting, and their lack of ability to manipulate make them a problem for the control system to solve. In view of this, the study investigates the impacts of considering the prediction of disturbances on the performance of the energy management system (EMS) based on the adaptive model predictive control (AMPC) algorithm in order to improve the operating costs of the micro-grid with hybrid-energy storage systems. Furthermore, adequate management of loads and electric vehicle (EV) charging can help enhance the micro-grid operation. This study also introduced the concept of demand-side management (DSM), which allows the customers to make decisions regarding their energy consumption and also help to reduce the peak load demand and to reshape the load profile so as to improve the efficiency of the system, environmental impacts, and reduction in the overall operational costs. More so, the intermittent nature of renewable energy and consumer random behavior introduces a stochastic component to the problem of control. Therefore, in order to solve this problem, this study utilizes an AMPC control technique, which provides some robustness to the control of systems with uncertainties. Lastly, the performances of the micro-grids used as a case study are evaluated through simulation modeling, implemented in MATLAB/Simulink environment, and the simulation results show the accuracy and efficiency of the proposed control technique. More so, the results also show how the AMPC can adapt to various generation scenarios, providing an optimal solution to power-sharing among the distributed energy resources (DERs) and taking into consideration both the physical and operational constraints and similarly, the optimization of the imposed operational criteria