Multilayer optimisation for day-ahead energy planning in microgrids

In the search for low carbon, reliable and affordable ways to provide electricity, an increased attention is going to the microgrid, a small-scale power system that uses a combination of energy generation and storage devices to serve local customers. The most promising feature of the microgrid is its flexibility to act as a standalone source of electricity for remote communities, and to be connected to the main power system, selling and purchasing power as required. Additionally, a microgrid can be considered as a coordinated system approach for incorporating intermittent renewable sources of energy. Microgrid customers can have power from their batteries or distributed generators, they can buy it from the utility grid, or they can reduce their consumption.When designing a new optimal planning tool for a microgrid, a major challenge (and opportunity) is to decide on what units to operate in order to meet the demand. The question is what mix will provide the performance needed at the lowest cost, or with the lowest possible emissions. Unfortunately, both objectives are often contradictory. Generally, low costs mean high emissions, and vice versa. A microgrid system operator may care more about achieving lower costs rather than lower emissions. Given the preferences, the operator needs to decide how to configure and operate the microgrid while satisfying all technical requirements, such as voltage stability and power balance. In order to control and manage the microgrid units in real-time while fully exploiting the benefit of long-term prediction, an off-line optimisation approach imposes itself to devise the online microgrid management. In this PhD thesis, an efficient multilayer control approach is developed which obtains a day-ahead unit commitment method to provide an economically and environmentally viable unit commitment (UC) that is physically feasible in terms of voltage violations. With the multilayer control approach, the future operational states of the controllable units within the microgrid are determined ahead of time. The proposed concept follows the idea of a day-ahead coordination including the unit commitment problem (scheduling layer), an off-line power flow calculation (executive layer) and a security check with feedback control (adjustment layer). Since the complete multilayer control concept works on a day-ahead time scale, the model can be considered as an off-line optimisation approach. The power reference set points provided by the multilayer control approach can, in turn, be used for an online microgrid implementation to achieve real-time system state updates

The politics of system innovation for emerging technologies: understanding the uptake of off-grid renewable electricity in rural Chile

Access to sustainable energy in the developing world has become a fundamental challenge in development and environmental policy in the 21st Century, and rural electrification in developing countries constitutes a central element of access to energy goals. However, traditional ways of providing electricity to dispersed rural populations (i.e. through centralised electricity infrastructure or fuel-based on-site generation) is proving to be ineffective, inefficient and less sustainable than the use of renewable energy technologies (RETs) in off-grid settings. Such ‘system innovations’ for sustainable electricity services in rural areas are the focus of this study, which seeks to understand the reasons underlying success or failure in the diffusion of radical innovations. Embracing evolutionary and constructivist theories of socio-technical change and sustainability transitions, the thesis attempts to explain the use and diffusion of PV (photovoltaic) and wind technology in off-grid rural electrification over the last 20 years in Chile, a country where access to rural electricity has increased from 53% to 95%. RETs have contributed to nearly 10% of that increment. By using a framework that combines Strategic Niche Management (SNM), systemic intermediation and power, agency and conflicts in decision making, the thesis analyses the dynamics between the development and adaptation of new technologies and their influence in regime shift through replication, scaling up and translation of new socio-technical practices. The thesis attempts to shed light on processes affecting niche construction and it concludes that internal niche processes are relevant to understanding how radical innovations are structured and stabilised from the aggregation of projects. However, those processes are not only a managerial activity that can be steered but a politically underpinned (and iterative) process between specific (socio-political) settings. The study also highlights the role of systemic intermediaries, government and incumbent actors in the dynamic interaction between emergent niche dynamics and traditional ways of improving electricity access

Optimal energy management of a microgrid system

Mestrado de dupla diplomação com École Superieure en Sciences AppliquéesA smart management strategy for the energy ows circulating in microgrids is necessary to economically manage local production and consumption while maintaining the balance between supply and demand. Finding the optimum set-points of the various generators and the best scheduling of the microgrid generators can lead to moderate and judicious use of the powers available in the microgrid. This thesis aims to apply an energy management system based on optimization algorithms to ensure the optimal control of microgrids by taking as main purpose the minimization of the energy costs and reduction of the gas emissions rate responsible for greenhouse gases. Two approaches have been proposed to nd the optimal operating setpoints. The rst one is based on a uni-objective optimization approach in which several energy management systems are implemented for three case studies. This rst approach treats the optimization problem in a uni-objective way where the two functions price and gas emission are treated separately through optimization algorithms. In this approach the used methods are simplex method, particle swarm optimization, genetic algorithm and a hybrid method (LPPSO). The second situation is based on a multiobjective optimization approach that deals with the optimization of the two functions: cost and gas emission simultaneously, the optimization algorithm used for this purpose is Pareto-search. The resulting Pareto optimal points represent di erent scheduling scenarios of the microgrid system.Uma estrat egia de gest~ao inteligente dos uxos de energia que circulam numa microrrede e necess aria para gerir economicamente a produ c~ao e o consumo local, mantendo o equil brio entre a oferta e a procura. Encontrar a melhor programa c~ao dos geradores de microrrede pode levar a uma utiliza c~ao moderada e criteriosa das pot^encias dispon veis na microrrede. Esta tese visa desenvolver um sistema de gest~ao de energia baseado em algoritmos de otimiza c~ao para assegurar o controlo otimo das microrredes, tendo como objetivo principal a minimiza c~ao dos custos energ eticos e a redu c~ao da taxa de emiss~ao de gases respons aveis pelo com efeito de estufa. Foram propostas duas estrat egias para encontrar o escalonamento otimo para funcionamento. A primeira baseia-se numa abordagem de otimiza c~ao uni-objetivo no qual v arios sistemas de gest~ao de energia s~ao implementados para tr^es casos de estudo. Neste caso o problema de otimiza c~ao e baseado na fun c~ao pre co e na fun c~ao emiss~ao de gases. Os m etodos de otimiza c~ao utilizados foram: algoritmo simplex, algoritmos gen eticos, particle swarm optimization e m etodo h brido (LP-PSO). A segunda situa c~ao baseia-se numa abordagem de otimiza c~ao multi-objetivo que trata a otimiza c~ao das duas fun c~oes: custo e emiss~ao de gases em simult^aneo. O algoritmo de otimiza c~ao utilizado para este m foi a Procura de Pareto. Os pontos otimos de Pareto resultantes representam diferentes cen arios de programa c~ao do sistema de microrrede

Multi-objective optimal power resources planning of microgrids with high penetration of intermittent nature generation and modern storage systems

Microgrids are self-controlled entities at the distribution voltage level that interconnect distributed energy resources (DERs) with loads and can be operated in either grid-connected or islanded mode. This type of active distribution network has evolved as a powerful concept to guarantee a reliable, efficient and sustainable electricity delivery as part of the power systems of the future. However, benefits of microgrids, such as the ancillary services (AS) provision, are not possible to be properly exploited before traditional planning methodologies are updated. Therefore, in this doctoral thesis, a named Probabilistic Multi-objective Microgrid Planning methodology with two versions, POMMP and POMMP2, is proposed for effective decision-making on the optimal allocation of DERs and topology definition under the paradigm of microgrids with capacity for providing AS to the main power grid. The methodologies are defined to consider a mixed generation matrix with dispatchable and non-dispatchable technologies, as well as, distributed energy storage systems and both conventional and power-electronic-based operation configurations. The planning methodologies are formulated based on a so-called true-multi-objective optimization problem with a configurable set of three objective functions. Accordingly, the capacity to supply AS is optimally enhanced with the maximization of the available active residual power in grid-connected operation mode; the capital, maintenance, and operation costs of microgrid are minimized, while the revenues from the services provision and participation on liberalized markets are maximized in a cost function; and the active power losses in microgrid´s operation are minimized. Furthermore, a probabilistic technique based on the simulation of parameters from their probabilistic density function and Monte Carlo Simulation is adopted to model the stochastic behavior of the non-dispatchable renewable generation resources and load demand as the main sources of uncertainties in the planning of microgrids. Additionally, POMMP2 methodology particularly enhances the proposal in POMMP by modifying the methodology and optimization model to consider the optimal planning of microgrid's topology with the allocation of DERs simultaneously. In this case, the concept of networked microgrid is contemplated, and a novel holistic approach is proposed to include a multilevel graph-partitioning technique and subsequent iterative heuristic optimization for the optimal formation of clusters in the topology planning and DERs allocation process. This microgrid planning problem leads to a complex non-convex mixed-integer nonlinear optimization problem with multiple contradictory objective functions, decision variables, and diverse constraint conditions. Accordingly, the optimization problem in the proposed POMMP/POMMP2 methodologies is conceived to be solved using multi-objective population-based metaheuristics, which gives rise to the adaptation and performance assessment of two existing optimization algorithms, the well-known Non-dominated Sorting Genetic Algorithm II (NSGAII) and the Multi-objective Evolutionary Algorithm Based on Decomposition (MOEA/D). Furthermore, the analytic hierarchy process (AHP) is tested and proposed for the multi-criteria decision-making in the last step of the planning methodologies. The POMMP and POMMP2 methodologies are tested in a 69-bus and 37-bus medium voltage distribution network, respectively. Results show the benefits of an a posteriori decision making with the true-multi-objective approach as well as a time-dependent planning methodology. Furthermore, the results from a more comprehensive planning strategy in POMMP2 revealed the benefits of a holistic planning methodology, where different planning tasks are optimally and simultaneously addressed to offer better planning results.Las microrredes son entes autocontrolados que operan en media o baja tensión, interconectan REDs con las cargas y pueden ser operadas ya sea en modo conectado a la red o modo isla. Este tipo de red activa de distribución ha evolucionado como un concepto poderoso para garantizar un suministro de electricidad fiable, eficiente y sostenible como parte de los sistemas de energía del futuro. Sin embargo, para explotar los beneficios potenciales de las microrredes, tales como la prestación de servicios auxiliares (AS), primero es necesario formular apropiadas metodologías de planificación. En este sentido, en esta tesis doctoral, una metodología probabilística de planificación de microrredes con dos versiones, POMMP y POMMP2, es propuesta para la toma de decisiones efectiva en la asignación óptima de DERs y la definición de la topología de microrredes bajo el paradigma de una microrred con capacidad para proporcionar AS a la red principal. Las metodologías se definen para considerar una matriz de generación mixta con tecnologías despachables y no despachables, así como sistemas distribuidos para el almacenamiento de energía y la interconnección de recursos con o sin una interfaz basada en dispositivos de electrónica de potencia. Las metodologías de planificación se formulan sobre la base de un problema de optimización multiobjetivo verdadero con un conjunto configurable de tres funciones objetivo. Con estos se pretende optimizar la capacidad de suministro de AS con la maximización de la potencia activa residual disponible en modo conectado a la red; la minimización de los costos de capital, mantenimiento y funcionamiento de la microrred al tiempo que se maximizan los ingresos procedentes de la prestación de servicios y la participación en los mercados liberalizados; y la minimización de las pérdidas de energía activa en el funcionamiento de la microrred. Además, se adopta una técnica probabilística basada en la simulación de parámetros a partir de la función de densidad de probabilidad y el método de Monte Carlo para modelar el comportamiento estocástico de los recursos de generación renovable no despachables. Adicionalmente,la POMMP2 mejora la propuesta de POMMP modificando la metodología y el modelo de optimización para considerar simultáneamente la planificación óptima de la topología de la microrred con la asignación de DERs. Así pues, se considera el concepto de microrredes interconectadas en red y se propone un novedoso enfoque holístico que incluye una técnica de partición de gráficos multinivel y optimización iterativa heurística para la formación óptima de clusters para el planeamiento de la topología y asignación de DERs. Este problema de planificación de microrredes da lugar a un complejo problema de optimización mixto, no lineal, no convexos y con múltiples funciones objetivo contradictorias, variables de decisión y diversas condiciones de restricción. Por consiguiente, el problema de optimización en las metodologías POMMP/POMMP2 se concibe para ser resuelto utilizando técnicas multiobjetivo de optimización metaheurísticas basadas en población, lo cual da lugar a la adaptación y evaluación del rendimiento de dos algoritmos de optimización existentes, el conocido Non-dominated Sorting Genetic Algorithm II (NSGAII) y el Evolutionary Algorithm Based on Decomposition (MOEA/D). Además, se ha probado y propuesto el uso de la técnica de proceso analítico jerárquico (AHP) para la toma de decisiones multicriterio en el último paso de las metodologías de planificación. Las metodologías POMMP/POMMP2 son probadas en una red de distribución de media tensión de 69 y 37 buses, respectivamente. Los resultados muestran los beneficios de la toma de decisiones a posteriori con el enfoque de optimización multiobjetivo verdadero, así como una metodología de planificación dependiente del tiempo. Además, los resultados de la estrategia de planificación con POMMP2 revelan los beneficios de una metodología de planificación holística, en la que las diferentes tareas de planificación se abordan de manera óptima y simultánea para ofrecer mejores resultados de planificación.Línea de investigación: Planificación de redes inteligentes We thank to the Administrative Department of Science, Technology and Innovation - Colciencias, Colombia, for the granted National Doctoral funding program - 647Doctorad

Impact of vehicle to grid in the power system dynamic behaviour

This work was supported in part by FCT-Fundação para a Ciência e a Tecnologia de Portugal, under the grant SFRH/BD/47973/2008 and within the framework of the Project "Green Island" with the Reference MIT-PT/SES-GI/0008/2008, by the European Commission within the framework of the European Project MERGE - Mobile Energy Resources in Grids of Electricity, contract nr. 241399 (FP7) and by INESC Porto - Instituto de Engenharia de Sistemas e Computadores do PortoTese de doutoramento. Sistemas Sustentáveis de Energia. Universidade do Porto. Faculdade de Engenharia. 201

Perspectives on adaptive dynamical systems

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches