Optimal Operation of Microgrid considering Renewable Energy Sources, Electric Vehicles and Demand Response

This paper proposes a new optimal operation of Microgrids (MGs) in a distribution system with wind energy generators (WEGs), solar photovoltaic (PV) energy systems, battery energy storage (BES) systems, electric vehicles (EVs) and demand response (DR). To reduce the fluctuations of wind, solar PV powers and load demands, the BES systems and DR are utilized in the proposed hybrid system. The detailed modeling of WEGs, solar PV units, load demands, BES systems and EVs has been presented in this paper. The objective considered here is the minimization of total operating cost of microgrid, and it is formulated by considering the cost of power exchange between the main power grid and microgrid, cost of wind and solar PV energy systems, cost of BES systems, EVs and the cost due to the DR in the system. Simulations are performed on a test microgrid, and they are implemented using GAMS software. Various case studies are performed with and without considering the proposed hybrid system

Joint Control of Manufacturing and Onsite Microgrid System Via Novel Neural-Network Integrated Reinforcement Learning Algorithms

Microgrid is a promising technology of distributed energy supply system, which consists of storage devices, generation capacities including renewable sources, and controllable loads. It has been widely investigated and applied for residential and commercial end-use customers as well as critical facilities. In this paper, we propose a joint state-based dynamic control model on microgrids and manufacturing systems where optimal controls for both sides are implemented to coordinate the energy demand and supply so that the overall production cost can be minimized considering the constraint of production target. Markov Decision Process (MDP) is used to formulate the decision-making procedure. The main computing challenge to solve the formulated MDP lies in the co-existence of both discrete and continuous parts of the high-dimensional state/action space that are intertwined with constraints. A novel reinforcement learning algorithm that leverages both Temporal Difference (TD) and Deterministic Policy Gradient (DPG) algorithms is proposed to address the computation challenge. Experiments for a manufacturing system with an onsite microgrid system with renewable sources have been implemented to justify the effectiveness of the proposed method

OPERATIONAL RELIABILITY AND RISK EVALUATION FRAMEWORKS FOR SUSTAINABLE ELECTRIC POWER SYSTEMS

Driven by a confluence of multiple environmental, social, technical, and economic factors, traditional electric power systems are undergoing a momentous transition toward sustainable electric power systems. One of the important facets of this transformation is the inclusion of high penetration of variable renewable energy sources, the chief among them being wind power. The new source of uncertainty that stems from imperfect wind power forecasts, coupled with the traditional uncertainties in electric power systems, such as unplanned component outages, introduces new challenges for power system operators. In particular, the short-term or operational reliability of sustainable electric power systems could be at increased risk as limited remedial resources are available to the operators to handle uncertainties and outages during system operation. Furthermore, as sustainable electric power systems and natural gas networks become increasingly coupled, the impacts of outages in one network can quickly propagate into the other, thereby reducing the operational reliability of integrated electric power-gas networks (IEPGNs). In light of the above discussion, a successful transition to sustainable electric power systems necessitates a new set of tools to assist the power system operators to make risk-informed decisions amid multiple sources of uncertainties. Such tools should be able to realistically evaluate the hour- and day-ahead operational reliability and risk indices of sustainable electric power systems in a computationally efficient manner while giving full attention to the uncertainties of wind power and IEGPNs. To this end, the research is conducted on five related topics. First, a simulation-based framework is proposed to evaluate the operational reliability indices of generating systems using the fixed-effort generalized splitting approach. Simulations show improvement in computational performance when compared to the traditional Monte-Carlo simulation (MCS). Second, a hybrid analytical-simulation framework is proposed for the short-term risk assessment of wind-integrated power systems. The area risk method – an analytical technique, is combined with the importance sampling (IS)-based MCS to integrate the proposed reliability models of wind speed and calculate the risk indices with a low computational burden. Case studies validate the efficacy of the proposed framework. Third, the importance sampling-based MCS framework is extended to include the proposed data-driven probabilistic models of wind power to avoid the drawbacks of wind speed models. Fourth, a comprehensive framework for the operational reliability evaluation of IEPGNs is developed. This framework includes new reliability models for natural gas pipelines and natural gas-fired generators with dual fuel capabilities. Simulations show the importance of considering the coupling between the two networks while evaluating operational reliability indices. Finally, a new chance-constrained optimization model to consider the operational reliability constraints while determining the optimal operational schedule for microgrids is proposed. Case studies show the tradeoff between the reliability and the operating costs when scheduling the microgrids

Competitive power control of distributed power plants

Joint Doctoral Programme in Electric Energy Systems : Universidad de Málaga, Universidad de Sevilla, Universidad del País Vasco y Universitat Politècnica de CatalunyaNowadays, the electrical energy sector is currently found in a dramatic changing paradigm, which moves towards an increasing trend in generating power at distribution levels, where electricity is typically consumed, by means of non-conventional/renewable based generation units. These new generation technologies, termed as distributed generation, not only offers a non-pollutant, cheap and efficient source of energy to cover increasing demand, but also enhance the reliability of supply to critical loads and reduce the need for additional grid reinforcements. Aside of the technical benefits provided, distributed generation will massively integrate renewable energy resources, with new type of loads and end-user actors, such as prosumers, demand responsive loads, or electric vehicles. Where these actors will actively participate in energy and auxiliary service markets, depending on their available or constrained energy needs. For this reason, the work presented in this Thesis deals with designing and implementing advanced hierarchical control solutions to renewable-based power plants with the purpose of achieving advanced grid conection performance while reaching maximum economic benefits from its optimum real-time operation. Initially, an extensive analysis on the main renewable-based power plant hierarchical control solutions currently on the shelf, is performed. This study not only covered the specific case of renewable-based power plants, but also advanced microgrid and smart grid control solutions. Once the main renewable-based power plant hierarchical solutions were analized, a novel Hierarchical Distributed Control Structure (HDCS) is proposed for increased management of renewable-based active distributed plants. This hierarchical control structure comprises all possible functional levels from the higher long-term economic scheduling layer, to the instantaneous supervisory control of the resource, emphasizing the entire operation and control functionalities needed for increasing the integration of active distributed power plants. In order to achieve real-time control capabilities in active distribution systems, the present thesis introduces a novel power sharing control strategy, based on the competitive operation of multiple active participating agents (distributed generators, demand response and energy storage systems) through the implementation of market rules. Such control capabilities are satisfied by applying a price control signal over the entire grid control architecture, being the final-end participating agent, the responsible entity in charge of deciding its own generation/demand involvement based on its marginal or affordable electricity costs. In addition, it reduces the information volume to be transmitted and processing requirements, as the higher control levels do not need to have knowledge on the detailed distribution system topology and contributing actors. In order to have a meaningful evaluation of the proposed competitive control capabilities, a wave power plant application has been selected, which constitutes a challenging scenario for the controller itself to achieve advanced real-time control capabilities in such an oscillating renewable energy resource. In order to suitably characterize the wave energy resource profile resulting from maximum energy absorption, this Thesis introduce a novel adaptive vector controller, which maximizes the energy extraction from the resource regardless of the dominant irregular wave frequency characteristics. For the specific wave power plant application considered, the competitive control does not only ensures real-time optimum resource allocation for satisfying a given production objective, but also provides optimum long term operation of the system. As a result, overall plant costs reductions can be achieved under the competitive operation, since the plant scheduled energy is satisfied by making use of the generation units with cheaper cumulative operation costsActualmente, el sector eléctrico se encuentra inmerso en un profundo proceso de restructuración, donde de cada vez más se tiende a generar energía a nivel de distribución, mediante el uso de generación no convencional/renovable. Estas nuevas tecnologías de generación, referidas como generación distribuida, no proporcionan unicamente una fuente de energía no-contaminante, barata y eficiente para cubrir el incremento de demanda, sinó que también pueden proporcionar seguridad de suministro a cargas críticas, así como reducir la necesidad de expansiones futuras de red. Además de las capacidades técnicas proporcionadas, la generación distribuida hará posible la integración masiva de sistemas de generación renovable, con nuevos tipos de cargas y usuarios finales, como prosumidores, cargas regulables, o vehiculos eléctricos, donde todos estos usuarios participaran activamente en mercados de energía y servicios auxiliares, dependiendo de sus requisitos de uso de energía. Por lo tanto, el trabajo realizado en esta tesis se centra en el diseño e implementación de soluciones jerárquicas de control avanzado en plantas de generación renovable, con el objetivo de obtener un comportamiento harmonioso de intercacción con la red, mientras la operación de la planta maximiza los beneficios derivados de su operación en tiempo real. Inicialmente, se ha llevado a cabo una revisión extensa sobre los sistemas de control jerárquico comunmente implementados en plantas de generación renovable, en microredes y en redes inteligentes. Una vez revisados los principales sistemas de control jerárquico en este tipo de aplicaciones, se propone un una novedosa estructura de control, que cubre todos los niveles de control posibles, desde el más alto nivel de gestión económica, hasta el control detallado del recurso de generación. Para lograr capacidades de control en tiempo real en sistemas activos de distribución, la presente tesis propone una nueva estrategia de control de reparto de potencia, basada en la operación competitiva de múltiples agentes participantes activos (generadores distribuidos, respuesta de demanda y sistemas de almacenamiento de energía) mediante la implementación de reglas del mercado. Dichas capacidades de control se satisfacen aplicando una señal de precio a lo largo de toda la arquitectura de control, siendo el agente de final, el ente responsable de decidir su propia participación en la generación/demanda en función de sus propios costes de electricidad marginales o asumibles. Además, reduce el volumen de información a transmitir y los requisitos de procesamiento de datos, ya que los niveles de control más altos no necesitan tener conocimiento sobre la topología del sistema de distribución detallado ni de la contribución de los actores adyacentes. Para llevar a cabo una evaluación significativa de las capacidades del controlador competitivo propuesto, se ha seleccionado una planta de generación undimotriz, como escenario más desfavorable, ya que el controlador debe asegurar un control estable de la potencia inyectada en un escenario altamente oscilante. Con el fin de caracterizar adecuadamente el perfil de recursos de energía de las olas resultante de la máxima absorción de energía, esta Tesis introduce un nuevo controlador de vector adaptativo, que maximiza la extracción de energía del recurso independientemente de las características dominantes de frecuencia de onda irregular. Para la aplicación de la planta de energía de onda específica considerada, el control competitivo no solo garantiza la asignación óptima de recursos en tiempo real para satisfacer un objetivo de producción dado, sino que también proporciona una operación óptima del sistema a largo plazo. Como resultado, se pueden lograr reducciones generales de los costos de la planta en el marco de la operación competitiva, ya que la energía programada de la planta se satisface haciendo uso de las unidadPostprint (published version

Competitive power control of distributed power plants

Nowadays, the electrical energy sector is currently found in a dramatic changing paradigm, which moves towards an increasing trend in generating power at distribution levels, where electricity is typically consumed, by means of non-conventional/renewable based generation units. These new generation technologies, termed as distributed generation, not only offers a non-pollutant, cheap and efficient source of energy to cover increasing demand, but also enhance the reliability of supply to critical loads and reduce the need for additional grid reinforcements. Aside of the technical benefits provided, distributed generation will massively integrate renewable energy resources, with new type of loads and end-user actors, such as prosumers, demand responsive loads, or electric vehicles. Where these actors will actively participate in energy and auxiliary service markets, depending on their available or constrained energy needs. For this reason, the work presented in this Thesis deals with designing and implementing advanced hierarchical control solutions to renewable-based power plants with the purpose of achieving advanced grid conection performance while reaching maximum economic benefits from its optimum real-time operation. Initially, an extensive analysis on the main renewable-based power plant hierarchical control solutions currently on the shelf, is performed. This study not only covered the specific case of renewable-based power plants, but also advanced microgrid and smart grid control solutions. Once the main renewable-based power plant hierarchical solutions were analized, a novel Hierarchical Distributed Control Structure (HDCS) is proposed for increased management of renewable-based active distributed plants. This hierarchical control structure comprises all possible functional levels from the higher long-term economic scheduling layer, to the instantaneous supervisory control of the resource, emphasizing the entire operation and control functionalities needed for increasing the integration of active distributed power plants. In order to achieve real-time control capabilities in active distribution systems, the present thesis introduces a novel power sharing control strategy, based on the competitive operation of multiple active participating agents (distributed generators, demand response and energy storage systems) through the implementation of market rules. Such control capabilities are satisfied by applying a price control signal over the entire grid control architecture, being the final-end participating agent, the responsible entity in charge of deciding its own generation/demand involvement based on its marginal or affordable electricity costs. In addition, it reduces the information volume to be transmitted and processing requirements, as the higher control levels do not need to have knowledge on the detailed distribution system topology and contributing actors. In order to have a meaningful evaluation of the proposed competitive control capabilities, a wave power plant application has been selected, which constitutes a challenging scenario for the controller itself to achieve advanced real-time control capabilities in such an oscillating renewable energy resource. In order to suitably characterize the wave energy resource profile resulting from maximum energy absorption, this Thesis introduce a novel adaptive vector controller, which maximizes the energy extraction from the resource regardless of the dominant irregular wave frequency characteristics. For the specific wave power plant application considered, the competitive control does not only ensures real-time optimum resource allocation for satisfying a given production objective, but also provides optimum long term operation of the system. As a result, overall plant costs reductions can be achieved under the competitive operation, since the plant scheduled energy is satisfied by making use of the generation units with cheaper cumulative operation costsActualmente, el sector eléctrico se encuentra inmerso en un profundo proceso de restructuración, donde de cada vez más se tiende a generar energía a nivel de distribución, mediante el uso de generación no convencional/renovable. Estas nuevas tecnologías de generación, referidas como generación distribuida, no proporcionan unicamente una fuente de energía no-contaminante, barata y eficiente para cubrir el incremento de demanda, sinó que también pueden proporcionar seguridad de suministro a cargas críticas, así como reducir la necesidad de expansiones futuras de red. Además de las capacidades técnicas proporcionadas, la generación distribuida hará posible la integración masiva de sistemas de generación renovable, con nuevos tipos de cargas y usuarios finales, como prosumidores, cargas regulables, o vehiculos eléctricos, donde todos estos usuarios participaran activamente en mercados de energía y servicios auxiliares, dependiendo de sus requisitos de uso de energía. Por lo tanto, el trabajo realizado en esta tesis se centra en el diseño e implementación de soluciones jerárquicas de control avanzado en plantas de generación renovable, con el objetivo de obtener un comportamiento harmonioso de intercacción con la red, mientras la operación de la planta maximiza los beneficios derivados de su operación en tiempo real. Inicialmente, se ha llevado a cabo una revisión extensa sobre los sistemas de control jerárquico comunmente implementados en plantas de generación renovable, en microredes y en redes inteligentes. Una vez revisados los principales sistemas de control jerárquico en este tipo de aplicaciones, se propone un una novedosa estructura de control, que cubre todos los niveles de control posibles, desde el más alto nivel de gestión económica, hasta el control detallado del recurso de generación. Para lograr capacidades de control en tiempo real en sistemas activos de distribución, la presente tesis propone una nueva estrategia de control de reparto de potencia, basada en la operación competitiva de múltiples agentes participantes activos (generadores distribuidos, respuesta de demanda y sistemas de almacenamiento de energía) mediante la implementación de reglas del mercado. Dichas capacidades de control se satisfacen aplicando una señal de precio a lo largo de toda la arquitectura de control, siendo el agente de final, el ente responsable de decidir su propia participación en la generación/demanda en función de sus propios costes de electricidad marginales o asumibles. Además, reduce el volumen de información a transmitir y los requisitos de procesamiento de datos, ya que los niveles de control más altos no necesitan tener conocimiento sobre la topología del sistema de distribución detallado ni de la contribución de los actores adyacentes. Para llevar a cabo una evaluación significativa de las capacidades del controlador competitivo propuesto, se ha seleccionado una planta de generación undimotriz, como escenario más desfavorable, ya que el controlador debe asegurar un control estable de la potencia inyectada en un escenario altamente oscilante. Con el fin de caracterizar adecuadamente el perfil de recursos de energía de las olas resultante de la máxima absorción de energía, esta Tesis introduce un nuevo controlador de vector adaptativo, que maximiza la extracción de energía del recurso independientemente de las características dominantes de frecuencia de onda irregular. Para la aplicación de la planta de energía de onda específica considerada, el control competitivo no solo garantiza la asignación óptima de recursos en tiempo real para satisfacer un objetivo de producción dado, sino que también proporciona una operación óptima del sistema a largo plazo. Como resultado, se pueden lograr reducciones generales de los costos de la planta en el marco de la operación competitiva, ya que la energía programada de la planta se satisface haciendo uso de las unida

Market-oriented micro virtual power prosumers operations in distribution system operator framework

As the European Union is on track to meet its 2020 energy targets on raising the share of renewable energy and increasing the efficiency in the energy consumption, considerable attention has been given to the integration of distributed energy resources (DERs) into the restructured distribution system. This thesis proposes market-oriented operations of micro virtual power prosumers (J.lVPPs) in the distribution system operator framework, in which the J.lVPPs evolve from home-oriented energy management systems to price-taking prosumers and to price-making prosumers. Considering the diversity of the DERs installed in the residential sector, a configurable J.l VPP is proposed first to deliver multiple energy services using a fuzzy logic-based generic algorithm. By responding to the retail price dynamics and applying load control, the J.lVPP achieves considerable electricity bill savings, active utilisation of energy storage system and fast return on investment. As the J.lVPPs enter the distribution system market, they are modelled as price-takers in a two-settlement market first and a chance-constrained formulation is proposed to derive the bidding strategies. The obtained strategy demonstrates its ability to bring the J.l VPP maximum profit based on different composition of DERs and to maintain adequate supply capacity to meet the demand considering the volatile renewable generation and load forecast. Given the non-cooperative nature of the actual market, the J.l VPPs are transformed into price-makers and their market behaviours are studied in the context of electricity market equilibrium models. The resulted equilibrium problems with equilibrium constraints (EPEC) are presented and solved using a novel application of coevolutionary approach. Compared with the roles of home-oriented energy management systems and price-taking prosumers, the J.lVPPs as price­ making prosumers have an improved utilisation rate of the installed DER capacity and a guaranteed profit from participating in the distribution system market

Market-oriented micro virtual power prosumers operations in distribution system operator framework

As the European Union is on track to meet its 2020 energy targets on raising the share of renewable energy and increasing the efficiency in the energy consumption, considerable attention has been given to the integration of distributed energy resources (DERs) into the restructured distribution system. This thesis proposes market-oriented operations of micro virtual power prosumers (J.lVPPs) in the distribution system operator framework, in which the J.lVPPs evolve from home-oriented energy management systems to price-taking prosumers and to price-making prosumers. Considering the diversity of the DERs installed in the residential sector, a configurable J.l VPP is proposed first to deliver multiple energy services using a fuzzy logic-based generic algorithm. By responding to the retail price dynamics and applying load control, the J.lVPP achieves considerable electricity bill savings, active utilisation of energy storage system and fast return on investment. As the J.lVPPs enter the distribution system market, they are modelled as price-takers in a two-settlement market first and a chance-constrained formulation is proposed to derive the bidding strategies. The obtained strategy demonstrates its ability to bring the J.l VPP maximum profit based on different composition of DERs and to maintain adequate supply capacity to meet the demand considering the volatile renewable generation and load forecast. Given the non-cooperative nature of the actual market, the J.l VPPs are transformed into price-makers and their market behaviours are studied in the context of electricity market equilibrium models. The resulted equilibrium problems with equilibrium constraints (EPEC) are presented and solved using a novel application of coevolutionary approach. Compared with the roles of home-oriented energy management systems and price-taking prosumers, the J.lVPPs as price­ making prosumers have an improved utilisation rate of the installed DER capacity and a guaranteed profit from participating in the distribution system market