Maximum penetration of microgeneration photovoltaic panels in distribution network

In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.

Reactive power management strategies in future smart grids

The reactive power management in distribution network with large penetration of distributed energy resources is an important task in future power systems. The control of reactive power allows the inclusion of more distributed recourses and a more efficient operation of distributed network. Currently, the reactive power is only controlled in large power plants and in high and very high voltage substations. In this paper, several reactive power control strategies considering a smart grids paradigm are proposed. In this context, the management of distributed energy resources and of the distribution network by an aggregator, namely Virtual Power Player (VPP), is proposed and implemented in a MAS simulation tool. The proposed methods have been computationally implemented and tested using a 32-bus distribution network with intensive use of distributed resources, mainly the distributed generation based on renewable resources. Results concerning the evaluation of the reactive power management algorithms are also presented and compared.

Estudo de uma bomba de calor de expansão direta assistida por energia solar para a preparação de AQS

Este estudo consiste na caracterização da eficiência energética de uma bomba de calor de expansão direta que utiliza a energia solar como fonte térmica. De uma forma geral, teve-se a obrigação de procurar cada vez mais recursos renováveis e neste sentido a bomba de calor de expansão direta tem um papel importante no aquecimento de águas quentes sanitárias (AQS). Como ponto de partida, foi realizada uma descrição detalhada sobre todos os equipamentos da bomba de calor e elaborado um desenho técnico que identifica todos os componentes. No laboratório (casa inteligente) realizaram-se vários ensaios a fim de interpretar com rigor os resultados obtidos do desempenho da bomba de calor (COP) e do fator médio de desempenho sazonal (SPF). No início, realizaram-se ensaios para determinar as perdas estáticas do sistema termodinâmico, de seguida foram elaborados ensaios segundo a norma EN 16147 e por fim, ensaios de acordo com o perfil de utilização de AQS definido. No estudo experimental do COP, obteve-se uma elevada eficiência energética com um valor médio de 4,12. O COP aumenta para valores médios de 5 quando a temperatura de água no termoacumulador desce para 35ºC. Verificou-se que durante o período diurno o COP aumenta aproximadamente de 10% relativamente ao período noturno. A potência elétrica é mais elevada (450W) quando a água no termoacumulador está perto da temperatura desejável (55ºC), originando um esforço maior da bomba de calor. No estudo experimental do SPF, verificou-se que nos ensaios segundo a norma EN16147 os valores obtidos variaram entre 1,39 e 1,50 (Classe “B”). No estudo realizado de acordo com o perfil de utilização de AQS definido pelo utilizador, o SPF é superior em 12% relativamente ao obtido segundo os ensaios realizados de acordo a norma EN16147. Verificou-se que o aumento da temperatura do ar exterior implica um aumento do SPF (cerca de 2% a 5%), enquanto a energia solar não influência nos resultados.

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

Optimal methodology for renewable energy dispatching in islanded operation

The management of energy resources for islanded operation is of crucial importance for the successful use of renewable energy sources. A Virtual Power Producer (VPP) can optimally operate the resources taking into account the maintenance, operation and load control considering all the involved cost. This paper presents the methodology approach to formulate and solve the problem of determining the optimal resource allocation applied to a real case study in Budapest Tech’s. The problem is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The problem has also been solved by Evolutionary Particle Swarm Optimization (EPSO). The obtained results are presented and compared.