Modelling and simulation infrastructure for smart energy and renewable technologies integration in urban districts

The 196 parties attending the conference on climate changes (COP21) in Paris highlighted the need of reducing greenhouse gas emissions [1]. In this regard, in the last years, many countries are providing incentives to promote the deployment of low-carbon and sustainable energy production technologies [2], generation such as Photovoltaic (PV) Systems. The International Energy Agency reports that [3] installation of Renewable Energy Sources (RES), Distributed Generation (DG) and an optimization of consumption with a smart use of energy is required in our cities in order to achieve the goal of reducing green house emissions. ICT technologies, in particular the Internet of Things, enable the possibility of controlling and optimizing consumption [4] hence increasing energy efficiency. The transition from centralized production system to a distributed generation, that can be based on renewable or on conventional sources, substantially modifies the operation of electricity networks: the direction of power flows in the MV lines and even in high voltage/medium voltage (HV/MV) transformers can be reversed, voltage profiles are modified, fault management is affected [5, 6], etc. For all these reasons, distribution networks need to become Smart and new control strategies, algorithms and technologies need to be tested and validated before their implementation and installation in real systems. In this context, ICT play a crucial role in both planning expansion and monitoring operation of distributed energy sources. The crucial roles of ICT and the emerging Internet-of-Things (IoT) are highlighted by the spread diffusion of heterogeneous and pervasive sensors in our houses, district and cities. IoT devices and sensors allow to collect large amounts of energy related data capable of describing the consumption behaviours of the citizens. Hence, the increasing presence of sensors calls for the development of distributed software infrastructure for exploiting such IoT devices for data management and collection. Furthermore, IoT devices enables the possibility of monitoring devices and system in order to develop models for the simulation and optimization on energy process. This Thesis presents a distributed infrastructure, called SMIRSE, for modelling and simulating renewable energy sources and smart policies integration in urban districts. SMIRSE is implemented as a modular infrastructure build with a micro-services approach that exploits Internet of Things communication protocols. This approach enabled interoperability between hardware and software components of the SMIRSE platform and at the mean time its modularity, extendability and scalability. Its modularity allowed the interfacing and integration between dedicated Real-time Grid Simulator, software simulation modules and real-time data in order to model the grid behavior. New modeling and simulation tools for i) Solar energy simulation, with a focus on Photovoltaic systems; ii) Integration of RES and smart policies with the distribution grid; iii) Characterization of thermal performance of Buildings and power consumption prediction; and iv) Buildings indoor temperature simulation and monitoring, have been designed, developed and integrated upon the backbone of the microservices-based infrastructure. The main advantage of the SMIRSE infrastructure is its capability in creating different scenarios for Multi-Energy-System simulation with a minimum effort. Examples of scenarios were SMIRSE can be used are: i) Installation of Renewable Energy Sources, ii) Grid reconfiguration, iii) Demand Response and iv) Demand Side Management. In addition, the proposed infrastructure enables to study the interoperability among different use-cases in a plug-play fashion. Finally, the proposed solution can integrate Smart Metering Architecture to exploit (near-) real-time data collected from the field to co-simulate different smart energy strategies with real information. The main contribution of this study is the design and development of a distributed infrastructure for energy system simulation that exploits state of the art ICT technology. Its worthnothing to say that such ICT technology have been customized for the purpose of developing energy system co-simulation infrastructure.