Optimal planning and operation of small size Microgrids with Electric Mobility infrastructure within Positive Energy Districts

The aim of the present thesis is to develop a tool for the optimal design and management of the microgrids with electric mobility infrastructure within Positive Energy Districts (PED) via objective of minimization of operational costs. The Chapter I contains the main scope of work of this thesis and the structure of it in order to give insight to a reader what they are going to find in this research thesis. In Chapter II, the focus is on Energy transition which is the driver for the development of microgrids to achieve EU’s decarbonization targets by 2030 and 2050, then this chapter goes thorough exploration of legislative and regulatory frameworks at both the European Union and Italian levels, especially pertaining to energy communities. The transposition of these EU directives in Italy is also explored. Then some information about the collective self-consumption and renewable energy community and difference between them is explained in details. In the end of this chapter energy price trends in the Italian market and its future scenarios are discussed in detail. The introductory Chapter III explains the concept of microgrids, definitions and its characteristics, then classifying them into AC, DC and hybrid type microgrids and further in the chapter literature review is performed taking into look on the present research work on microgrids its planning and management. Based on the literature review the chapter then examining diverse numerical methods for EMS i.e. classical, metaheuristics and intelligent methods. Chapter IV provides an in-depth discussion of the PED, the ALPGRIDS project, and a detailed overview of the Savona pilot project which is one of the pilot site in the Alpgrids project to be developed as a PED. The primary objectives of this project revolve around the exploration and implementation of a sustainable power system, specifically the existing Medium Voltage Microgrid (MVM), within the context of a local Energy Community and a virtual power plant scheme. The project aims to achieve a substantial degree of penetration of Renewable Energy Sources (RES) within a significant section of the urban landscape, taking into account the diverse types of buildings and their varying patterns of energy consumption. Furthermore, the project seeks to investigate a carbon-neutral network scheme that incorporates cutting-edge technologies such as hydrogen Combined Heat and Power (CHP) units and wind turbines. The pilot study associated with this project concentrates on fulfilling the stringent supply reliability requirements of research laboratories and the unique demand profiles of buildings, particularly those with high heating and cooling energy needs. The ultimate goal is to significantly reduce the use of primary energy and curb pollutant emissions, thereby contributing to the broader objectives of environmental sustainability and energy efficiency. This project, therefore, stands at the intersection of technological innovation and environmental stewardship, aiming to pave the way for a more sustainable and energy-efficient future. Additionally, the chapter entails calculations for determining the energy needs of the Mini-campus. These computations consider a multitude of factors, including the building's thermal attributes, patterns of occupancy, and assumptions about power consumption for appliances and lighting. Knowing the energy requirements is crucial for making decisions pertaining to energy efficiency, cost control, and sustainability. This understanding empowers us to pinpoint areas where energy-saving measures can be applied, thereby optimizing the building's operational performance and minimizing its environmental footprint. In essence, these calculations serve as a roadmap, guiding us towards a more sustainable and cost-effective utilization of energy resources, while also contributing to the broader goals of environmental conservation and sustainability. Chapter V outlines the optimal design model for the Mini-campus, utilizing the Homer Grid software to achieve an efficient sizing of technologies to be integrated into the microgrid. Utilizing Homer grid, we can strategically curtail the peak power we purchase from the utility each month. This chapter helps in understanding different input parameter for the optimal design of electrical and thermal technologies with Homer grid, then some technical features of microgrids and its components, then at the end of this chapter results with the optimal size of the different technologies are presented with different cases analysed precisely to cater the need of the Savona pilot. Subsequently, Chapter VI introduces the proposed optimal management model, elucidating the complexities of input parameters, decision variables, constraints, and objective functions. It presents a customized Mixed Integer Linear Programming (MILP) model tailored for the Savona pilot project microgrid, encompassing all significant constraints and decision variables. The constraints incorporate all the technologies to be installed, the size of which was influenced by the results from the optimal design model via Homer Grid. The constraints also include the E-mobility infrastructure, which comprises six chargers: 2 DC, 2 AC, and 2 V2G chargers. The model considers 14 different cars of various models from different manufacturers, each possessing distinct charging capacities either by AC, DC, or V2G technology. The primary objective function of this model is the minimization of operational costs. Chapter VII provides an exhaustive case study application, detailing the data acquisition methods employed for microgrid management. This includes the processing of raw data by interpolating it to quarter-hourly data. This data is further analyzed to determine its suitability for the model, depending on the location and usage type. This chapter also offers a thorough discussion of results and their implications. In the results section, cases for the different objective functions are displayed, and finally, the sensitivity analysis on electricity prices results are shown. This analysis demonstrates the influence of electricity prices on the effective management of the microgrids. Finally, Chapter VIII concludes the thesis, summarizing the key learnings and their potential applications. It provides valuable insights into the scope and significance of the research and future work, highlighting the importance of this study in the field of microgrid management.