Optimal Sizing and Environ-Economic Analysis of PV-BESS Systems for Jointly Acting Renewable Self-Consumers

Future residential applications could benefit from nanogrids that integrate photovoltaics (PV) and battery energy storage systems (BESS), especially after the establishment of recent European Community directives on renewable energy communities (RECs) and jointly acting renewable self-consumers (JARSCs). These entities consist of aggregations of users who share locally produced energy with the aim of gaining economic, environmental, and social benefits by enhancing their independence from the electricity grid. In this regard, the sizing of the PV and BESS systems is an important aspect that results in a trade-off from technical, economic, and environmental perspectives. To this end, this paper presents an investigation on the optimal PV-BESS system sizing of a condominium acting as a JARSC community, which includes a common PV plant and EMS, operated by rule-based criteria. PV-BESS sizing results are investigated from economic and environmental perspectives, considering a case study located in Milan, Italy. In these regards, in addition to the common techno-economic criteria, carbon dioxide emissions are considered with particular attention, as their reduction is the driving ethos behind recent EU directives

Sistemi di gestione dell'energia e strategie di ottimizzazione per l'integrazione dei veicoli elettrici considerando gli aspetti economici e ambientali

Il cambiamento climatico in atto ci spinge ad intervenire rapidamente con azioni efficaci e durature nel tempo. Tra i principali settori inquinanti, l'energia utilizzata negli edifici, nelle industrie e nei trasporti è causa della gran parte delle emissioni di gas serra a livello mondiale. L'elettrificazione di questi settori è una delle soluzioni ottimali per il processo di decarbonizzazione supportando le politiche della transizione energetica in corso. La produzione di energia elettrica da fonti rinnovabili e la crescita esponenziale del mercato dei veicoli elettrici a livello mondiale sono la chiave per un futuro sostenibile. Tuttavia, nonostante il loro potenziale, portano l'attenzione sulla loro reciproca integrazione al fine di comprendere a fondo i reali vantaggi dal punto di vista energetico, economico ed ambientale. Inoltre, la possibilità di scambio energetico bidirezionale grazie all'avvento della tecnologia Vehicle-to-Grid (V2G) definisce nuove opportunità di integrazione e supporto alla rete elettrica. In questo lavoro, vengono studiate la gestione energetica e il controllo ottimizzato per l'integrazione dei veicoli elettrici con la rete elettrica e i sistemi di generazione rinnovabile distribuita. Nella prima parte viene introdotto il problema delle emissioni, l'elettrificazione dei trasporti e le definizioni di alcuni concetti chiave. Successivamente, l'integrazione dei veicoli elettrici viene studiata da due diversi punti di vista. Il primo, in parte in collaborazione con la Christian-Albrechts-Universität (CAU) a Kiel, si focalizza su aspetti legati all'elettronica di potenza e al controllo di basso livello, mostrando un confronto tra diverse topologie di convertitori DC-DC (DAB), un'analisi sull'efficienza totale di ricarica del veicolo e la simulazione di un sistema V2G sperimentale per la fornitura di servizi ancillari. Il secondo invece si concentra maggiormente sulla gestione ed il controllo predittivo dei flussi energetici per l'integrazione dei veicoli elettrici con microreti, focalizzando l'attenzione su aspetti economici ed ambientali. In particolare, viene mostrata l'implementazione e la validazione sperimentale di un sistema di controllo real-time per una stazione di ricarica fotovoltaica installata presso l'Università di Trieste, un sistema V2G integrato all'interno di uno ski-resort Alpino ed infine, uno studio relativo ad una microrete condominiale che mostra i vantaggi legati ad un gruppo di autoconsumatori che agiscono collettivamente.Ongoing climate change is driving the need for rapid action with effective and long-term impacts. Among the major polluting sectors, energy used in buildings, industries, and transportation accounts for most of the world's greenhouse gas emissions. Electrification of these sectors is one of the optimal solutions for the decarbonization process by supporting the ongoing energy transition policies. Electricity generation from renewable sources and the exponential growth of the global electric vehicle market are the key to a sustainable future. However, despite their potential, they bear attention to their mutual integration in order to fully understand the real benefits from energy, economic and environmental perspectives. In addition, the possibility of two-way energy exchange through the advent of Vehicle-to-Grid (V2G) technology defines new opportunities for integration and support to the power grid. In the present work, optimized energy management and control for the integration of electric vehicles with the power grid and distributed renewable generation systems are studied. In the first part, the emission problem, electrification of transportation and definitions of some key concepts are introduced. Next, the integration of electric vehicles is studied from two different perspectives. The first, partially in collaboration with the Christian-Albrechts-Universität (CAU) in Kiel, focuses on aspects related to power electronics and low-level control, showing a comparison of different DC-DC converter (DAB) topologies, an analysis of total vehicle charging efficiency, and a simulation of an experimental V2G system for providing ancillary services. The second focuses more on the management and predictive control of energy flows for the integration of electric vehicles with microgrids, focusing on economic and environmental aspects. In particular, it shows the implementation and experimental validations of a real-time control system for a photovoltaic charging station installed at the University of Trieste, an integrated V2G system within an Alpine ski-resort, and finally, a study related to a condominium microgrid showing the benefits related to a group of jointly acting renewables self-consumers

Optimal Sizing and Environ-Economic Analysis of PV-BESS Systems for Jointly Acting Renewable Self-Consumers

Future residential applications could benefit from nanogrids that integrate photovoltaics (PV) and battery energy storage systems (BESS), especially after the establishment of recent European Community directives on renewable energy communities (RECs) and jointly acting renewable self-consumers (JARSCs). These entities consist of aggregations of users who share locally produced energy with the aim of gaining economic, environmental, and social benefits by enhancing their independence from the electricity grid. In this regard, the sizing of the PV and BESS systems is an important aspect that results in a trade-off from technical, economic, and environmental perspectives. To this end, this paper presents an investigation on the optimal PV-BESS system sizing of a condominium acting as a JARSC community, which includes a common PV plant and EMS, operated by rule-based criteria. PV-BESS sizing results are investigated from economic and environmental perspectives, considering a case study located in Milan, Italy. In these regards, in addition to the common techno-economic criteria, carbon dioxide emissions are considered with particular attention, as their reduction is the driving ethos behind recent EU directives

Simulating the Diffusion of Residential Rooftop Photovoltaic, Battery Storage Systems and Electric Cars in Italy. An Exploratory Study Combining a Discrete Choice and Agent-Based Modelling Approach

Rooftop solar photovoltaic (PV) systems could significantly contribute to renewable energy production and reduce domestic energy costs. In Italy, as in other countries, the current incentives generate a modest annual increase after the generous fiscal incentives that kick-started the PV market in the 2008–2013 period. Several factors are, however, at play that can speed up the installation process, such as the improvements in PV technology at declining prices, the increased availability of battery-storage (BS) systems, the growing use of electric appliances, the uptake of electric cars, and the increased environmental awareness. We integrate two research methodologies, discrete choice modeling and agent-based modeling, to understand how these factors will influence households’ decisions regarding PV and BS installations and how agents interact in their socioeconomic environment. We predict that in Italy, given the preference structure of homeowners, the continuing decline in costs, and the social interaction, 40–45% of homeowners will have PV or PV and BS installed by 2030, thanks to the existing investment tax credit policy

Efficiency Trade-off-Oriented Analysis for the integration of DC-DC Converter and Battery Pack in V2G Applications

Growing concerns about environmental aspects and clean energy generation call for effective solutions to reduce the demand for fossil fuels and greenhouse gas emissions. One solution of particular interest is the use of electric vehicles (EVs), which are considered one of the most favourable strategies for reducing pollution in the transport sector. Besides battery charging process, the EV battery pack can serve as an energy storage system (ESS) to support the grid, thanks to vehicle-to-grid (V2G) ancillary services. During the EV power exchange with the main grid, the overall efficiency depends not only on the converter but also on the battery. Typically, power converters, in particular dual-active-bridge (DAB) converters, present a low efficiency at light loads (i.e. low C-rates) and higher values at high power levels. The battery efficiency, on the other hand, decreases almost linearly as the power increases. Therefore, there is an optimum C-rate that could be selected to operate the converter and the battery when they are connected to the grid in order to minimize the losses of the overall system. In this context, the paper aims to analyze the trade-off between several designed lithium-ion battery packs and DAB efficiencies to find the best compromise. Both simulation and experimental results are presented to validate the correctness of the theoretical analyses, which also lead to an efficiency-focused design method for V2G applications

Vehicle-to-ski: A V2G optimization-based cost and environmental analysis for a ski resort

Ski resorts are becoming perfect demonstrations for the integration of renewable sources. Moreover, the ever-growing global fleet of electric cars (EV) and the increase of battery capacities allow the vehicles to be used for purposes other than driving. This paper aims to study the implementation of a vehicle-to-grid (V2G) application and the development of an MPC-based energy management system (EMS) within a ski resort in the Trentino-Alto Adige Italian region. Using real data for load and production power estimation, the study analyses the economic and environmental impact in three different scenarios by considering the resort’s future trends. The results show that photovoltaic power generation has a significant impact on both cost and environmental aspects, leading to a reduction in total expenditure and CO2 of about 7%. However, assuming an increasing number of charging stations, the exploitation of V2G technology for energy arbitrage does not lead to significant total cost and CO2 reductions (~2%) for the future scenarios. Conversely, self-consumption improves (~100%) using different charging strategies. Despite this, a sensitivity analysis on PV production and a joint increase in EVs and energy price gap leads to a significant reduction in total costs of up to 7.7% and 15.2%, respectively

ηmax-Charging Strategy for Lithium-Ion Batteries in V2G Applications

The design of charging strategies for lithium-ion (Li-ion) batteries depends on the application. In electric vehicle applications, high charging speed and long battery life are essential requirements. However, with the advent of vehicle-to-grid (V2G) and potential remuneration for electric grid support, maximum user profit could gain increasing interest through efficient operation that also optimizes battery health. Conventional constant-current constant voltage (CCCV) and constant-power constant-voltage (CPCV) charging strategies do not include the optimum efficiency of the battery and charging stations. In this paper, a charging strategy is introduced aiming at maximizing the instantaneous efficiency (ηmax of the Li-ion battery and the charging station which minimizes the energy waste. For this purpose, 18650 Li-ion cells and a dual-active-bridge (DAB) converter are considered in the simulations and experimental validations. The results show that the ηmax -charging strategy outperforms conventional CCCV and CPCV charging strategies in terms of efficiency and material-lifetime compatibility

Energy Scheduling and Performance Evaluation of an e-Vehicle Charging Station

This paper proposes an energy management system (EMS) for a photovoltaic (PV) grid-connected charging station with a battery energy storage system (BESS). The main objective of this EMS is to manage the energy delivered to the electric vehicle (EV), considering the price and CO2 emissions due to the grid’s connection. Thus, we present a multi-objective two-stage optimization to reduce the impact of the charging station on the environment, as well as the costs. The first stage of the optimization provides an energy schedule, taking into account the PV forecast, the hourly grid’s CO2 emissions factor, the electricity price, and the initial state of charge of the BESS. The output from this first stage corresponds to the maximum power permitted to be delivered to the EV by the grid. Then, the second stage of the optimization is based on model predictive control that looks to manage the energy flow from the grid, the PV, and the BESS. The proposed EMS is validated using an actual PV/BESS charging station located at the University of Trieste, Italy. Then, this paper presents an analysis of the performance of the charging station under the new EMS considering three main aspects, economic, environmental, and energy, for one month of data. The results show that due to the proposed optimization, the new energy profile guarantees a reduction of 32% in emissions and 29% in energy costs