Integrated hybrid multi-regional input-output for assessing life cycle air emissions of the Italian power system

The air emissions of the Italian power system, as well as national emissions between 2010 and 2017 and projections to 2040, have been assessed from a lifecycle perspective, using an integrated hybrid two-region input-output model of Italy versus the rest of the world. The Italian economy is divided into 42 sectors, including electricity, which is further disaggregated into seven technologies. Detailed electricity sector data, from Istat, are fed into the EXIOBASE input-output database. NAMEA tables represent overall air emissions, while the Ecoinvent database is used for the electricity sector. Electricity transition scenarios from Terna and Snam have been integrated into input-output and air emission databases. Demand and emissions were tracked within the electricity sector over medium-term, and the findings showed a sharp decrease between 2017 and 2025, from 97.5 MtCO2 to 32.6 MtCO2. By 2040, air emissions from the electricity sector are expected to grow gradually, compared to those of 2030, from 22.2 MtCO2 to 25.9 MtCO2, suggesting that the demand between 2030 and 2040 grows faster than the decarbonization effort during the same period. There is an overall, gradual downtrend between 2010 and 2040, with all air emission categories declining by half from both production and consumption-based perspectives in this period

Hierarchical-power-flow-based energy management for alternative/direct current hybrid microgrids

Modern microgrids are systems comprising both Alternative Current (AC) and Direct Current (DC) subgrids, integrated with Distributed Generations (DGs), storage systems, and Electric Vehicles (EVs) parking facilities. Achieving stable and reliable load flow control amidst varying load, generation, and charging/discharging strategies requires a hierarchical control scheme. This paper proposes an hourly power flow (PF) analysis within an Energy Management System (EMS) for AC/DC Hybrid Microgrids interconnected via an Interlinking Converter (IC) in both grid-connected and islanded modes. The framework operates within a two-level hierarchically controlled platform. Tertiary control at the top level optimizes DGs' reference power for generation and consumption, minimizing power purchase costs and load shedding in grid-connected and islanded modes, respectively. DG converters employ current control mode to share their power references as the primary controller. While no secondary controller is adopted in this scheme, the Battery Energy Storage System (BESS) in islanded mode utilizes P/Q droop control to maintain voltage and frequency in the AC subsystem. Power sharing between AC and DC subgrids through IC is determined by the difference between AC grid frequency and DC link voltage. Integration of controlled converters’ buses into PF equations enables solving the unified system using the traditional Newton-Raphson (NR) method. A segment of a real distribution grid planned for installation in Italy under the HYPERRIDE project serves as a case study. Comparison with MATLAB/Simulink results confirms the effectiveness, precision, and convergence speed of the proposed model and control schemes, demonstrating efficient load distribution and voltage/frequency restoration in islanded mode

Time resolved confocal luminescence investigations on Reverse Proton Exchange Nd:LiNbO3 channel waveguides

This paper was published in Optics Express and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://dx.doi.org/10.1364/OE.15.008805. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under la

A blockchain-based architecture for tracking and remunerating fast frequency response

The increasing penetration of renewable sources introduces new challenges for power systems’ stability, especially for isolated systems characterized by low inertia and powered through a single diesel power plant, such as it happens in small islands. For this reason, research projects, such as the BLORIN project, have focused on the provision of energy services involving electric vehicles owners residential users to mitigate possible issues on the power system due to unpredictable generation from renewable sources. The residential users were part of a blockchain-based platform, which also the Distributors/Aggregators were accessing. This paper describes the integrated framework that was set up to verify the feasibility and effectiveness of some of the methodologies developed in the BLORIN project for fast frequency response in isolated systems characterized by low rotational inertia. The validation of the proposed methodologies for fast frequency response using Vehicle-to-Grid or Demand Response programs was indeed carried out by emulating the dynamic behavior of different power resources in a Power Hardware-in-the-Loop environment using the equipment installed at the LabZERO laboratory of Politecnico di Bari, Italy. The laboratory, hosting a physical microgrid as well as Power Hardware-in-the-Loop facilities, was integrated within the BLORIN blockchain platform. The tests were conducted by assuming renewable generation development scenarios (mainly photovoltaic) and simulating the system under the worst-case scenarios caused by reduced rotational inertia. The experiments allowed to fully simulate users’ interaction with the energy system and blockchain network reproducing realistic conditions of tracking and remuneration of users’ services. The results obtained show the effectiveness of the BLORIN platform for the provision, tracking and remuneration of grid services by electric vehicles and end users, and the benefits that are achieved in terms of reducing the number of diesel generating units that need to be powered on just to provide operational reserve due to the penetration of renewable sources, resulting in fuel savings and reduced emissions

Review of potential and actual penetration of solar power in Vietnam

With the average solar radiation reaching up to 5 kWh/m2, Vietnam is considered as a country showing an excellent potential for solar power production. Since the year 2000, there have been a lot of studies about the potential of this source in Vietnam. So far, many applications of solar power have been implemented on small, medium, and large scales. In fact, the total capacity of current grid-connected solar power plants has exceeded the planned capacity by 2020 nearly 6 times. However, the studies of solar potential in Vietnam are still incomplete. The policies and mechanisms for developing solar power projects have received attention from the authorities but have not been really satisfactory. The infrastructure is still poor and the power system does not keep up with the development of modern grids. This paper reviewed the potential and actual implementation stage of photovoltaic projects in Vietnam. Moreover, the barriers and challenges of institution, technique, economy, and finance have been considered explicitly for the future development of solar energy in Vietnam

Critical Assessments of the Potential for Integrating Renewable Energy into Isolated Grids on Vietnamese Islands: The Case of the An-Binh Grid

Renewable electricity for off-grid areas is widely seen as one of the top choices in supporting local economic development in most countries, and so is Vietnam. Over the years, many isolated networks using renewable energy sources have been deployed for off-grid areas in Vietnam. However, the use of these energy sources in Vietnam’s isolated networks is still facing many challenges due to its infancy here. The issues of reliability and vulnerability of these networks are not given the expected attention. Another challenge is that the issues of the operational security of these systems could also be negatively affected by the variable nature of renewable sources, including static and dynamic security. For this reason, this study aims to contribute to a better understanding of integrating renewable energy into isolated networks, and in this case, using solar power for the An-Binh Island grid in Vietnam. The findings from this study suggest that choosing the right structure of the power mix could contribute to improving the operational security of isolated networks. Moreover, several solutions to enhance the reliability of this grid are also proposed. The NEPLAN environment was selected for simulation and analysis for all the scenarios in this study

Surface Periodic Poling in Lithium Niobate and Lithium Tantalate

Periodic Poling of Lithium Niobate crystals (PPLN) by means of electric field has revealed the best technique for finely tailoring PPLN structures and parameters, which play a central role in many current researches in the field of nonlinear integrated optics. Besides the most studied technique of bulk poling, recently a novel technique where domain inversion occurs just in a surface layer using photoresist or silica masks has been devised and studied. This surface periodic poling (SPP) approach is best suited when light is confined in a thin surface guiding layer or stripe, as in the case of optical waveguide devices. Also, we found that SPP respect to bulk poling offers two orders of magnitude reduction on the scale of periodicity, so that even nanostructures can be obtained provided an high resolution holographic mask writing technique is adopted. We were able to demonstrate 200 nm domain size, and also good compatibility with alpha-phase proton exchange channel waveguide fabrication. Our first experiments on Lithium Tantalate have also shown that the SPP technology appears to be applicable to this crystal (SPPLT), whose properties can allow to overcome limitations such as optical damage or UV absorption still present in PPLN devices. Finally, the issue of SPP compatibility with proton exchange waveguide fabrication will be addresse

Solving congestions with pumped hydro storage under high penetration of renewable energy in Vietnam: The case of Ninh Thuan HV grid

Renewable energy sources are increasingly penetrating all power networks worldwide, despite the security status of these networks threatened by the fickle nature of these sources. Ninh Thuan Province (Vietnam) experienced a solar power boom in 2019–2021 and, with it, the congestion of both the local transmission and distribution networks. To solve congestions and operational security issues, large-scale storage solutions were considered and, due to land availability, Pumped Hydro Storage (PHS) technology was selected to solve these problems. However, the operational risks of cascade outage when integrating both renewables and a PHS system needs to be carefully considered, especially in a bulk power system. For this reason, this study examined the potential of integrating a large-scale grid-connected PHS system in ensuring operational security against the impacts of solar power plants in Ninh Thuan. The analyses of static and dynamic security were carried out for scenarios with and without the PHS system, including under current operational conditions. The results of the simulations show that the presence of the PHS improves both static and dynamic performance of the system, thus allowing full exploitation of solar power and avoiding curtailment. NEPLAN environment was chosen to simulate all scenarios under the Vietnamese grid code

Refining Long Short-Term Memory Neural Network Input Parameters for Enhanced Solar Power Forecasting

This article presents a research approach to enhancing the quality of short-term power output forecasting models for photovoltaic plants using a Long Short-Term Memory (LSTM) recurrent neural network. Typically, time-related indicators are used as inputs for forecasting models of PV generators. However, this study proposes replacing the time-related inputs with clear sky solar irradiance at the specific location of the power plant. This feature represents the maximum potential solar radiation that can be received at that particular location on Earth. The Ineichen/Perez model is then employed to calculate the solar irradiance. To evaluate the effectiveness of this approach, the forecasting model incorporating this new input was trained and the results were compared with those obtained from previously published models. The results show a reduction in the Mean Absolute Percentage Error (MAPE) from 3.491% to 2.766%, indicating a 24% improvement. Additionally, the Root Mean Square Error (RMSE) decreased by approximately 0.991 MW, resulting in a 45% improvement. These results demonstrate that this approach is an effective solution for enhancing the accuracy of solar power output forecasting while reducing the number of input variables