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20 result(s) for "RES penetration"
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A Review of Pumped Hydro Storage Systems
With the increasing global demand for sustainable energy sources and the intermittent nature of renewable energy generation, effective energy storage systems have become essential for grid stability and reliability. This paper presents a comprehensive review of pumped hydro storage (PHS) systems, a proven and mature technology that has garnered significant interest in recent years. The study covers the fundamental principles, design considerations, and various configurations of PHS systems, including open-loop, closed-loop, and hybrid designs. Furthermore, the review highlights the crucial role of PHS systems in integrating renewable energy sources, mitigating peak load demands, and enhancing grid stability. An in-depth analysis of current and emerging trends, technical challenges, environmental impacts, and cost-effectiveness is also provided to identify potential areas for future research and development. The paper concludes by offering a perspective on the challenges and opportunities that PHS systems present, underlining their potential to significantly contribute to a sustainable and reliable energy future.
A hybrid renewable energy system with advanced control strategies for improved grid stability and power quality
The global shift toward Renewable Energy Systems (RESs) has gained momentum due to their environmental benefits over traditional fossil fuel-based power generation. However, integrating RESs—such as wind turbines and photovoltaic systems—into the utility grid introduces significant technical challenges. These challenges stem from the nonlinear characteristics, intermittent nature, and inherent uncertainties of RESs. High penetration levels of RESs exacerbate issues such as inadequate generation reserves, elevated fault currents, increased system uncertainties, and degraded power quality. The unpredictable and energy-dilute nature of wind and solar resources further complicates grid stability and control. To address these challenges, this paper proposes a hybrid RES architecture integrated with the grid, enhanced by advanced control strategies to improve system performance. The proposed framework incorporates cutting-edge technologies, including Flexible AC Transmission Systems (FACTS), fault current limiters, and energy storage systems, to mitigate technical barriers and ensure stable grid operation. The system design and performance evaluation are conducted through comprehensive software simulations using Python and Power System Simulation for Engineering (PSSE). Simulation results demonstrate the effectiveness of the proposed approach in enhancing grid stability, power quality, and fault resilience under high-RES penetration scenarios. The proposed strategy reduces THD to 1.8% (vs. 3.1% for conventional PI control), limits voltage fluctuations to ± 2.1%, and maintains frequency deviations within ± 0.1 Hz—outperforming both IEEE 519 and EN 50,160 standards. Comparative analysis shows 40% faster settling times than MPC-based approaches. This study provides a robust solution for the seamless integration of RESs into modern power systems, paving the way for a sustainable energy future.
Towards Automated Model Selection for Wind Speed and Solar Irradiance Forecasting
Given the recent increase in demand for electricity, it is necessary for renewable energy sources (RESs) to be widely integrated into power networks, with the two most commonly adopted alternatives being solar and wind power. Nonetheless, there is a significant amount of variation in wind speed and solar irradiance, on both a seasonal and a daily basis, an issue that, in turn, causes a large degree of variation in the amount of solar and wind energy produced. Therefore, RES technology integration into electricity networks is challenging. Accurate forecasting of solar irradiance and wind speed is crucial for the efficient operation of renewable energy power plants, guaranteeing the electricity supply at the most competitive price and preserving the dependability and security of electrical networks. In this research, a variety of different models were evaluated to predict medium-term (24 h ahead) wind speed and solar irradiance based on real-time measurement data relevant to the island of Crete, Greece. Illustrating several preprocessing steps and exploring a collection of “classical” and deep learning algorithms, this analysis highlights their conceptual design and rationale as time series predictors. Concluding the analysis, it discusses the importance of the “features” (intended as “time steps”), showing how it is possible to pinpoint the specific time of the day that most influences the forecast. Aside from producing the most accurate model for the case under examination, the necessity of performing extensive model searches in similar studies is highlighted by the current work.
One-Day-Ahead Solar Irradiation and Windspeed Forecasting with Advanced Deep Learning Techniques
In recent years, demand for electric energy has steadily increased; therefore, the integration of renewable energy sources (RES) at a large scale into power systems is a major concern. Wind and solar energy are among the most widely used alternative sources of energy. However, there is intense variability both in solar irradiation and even more in windspeed, which causes solar and wind power generation to fluctuate highly. As a result, the penetration of RES technologies into electricity networks is a difficult task. Therefore, more accurate solar irradiation and windspeed one-day-ahead forecasting is crucial for safe and reliable operation of electrical systems, the management of RES power plants, and the supply of high-quality electric power at the lowest possible cost. Clouds’ influence on solar irradiation forecasting, data categorization per month for successive years due to the similarity of patterns of solar irradiation per month during the year, and relative seasonal similarity of windspeed patterns have not been taken into consideration in previous work. In this study, three deep learning techniques, i.e., multi-head CNN, multi-channel CNN, and encoder–decoder LSTM, were adopted for medium-term windspeed and solar irradiance forecasting based on a real-time measurement dataset and were compared with two well-known conventional methods, i.e., RegARMA and NARX. Utilization of a walk-forward validation forecast strategy was combined, firstly with a recursive multistep forecast strategy and secondly with a multiple-output forecast strategy, using a specific cloud index introduced for the first time. Moreover, the similarity of patterns of solar irradiation per month during the year and the relative seasonal similarity of windspeed patterns in a timeseries measurements dataset for several successive years demonstrates that they contribute to very high one-day-ahead windspeed and solar irradiation forecasting performance.
Managing BEV Charge to Obtain a Positive Impact on a National Power System
This paper’s research question is to evaluate the potential impact of large numbers of battery electric vehicles (BEVs) on the future electric grid, and whether the flexibility of BEV charging can induce enough system benefits to remunerate BEV users for the change in their recharging pattern. The considered scenario refers to the Italian situation and what might occur through the year 2040, where a share of BEV stock of 40% can be foreseen, as well as significant increases in PV and wind generation. Although this study is focused on Italy, its results are applicable, with minor differences, to several EU countries. This paper first shows that the future impact of increasing penetration of BEVs appears to be compatible with the expected growth of generation from renewable energy sources (RES) and the corresponding reduction in fossil fuel-based generation. It also gives an estimate of the CO2 emission reduction resulting from these changes, considering an unmanaged BEV charge profile and two different managed profiles that shift the car’s charging period to hours of the day when they have no negative impact on the grid and maximize the utilization of RES. Finally, it shows an evaluation of the economic benefits of displacing private car charging ranging from 4 to 10 cEUR/kWh, which could be used as tariff incentives to stimulate this displacing in recharging time.
Insights from a Comprehensive Capacity Expansion Planning Modeling on the Operation and Value of Hydropower Plants under High Renewable Penetrations
This paper presents a quantitative assessment of the value of hydroelectric power plants (HPPs) in power systems with a significant penetration of variable renewable energy sources (VRESs). Through a capacity expansion planning (CEP) model that incorporates a detailed representation of HPP operating principles, the study investigates the construction and application of HPP rule curves essential for seasonal operation. A comparative analysis is also conducted between the proposed rule curve formulation and alternative modeling techniques from the literature. The CEP model optimizes installed capacities per technology to achieve predefined VRES penetration targets, considering hourly granularity and separate rule curves for each HPP. A case study involving twelve reservoir hydropower stations and two open-loop pumped hydro stations is examined, accounting for standalone plants and cascaded hydro systems across six river basins. The study evaluates the additional generation and storage required to replace the hydropower fleet under high VRES penetration levels, assessing the resulting increases in total system cost emanating from introducing such new investments. Furthermore, the study approximates the storage capabilities of HPPs and investigates the impact of simplified HPP modeling on system operation and investment decisions. Overall, the findings underscore the importance of reevaluating hydro rule curves for future high VRES penetration conditions and highlight the significance of HPPs in the energy transition towards carbon neutrality.
PV Penetration under Market Environment and with System Constraints
The installed capacity of PVs in the distribution grid is affected not only by network constraints, but also by the economic viability of the related investments. Depending on the market participation models, this is determined critically by the Day Ahead Market (DAM) prices. Increasing RES installations in a country usually results in a long term drop in the market prices and, as a consequence, a reduction in the income of the PVs investors and possible market cannibalization. This paper models the effect of large-scale penetration of PVs on the market prices and identifies the optimal penetration level for the viability of PV projects. The optimal penetration is highly related to the installation of new PVs and this is a parameter for the analysis. Therefore, the paper identifies different penetration costs for the different installation cost. Furthermore, the PV network hosing capacity can be increased by distribution network reinforcements. Therefore, in the paper, the investments for enhancement of the distribution grid are assessed with respect to market prices and are analyzed at the macroscopic level. Again, the analysis considers different costs for network reinforcements.
Decarbonizing the Energy System of Non-Interconnected Islands: The Case of Mayotte
Islands face unique challenges on their journey towards achieving carbon neutrality by the mid-century, due to the lack of energy interconnections, limited domestic energy resources, extensive fossil fuel dependence, and high load variance requiring new technologies to balance demand and supply. At the same time, these challenges can be turned into a great opportunity for economic growth and the creation of jobs with non-interconnected islands having the potential to become transition frontrunners by adopting sustainable technologies and implementing innovative solutions. This paper uses an advanced energy–economy system modeling tool (IntE3-ISL) accompanied by plausible decarbonization scenarios to assess the medium- and long-term impacts of energy transition on the energy system, emissions, economy, and society of the island of Mayotte. The model-based analysis adequately captures the specificities of Mayotte and examines the complexity, challenges, and opportunities to decarbonize the island’s non-interconnected energy system. The energy transition necessitates the adoption of ambitious climate policy measures and the extensive deployment of low- and zero-carbon technologies both in the demand and supply sides of the energy system, accounting for the unique characteristics of each individual sector, while sectoral integration is also important. To reduce emissions from hard-to-abate sectors, such as transportation and industry, the measures and technologies can include the installation and use of highly efficient equipment, the electrification of end uses (such as the widespread adoption of electric vehicles), the large roll-out of renewable energy sources, as well as the production and use of green hydrogen and synthetic fuels.
Dynamic Modeling and Simulation of Non-Interconnected Systems under High-RES Penetration: The Madeira Island Case
The defossilization of power generation is a prerequisite goal in order to reduce greenhouse gas emissions and transit for a sustainable economy. Achieving this goal requires increasing the penetration of renewable energy sources (RESs) such as solar and wind power. The gradual shrinking of conventional generation units in an energy map introduces new challenges to the stability of power systems as there is a considerable reduction of stored rotational energy in the synchronous generators (SGs) and the capability to control their power output, which has been taken for granted until today. Inertia and primary reserve reduction have a substantial effect on the ability of the power system to maintain its security and self-resilience during contingency events. Such issues become more evident in the case of non-interconnected islands (NII) as they have unique features associated with their small size and low inertia. The present study examines in depth the NII system of Madeira, which is composed of thermal, hydro, solid-waste, wind and solar generation units, and additional RES integration is planned for the near future. Electromagnetic transient (EMT) simulations are performed for both the current and future states of the system, including the installation of planned variable RES capacities. To alleviate the stability issues that occurred in the high-RES scenario, the introduction of a utility-scale battery energy storage system (BESS), capable of mitigating the active power imbalance due to the power system’s disturbances resultant of RES penetration, is examined. In addition, a comparison between a flywheel energy storage system (FESS) and BESS is shortly investigated. The grid has been modeled and simulated utilizing the open-source, object-oriented modeling language Modelica. The dynamic simulation results proved that battery storage is a promising technology that can be a solution for transitioning to a sustainable power system, maintaining its self-resilience under severe disturbances such as rapid load changes, the tripping of generation units and short-circuits.
How Can EVs Support High RES Penetration in Islands
The electrification of the transportation sector contributes to a cleaner environment in non-interconnected island (NII) systems or standalone islands. Moreover, e-mobility can significantly contribute to achieving very high renewable energy source (RES) penetration levels in islands, allowing a reduction both in the emissions due to the conventional generation and the system’s cost. Ιncreased RES penetration, however, can pose technical challenges for an island’s system. In order to overcome these challenges, new technologies like grid-forming converters are important. Moreover, the provision of new ancillary services in relation to battery storage systems might be considered, while novel control and protection schemes are needed to ensure secure operation. E-mobility can also contribute to solving technical problems that arise from very high RES penetration by providing frequency containment reserves or reactive power compensation. Since EV charging demand introduces modifications in the system’s load curve, e-mobility may affect the power grid for long-term planning and short-term operation, i.e., line loading and voltages. The application of specifically developed smart charging methodologies can mitigate the relevant grid impact, while effective exploitation of EV–RES synergies can achieve higher RES penetration levels. This paper examines how e-mobility can contribute to increasing RES penetration in islands while considering the technical issues caused. In particular, this paper takes into account the distinct characteristics of NIIs towards the identification of solutions that will achieve very high RES penetration while also addressing the relevant technical challenges (voltage control, frequency control, short circuit protection, etc.). The effect of e-mobility in the power grid of NII systems is evaluated, while smart charging methodologies to mitigate the relevant impact and further increase RES penetration are identified.