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18 pages, 2013 KiB

Open AccessArticle

The Concept of Spatial Reliability Across Renewable Energy Systems—An Application to Decentralized Solar PV Energy

by Athanasios Zisos, Dimitrios Chatzopoulos and Andreas Efstratiadis

Energies 2024, 17(23), 5900; https://doi.org/10.3390/en17235900 - 25 Nov 2024

Viewed by 317

Abstract

Decentralized planning of renewable energy systems aims to address the substantial spatiotemporal variability, and thus uncertainty, associated with their underlying hydrometeorological processes. For instance, solar photovoltaic (PV) energy is driven by two processes, namely solar radiation, which is the main input, and ambient [...] Read more.

Decentralized planning of renewable energy systems aims to address the substantial spatiotemporal variability, and thus uncertainty, associated with their underlying hydrometeorological processes. For instance, solar photovoltaic (PV) energy is driven by two processes, namely solar radiation, which is the main input, and ambient temperature, with the latter affecting the panel efficiency under specific weather conditions. The objective of this work is to provide a comprehensive investigation of the role of spatial scale by assessing the theoretical advantages of the distributed production of renewable energy sources over those of centralized, in probabilistic means. Acknowledging previous efforts for the optimal spatial distribution of different power units across predetermined locations, often employing the Modern Portfolio Theory framework, this work introduces the generic concept of spatial reliability and highlights its practical use as a strategic planning tool for assessing the benefits of distributed generation at a large scale. The methodology is verified by considering the case of Greece, where PV solar energy is one of the predominant renewables. Following a Monte Carlo approach, thus randomly distributing PVs across well-distributed locations, scaling laws are derived in terms of the spatial probability of capacity factors. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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16 pages, 6571 KiB

Open AccessArticle

Wall Shading Losses of Photovoltaic Systems

by Joseph Appelbaum, Assaf Peled and Avi Aronescu

Energies 2024, 17(20), 5089; https://doi.org/10.3390/en17205089 - 13 Oct 2024

Cited by 1 | Viewed by 678

Abstract

The deployment of photovoltaic (PV) systems on rooftops in urban environments may encounter shading on the PV collectors from surrounding walls, acting adversely on the generated electricity of the PV systems. Most studies on the shading of PV systems do not deal analytically [...] Read more.

The deployment of photovoltaic (PV) systems on rooftops in urban environments may encounter shading on the PV collectors from surrounding walls, acting adversely on the generated electricity of the PV systems. Most studies on the shading of PV systems do not deal analytically with the shading losses of PV collectors affected by walls, fences, and obscuring objects. The present article mathematically formulates shadow expressions for wall and inter-row shading on PV collectors and calculates the percentage of annual shading losses affected by wall heights and azimuth angles, the distances of walls to collectors, and the length and azimuth angles of collectors. This study indicates that the shading losses increase for shorter distances from the collector to the walls and for higher walls. Shading losses may reach 7 percent for wall heights of 4 m and at a distance of 2 m from the collectors to a wall. The results indicate that wall shading dominates inter-row shading. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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17 pages, 2190 KiB

Open AccessArticle

Analysis of Demand Response in Electric Systems with Strong Presence of Intermittent Generation Using Conditional Value-at-Risk

by Rafael V. X. de Souza and Thales Sousa

Energies 2024, 17(18), 4688; https://doi.org/10.3390/en17184688 - 20 Sep 2024

Viewed by 579

Abstract

The integration of renewable sources, such as hydro, wind, and solar power, into electrical systems has profoundly transformed the sector’s dynamics. The inherent intermittency of these energy sources, due to the uncertainty associated with inflows, winds, and solar irradiation, introduces considerable challenges in [...] Read more.

The integration of renewable sources, such as hydro, wind, and solar power, into electrical systems has profoundly transformed the sector’s dynamics. The inherent intermittency of these energy sources, due to the uncertainty associated with inflows, winds, and solar irradiation, introduces considerable challenges in the operation and planning of the electrical system. In this context, demand response emerges as a promising solution to handle the fluctuations in renewable generation and maintain system stability and reliability. Therefore, this study presents a new approach to the demand response program through the modeling of an optimal power flow problem to minimize operational costs, considering the uncertainties in hydro, wind, and solar generation by applying the Conditional Value-at-Risk (CVaR) risk metric. The mathematical modeling of the problem was conducted, and the problem was solved using the MINOS solver. To validate the model, simulations were carried out using modified IEEE systems of 14, 30, 57, and 118 buses, considering operation planning for the next 24 h. Furthermore, sensitivity analyses were performed by altering the CVaR parameters. As a result of the simulations, the total operational cost, electrical losses, and hourly generation at each bus by source type were determined, highlighting how CVaR impacts the operation of this type of system. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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20 pages, 1946 KiB

Open AccessFeature PaperArticle

Statistical Analysis of Electricity Prices in Germany Using Benford’s Law

by Marek Pavlík, Matej Bereš, Ardian Hyseni and Jaroslav Petráš

Energies 2024, 17(18), 4606; https://doi.org/10.3390/en17184606 - 13 Sep 2024

Viewed by 817

Abstract

The year 2022 was marked by a significant increase in electricity prices in Germany, with prices reaching extreme levels due to various geopolitical and climatic factors. This research analyzes the evolution of electricity prices in Germany from 2015 to 2024 and applies Benford’s [...] Read more.

The year 2022 was marked by a significant increase in electricity prices in Germany, with prices reaching extreme levels due to various geopolitical and climatic factors. This research analyzes the evolution of electricity prices in Germany from 2015 to 2024 and applies Benford’s Law to examine the distribution of the first digits of these prices. Historical electricity price data from Germany, obtained from publicly available sources, were used for the analysis. We applied Benford’s Law to determine the frequency of occurrence of the first digits of electricity prices and compared the results with the expected distribution according to Benford’s Law. We also considered the impact of negative electricity prices. The results suggest that external factors, such as geopolitical events and climatic conditions, have a significant impact on the volatility of electricity prices. Benford’s Law can be a useful tool for analyzing electricity prices, although its application to this market shows certain deviations. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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13 pages, 4684 KiB

Open AccessArticle

Analysis of Losses Associated with Series Resistance (Rs) in Simple-Structured c-Si Solar Cells

by Manuel J. Heredia-Rios, Luis Hernandez-Martinez, Monico Linares-Aranda, Mario Moreno-Moreno and Javier Flores Méndez

Energies 2024, 17(7), 1520; https://doi.org/10.3390/en17071520 - 22 Mar 2024

Viewed by 1303

Abstract

The assessment of photovoltaic devices, which convert light energy into electricity, has become significantly more relevant due to the aspiration to reduce pollution on a global scale. In this context, the pursuit of optimizing the efficiency of converting light energy into electrical energy [...] Read more.

The assessment of photovoltaic devices, which convert light energy into electricity, has become significantly more relevant due to the aspiration to reduce pollution on a global scale. In this context, the pursuit of optimizing the efficiency of converting light energy into electrical energy involves exhaustive studies and structural analyses of solar cells, all directed toward achieving this goal. This study introduces a research proposal aimed at analyzing the losses associated with series resistance (Rs). The analysis takes into account each component comprising this resistance, proposing a network of resistances that precisely models each of these elements. The aforementioned research focused on simple-structured crystalline silicon cells. During this investigation, the junction depth (xj) of the n-p materials was varied, with the aim of achieving efficiencies in the range of 12%. However, in the pursuit of this desired efficiency, a significant impact on series resistance was observed when analyzing the I-V curves of the cells obtained in each manufacturing process. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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12 pages, 3032 KiB

Open AccessArticle

Synthesis of Solar Production and Energy Demand Profiles Using Markov Chains for Microgrid Design

by Hugo Radet, Bruno Sareni and Xavier Roboam

Energies 2023, 16(23), 7871; https://doi.org/10.3390/en16237871 - 1 Dec 2023

Viewed by 873

Abstract

Uncertainties related to the energy produced and consumed in smart grids, especially in microgrids, are among the major issues for both their design and optimal management. In that context, it is essential to have representative probabilistic scenarios of these environmental uncertainties. The intensive [...] Read more.

Uncertainties related to the energy produced and consumed in smart grids, especially in microgrids, are among the major issues for both their design and optimal management. In that context, it is essential to have representative probabilistic scenarios of these environmental uncertainties. The intensive development and massive installation of smart meters will help to better characterize local energy consumption and production in the following years. However, models representing these variables over large timescales are essential for microgrid design. In this paper, we explore a simple method based on Markov chains capable of generating a large number of probabilistic production or consumption profiles from available historical measurements. We show that the developed approach can capture the main characteristics and statistical variability of real data on both short-term and long-term scales. Moreover, the correlation between both production and demand is conserved in generated profiles with respect to historical measurements. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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Review

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36 pages, 7325 KiB

Open AccessReview

Integrative Review-Based Conceptual Modeling: An Agent-Based Modeling Synthesis of Dynamic Energy Tariff Research and Models

by Simon Johanning, Paul Bruggemans, Oreane Edelenbosch and Thomas Bruckner

Energies 2024, 17(22), 5715; https://doi.org/10.3390/en17225715 - 15 Nov 2024

Viewed by 361

Abstract

Adoption of dynamic energy tariffs by households is crucial for the transition to carbon-neutral energy systems. Influencing the adoption patterns of these tariffs necessitates an examination of the drivers, decision components, and contextual factors influencing household decisions. Few computational models address this comprehensively, [...] Read more.

Adoption of dynamic energy tariffs by households is crucial for the transition to carbon-neutral energy systems. Influencing the adoption patterns of these tariffs necessitates an examination of the drivers, decision components, and contextual factors influencing household decisions. Few computational models address this comprehensively, often omitting non-financial decision variables. Moreover, methodologically robust integrative reviews on this topic are scarce. To address this gap, this paper develops a concept-centered integrative review methodology aimed at deriving computer models for socio-techno-economic simulations of household adoption of sustainable technologies. The methodology encompasses five sequential phases: Setup, Literature Search, Analysis, Synthesis and Conceptual Model, and Discussion. To illustrate the methodology, it is applied to the case of household adoption of dynamic energy tariffs, resulting in an abstract conceptual model adaptable to local contexts. The review reveals a lack of consensus on modeled tariffs but highlights the significance of tariff complexity, relative advantage, household heterogeneity, and various agent properties. It also identifies potential improvements in model fundamentals, particularly spatial modeling. The developed process model focuses on the stages ‘knowledge’, ‘decision’, and ‘reevaluation’. The article contributes by presenting a comprehensive review scheme and delivering a concept-centered integrative review along with an explicit conceptual model derived from it. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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23 pages, 4528 KiB

Open AccessReview

The Impact of Air Renewal with Heat-Recovery Technologies on Energy Consumption for Different Types of Environments in Brazilian Buildings

by York Castillo Santiago, Daiane Busanello, Alexandre F. Santos, Osvaldo J. Venturini and Leandro A. Sphaier

Energies 2024, 17(16), 4065; https://doi.org/10.3390/en17164065 - 16 Aug 2024

Viewed by 781

Abstract

This work evaluates the impact of air renewal on energy consumption for indoor environments. For this purpose, an analysis of the problem of air renewal at a Brazilian level was carried out, as well as research into the energy impact of air renewal [...] Read more.

This work evaluates the impact of air renewal on energy consumption for indoor environments. For this purpose, an analysis of the problem of air renewal at a Brazilian level was carried out, as well as research into the energy impact of air renewal without energy recovery and the different existing technologies for recovering energy from renewed air. On the other hand, the influence of heat-recovery systems was analyzed in three Brazilian cities (Manaus, São Paulo, and Brasília) for different environments, where a classroom in Manaus has an approximately 50% external air factor and a 42% sensible heat factor. However, classrooms in São Paulo and Brasília have a lower external air factor (27% and 8%, respectively) and a higher sensible heat factor (61% and 78%, respectively). Considering a system with heat recovery, the external air factor decreases to 23%, 10%, and 3% for Manaus, São Paulo, and Brasília, respectively. This allows us to understand the influence of heat-recovery systems, which reduce the external air factor and increase the sensible heat factor. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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19 pages, 3812 KiB

Open AccessReview

Saudi Arabia’s Journey toward a Renewable Future

by Saad F. Al-Gahtani

Energies 2024, 17(11), 2444; https://doi.org/10.3390/en17112444 - 21 May 2024

Cited by 1 | Viewed by 3005

Abstract

Recent statistics indicate that as of 2023, the global renewable energy capacity has reached new heights, with Saudi Arabia significantly contributing to this growth through its strategic initiatives. The kingdom is particularly focusing on harnessing solar power, given its abundant sunlight, and is [...] Read more.

Recent statistics indicate that as of 2023, the global renewable energy capacity has reached new heights, with Saudi Arabia significantly contributing to this growth through its strategic initiatives. The kingdom is particularly focusing on harnessing solar power, given its abundant sunlight, and is also exploring wind energy, leveraging its vast desert landscapes. These efforts are part of Saudi Arabia’s broader strategy to become a global leader in renewable energy. This paper provides a detailed exploration of Saudi Arabia’s ambitious journey from a fossil-fuel-dominated energy sector to a more sustainable, renewable-energy-driven future. Anchored in the broader context of global energy trends, the study emphasizes the critical shift toward renewable resources, with a particular focus on Saudi Arabia’s unique position in this global movement. Key to this transition is Saudi Arabia’s Vision 2030, a strategic framework that guides the country’s renewable energy policies and initiatives. A comprehensive review of these policies, including other governmental and international collaborations that support renewable energy development, is offered. The current state of renewable energy in Saudi Arabia is assessed, including an overview of existing projects and production statistics. The paper also explores emerging technologies such as energy storage systems and smart grid solutions, emphasizing their role in Saudi Arabia’s energy transition. An impact assessment is conducted to understand the environmental, economic, and social effects of this energy shift. The paper also includes a comparative analysis of other countries’ renewable energy transitions, extracting lessons and best practices applicable to the Saudi context. Strategic recommendations and reflections on Saudi Arabia’s future role in the global energy landscape are provided for stakeholders in energy policy, environmental planning, and sustainable development. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response)

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