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24 pages, 7472 KiB

Open AccessFeature PaperArticle

Reducing CO₂ Emissions for PV-CHP Hybrid Systems by Using a Hierarchical Control Algorithm

by Tanja M. Kneiske

Energies 2023, 16(17), 6176; https://doi.org/10.3390/en16176176 - 25 Aug 2023

Cited by 1 | Viewed by 1262

Abstract

National targets for CO

_{2}

reduction in the German building sector have stagnated due to low refurbishment rates. This paper proposes an alternative approach using highly efficient, decentralized energy systems. By combining photovoltaic (PV) systems and combined heat and power (CHP) plants controlled [...] Read more.

National targets for CO

_{2}

reduction in the German building sector have stagnated due to low refurbishment rates. This paper proposes an alternative approach using highly efficient, decentralized energy systems. By combining photovoltaic (PV) systems and combined heat and power (CHP) plants controlled by a modified hierarchical control algorithm, CO

_{2}

emissions can be reduced. Results from a single-family home show a 13% CO

_{2}

reduction with only 11% higher operational costs on heating days. On summer days, up to 50% CO

_{2}

emissions can be avoided without additional costs. The control algorithm easily adapts to changing input parameters, making it suitable for different countries and business cases. Overall, with its modified control, the PV-CHP hybrid system can effectively reduce CO

_{2}

emissions and adapt to varying conditions. The control can be easily used for other energy systems, like fuel cells or heat pumps. Full article

(This article belongs to the Special Issue Renewable Energy Planning and Energy Management Systems)

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18 pages, 3841 KiB

Open AccessArticle

Comparative Analysis of Eight Numerical Methods Using Weibull Distribution to Estimate Wind Power Density for Coastal Areas in Pakistan

by Iqrar Hussain, Aun Haider, Zahid Ullah, Mario Russo, Giovanni Mercurio Casolino and Babar Azeem

Energies 2023, 16(3), 1515; https://doi.org/10.3390/en16031515 - 3 Feb 2023

Cited by 8 | Viewed by 1913

Abstract

Currently, Pakistan is facing severe energy crises and global warming effects. Hence, there is an urgent need to utilize renewable energy generation. In this context, Pakistan possesses massive wind energy potential across the coastal areas. This paper investigates and numerically analyzes coastal areas’ [...] Read more.

Currently, Pakistan is facing severe energy crises and global warming effects. Hence, there is an urgent need to utilize renewable energy generation. In this context, Pakistan possesses massive wind energy potential across the coastal areas. This paper investigates and numerically analyzes coastal areas’ wind power density potential. Eight different state-of-the-art numerical methods, namely an (a) empirical method, (b) graphical method, (c) wasp algorithm, (d) energy pattern method, (e) moment method, (f) maximum likelihood method, (g) energy trend method, and (h) least-squares regression method, were analyzed to calculate Weibull parameters. We computed Weibull shape parameters (WSP) and Weibull scale parameters (WCP) for four regions: Jiwani, Gwadar, Pasni, and Ormara in Pakistan. These Weibull parameters from the above-mentioned numerical methods were analyzed and compared to find an optimal numerical method for the coastal areas of Pakistan. Further, the following statistical indicators were used to compare the efficiency of the above numerical methods: (i) analysis of variance (

R^{2}

), (ii) chi-square (

X^{2}

), and (iii) root mean square error (RMSE). The performance validation showed that the energy trend and graphical method provided weak performance for the observed period for four coastal regions of Pakistan. Further, we observed that Ormara is the best and Jiwani is the worst area for wind power generation using comparative analyses for actual and estimated data of wind power density from four regions of Pakistan. Full article

(This article belongs to the Special Issue Renewable Energy Planning and Energy Management Systems)

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21 pages, 1172 KiB

Open AccessArticle

Heuristic Retailer’s Day-Ahead Pricing Based on Online-Learning of Prosumer’s Optimal Energy Management Model

by Mohammad Hossein Nejati Amiri, Mehdi Mehdinejad, Amin Mohammadpour Shotorbani and Heidarali Shayanfar

Energies 2023, 16(3), 1182; https://doi.org/10.3390/en16031182 - 20 Jan 2023

Cited by 1 | Viewed by 1256

Abstract

Smart grids have introduced several key concepts, including demand response, prosumers—active consumers capable of producing, consuming, and storing both electrical and thermal energies—retail market, and local energy markets. Preserving data privacy in this emerging environment has raised concerns and challenges. The use of [...] Read more.

Smart grids have introduced several key concepts, including demand response, prosumers—active consumers capable of producing, consuming, and storing both electrical and thermal energies—retail market, and local energy markets. Preserving data privacy in this emerging environment has raised concerns and challenges. The use of novel methods such as online learning is recommended to address these challenges through prediction of the behavior of market stakeholders. In particular, the challenge of predicting prosumers’ behavior in an interaction with retailers requires creating a dynamic environment for retailers to set their optimal pricing. An innovative model of retailer–prosumer interactions in a day-ahead market is presented in this paper. By forecasting the behavior of prosumers by using an online learning method, the retailer implements an optimal pricing scheme to maximize profits. Prosumers, however, seek to reduce energy costs to the greatest extent possible. It is possible for prosumers to participate in a price-based demand response program voluntarily and without the retailer’s interference, ensuring their privacy. A heuristic distributed approach is applied to solve the proposed problem in a fully distributed framework with minimum information exchange between retailers and prosumers. The case studies demonstrate that the proposed model effectively fulfills its objectives for both retailer and prosumer sides by adopting the distributed approach. Full article

(This article belongs to the Special Issue Renewable Energy Planning and Energy Management Systems)

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32 pages, 515 KiB

Open AccessArticle

A Method for Reducing the Instability of Negawatts Considering Changes in the Behavior of Consumers

by Koichi Takai, Yuto Tamura and Norihiko Shinomiya

Energies 2023, 16(3), 1072; https://doi.org/10.3390/en16031072 - 18 Jan 2023

Viewed by 2553

Abstract

Negawatt trading is expected to improve energy efficiency via the prediction of peak demands and power-saving requests. However, the amount of power saved by consumers is not stable. The accurate prediction of demands and making appropriate requests with respect to power saving are [...] Read more.

Negawatt trading is expected to improve energy efficiency via the prediction of peak demands and power-saving requests. However, the amount of power saved by consumers is not stable. The accurate prediction of demands and making appropriate requests with respect to power saving are difficult obstacles that need to be overcome in order to attain useful negawatt trading processes. To increase the accuracy of predictions and requests, earlier research suggests some methods or linear problems. On the other hand, the investigation of factors that affect consumption is important for correcting the current instability. In this research study, weather changes including temperature, time passing, and the consciousness of consumers are considered as important factors against electricity demands. In this paper, we propose a behavioral model of consumers using weather data. By using this behavioral model, the effectiveness of the suggested methods in earlier research for improving negawatt trading and the uncertainty of negawatts caused by weather changes is investigated. Full article

(This article belongs to the Special Issue Renewable Energy Planning and Energy Management Systems)

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18 pages, 3201 KiB

Open AccessArticle

Barriers to the Expansion of Sugarcane Bioelectricity in Brazilian Energy Transition

by Munir Younes Soares, Dorel Soares Ramos, Margareth de Oliveira Pavan and Fabio A. Diuana

Energies 2023, 16(2), 955; https://doi.org/10.3390/en16020955 - 14 Jan 2023

Viewed by 1243

Abstract

This article evaluated bioelectricity’s evolving competitiveness and systemic complementarity benefits, both in comparison with other renewable sources. To do so, the results of several energy auctions were analysed, and a modelling exercise was developed using an optimisation model based on stochastic dual dynamic [...] Read more.

This article evaluated bioelectricity’s evolving competitiveness and systemic complementarity benefits, both in comparison with other renewable sources. To do so, the results of several energy auctions were analysed, and a modelling exercise was developed using an optimisation model based on stochastic dual dynamic programming. The results indicate that wind and solar energies became the least cost expansions, and sugarcane bioelectricity lost significance and competitiveness in this environment. At the same time, the study shows that wind power’s potential to be complementary to hydropower generation is greater than bioenergy in Brazil. These findings have relevant policy implications regarding the power sector and whether bioelectricity from sugarcane should still be incentivised along with wind power sources. It is worthwhile to point out that although the Brazilian case is explored in the article, it can be used as an example by other countries, especially developing ones, that can take advantage of Brazilian expertise on biomass exploitation aiming at integration with the power sector. Full article

(This article belongs to the Special Issue Renewable Energy Planning and Energy Management Systems)

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16 pages, 7515 KiB

Open AccessArticle

Framework of Transactive Energy Market Strategies for Lucrative Peer-to-Peer Energy Transactions

by Arun S. Loganathan, Vijayapriya Ramachandran, Angalaeswari Sendraya Perumal, Seshathiri Dhanasekaran, Natrayan Lakshmaiya and Prabhu Paramasivam

Energies 2023, 16(1), 6; https://doi.org/10.3390/en16010006 - 20 Dec 2022

Cited by 9 | Viewed by 1664

Abstract

Leading to the enhancement of smart grid implementation, the peer-to-peer (P2P) energy transaction concept has grown dramatically in recent years allowing the end-users to successfully exchange their excess generation and demand in a more profitable way. This paper presents local energy market (LEM) [...] Read more.

Leading to the enhancement of smart grid implementation, the peer-to-peer (P2P) energy transaction concept has grown dramatically in recent years allowing the end-users to successfully exchange their excess generation and demand in a more profitable way. This paper presents local energy market (LEM) architecture with various market strategies for P2P energy trading among a set of end-users (consumers and prosumers) in a smart residential locality. In a P2P fashion, prosumers/consumers can export/import the available generation/demand in the LEM at a profit relative to utility prices. A common portal known as the transactive energy market operator (TEMO) is introduced to manage the trading in the LEM. The goal of the TEMO is to develop a transaction agreement among P2P players by establishing a price for each transaction based on the price and trading demand provided by the participants. A few case studies on a location with ten residential P2P participants validate the performance of the proposed TEMO. Full article

(This article belongs to the Special Issue Renewable Energy Planning and Energy Management Systems)

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24 pages, 7803 KiB

Open AccessArticle

Teaching Power-Sector Models Social and Political Awareness

by Anna Garcia-Teruel, Yvonne Scholz, Wolfgang Weimer-Jehle, Sigrid Prehofer, Karl-Kiên Cao and Frieder Borggrefe

Energies 2022, 15(9), 3275; https://doi.org/10.3390/en15093275 - 29 Apr 2022

Cited by 2 | Viewed by 1521

Abstract

Energy-system scenarios are widely used to relate the developments of the energy supply and the resulting carbon-emission pathways to political measures. To enable scenario analyses that adequately capture the variability of renewable-energy resources, a specialised type of power-sector model (PSM) has been developed [...] Read more.

Energy-system scenarios are widely used to relate the developments of the energy supply and the resulting carbon-emission pathways to political measures. To enable scenario analyses that adequately capture the variability of renewable-energy resources, a specialised type of power-sector model (PSM) has been developed since the beginning of this century, which uses input data with hourly resolution at the national or subnational levels. These models focus on techno-economic-system optimisation, which needs to be complemented with expert socioeconomic knowledge in order to prevent solutions that may be socially inacceptable or that oppose political goals. A way to integrate such knowledge into energy-system analysis is to use information from framework scenarios with a suitable geographical and technological focus. We propose a novel methodology to link framework scenarios to a PSM by applying complexity-management methods that enable a flexible choice of base scenarios that are tailored to suit different research questions. We explain the methodology, and we illustrate it in a case study that analyses the influence of the socioeconomic development on the European power-system transition until 2050 by linking the power-sector model, REMix (renewable-energy mix), to regional framework scenarios. The suggested approach proves suitable for this purpose, and it enables a clearer link between the impact of political measures and the power-system development. Full article

(This article belongs to the Special Issue Renewable Energy Planning and Energy Management Systems)

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Review

Jump to: Research

24 pages, 2963 KiB

Open AccessReview

A Review on Modeling Variable Renewable Energy: Complementarity and Spatial–Temporal Dependence

by Anderson Mitterhofer Iung, Fernando Luiz Cyrino Oliveira and André Luís Marques Marcato

Energies 2023, 16(3), 1013; https://doi.org/10.3390/en16031013 - 17 Jan 2023

Cited by 4 | Viewed by 2314

Abstract

The generation from renewable sources has increased significantly worldwide, mainly driven by the need to reduce the global emissions of greenhouse gases, decelerate climate changes, and meet the environmental, social, and governance agenda (ESG). The main characteristics of variable renewable energy (VRE) are [...] Read more.

The generation from renewable sources has increased significantly worldwide, mainly driven by the need to reduce the global emissions of greenhouse gases, decelerate climate changes, and meet the environmental, social, and governance agenda (ESG). The main characteristics of variable renewable energy (VRE) are the stochastic nature, its seasonal aspects, spatial and time correlations, and the high variability in a short period, increasing the complexity of modeling, planning, operating, and the commercial aspects of the power systems. The research on the complementarity and dependence aspects of VREs is gaining importance, given the development of hybrid generation systems and an array of VREs generators spread over a large region, which could be compounded by different renewable sources, such as hydro, solar, and wind. This review is based on a systematic literature review, providing a comprehensive overview of studies that investigated applied methodologies and methods to address dependence and complementarity. It is a recent field of interest, as 60% of the articles were published in the last five years, a set of methods that have been employed to address this issue, from conventional statistics methods to artificial intelligence. The copulas technique appears as an important approach to modeling renewable energy interdependence. There is a gap in articles comparing the accuracy of the methods employed and the computational efforts. Full article

(This article belongs to the Special Issue Renewable Energy Planning and Energy Management Systems)

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