Using spatial elimination and ranking methods in the renewable energy investment parcel search process DOI Creative Commons
Jakub Bobrowski, Grażyna Łaska

Energy, Journal Year: 2023, Volume and Issue: 285, P. 129517 - 129517

Published: Oct. 30, 2023

The study presents a framework for an elimination algorithm aimed at determining potential investment locations photovoltaic farms in three separate counties located northeastern Poland. research focuses on identifying environmental and economic criteria solar farm locations, establishing boundary values, discussing the outcomes of multi-criteria decision support using Boolean method Borda ranking methods. Through amalgamation decision-making model, ten different location variants were derived, ranging from best (Variant 1) to worst 10), out total 1024 variants. results highlight five critical that persisted after algorithm: distance medium voltage lines, roads, parcel shape, average width, slope. analysis revealed analysed have between 150 1336 optimal (depending area) satisfy all specified conditions. This method, which enables swift reproducible identification suitable areas construction, can be applied various European regions.

Language: Английский

Optimizing Electricity Markets Through Game-Theoretical Methods: Strategic and Policy Implications for Power Purchasing and Generation Enterprises DOI Creative Commons
Lefeng Cheng, Pengrong Huang, Mengya Zhang

et al.

Mathematics, Journal Year: 2025, Volume and Issue: 13(3), P. 373 - 373

Published: Jan. 23, 2025

This review proposes a novel integration of game-theoretical methods—specifically Evolutionary Game Theory (EGT), Stackelberg games, and Bayesian games—with deep reinforcement learning (DRL) to optimize electricity markets. Our approach uniquely addresses the dynamic interactions among power purchasing generation enterprises, highlighting both theoretical underpinnings practical applications. We demonstrate how this integrated framework enhances market resilience, informs evidence-based policy-making, supports renewable energy expansion. By explicitly connecting our findings regulatory strategies real-world scenarios, we underscore political implications applicability results in diverse global systems. integrating EGT with advanced methodologies such as DRL, study develops comprehensive that nature markets strategic adaptability participants. hybrid allows for simulation complex capturing nuanced decision-making processes enterprises under varying conditions uncertainty competition. The systematically evaluates effectiveness cost-efficiency various control policies implemented within markets, including pricing mechanisms, capacity incentives, measures aimed at enhancing competition transparency. analysis underscores potential significantly enhance enabling better withstand shocks sudden demand fluctuations, supply disruptions, changes. Moreover, DRL facilitates promotion sustainable by modeling adoption technologies optimizing resource allocation. leads improved overall performance, characterized increased efficiency, reduced costs, greater sustainability. contribute development robust frameworks support competitive efficient an evolving landscape. leveraging adaptive capabilities policymakers can design regulations not only address current challenges but also anticipate adapt future developments. proactive is essential fostering resilient infrastructure capable accommodating rapid advancements shifting consumer demands. Additionally, identifies key areas research, exploration multi-agent techniques need empirical studies validate models simulations discussed. provides roadmap through policy-driven interventions, bridging gap between game-theoretic

Language: Английский

Citations

2
A new fuzzy model of multi-criteria decision support based on Bayesian networks for the urban areas' decarbonization planning DOI Creative Commons
Maria Mrówczyńska, Marta Skiba, Agnieszka Leśniak

et al.

Energy Conversion and Management, Journal Year: 2022, Volume and Issue: 268, P. 116035 - 116035

Published: July 25, 2022

The study introduces a framework for forecasting and decision-making in multi-criteria processes proposes their application the decarbonization of urban areas. Optimizing process is an integrated set information-processing-decision activities which actual data, expert knowledge using fuzzy inference rules, Geographic Information System, Bayesian networks are combined. Using proposed tools leads to designing new approach improving energy efficiency cities reducing CO2 emissions renewable energy. integration modern computational methods rational planning environmentally friendly energy-conscious smart by provisions Fit 55 packages. effectiveness has been demonstrated example three scenarios considering different types sources that can be implemented success probability decarbonizing these areas was calculated defined quarters city Zielona Góra with parameters. Thereby usefulness method confirmed. Significantly, likelihood successful deployment photovoltaics (PV) estimated at 55.25% heat pumps 28.79%. enables clear interpretation results, may basis planning.

Language: Английский

Citations

22
Spatial Modeling of Flood-Vulnerability as Basic Data for Flood Mitigation DOI Open Access
Iin Arianti, Muhammad Rafani, Nurul Fitriani

et al.

Civil Engineering Journal, Journal Year: 2023, Volume and Issue: 9(4), P. 787 - 798

Published: April 1, 2023

Identifying risks in flood-prone areas is necessary to support risk management decisions. This research was conducted establish a vulnerability model of flood hazards the city Pontianak. The based on scoring and weighting biophysical factors. AHP method logical formulations were used model. result showed that accuracy by determine floods 80% Pontianak City. using level 84%. Kappa value 1 76.7%. explains most City has very high vulnerability, which 31,440,568.8 m2 or 29.11% total area 108,003,319.8 m2. vulnerable 29,945,485.7 27.73%, less safe 22,126,936.3 20.49%, with being 24,490,328.7 m2or 22.67% area. contributes government policies regarding urban development future, as an effort mitigate against flooding. Doi: 10.28991/CEJ-2023-09-04-02 Full Text: PDF

Language: Английский

Citations

11
Global policy stocktake of urban climate resilience: A literature review DOI
Hao Han, Xuemei Bai, Liang Dong

et al.

Resources Conservation and Recycling, Journal Year: 2024, Volume and Issue: 212, P. 107923 - 107923

Published: Sept. 21, 2024

Language: Английский

Citations

4
Smart Hotspot Detection Using Geospatial Artificial Intelligence: A Machine Learning Approach to Reduce Flood Risk DOI Creative Commons
Seyed M. H. S. Rezvani,

Alexandre Gonçalves,

Maria João Falcão Silva

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 115, P. 105873 - 105873

Published: Oct. 2, 2024

Language: Английский

Citations

2
High-resolution, open-source modeling of inland flooding impacts on the North Carolina bulk electric power grid DOI Creative Commons
Luis Prieto-Miranda, Jordan Kern

Environmental Research Energy, Journal Year: 2024, Volume and Issue: 1(1), P. 015005 - 015005

Published: March 1, 2024

Abstract Although damages to local distribution systems from wind and fallen trees are typically responsible for the largest fraction of electricity outages during hurricanes, caused by flooding electrical substations pose a unique risk. Electrical key component electric power systems, in some areas, loss single substation can cause widespread outages. Before repairing damaged substations, utilities must first allow floodwaters recede, potentially leaving customers without weeks following storms. As economic losses continue increase U.S., there has been increasing attention paid potential impacts on systems. Yet, this mostly limited geospatial risk assessments that identify what assets path flooding. Here, we present major attempt understand how hurricanes other extreme precipitation events affects dynamic behavior networks, including demand generation, altered flows through transmission lines. We use North Carolina, hit three past seven years, as test case. Using open-source data grid infrastructure, develop high-resolution direct current optimal flow model simulates production generators network consisting 662 nodes 790 then simulate operations historical (2018) storm Hurricane Florence. Time series depth at discrete set ‘high water’ mark points used spatially interpolate across footprint area storms an hourly basis. Outages solar farms due translated location-specific throughout network. perform sensitivity analysis explore function height sensitive equipment substations. Results shed light localized have wider (including areas not affected flooding), with performance tracked terms line flows/congestion, generation outputs, customer

Language: Английский

Citations

1
Power Distribution Systems’ Vulnerability by Regions Caused by Electrical Discharges DOI Creative Commons
Andréia S. Santos, Lucas Teles Faria, Mara Lúcia Martins Lopes

et al.

Energies, Journal Year: 2023, Volume and Issue: 16(23), P. 7790 - 7790

Published: Nov. 27, 2023

Energy supply interruptions or blackouts caused by faults in power distribution feeders entail several damages to utilities and consumer units: financial losses, damage reliability, quality deterioration, etc. Most studies the specialized literature concerning systems present methodologies for detecting, classifying, locating after their occurrence. In contrast, main aim of this study is prevent estimating city regions whose grid most vulnerable them. sense, work incorporates a geographical-space via spatial data analysis using local variable electrical discharge density that can increase fault risks. A geographically weighted applied aggregated produce thematic maps with are more failures. The implemented QGIS R programming environments. It real transformers discharges medium-sized approximately 200,000 inhabitants. study, we highlight moderate positive correlation between percentage central western areas under study.

Language: Английский

Citations

3
Electricity sector resilience in response to extreme weather and climate-related events: Tools and datasets DOI Creative Commons
Hamidreza Ashrafi, Tarannom Parhizkar

The Electricity Journal, Journal Year: 2023, Volume and Issue: 36(6), P. 107290 - 107290

Published: June 27, 2023

The significant increase in both the severity and frequency of climatological catastrophes draws attention to necessity for a more climate-resilient electricity sector. In recent years, several databases platforms have been developed assess resilience sector response extreme weather climate-related events. This study conducts comprehensive review used assessing climate It discusses existing gaps challenges these datasets proposes future path.

Language: Английский

Citations

2
Risk and Resiliency Assessments of Renewable Dominated Edge of Grid Under High-Impact Low-Probability Events -A Review DOI
Tossaporn Surinkaew, Rakibuzzaman Shah, Syed Islam

et al.

2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT), Journal Year: 2022, Volume and Issue: 320, P. 1 - 6

Published: Sept. 23, 2022

Low-probability high-impact (HILP) events such as windstorms, earthquakes, wildfires, and floods, which can cause significant damages to power systems, are inevitable unpredictable. Besides, uncertainties from distributed renewable energy resources may prevent conventional techniques improve reliability of grids. In previous research works, several strategies have been introduced investigate risk resiliency, find effective solutions system under extreme events. this paper, a critical review these is presented. Modelings the HILP dis-cussed. conclusion, paper pinpoints findings give directions for robustly protecting systems.

Language: Английский

Citations

3
Using spatial elimination and ranking methods in the renewable energy investment parcel search process DOI Creative Commons
Jakub Bobrowski, Grażyna Łaska

Energy, Journal Year: 2023, Volume and Issue: 285, P. 129517 - 129517

Published: Oct. 30, 2023

The study presents a framework for an elimination algorithm aimed at determining potential investment locations photovoltaic farms in three separate counties located northeastern Poland. research focuses on identifying environmental and economic criteria solar farm locations, establishing boundary values, discussing the outcomes of multi-criteria decision support using Boolean method Borda ranking methods. Through amalgamation decision-making model, ten different location variants were derived, ranging from best (Variant 1) to worst 10), out total 1024 variants. results highlight five critical that persisted after algorithm: distance medium voltage lines, roads, parcel shape, average width, slope. analysis revealed analysed have between 150 1336 optimal (depending area) satisfy all specified conditions. This method, which enables swift reproducible identification suitable areas construction, can be applied various European regions.

Language: Английский

Citations

1