Geospatial multi-criteria analysis for identifying optimum wind and solar sites in Africa: Towards effective power sector decarbonization

Doorga, Jay Rovisham Singh; Hall, Jim W.; Eyre, Nick

doi:10.1016/j.rser.2022.112107

Cited by 27 publications

(9 citation statements)

References 42 publications

(42 reference statements)

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“…This result is consistent with the maps of related study conducted in this country [96]. Meanwhile, our findings are harmonic with the report of a recent study investigating the site suitability for wind and solar plants in the entire African continent [97]. We both stated that the whole continent has moderate to very high suitability for solar plants, whereas the northern countries were the most likely to deploy wind turbines alongside solar PV panels.…”

Section: Discussionsupporting

confidence: 93%

Global Spatial Suitability Mapping of Wind and Solar Systems Using an Explainable AI-Based Approach

Sachit

Shafri

Abdullah

et al. 2022

IJGI

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An assessment of site suitability for wind and solar plants is a strategic step toward ensuring a low-cost, high-performing, and sustainable project. However, these issues are often handled on a local scale using traditional decision-making approaches that involve biased and non-generalizable weightings. This study presents a global wind and solar mapping approach based on eXplainable Artificial Intelligence (XAI). To the best of the author’s knowledge, the current study is the first attempt to create global maps for siting onshore wind and solar power systems and formulate novel weights for decision criteria. A total of 13 conditioning factors (independent variables) defined through a comprehensive literature review and multicollinearity analysis were assessed. Real-world renewable energy experiences (more than 55,000 on-site wind and solar plants worldwide) are exploited to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-layer Perceptron (MLP). Then, the output of ML models was explained using SHapley Additive exPlanations (SHAP). RF outperformed SVM and MLP in both wind and solar modeling with an overall accuracy of 90% and 89%, kappa coefficient of 0.79 and 0.78, and area under the curve of 0.96 and 0.95, respectively. The high and very high suitability categories accounted for 23.2% (~26.84 million km2) of the site suitability map for wind power plants. In addition, they covered more encouraging areas (24.0% and 19.4%, respectively, equivalent to ~50.31 million km2) on the global map for hosting solar energy farms. SHAP interpretations were consistent with the Gini index indicating the dominance of the weights of technical and economic factors over the spatial assessment under consideration. This study provides support to decision-makers toward sustainable power planning worldwide.

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Section: Discussionsupporting

confidence: 93%

Global Spatial Suitability Mapping of Wind and Solar Systems Using an Explainable AI-Based Approach

Sachit

Shafri

Abdullah

et al. 2022

IJGI

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“…To this end, SRK S.A. is considering the possibility of building a number of photovoltaic farms on its sites, which would partially secure the Company's energy needs and to some extent protect the pumping stations from a sudden lack of power from the grid (Prakash, Prasad, 2022; WoszczyDski et al, 2023). The term "blackout" is used to describe a sudden and severe failure of the power system that results in a lack of power from the national grid over a large area (Bazaluk et al, 2021;Doorga et al, 2022). Such an interruption in power supply may last only a few minutes, but usually a blackout is understood as a longer power outage of even several days (Fidalgo-Valverde et al ).…”

Section: Methodsmentioning

confidence: 99%

Untitled

2024

SPSUTOM

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The originality of the conducted research lies in a holistic approach to analysing entrepreneurs' satisfaction, identifying statistical relationships between satisfaction and diverse economic behaviours, and exploring the role of emotions in making business decisions. This collectively provides a new perspective on the behavioral finance of businesses. Literature reviewEmotions play a significant role in the process of making business decisions. Despite the common tendency to focus on data and facts analysis, it is emotions, both conscious and hidden, that influence the shaping of strategies, the selection of business partners, and the willingness to take risks. Entrepreneurs, considering their personal emotions, introduce a subjective element into the decision-making process, which can lead to both successes and failures.The origin of the word "emotion" derives from the Latin verb "motere," meaning "to move".However, to fully understand the meaning of this term, it is worth noting the prefix "e-", suggesting something more than just movement or stirringit may indicate an additional, extended, or surpassing basic activity. This prefix indicates that emotions have a tendency to act or react (Goleman, 1997, p. 27). Emotions are not only associated with experiencing specific mental states but also with a tendency to evoke particular behaviors or reactions. They are deeply embedded within a person and often guide their actions and influence the decisions made.According to D. Goleman, emotions can be defined as a complex blend of feelings and thoughts that are associated with specific psychological states and biological reactions of the organism. These emotional states, along with predispositions to action, constitute an integral part of the human heritage passed down to us by evolution (Goleman, 1997, p. 442). D. Goleman asserts that emotions essentially serve as stimuli shaping an individual's readiness for action. These are rapid life-saving or life-sustaining plans embedded in our psyche by evolutionary history. Emotional reactions triggered by various situations, such as fear, joy, anger, or sadness, not only influence human thoughts and feelings but also activate instincts and prepare individuals to take appropriate actions at the given moment. Therefore, comprehending emotions is crucial for a better understanding of human behaviour and responses in various life situations.Another renowned psychologist, R. Lazarus, proposes a more intricate approach to emotions. He contends that emotions result from an individual's appraisal of a situation, rather than being merely reactions to specific stimuli. According to his theory, emotions are more

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“…The system designed compared to the extension of the grid and diesel systems was also found to have the best energy, economic, and ecological performances. Similar research was conducted by [14] which applied a multicriteria geospatial optimization to identify the best locations on the whole African continent for onshore wind and solar PV. The model could be impacted by several variables, including those related to legal, technological, political, environmental, socioeconomic, and investment risk.…”

Section: Introductionmentioning

confidence: 95%

Optimal design and sizing of a hybrid energy system for water pumping applications

Amusan,

Nwulu,

Gbadamosi

2024

IET Renewable Power Gen

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One of the ways to increase the participation and penetration of renewable energy resources is to bring down the cost of these abundant resources for easy implementation and affordability. In this paper, a generalized reduced gradient (GRG) non‐linear optimization algorithm is implemented to solve a tri‐objective optimal design and sizing of a low‐cost hybrid mix consisting of a photovoltaic (PV) power plant, biomass power plant (BPP), and battery energy system for water pumping load applications in the University of Johannesburg, South Africa considering four different hybrids of biomass‐battery, PV‐battery, PV‐biomass, and PV‐biomass‐battery. The optimization model considers available energy and battery state of charge while minimizing least cost of energy (LCOE), carbon dioxide emission (tCO2eq), and loss of power supply probability (LPSP) including carbon tax incentive and penalty. The results when compared against particle swarm optimization (PSO) show the superiority of GRG over PSO with an optimal combination of PV‐biomass‐battery mix with optimal size of the PV power plant as 360.50 kW, the BPP 181.08 kW, and the battery size of 6,553.60 kWh giving a minimal optimal LCOE, CO2 emission and LPSP of 0.018 $/kWhr (with carbon tax), and 0.016 $/kWhr (without carbon tax), 28,067.73tCO2eq tCO2eq, and 1.7%, respectively. These values give a competitive advantage compared to the unit cost and values of CO2 emission and LPSP currently in the literature.

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Geospatial multi-criteria analysis for identifying optimum wind and solar sites in Africa: Towards effective power sector decarbonization

Cited by 27 publications

References 42 publications

Global Spatial Suitability Mapping of Wind and Solar Systems Using an Explainable AI-Based Approach

Global Spatial Suitability Mapping of Wind and Solar Systems Using an Explainable AI-Based Approach

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Optimal design and sizing of a hybrid energy system for water pumping applications

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