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Amos Oppong
School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China

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Journal article
Published: 01 June 2021 in Sustainability
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The determinants of providing affordable electricity for all in top energy-consuming African countries vary and are in line with the percentage of the current population with access to electricity and volatility in a country’s electric power system, but there is rare evidence of such research. This study categorizes Egypt–Algeria as a panel of countries with 100% access to electricity, and Nigeria–South Africa as otherwise, to investigate the causal relationship between domestic electricity demand, renewable electricity generation, population, and GDP. The study proposed and implemented a novel machine learning model for viable and volatility-driven pathways for renewable electric power transition up to 2030. Results from Pedroni cointegration analysis suggest no evidence of long-run relationships among the variables. Nonetheless, there exists a short-run unidirectional causal relationship from GDP to electricity consumption for Nigeria–South Africa; all except Egypt can achieve 100% access to green electricity. The implication is that, through radical renewable electricity generation innovations, countries can achieve renewable-dominated electric power systems despite expected disruptions from the coronavirus pandemic. For sustainable energy planning, countries aiming to achieve 100% renewables is possible due to the radical transition pathways since it takes into account the volatility.

ACS Style

Mark Agyei-Sakyi; Yunfei Shao; Oppong Amos; Armah Marymargaret. Determinants of Electricity Consumption and Volatility-Driven Innovative Roadmaps to One Hundred Percent Renewables for Top Consuming Nations in Africa. Sustainability 2021, 13, 6239 .

AMA Style

Mark Agyei-Sakyi, Yunfei Shao, Oppong Amos, Armah Marymargaret. Determinants of Electricity Consumption and Volatility-Driven Innovative Roadmaps to One Hundred Percent Renewables for Top Consuming Nations in Africa. Sustainability. 2021; 13 (11):6239.

Chicago/Turabian Style

Mark Agyei-Sakyi; Yunfei Shao; Oppong Amos; Armah Marymargaret. 2021. "Determinants of Electricity Consumption and Volatility-Driven Innovative Roadmaps to One Hundred Percent Renewables for Top Consuming Nations in Africa." Sustainability 13, no. 11: 6239.

Journal article
Published: 25 March 2021 in Journal of Cleaner Production
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The need to transform electric power systems to a cleaner electricity mix to help save the climate is undisputable but existing transition pathways have become unreliable due to inadequate representation of both demand and supply-side determinants of electric power supply, as well as failure to inculcate volatility in electric power systems in the core transition modelling. This study inculcates demand and supply-side determinants to investigate the long- and short-run causal relationships between the electric power system, macroeconomic performance, demography, environmental quality, and capital formation, for Sweden. We also propose and implement econometric and two-stage attention-based machine learning models for volatility-consistent electric power forecasting. Using annual data spanning 1990-2018, the results suggest a long-run relationship exists between electricity generation and the independent variables. Empirical results for the volatility-consistent attention-based machine learning model predict that Sweden’s electric power demand in 2050 could reach ∼112TWh if conservation practices are implemented, and ∼146TWh if otherwise. If conservation practices are implemented, evidence from selected volatility-consistent simulations show that Sweden can provide 100% of all her electricity demand from cleaner sources by 2030. The findings depict that Sweden must implement stringent and radical policies to achieve its mid-century green electricity targets.

ACS Style

Jie Ma; Amos Oppong; Godfred K.B. Adjei; Henrietta Adjei; Emmanuel Atta-Osei; Mark Agyei-Sakyi; David Adu-Poku. Demand and supply-side determinants of electric power consumption and representative roadmaps to 100% renewable systems. Journal of Cleaner Production 2021, 299, 126832 .

AMA Style

Jie Ma, Amos Oppong, Godfred K.B. Adjei, Henrietta Adjei, Emmanuel Atta-Osei, Mark Agyei-Sakyi, David Adu-Poku. Demand and supply-side determinants of electric power consumption and representative roadmaps to 100% renewable systems. Journal of Cleaner Production. 2021; 299 ():126832.

Chicago/Turabian Style

Jie Ma; Amos Oppong; Godfred K.B. Adjei; Henrietta Adjei; Emmanuel Atta-Osei; Mark Agyei-Sakyi; David Adu-Poku. 2021. "Demand and supply-side determinants of electric power consumption and representative roadmaps to 100% renewable systems." Journal of Cleaner Production 299, no. : 126832.

Journal article
Published: 28 July 2020 in Journal of Cleaner Production
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A boom in renewable energy consumption as a percentage of final energy consumption (REC) has a significant impact on cleaner production and environmental sustainability. However, studies on REC as for an individual country-case and panel case approach for top emitters are rare. Against this backdrop, this study investigates the long-run drivers of REC by using a time series data from 1990 to 2015. The FMOLS-grouped results indicate that economic growth and trade openness increase REC whereas population growth has a negative but significant impact on REC. To check for causal links, the innovating accounting approach using variance decomposition analysis is applied. The results show that there is a unidirectional causality running from economic growth, trade openness, and population growth to REC. Further, the predictive accuracy of the FMOLS based econometric output and the bi-directional long short-term memory (Bi-LSTM) is analyzed. The Bi-LSTM formulated algorithm outperformed the econometric output. The Bi-LSTM is utilized to forecast REC to the year 2030. The output from the Bi-LSTM shows that China, the US, India, the Russian Federation’s, and Japan’s REC will hit ∼11.3395, ∼11.1245, ∼34.6969, ∼2.9097, and ∼7.4859, respectively. The US and Japan’s REC levels will increase while that of China, India, and Russia Federation will decrease. As a policy implication, new policy directives for China, India, and the Russian Federation are required to boost REC levels.

ACS Style

Joy Korang Agyeman; Bismark Ameyaw; Yao Li; Jamal Appiah-Kubi; Augustine Annan; Amos Oppong; Martinson Ankrah Twumasi. Modeling the long-run drivers of total renewable energy consumption: Evidence from top five heavily polluted countries. Journal of Cleaner Production 2020, 277, 123292 .

AMA Style

Joy Korang Agyeman, Bismark Ameyaw, Yao Li, Jamal Appiah-Kubi, Augustine Annan, Amos Oppong, Martinson Ankrah Twumasi. Modeling the long-run drivers of total renewable energy consumption: Evidence from top five heavily polluted countries. Journal of Cleaner Production. 2020; 277 ():123292.

Chicago/Turabian Style

Joy Korang Agyeman; Bismark Ameyaw; Yao Li; Jamal Appiah-Kubi; Augustine Annan; Amos Oppong; Martinson Ankrah Twumasi. 2020. "Modeling the long-run drivers of total renewable energy consumption: Evidence from top five heavily polluted countries." Journal of Cleaner Production 277, no. : 123292.

Journal article
Published: 02 January 2020 in Journal of Cleaner Production
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The disparities in development levels of countries in Africa necessitate correspondingly sensitive categorization approaches because effective renewable energy-related (RER) decisions, policy-making, and subsequent implementation hinges on workable categorization indices. However, studies on sensitive categorization approaches for energy-environment-economy (3E) interdependencies for Africa is rare. This study uses a sensitive characteristic-driven approach to explore the interdependencies in 3E indicators for carbon dioxide (CO2) emissions, renewable energy consumption (REC), fossil fuel energy consumption, gross domestic product (GDP), population, and gross fixed capital formation in 39 African countries. Further, we forecast the dollar values of policy innovations necessary to facilitate the transition to 100% renewable energies for 2030. Using balanced data spanning 2000–2014, the empirical results from the panel vector error-correction model show long-run Granger causality in CO2 emissions, REC and GDP models for Africa, but no evidence of such relationship was found four sub-panels. The results depict varied individual unidirectional and bidirectional causalities among the variables in each panel. Evidence from variance decomposition analysis show that ∼93% of innovations required to achieve renewable energy-led Africa must happen in REC. Results from the high precision own-data-driven forecast puts total energy demand in Africa at ∼25QBtu in 2030 with ∼40% from renewables. Estimates of the dollar value of innovations depict that it would cost Africa ∼ US$3367.2 billion [in 2030 only] to transition to 100% renewables. We find RER investment (RERIs), in billion US$, ranging from 2.69 to 1274.12 for seven sub-panels. Yet, the panel of Moderate Lower Middle-Income Economies need not to make further investments because their existing REIRs could be enough to help the region reach 100% renewables by 2030. The findings herein imply that RER policies in Africa must be intensified to achieve 100% renewable energy target.

ACS Style

Amos Oppong; Ma Jie; Kingsley N. Acheampong; Mark A. Sakyi. Variations in the environment, energy and macroeconomic interdependencies and related renewable energy transition policies based on sensitive categorization of countries in Africa. Journal of Cleaner Production 2020, 255, 119777 .

AMA Style

Amos Oppong, Ma Jie, Kingsley N. Acheampong, Mark A. Sakyi. Variations in the environment, energy and macroeconomic interdependencies and related renewable energy transition policies based on sensitive categorization of countries in Africa. Journal of Cleaner Production. 2020; 255 ():119777.

Chicago/Turabian Style

Amos Oppong; Ma Jie; Kingsley N. Acheampong; Mark A. Sakyi. 2020. "Variations in the environment, energy and macroeconomic interdependencies and related renewable energy transition policies based on sensitive categorization of countries in Africa." Journal of Cleaner Production 255, no. : 119777.

Journal article
Published: 02 April 2019 in Energy Policy
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In this study, we investigate the direction of causal relationship between carbon dioxide (CO2) emissions from fossil fuel combustion only (CO2EFFCO) and economic growth for the USA, China, Canada, and Nigeria by using annual time series data for the period 1990–2016. The results depict a unidirectional causality running from gross domestic product per capita to CO2EFFCO for the USA, China, and Canada. However, no causality direction was found for Nigeria. Furthermore, with the quest to achieve cleaner energy targets, we formulate long short-term memory (LSTM) algorithm devoid of exogenous variables and assumptions required to forecast CO2EFFCO for the USA, China, Canada, and Nigeria. Based on the performance of our algorithm, we propose emission-mitigation pathways for the countries herein to follow to achieve zero CO2EFFCO by the year 2030. The emission-mitigation pathways demonstrate that intensifying and promoting current and future policies that mitigate CO2EFFCO based on our projections are enough to reduce energy-related CO2EFFCO to a considerable level.

ACS Style

Bismark Ameyaw; Li Yao; Amos Oppong; Joy Korang Agyeman. Investigating, forecasting and proposing emission mitigation pathways for CO2 emissions from fossil fuel combustion only: A case study of selected countries. Energy Policy 2019, 130, 7 -21.

AMA Style

Bismark Ameyaw, Li Yao, Amos Oppong, Joy Korang Agyeman. Investigating, forecasting and proposing emission mitigation pathways for CO2 emissions from fossil fuel combustion only: A case study of selected countries. Energy Policy. 2019; 130 ():7-21.

Chicago/Turabian Style

Bismark Ameyaw; Li Yao; Amos Oppong; Joy Korang Agyeman. 2019. "Investigating, forecasting and proposing emission mitigation pathways for CO2 emissions from fossil fuel combustion only: A case study of selected countries." Energy Policy 130, no. : 7-21.

Journal article
Published: 25 February 2018 in Sustainability
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Renewable energy, as an environmentally friendly and sustainable source of energy, is key to realizing the nationally determined contributions of the United States (US) to the December 2015 Paris agreement. Policymakers in the US rely on energy forecasts to draft and implement cost-minimizing, efficient and realistic renewable and sustainable energy policies but the inaccuracies in past projections are considerably high. The inaccuracies and inconsistencies in forecasts are due to the numerous factors considered, massive assumptions and modeling flaws in the underlying model. Here, we propose and apply a machine learning forecasting algorithm devoid of massive independent variables and assumptions to model and forecast renewable energy consumption (REC) in the US. We employ the forecasting technique to make projections on REC from biomass (REC-BMs) and hydroelectric (HE-EC) sources for the 2009–2016 period. We find that, relative to reference case projections in Energy Information Administration’s Annual Energy Outlook 2008, projections based on our proposed technique present an enormous improvement up to ~138.26-fold on REC-BMs and ~24.67-fold on HE-EC; and that applying our technique saves the US ~2692.62PJ petajoules(PJ) on HE-EC and ~9695.09PJ on REC-BMs for the 8-year forecast period. The achieved high-accuracy is also replicable to other regions.

ACS Style

Jie Ma; Amos Oppong; Kingsley Nketia Acheampong; Lucille Aba Abruquah. Forecasting Renewable Energy Consumption under Zero Assumptions. Sustainability 2018, 10, 576 .

AMA Style

Jie Ma, Amos Oppong, Kingsley Nketia Acheampong, Lucille Aba Abruquah. Forecasting Renewable Energy Consumption under Zero Assumptions. Sustainability. 2018; 10 (3):576.

Chicago/Turabian Style

Jie Ma; Amos Oppong; Kingsley Nketia Acheampong; Lucille Aba Abruquah. 2018. "Forecasting Renewable Energy Consumption under Zero Assumptions." Sustainability 10, no. 3: 576.