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Energy and Environment Research
Number of Followers: 13  Open Access journalISSN (Print) 1927-0569 - ISSN (Online) 1927-0577 Published by CCSE  [43 journals]
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- Reviewer Acknowledgements for Energy and Environment Research, Vol. 12,
No. 1
Abstract: Reviewer Acknowledgements for Energy and Environment Research, Vol. 12, No. 1
PubDate: Wed, 01 Jun 2022 02:55:09 +000
- Problems of Invasive Species of Water Hyacinth (Eichhornia Crassipes
[Mart.] Solms) in Cameroon with Special Reference to Its Eradication and
Valorization: A Bibliographical Review
Abstract: Originally from South America, the water hyacinth (Eichhornia crassipes [Mart.] Solms) has been introduced in several parts of the world as an ornamental plant and particularly in Cameroon. However, this plant later became one of the most dangerous freshwater aquatic plant species. For this, it has been the subject of a global reflection because due to its rapid spread and its rapid development, it is at the origin of the difficulties encountered in the sector of river or maritime navigation, irrigation and life in an aquatic environment. In Cameroon, we observe a lot of damage to the environment and local economy caused by water hyacinth pollution of lakes and rivers. However, its infestation can be controlled by physical, chemical and biological methods of control which prove to be better adapted to a sustainable management of the hyacinth. Alongside these methods, there is an urgent need to reflect on its promotion, including its popularization, which will offer the populations of the areas concerned opportunities and impetus towards a change in pro-environmental behavior in the management of national heritage. This research work examines current research activities on the subject, based on the scientific and technological relevance of Eichhornia crassipes in the light of existing knowledge. In a specific way, this paper will focus on the systematic and the morphological description of the water hyacinth, the dispersion and the problems created by its presence, the means of control and valorization of the water hyacinth.
PubDate: Tue, 31 May 2022 06:31:00 +000
- Long Term Electricity Load Forecast Based on Machine Learning for
Cameroon’s Power System
Abstract: A reliable power supply has long been identified as an important economic growth parameter. Electricity load forecasts predict the future behavior of the electricity load. Carrying out a forecast is important for real-time dispatching of power, grid maintenance scheduling, grid expansion planning, and generation planning depending on the forecasting horizon. Most of the methods used in long-term load forecasting are regressions and are limited to predicting peak loads of a yearly or monthly resolution with low accuracy. In this paper, we propose a method based on long short-term memory-recurrent neural networks (LSTM-RNN) cells with relations between identified influential econometric load-driving parameters which includes: the Gross Domestic Product (GDP), Population (H), and past Electric Load Data. To the best of our knowledge, the use of the GDP and H as two additional independent variables in load forecast modelling using machine learning techniques is a novelty in Cameroon. A comparison was performed between a linear regression (LR)-based long-term load forecast model (a model currently used by the Transmission System Operator of Cameroon) and LSTM-RNNs model constructed. The results generated were evaluated using a Mean Absolute Percentage Error (MAPE) within the same period of evaluation, and the overall value of the MAPE obtained for LSTM-RNNs model was 5.4962 whereas that for the LR model was 7.5422. Based on these results, the LSTM-RNN model is considered highly accurate and competent. The model was used to generate a forecast for the period of 2022–2026 with an hourly resolution. A MAPE of 5.4962 was obtained with a computational time of approximately ten minutes, making the model vital for offline use by utilities due to its capacity to quantitatively and accurately predict long-term load with an hourly resolution.
PubDate: Mon, 30 May 2022 03:25:15 +000
- A Novel Integrated Design for Heat and Water Recovery from Exhaust Flue
Gas of Bandar Abbas Power Plant
Abstract: This study concerns a theoretical design of a condensing heat exchanger for a 320 MW unit of Bandar Abbas thermal power plant in the south of Iran. A film theory in conjunction with heat and mass transfer analogy is used as the theoretical basis of the design. The condensing unit is used for heat and mass recovery from the natural gas-fired boiler flue gases. The assumed condensing unit includes 4 equal capacity condensing heat exchangers, each of which is supposed to reduce the flue gas temperature from 160 ℃
to 53℃. Decreasing the flue gas temperature to below the dew point temperature of its water vapor causes condensation (latent) and sensible heat transfer. The analysis was done for 13%, 15%, and 17% of the water vapor volume fraction in the flue gases, and based on the 17% water vapor fraction, 52.8 tons/hr of water was recovered. This recovered water could be used as the cooling tower makeup, and accordingly, almost 14% of water consumption is saved. The recovered heat by the condensing unit is also being used as the heat source of an ORC cycle, and up to 2.8 MW power is estimated to be generated depending on the evaporation temperature.
PubDate: Mon, 30 May 2022 02:32:03 +000
- Dynamic Economic Analysis between Renewable Energy, Carbon Dioxide
Emissions, Trade and GDP based on VECM Granger test and Wavelet Analysis
Abstract: In this study, we explored the dynamic economic relationship between Taiwan’s GDP growth, renewable energy consumption, foreign trade openness, and CO2 emissions from 1965 to 2016. Our analysis is based on using updated data to test the existence of Taiwan's EKC model and discuss the causal relationship between CO2 emissions and variables such as GDP growth, renewable energy consumption, and foreign trade opening. We used multicollinearity analysis to test the stationarity of the quadratic form of the EKC model, ADF and KPSS techniques, and Johansen and Juselius cointegration tests and found that there is a long-term equilibrium. By using VECM Granger causality test and wavelet coherence analysis, we further explored the causal relationship between CO2 emissions and other related variables, and found that there is a two-way causal relationship between carbon dioxide emissions and renewable energy consumption in the short term. In addition, from the wavelet correlation analysis of GDP growth and CO2 emissions, it can be seen that 1992 was a turning point in Taiwan’s economic development.
PubDate: Tue, 29 Mar 2022 01:54:26 +000
- Integrated Carbon Policy Design for Achieving Net-Zero Targets
Abstract: Several countries have set net-zero targets, and many more will announce in the next few years. Countries have used carbon pricing as an instrument to cut Greenhouse Gas (GHG) emissions and provide a price signal to attract private investments to achieve net-zero targets. However, current carbon policy in countries with net-zero targets remains inadequate and asymmetrical to overcome net-zero challenges; there are visible gaps in the carbon price level, sectoral coverage, and mechanism to reward carbon-neutral initiatives. This paper proposed an integrated carbon policy design covering economic, technical, and social dimensions and discussed how an integrated policy design approach could be effective in helping countries achieve net-zero objectives. The paper makes recommendations for net-zero policymakers. First, a stable and appropriate carbon price must be in place to attract private investments in carbon offset measures and commercialize clean technologies. Second, governments should use an effective revenue recycling mechanism to engage firms and citizens in mitigating the side effects of the carbon price regime and win their trust. Third, countries should promote behavioral changes and carbon footprint reduction measures through citizen participation.
PubDate: Tue, 29 Mar 2022 01:51:09 +000
