An analytical study to predict the future of Pakistan’s energy sustainability versus rest of South Asia

Rasheed, Rizwan; Rizwan, Asfra; Javed, Hajra; Yasar, Abdullah; Tabinda, Amtul Bari; Bhatti, Sumera Gull; Su, Yuehong

doi:10.1016/j.seta.2020.100707

Cited by 16 publications

(8 citation statements)

References 87 publications

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“…Many researchers have scrutinized the energy system situation of South Asian countries, mainly competitive assessment of the wind power industry [28], status and potential of hydroelectric power generation, and the evaluation of mitigation measures for ecological conservation [29]. Other researchers have reviewed economic rise and poverty mitigation by adopting clean energy in South Asia, challenges, and barriers related to sustainable development in the region [30]. The conceptual framework built is related to the environmental sustainability of South Asian countries using a weighted Data Envelopment Analysis for the years 2001-2015 in Reference [31].…”

Section: Figure 2 Re Development Challenges In South Asian Countriesmentioning

confidence: 99%

Assessment of the Electricity System Transition towards High Share of Renewable Energy Sources in South Asian Countries

Rana

Gróf

2022

Energies

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The progressive use of renewable energy sources to ensure a continuous and abundant energy supply is the significant target towards a sustainable and secure energy system. Previously, the countries that had relied on fossil fuel as a dominating energy source are now endorsing energy system transition towards renewable energy sources. In this study, a comparative assessment of the energy problems of South Asian countries is summarized. Nevertheless, there are many similarities and differences in the electricity supply system of these countries. Long-term planning for renewable energy development is suggested for a diverse population and dispersed geographical location considering all the significant challenges. However, appropriate schemes are imperative for integrating significant renewable energy sources. This study introduces a foresight plan of the electricity model according to the demand and supply balance for extensive technical analysis. The EnergyPLAN modeling tool was employed to work out a more ambitious VRE integration scenario than the official plans. The reference model was validated according to legitimate and authentic data, and then, the technically most feasible renewable energy-based alternate scenario was built. The additional grid integration cost of variable renewable energy was quantitatively investigated for comprehensive power system modeling for a real-time economic analysis. The results may be adapted and support developing more sustainable power generation serving 1787 million in South Asian countries.

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Section: Figure 2 Re Development Challenges In South Asian Countriesmentioning

confidence: 99%

Assessment of the Electricity System Transition towards High Share of Renewable Energy Sources in South Asian Countries

Rana

Gróf

2022

Energies

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“…According to the observation, Turkey depends mainly on coal (37%), natural gas (19%), hydropower (29%), and renewable energy (15%) [38] to generate electricity. Turkey imports 72% of these total primary energy supplies (oil, natural gas, coal), which is certainly an enormous load on the Turkish economy [32,39]. In this regard, the research [40] analyzes the operational performance and investment performance of natural gas-, oil-, and coalbased thermal power plant operated by public and private sectors of Turkey.…”

Section: Turkey Scenariomentioning

confidence: 99%

Energy Storage for Energy Security and Reliability through Renewable Energy Technologies: A New Paradigm for Energy Policies in Turkey and Pakistan

et al. 2021

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Forecasting the microeconomics of electricity will turn into a challenging process when electricity is produced through renewable energy technologies (RET). These technologies are mainly sunlight-based photovoltaic (PV), wind power, and tidal resources, which vigorously rely upon ecological conditions. For a reliable and livable energy supply to the electricity grid from renewable means, electrical energy storage technologies can play an important role while considering the weather effects in order to provide immaculate, safe, and continuous energy throughout the generation period. Energy storage technologies (ESTs) charge themselves during the low power demand period and discharge when the demand of electricity increases in such a way that they act as a catalyst to provide energy boost to the power grid. In this paper, we presented and discussed the renewable ESTs for each type with respect to their operational mechanism. In this regard, the renewable energy scenarios of Pakistan and Turkey are first discussed in detail by analyzing the actual potential of each renewable energy resource in both the countries. Then, policy for the EST utilization for both the countries is recommended in order to secure sustainable and reliable energy provision.

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“…However, traditional energy stocks are limited, and carbon dioxide emissions during combustion can cause environmental problems, including global warming and the greenhouse effect. As a result, the adjustment of the energy structure and the development and utilization of new energy sources have gradually attracted the attention of all countries in the world [2]. Solar energy is a clean, green, sustainable, and renewable energy source.…”

Section: Introductionmentioning

confidence: 99%

Short-Term Photovoltaic Power Forecasting Based on Historical Information and Deep Learning Methods

Guo

Yan

2022

Sensors

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The accurate prediction of photovoltaic (PV) power is essential for planning power systems and constructing intelligent grids. However, this has become difficult due to the intermittency and instability of PV power data. This paper introduces a deep learning framework based on 7.5 min-ahead and 15 min-ahead approaches to predict short-term PV power. Specifically, we propose a hybrid model based on singular spectrum analysis (SSA) and bidirectional long short-term memory (BiLSTM) networks with the Bayesian optimization (BO) algorithm. To begin, the SSA decomposes the PV power series into several sub-signals. Then, the BO algorithm automatically adjusts hyperparameters for the deep neural network architecture. Following that, parallel BiLSTM networks predict the value of each component. Finally, the prediction of the sub-signals is summed to generate the final prediction results. The performance of the proposed model is investigated using two datasets collected from real-world rooftop stations in eastern China. The 7.5 min-ahead predictions generated by the proposed model can reduce up to 380.51% error, and the 15 min-ahead predictions decrease by up to 296.01% error. The experimental results demonstrate the superiority of the proposed model in comparison to other forecasting methods.

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An analytical study to predict the future of Pakistan’s energy sustainability versus rest of South Asia

Cited by 16 publications

References 87 publications

Assessment of the Electricity System Transition towards High Share of Renewable Energy Sources in South Asian Countries

Assessment of the Electricity System Transition towards High Share of Renewable Energy Sources in South Asian Countries

Energy Storage for Energy Security and Reliability through Renewable Energy Technologies: A New Paradigm for Energy Policies in Turkey and Pakistan

Short-Term Photovoltaic Power Forecasting Based on Historical Information and Deep Learning Methods

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