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Record W6995501967

OPTIMAL WIND ENERGY PENETRATION MODEL FOR PAKISTAN

2015· dissertation· en· W6995501967 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHEC National Digital Library · 2015
Typedissertation
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWind powerHydropowerEnergy mixElectricity generationElectric power systemRenewable energyElectricityMarket penetrationFossil fuelSustainable development
DOInot available

Abstract

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An affordable, economic and sustainable electric energy system remains a challenging question for the researchers due to constraints on primary energy supply and technology economics. Modeling the energy system and simulating the scenarios is a scientific way to arrive at informed policy decisions for an energy system for a country. 
\nThe historical generation mix of the ex-WAPDA system, which is now managed by National Transmission and Dispatch Company (NTDC) was Hydro dominant since its birth till year 1992. Subsequently the thermal power share started substituting hydropower shifting the generation dominance to thermal. Pakistan is one of the most fortunate countries of the world, which is having abundant hydropower potential of 46,000MW. Unfortunately due to lack of consensus on political scene, development of several identified hydro sites into power production projects could not achieved, resulting acute load shedding due to shortage of power generation. Presently generation mix is dominant by expensive fossil fuels and there is dire need to exploit alternate energy resources. The most promising option for Pakistan power sector is wind power having estimated potential of 140,000 MW. In present research efforts have been made in developing optimal wind energy penetration model for Pakistan having long term sustainable wind power to meet demand under electricity market through policy incentives, mechanism and regulations with least cost flow along the complete value chain including manufacturing, implementation and penetration. 
\nInternational data analysis and literature review shows that the success of wind deployment is in the success of local manufacturing of wind turbines. However, stable and sizeable level of wind deployment is pre-requisite for the manufacturing of wind turbines locally. The international experience shows that optimal level of wind power deployment to ensure the wind manufacturing is in the range of 400-500MW. In modeling energy system for Pakistan with wind power, a deployment level of 550MW has been determined. 
\nTo model the energy system with wind power, the economic viability, consumer's affordability, security of supply, sustainability and diversity were considered as key parameters to design the energy scenarios. Three scenarios with the optimal level of 550MW of wind power, including i) base scenario with existing mix, ii) Policy scenario with hydro & coal, and iii) sustainability scenario with hydro & nuclear have been modeled over a period 2014-2035 to assess the policy 
\ncost comparing with no wind base case. Requisite data collected from local and international data sources including International Energy Agency (IEA), United Stated Energy Information Administration (EIA) and International Renewable Energy Agency (IRENA), Global Wind Energy Council (GWEC), NEPRA and planning department. The energy system simulated and analyzed in the Long-range Energy Alternatives Planning System (LEAP) software environment. 
\n Three scenarios including i) Governments ongoing initiatives as Business As Usual (BAU) scenario, ii) Policy Scenario, targeting 550 MW wind and iii) Sustainability Scenario 550 MW wind were simulated with full self-sufficiency and energy security. The results of the simulation of these scenarios show that policy scenario when compared with base case result 347 million tons more carbon dioxide emissions and cost saving of 4.8 billion US$ in net present value. So the cost saving is 14US$ per ton of excess carbon dioxide emissions. Whereas, the sustainability scenario when compared with base case result in 2177 million carbon dioxide emissions saving at an additional cost of 19.8 billion USD in net present value. So the cost of emission reduction is 9 US$ per ton of carbon dioxide emissions, which is much less than the policy cost of 15 US$ per ton in Alberta energy system, Canada. So, this international benchmark comparison shows that it's economically viable for government to devise the policy incentives to meet the objective of self-sufficiency and environmental sustainability. This sustainability scenario can be used to achieve environmental targets, if imposed under the United Nations Framework of Climate Change (UNFCC) and design climate change policies. 
\nThe international experience shows that a country specific optimal model is pre-requisite for the wind turbine manufacturing locally to achieve the desired energy system with wind penetration in Pakistan. The results of the policy cost are encouraging to develop a regulatory and policy model for the local manufacturing of wind turbine in Pakistan as well. It will add to economic benefits with local employment generation to reduce the effective policy cost. A wind turbine manufacturing regulatory and policy model establishing the Wind Technology Investment Company, Wind Development Investment Company and Wind Technology Development Bank etc. with their optimal architecture have been proposed. This model is with the government incentives, firm commitments and revolving endowment for sustainable supply of wind turbines manufactured locally with employing full local technical expertise. This will be an optimal model with an effective policy framework to ensure foreign investment, fair wind power pricing, institutional reforms in management and technology, local manufacturing/employment and technical base in Pakistan.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.787
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.234
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it