بازار برق سبز و قابل اعتماد
ترجمه نشده

بازار برق سبز و قابل اعتماد

عنوان فارسی مقاله: طراحی مشوق های مالیاتی و یارانه ای به سمت یک بازار برق سبز و قابل اعتماد
عنوان انگلیسی مقاله: Designing tax and subsidy incentives towards a green and reliable electricity market
مجله/کنفرانس: انرژی – Energy
رشته های تحصیلی مرتبط: مهندسی برق، حسابداری، اقتصاد
گرایش های تحصیلی مرتبط: حسابداری مالیاتی، اقتصاد انرژی
کلمات کلیدی فارسی: مدل گسترش بازار برق، قدرت بازار، سیاست های تشویقی ظرفیت پاسخ سریع و انتشارات
کلمات کلیدی انگلیسی: Electricity market expansion model, Market power, Emission and fast response capacity incentive policies
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.energy.2020.117033
دانشگاه: Portfolio Planning & Optimization Group at AGL, Australia
صفحات مقاله انگلیسی: 14
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 6.153 در سال 2019
شاخص H_index: 158 در سال 2020
شاخص SJR: 2.048 در سال 2019
شناسه ISSN: 0360-5442
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E14452
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

Nomenclature

۱٫ Introduction

۲٫ Tax and subsidy design framework for competitive electricity markets

۳٫ Solution methodology

۴٫ Case study and simulation results

۵٫ Conclusion

۶٫ Modeling platform

References

بخشی از مقاله (انگلیسی)

Abstract

Incentive schemes and policies play an important role in reducing carbon emissions from electricity generation. This paper investigates designing tax and subsidy incentives towards a reliable and low emission electricity market, using Australia’s National Electricity Market as a case study. In this work, a novel framework is proposed to design interactive tax/subsidy incentives on both emission reduction and resource adequacy in competitive electricity markets as a game model. In our model, market participants decide on their capacity expansion/retirement strategies considering the impact of designed incentive schemes on their long-term operation such that the desired levels of emission reduction and fast response generation are achieved in the network. The simulation results for Australia’s electricity market during 2017-2052, indicate the necessity of incentive policies, in spite of the cost reduction trajectory for renewable technologies, to reach the emission intensity reduction above 45% in the market by 2052. In 80% emission intensity reduction scenario, the designed incentive schemes highly encourage the investment on synchronous renewables, +17 GW, storage technologies, +15.7 GW, and transmission lines, +1.6 GW, to support high additional penetration of Variable Renewable Energy, wind and solar, +39 GW, which paves the way to transition to a green and reliable electricity market.

Introduction

The electricity markets are undergoing a significant transition, in which renewable energy and clean energy play an important role. Integration of variable and distributed energy resources provides opportunities for clean and low cost generation [1]. However, many new generation technologies do not inherently provide system services that were previously provided as a consequence of energy provision [2]. Hence, existence of adequate fast response dispatchable capacity is required to enable high levels of Variable Renewable Energy (VRE) integration in the market. This paper presents a novel incentive design framework to quantify the required tax and subsidy levels on CO2 emission and fast response capacity to ensure emission reduction and resource adequacy in competitive electricity markets. Note that CO2 is the baseline greenhouse gas that is used as a benchmark for other gases [3]. While many studies have investigated various aspects of this problem, very few are quantitative and take into account the competitive behaviour of market players and the impact of incentive policies on their decisions. Our framework achieves this and presents quantitative results by adopting a game-theoretic approach.

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