Profit Maximization of Microgrid Aggregator Under Power Market Environment

被引：19

作者：

Ahmad, Furkan ^{[1
]}

Alam, Mohammad Saad ^{[1
,2
]}

Shahidehpour, Mohammad ^{[3
,4
]}

机构：

[1] Aligarh Muslim Univ, Zakir Husain Coll Engn & Technol, Elect Engn Dept, Aligarh 202002, Uttar Pradesh, India

[2] Aligarh Muslim Univ, Ctr Adv Res Electfied Transportat, Aligarh 202001, Uttar Pradesh, India

[3] IIT, Dept Elect & Comp Engn, Chicago, IL 60616 USA

[4] King Abdulaziz Univ, Renewable Energy Res Grp, Jeddah 21589, Saudi Arabia

来源：

IEEE SYSTEMS JOURNAL | 2019年 / 13卷 / 03期

关键词：

Bidding strategies; Indian power market; microgrid; power-trading optimization; OPTIMAL BIDDING STRATEGY; RENEWABLE-ENERGY; DEMAND RESPONSE; IMPLEMENTATION; OPTIMIZATION; INTEGRATION; MECHANISM; SYSTEM;

D O I：

10.1109/JSYST.2018.2829343

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The integration of smart microgrid on the large scale in the Indian power market has been highly captivating paradigm since the incorporation of the open access power market under the Indian Electricity Act (IEA) 2003. Efficiency and liquidity of the power market are also rising gradually after the inception of power exchanges (PXs) in 2008. This study presents a comprehensive framework to participate at PXs-based electricity trading platform and to determine the market-clearing price considering single and double side closed bidding mechanism for N bid area. Further, an "optimized algorithm" is proposed to integrate microgrids in the Indian power market by taking into account several characteristics of IEA 2003 and the 2010 power market regulation. Further, to validate the proposed work, the proposed optimization algorithm is applied to a case study considering a 2.5-MWp grid-connected solar PV-based microgrid with an average load of 2060.2 kW in the Indian power market for an hourly power trading in a financial year time horizon.

引用

页码：3388 / 3399

页数：12

共 31 条

[21] Adaptive Portfolio Optimization for Multiple Electricity Markets Participation [J].