Optimal Coordinated Bidding Strategy of Wind and Solar System with Energy Storage in Day-ahead Market
نویسندگان
چکیده
Although wind and solar power is the major reliable renewable energy sources used in grids, fluctuation unpredictability of these require use ancillary services, thereby increasing integration cost. This study proposes a wind, solar, pumped-storage cooperative (WSPC) model that can be applied to large-scale systems connected dispersed sources. provides an optimized coordinated bidding strategy day-ahead market, along with method facilitate revenue distribution among participating members. takes advantage natural complementary characteristics while using pumped storage adjust total output power. In strategy, proportion energies provided as firm power, which lower service requirement. Moreover, multi-period power-providing mode adopted reflect wind-solar each period accurately. The duration selected variable accommodate seasonal characteristics. ensures provision maintain high under varied ratios wind-solar, obtaining higher revenue. By method, short-term influencing factors are considered provide economic farms photovoltaic stations. this way, fairly realized Finally, effectiveness economy proposed validated based on actual data obtained from grid California, USA.
منابع مشابه
Two-Stage Stochastic Day-Ahead Market Clearing in Gas and Power Networks Integrated with Wind Energy
The significant penetration rate of wind turbines in power systems made some challenges in the operation of the systems such as large-scale power fluctuations induced by wind farms. Gas-fired plants with fast starting ability and high ramping can better handle natural uncertainties of wind power compared to other traditional plants. Therefore, the integration of electrical and natural gas syste...
متن کاملOptimal Bidding Strategy for GENCO with Green Power in Day-ahead Electricity Market
The electricity market has evolved from a regulated monopoly to a more liberalized competitive market, which allows a generating company (GENCO) to bid to provide energy. The two-period structure of the electricity market (day-ahead and real-time market) introduces a mechanism for determining the GENCO’s optimal bidding strategy. The difference between clearing prices for each period adds uncer...
متن کاملOptimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market
Wind Power Producers (WPPs) seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e., the expected profit-m...
متن کاملOptimal Bidding Strategies of GENCOs in Day-Ahead Energy and Spinning Reserve Markets Based on Hybrid GA-Heuristic Optimization Algorithm
In an electricity market, every generation company (GENCO) attempts to maximize profit according to other participants bidding behaviors and power systems operating conditions. The goal of this study is to examine the optimal bidding strategy problem for GENCOs in energy and spinning reserve markets based on a hybrid GA-heuristic optimization algorithm. The heuristic optimization algorithm used...
متن کاملstability and attraction domains of traffic equilibria in day-to-day dynamical system formulation
در این پژوهش مسئله واگذاری ترافیک را از دید سیستم های دینامیکی فرمول بندی می کنیم.فرض کرده ایم که همه فاکتورهای وابسته در طول زمان ثابت باشند و تعادل کاربر را از طریق فرایند منظم روزبه روز پیگیری کنیم.دینامیک ترافیک توسط یک نگاشت بازگشتی نشان داده می شود که تکامل سیستم در طول زمان را نشان می دهد.پایداری تعادل و دامنه جذب را توسط مطالعه ویژگی های توپولوژیکی تکامل سیستم تجزیه و تحلیل می کنیم.پاید...
ذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of modern power systems and clean energy
سال: 2022
ISSN: ['2196-5420', '2196-5625']
DOI: https://doi.org/10.35833/mpce.2020.000037