Flexible block offers and a three-stage market clearing method for distribution-level electricity markets with grid limits

2021 ◽  
Vol 130 ◽  
pp. 106985
Author(s):  
Shaojun Huang ◽  
Yuming Zhao ◽  
Konstantin Filonenko ◽  
Yun Wang ◽  
Tianlong Xiong ◽  
...  
Keyword(s):  
Electricity Markets ◽  
Market Clearing ◽  
Clearing Method

scholarly journals A Two-Sided Price-Decoupled Pay-As-Bid Auction Approach for the Clearing of Day-Ahead Electricity Markets

2020 ◽  
Vol 162 ◽  
pp. 01006
Author(s):  
Dávid Csercsik
Keyword(s):  
Objective Function ◽  
Electricity Markets ◽  
Supply And Demand ◽  
Conventional Approach ◽  
Small Scale ◽  
Power Balance ◽  
Market Clearing ◽  
Multiunit Auctions ◽  
Market Clearing Price ◽  
Characteristic Features

In this paper we propose a possible alternative for conventional pay-as-clear type multiunit auctions commonly used for the clearing of day-ahead power exchanges, and analyse some of its characteristic features in comparison with conventional clearing. In the proposed framework, instead of the concept of the uniform market clearing price, we introduce limit prices separately for supply and demand bids, and in addition to the power balance constraint, we formulate constraints for the income balance of the market. The total traded quantity is used as the objective function of the formulation. The concept is demonstrated on a simple example and is compared to the conventional approach in small-scale market simulations.

Comparative study between two market clearing schemes in wind dominant electricity markets

2015 ◽  
Vol 9 (15) ◽  
pp. 2215-2223 ◽  
Author(s):  
Seyed-Mostafa Farashbashi-Astaneh ◽  
Zhe Chen ◽  
Weihao Hu
Keyword(s):  
Comparative Study ◽  
Electricity Markets ◽  
Market Clearing

scholarly journals Optimal bidding functions for renewable energies in sequential electricity markets

OR Spectrum ◽  
2021 ◽  
Author(s):  
Benedikt Finnah
Keyword(s):  
Electricity Markets ◽  
Optimal Policy ◽  
Decision Problem ◽  
Energy Markets ◽  
Market Clearing ◽  
Energy Trading ◽  
Market Participants ◽  
Price Process ◽  
Market Clearing Price ◽  
Optimal Bidding

AbstractIn most modern energy markets, electricity is traded in pay-as-clear auctions. Usually, multiple sequential markets with daily auctions, in which each hourly product is traded separately, coexist. In each market and for each traded hour, each power producer and consumer submits multiple price and volume combinations, called bids. After all bids are submitted by the market participants, the market-clearing price for each hour is published, and the market participants must fulfill their accepted commitments. The corresponding decision problem is particularly difficult to solve for market participants with stochastic supply or demand. We formulate the energy trading problem as a dynamic program and derive the optimal bidding functions analytically via backward recursion. We demonstrate that, for each hour and market, the optimal bidding function is completely defined by two bids. While we focus on power producers with stochastic supply (e.g., wind or solar), our model is applicable to power consumers with stochastic demand, as well. The optimal policy is applicable in most liberalized energy markets, virtually independent of the structure of the underlying electricity price process.

scholarly journals Forecasting of Market Clearing Volume Using Wavelet Packet-Based Neural Networks with Tracking Signals

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6065
Author(s):  
Sumit Saroha ◽  
Marta Zurek-Mortka ◽  
Jerzy Ryszard Szymanski ◽  
Vineet Shekher ◽  
Pardeep Singla
Keyword(s):  
Electricity Markets ◽  
Wavelet Packet ◽  
Demand Forecasting ◽  
Time Lags ◽  
Market Clearing ◽  
Mutual Correlation ◽  
Proposed Model ◽  
Yearly Average ◽  
Auto Correlation Function ◽  
Linear Neural Network

In order to analyze the nature of electrical demand series in deregulated electricity markets, various forecasting tools have been used. All these forecasting models have been developed to improve the accuracy of the reliability of the model. Therefore, a Wavelet Packet Decomposition (WPD) was implemented to decompose the demand series into subseries. Each subseries has been forecasted individually with the help of the features of that series, and features were chosen on the basis of mutual correlation among all-time lags using an Auto Correlation Function (ACF). Thus, in this context, a new hybrid WPD-based Linear Neural Network with Tapped Delay (LNNTD) model, with a cyclic one-month moving window for a one-year market clearing volume (MCV) forecasting has been proposed. The proposed model has been effectively implemented in two years (2015–2016) and unconstrained MCV data collected from the Indian Energy Exchange (IEX) for 12 grid regions of India. The results presented by the proposed models are better in terms of accuracy, with a yearly average MAPE of 0.201%, MAE of 9.056 MWh, and coefficient of regression (R2) of 0.9996. Further, forecasts of the proposed model have been validated using tracking signals (TS’s) in which the values of TS’s lie within a balanced limit between −492 to 6.83, and universality of the model has been carried out effectively using multiple steps-ahead forecasting up to the sixth step. It has been found out that hybrid models are powerful forecasting tools for demand forecasting.

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