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

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.

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Market Clearing Price prediction using ANN in Indian Electricity Markets

2016 International Conference on Energy Efficient Technologies for Sustainability (ICEETS) ◽

10.1109/iceets.2016.7583797 ◽

2016 ◽

Cited By ~ 2

Author(s):

Anamika ◽

Niranjan Kumar

Keyword(s):

Electricity Markets ◽

Market Clearing ◽

Price Prediction ◽

Market Clearing Price

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An Integration Mechanism between Demand and Supply Side Management of Electricity Markets

Energies ◽

10.3390/en11123314 ◽

2018 ◽

Vol 11 (12) ◽

pp. 3314 ◽

Cited By ~ 3

Author(s):

Zixu Liu ◽

Xiaojun Zeng ◽

Fanlin Meng

Keyword(s):

Electricity Market ◽

Dynamic Pricing ◽

Supply And Demand ◽

Coordination Mechanism ◽

Supply Side ◽

Market Demand ◽

Demand Side ◽

Market Clearing ◽

Demand And Supply ◽

Market Clearing Price

One of the main challenges in the emerging smart grid is to jointly consider the demand and supply, which is also reflected in the wholesale market (supply side) and the retail market (demand side). When integrating the demand and supply side into one framework, the mechanism for determining the market clearing price has been changed. This is due to the demand variations in the demand side in response to the market clearing price and the change of generation costs in the supply side from the demand variation. In order to find the best balance between the supply and demand under the demand response management scheme, this paper proposes a new integrated supply and demand coordination mechanism for the electricity market and smart pricing methods for generator and retailers. Another important contribution of this paper is to develop an efficient algorithm to find the match equilibrium between the demand and supply sides in the new proposed mechanism. Experimental results demonstrate that the new mechanism can effectively handle unpredictable demand under dynamic retail pricing and support the ISO to dispatch the generation economically. It can also help in achieving the goals of dynamic pricing such as maximizing the profits for retailers.

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Optimal bidding functions for renewable energies in sequential electricity markets

OR Spectrum ◽

10.1007/s00291-021-00646-9 ◽

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.

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Market Clearing Price Forecasting in Deregulated Electricity Markets Using Adaptively Trained Neural Networks

Advances in Artificial Intelligence - Lecture Notes in Computer Science ◽

10.1007/11752912_8 ◽

2006 ◽

pp. 56-66 ◽

Cited By ~ 9

Author(s):

Pavlos S. Georgilakis

Keyword(s):

Neural Networks ◽

Electricity Markets ◽

Price Forecasting ◽

Market Clearing ◽

Market Clearing Price

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Decomposition of Market Clearing Price in Electricity Markets

IEEJ Transactions on Power and Energy ◽

10.1541/ieejpes.126.297 ◽

2006 ◽

Vol 126 (3) ◽

pp. 297-307 ◽

Cited By ~ 1

Author(s):

Tsunehisa Wachi ◽

Suguru Fukutome ◽

Luonan Chen ◽

Yoshinori Makino

Keyword(s):

Electricity Markets ◽

Market Clearing ◽

Market Clearing Price

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LSTM- and GRU-Based Time Series Models for Market Clearing Price Forecasting of Indian Deregulated Electricity Markets

Advances in Intelligent Systems and Computing - Soft Computing and Signal Processing ◽

10.1007/978-981-13-3393-4_70 ◽

2019 ◽

pp. 693-700

Author(s):

Ashish Ubrani ◽

Simran Motwani

Keyword(s):

Time Series ◽

Electricity Markets ◽

Time Series Models ◽

Price Forecasting ◽

Market Clearing ◽

Market Clearing Price

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Market-Clearing Price Forecasting for Indian Electricity Markets

Proceeding of International Conference on Intelligent Communication, Control and Devices - Advances in Intelligent Systems and Computing ◽

10.1007/978-981-10-1708-7_72 ◽

2016 ◽

pp. 633-642

Author(s):

Anamika ◽

Niranjan Kumar

Keyword(s):

Electricity Markets ◽

Price Forecasting ◽

Market Clearing ◽

Market Clearing Price

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Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽

10.3390/electronics10121452 ◽

2021 ◽

Vol 10 (12) ◽

pp. 1452

Author(s):

Cristian Mateo Castiblanco-Pérez ◽

David Esteban Toro-Rodríguez ◽

Oscar Danilo Montoya ◽

Diego Armando Giral-Ramírez

Keyword(s):

Genetic Algorithm ◽

Objective Function ◽

Programming Model ◽

Distribution Networks ◽

Optimization Method ◽

Optimal Placement ◽

Mixed Integer ◽

Power Balance ◽

Continuous Version ◽

Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

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