scholarly journals Continuous Reinforcement Algorithm and Robust Economic Dispatching-Based Spot Electricity Market Modeling considering Strategic Behaviors of Wind Power Producers and Other Participants

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Zhenyu Zhao ◽  
Shuguang Yuan ◽  
Qingyun Nie ◽  
Weishang Guo
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Gradient Descent ◽  
Economic Dispatch ◽  
Test System ◽  
Modeling Approach ◽  
Continuous State ◽  
Market Operation ◽  
System Operator ◽  
Action Spaces

In a spot wholesale electricity market containing strategic bidding interactions among wind power producers and other participants such as fossil generation companies and distribution companies, the randomly fluctuating natures of wind power hinders not only the modeling and simulating of the dynamic bidding process and equilibrium of the electricity market but also the effectiveness about keeping economy and reliability in market clearing (economic dispatching) corresponding to the independent system operator. Because the gradient descent continuous actor-critic algorithm is demonstrated as an effective method in dealing with Markov’s decision-making problems with continuous state and action spaces and the robust economic dispatch model can optimize the permitted real-time wind power deviation intervals based on wind power producers’ bidding power output, in this paper, considering bidding interactions among wind power producers and other participants, we propose a gradient descent continuous actor-critic algorithm-based hour-ahead electricity market modeling approach with the robust economic dispatch model embedded. Simulations are implemented on the IEEE 30-bus test system, which, to some extent, verifies the market operation economy and the robustness against wind power fluctuations by using our proposed modeling approach.

scholarly journals Simulated Annealing Algorithm for Dynamic Economic Dispatch Problem in the Electricity Market Incorporating Wind Energy

2020 ◽  
Vol 25 (6) ◽  
pp. 719-727
Author(s):  
Riyadh Bouddou ◽  
Farid Benhamida ◽  
Mekki Haba ◽  
Moussa Belgacem ◽  
Mohammed Amine Meziane
Keyword(s):  
Simulated Annealing ◽  
Wind Energy ◽  
Electricity Market ◽  
Simulated Annealing Algorithm ◽  
Supply And Demand ◽  
Economic Dispatch ◽  
Test System ◽  
Energy Integration ◽  
Market Clearing ◽  
Dynamic Economic Dispatch

In this paper, a bid-based dynamic economic dispatch (BBDED) problem is solved in the electricity market system under bidding strategies, including wind energy penetration using simulated annealing (SA) algorithm. The multi-objective dispatch model allows generating companies (GENCOs) and their customers to submit supply and demand bids to a market controller known as the independent system operator (ISO) and follow a bidding strategy. ISO is responsible for the market clearing and settlement to maximize the social profit and benefit for GENCOs and customers during trading periods. To study the effect and advantages of wind energy integration in the BBDED problem, the wind energy generation is computed using the forecasted wind speeds and included in the dispatch model. In this regard, the ISO's dispatch model is formulated as a bilevel nonlinear optimization problem. The higher-level is solving the market-clearing with and without wind energy, and the lower level is maximizing GENCO's social profit. The proposed SA algorithm is evaluated for optimality, convergence, robustness, and computational efficiency tested on an IEEE 30-bus test system. The simulation results are compared with those found using different algorithm-based approaches, considering various constraints like power balancing, generator limits, ramp rate limits, and transmission losses.

scholarly journals Optimal Wind Power Uncertainty Intervals for Electricity Market Operation

2018 ◽  
Vol 9 (1) ◽  
pp. 199-210 ◽  
Author(s):  
Ying Wang ◽  
Zhi Zhou ◽  
Audun Botterud ◽  
Kaifeng Zhang
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Market Operation

scholarly journals Parallel hybrid enhanced inherited GA based scuc in a distributed cluster

2012 ◽  
Vol 1 (1) ◽  
pp. 96 ◽  
Author(s):  
Christopher Columbus C ◽  
Sishaj P. Simon
Keyword(s):  
Electricity Market ◽  
Message Passing ◽  
Message Passing Interface ◽  
Unit Commitment ◽  
Economic Dispatch ◽  
Relaxation Method ◽  
Master Problem ◽  
Solution Quality ◽  
System Operator ◽  
New Formulation

In the deregulated electricity market, secure operation is an enduring concern of the independent system operator (ISO). For a secure and economical hourly generation schedule of the day ahead market, ISO executes the security constrained unit commitment (SCUC) problem. In this paper, a new formulation of SCUC problem, considering more practical constraints are presented. The proposed SCUC formulation includes constraints, such as hourly power demand, system reserves, ramp up/down limits, minimum ON/OFF duration limits. Unlike the traditional SCUC techniques the proposed method solves the Security Constrained Economic Dispatch (SCED) from the UC. To solve such SCUC model, a hybrid solution method consists of an enhanced inherited genetic algorithm (EIGA) is used for unit commitment master problem and Lambda relaxation method is used for the economic dispatch sub-problem. The message passing interface (MPI) based technique is used to implement the hybrid EIGA in distributed memory model. The time complexity and the solution quality with respect to the number of processors in a cluster are thoroughly analyzed. The effectiveness of the proposed method to solve the SCUC problem is shown on different test systems.

Wind Power Forecasting Using Wavelet Transform and General Regression Neural Network for Ontario Electricity Market

2020 ◽  
Vol 13 (1) ◽  
pp. 16-26
Author(s):  
Sumit Saroha ◽  
Sanjeev K. Aggarwal
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Wavelet Transform ◽  
Wind Power ◽  
Electricity Market ◽  
General Regression Neural Network ◽  
Percentage Error ◽  
Wind Power Forecasting ◽  
General Regression ◽  
Power Forecasting

Objective: The estimation accuracy of wind power is an important subject of concern for reliable grid operations and taking part in open access. So, with an objective to improve the wind power forecasting accuracy. Methods: This article presents Wavelet Transform (WT) based General Regression Neural Network (GRNN) with statistical time series input selection technique. Results: The results of the proposed model are compared with four different models namely naïve benchmark model, feed forward neural networks, recurrent neural networks and GRNN on the basis of Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) performance metric. Conclusion: The historical data used by the presented models has been collected from the Ontario Electricity Market for the year 2011 to 2015 and tested for a long time period of more than two years (28 months) from November 2012 to February 2015 with one month estimation moving window.

scholarly journals A Coordinated Control of Offshore Wind Power and BESS to Provide Power System Flexibility

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4650
Author(s):  
Martha N. Acosta ◽  
Francisco Gonzalez-Longatt ◽  
Juan Manuel Roldan-Fernandez ◽  
Manuel Burgos-Payan
Keyword(s):  
Energy Storage ◽  
Power System ◽  
Wind Power ◽  
Single Layer ◽  
Coordinated Control ◽  
Test System ◽  
Power Converter ◽  
Control Logic ◽  
Battery Energy Storage ◽  
Battery Energy

The massive integration of variable renewable energy (VRE) in modern power systems is imposing several challenges; one of them is the increased need for balancing services. Coping with the high variability of the future generation mix with incredible high shares of VER, the power system requires developing and enabling sources of flexibility. This paper proposes and demonstrates a single layer control system for coordinating the steady-state operation of battery energy storage system (BESS) and wind power plants via multi-terminal high voltage direct current (HVDC). The proposed coordinated controller is a single layer controller on the top of the power converter-based technologies. Specifically, the coordinated controller uses the capabilities of the distributed battery energy storage systems (BESS) to store electricity when a logic function is fulfilled. The proposed approach has been implemented considering a control logic based on the power flow in the DC undersea cables and coordinated to charging distributed-BESS assets. The implemented coordinated controller has been tested using numerical simulations in a modified version of the classical IEEE 14-bus test system, including tree-HVDC converter stations. A 24-h (1-min resolution) quasi-dynamic simulation was used to demonstrate the suitability of the proposed coordinated control. The controller demonstrated the capacity of fulfilling the defined control logic. Finally, the instantaneous flexibility power was calculated, demonstrating the suitability of the proposed coordinated controller to provide flexibility and decreased requirements for balancing power.

Sign in / Sign up

Export Citation Format

Share Document