Papers by Mohammad Reza Salehizadeh
SEGAN, 2021
Providing efficient support mechanisms for renewable energy promotion has drawn much attention fr... more Providing efficient support mechanisms for renewable energy promotion has drawn much attention from researchers in the recent years. The connection of a new renewable power plant to the transmission system has impacts on different electricity market indices since the other strategic generation units change their behaviour in the new multi-agent environment. In this paper, as the main contribution to the previous literature, a combination of multi-criteria decision-making approach and multi-agent modelling technique is developed to obtain the maximum possible profits for an intended renewable generation plan and also direct the investment to be located in a way to improve electricity market indices besides supporting renewable energy promotion. Fuzzy Q-learning electricity market modelling approach in combination with the technique for order preference by similarity (TOPSIS) is used as a new decision support system for promotion of renewable energy for the first time in the literature. The proposed interactive multi-criteria decision-making framework between the independent system operator (ISO) and the renewable power plant planner provides a win-win situation that improve market indices while help the renewable power plant planning. The effectiveness of the proposed method is examined on the IEEE 30-bus test system and the results are discussed.
IET Generation, Transmission & Distribution, 2020
As an intermediator between the wholesale electricity market and retail market, a typical load ag... more As an intermediator between the wholesale electricity market and retail market, a typical load aggregator (LA) submits an optimal bid to the system operator to meet the expected demands of its customers. In this regard, the provision of an effective optimal bidding strategy is very crucial for an LA to increase its profit. Within this context, this paper proposes a two-stage artificial neural network (ANN) based adaptive bidding strategy procedure for an LA by revealing, modeling, and predicting the aggregative behavior of the competitors in an hourly electricity market. To this end, we develop the concept of decentralized equivalent rival (DER) whose behavior in the electricity market reflects the aggregation of behaviors of all individual competitors. Also, an equivalent market which its outcomes are approximately equal to those of the real market is modeled. The equivalent market's participants are the LA and its corresponding DER. The proposed approach is capable enough to consider transmission constraints. The performance of the proposed approach has been examined on an illustrative example and the IEEE 30-bus test system by considering transmission network constraints. The proposed ANN-based adaptive bidding strategy has compared with a Q-learning-based bidding approach and the results are analyzed.
SIMULATION: Transactions of The Society for Modeling and Simulation International, 2019
In this paper, a detailed mathematical optimization model of electrolyzer/fuel cell technology co... more In this paper, a detailed mathematical optimization model of electrolyzer/fuel cell technology connected to the grid through limited rating converters is developed. The model is so defined that it can tackle voltage fluctuation and meet the power ramp rate limitations inflicted by integration of constant-speed wind turbines at the Point of Common Coupling. The flicker mitigation and power ramp rate control problem in the presence of wind generation and variable electrical loads is defined as a nonlinear constrained optimization problem, in which voltage fluctuation is minimized as the objective function and the power ramp rate limitations are respected by the defined real-time ramp rate constraint. The problem is solved using the sequential quadratic programming method, which is a fast solver, by adjusting suitable initial points to be appropriate for real-time applications. The simulation results validate the efficiency of the proposed method and show dramatic improvement in flicker mitigation, power ramp rate control, and system rating reduction in comparison with the proportional-integral control method that was developed in previous studies.
energies, 2019
Exposure to extreme weather conditions increases power systems' vulnerability in front of high im... more Exposure to extreme weather conditions increases power systems' vulnerability in front of high impact, low probability contingency occurrence. In the post-restructuring years, due to the increasing demand for energy, competition between electricity market players and increasing penetration of renewable resources, the provision of effective resiliency-based approaches has received more attention. In this paper, as the major contribution to current literature, a novel approach is proposed for resiliency improvement in a way that enables power system planners to manage several resilience metrics efficiently in a bi-objective optimization planning model simultaneously. For demonstration purposes, the proposed method is applied for optimal placement of the thyristor controlled series compensator (TCSC). Improvement of all considered resilience metrics regardless of their amount in a multi-criteria decision-making framework is novel in comparison to the other previous TCSC placement approaches. Without loss of generality, the developed resiliency improvement approach is applicable in any power system planning and operation problem. The simulation results on IEEE 30-bus and 118-bus test systems confirm the practicality and effectiveness of the developed approach. Simulation results show that by considering resilience metrics, the performance index, importance of curtailed consumers, congestion management cost, number of curtailed consumers, and amount of load loss are improved by 0.63%, 43.52%, 65.19%, 85.93%, and 85.94%, respectively.
By increasing renewable resource penetration, the need for developing fast and reliable market mo... more By increasing renewable resource penetration, the need for developing fast and reliable market modeling approaches in the presence of these resources has gained greater attention. In this paper, fuzzy Q-learning approach is proposed for hour-ahead electricity market modeling in presence of renewable resources. The proposed approach is implemented on IEEE 30-bus test system. The effectiveness of the proposed approach is evaluated and compared with Q-learning approach for both normal and stressful cases. Simulation results indicate that the proposed approach is able to model electricity market for a range of continuous multidimensional renewable power penetration in considerably less iterations compared with Q-learning approach. Moreover, the probability of finding Nash equilibrium is becoming higher by using fuzzy Q-learning approach, while the other indices such as average social welfare, average of locational marginal prices (LMPs), and average standard of deviation of LMPs do not change considerably.
Springer Series in Reliability Engineering, 2015
Since the beginning of power system restructuring and creation of numerous temporal power markets... more Since the beginning of power system restructuring and creation of numerous temporal power markets, transmission congestion has become a serious challenge for independent system operators around the globe. On the other hand, in recent years, emission reduction has become a major concern for the electricity industry. As a widely accepted solution, attention has been drawn to renewable power resources promotion. However, penetration of these resources impacts on transmission congestion. In sum, these challenges reinforce the need for new approaches to facilitate interaction between the operator and energy market players defined as the generators (power generation companies) in order to provide proper operational signals for the operator. The main purpose of this chapter is to provide a combination of a leader-follower game theoretical mechanism and multiattribute decision-making for the operator to choose his best strategy by considering congestion-driven and environmental attributes. First the operator (as the leader) chooses K strategies arbitrarily. Each strategy is constituted by emission penalty factors for each generator, the amount of purchased power from renewable power resources, and a bid cap that provides a maximum bid for the price of electrical power for generators who intend to sell their power in the market. For each of the K strategies, the generators (as the followers) determine their optimum bids for selling power in the market. The interaction between generation companies is modeled as Nash-Supply Function equilibrium (SFE) game. Thereafter, for each of the K strategies, the operator performs congestion management and congestion-driven attributes and emission are obtained. The four different attributes are congestion cost, average locational marginal price (LMP) for different system buses, variance of the LMPs, and the generators' emission. Finally, the operator's preferred strategy is selected using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The proposed procedure is applied to the IEEE reliability 24-bus test system and the results are analyzed. AQ1
Power system operation in the era of post-restructuring faces several challenges: transmission co... more Power system operation in the era of post-restructuring faces several challenges: transmission congestion frequently occurs, security is deterred more than in the past, emission reduction is becoming a matter of importance and intermittent renewable power generation resources (RPGR) have been widely promoted. This paper intends to solve these challenges in a multi-objective optimisation framework. The proposed procedure comprises two stages: in the a priori stage, transmission congestion management cost (TCMC) and emission are traded-off via a proposed stochastic augmented ε-constraint technique which yields a set of non-dominated solutions. In the a posteriori stage, a solution is selected by considering power system security. For this purpose, two strategies are proposed: in the first strategy, based on a proposed managerial vision, a combination of data envelopment analysis introduced by Charnes, Cooper, and Rhodes (CCR-DEA), cross-efficiency technique and robustness analysis is deployed to select the most robust super-efficient solution. The advantage of the proposed a posteriori approach is that selecting the final solution is not subjected to assigning weights to the objective functions and/or providing higher-level information. In the second strategy, first the effective scenarios due to outage of transmission components are identified using CCR-DEA and next, each scenarios’ degree of severity (DOS) is obtained using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The sums of the DOS of non-dominated solutions’ effective scenarios are evaluated for final decision making. The proposed approach is applied to IEEE 24 bus test system and the results are analysed.
Since the beginning of power system restructuring and creation of numerous temporal power markets... more Since the beginning of power system restructuring and creation of numerous temporal power markets, transmission congestion has become a serious challenge for independent system operators around the globe. On the other hand, in recent years, emission reduction has become a major concern for the electricity industry. As a widely accepted solution, attention has been drawn to renewable power resources promotion. However, penetration of these resources impacts on transmission congestion. In sum, these challenges reinforce the need for new approaches to facilitate interaction between the operator and energy market players defined as the generators (power generation companies) in order to provide proper operational signals for the operator. The main purpose of this chapter is to provide a combination of a leader–follower game theoretical mechanism and multiattribute decision-making for the operator to choose his best strategy by considering congestion-driven and environmental attributes. First the operator (as the leader) chooses K strategies arbitrarily. Each strategy is constituted by emission penalty factors for each generator, the amount of purchased power from renewable power resources, and a bid cap that provides a maximum bid for the price of electrical power for generators who intend to sell their power in the market. For each of the K strategies, the generators (as the followers) determine their optimum bids for selling power in the market. The interaction between generation companies is modeled as Nash-Supply Function equilibrium (SFE) game. Thereafter, for each of the K strategies, the operator performs congestion management and congestion-driven attributes and emission are obtained. The four different attributes are congestion cost, average locational marginal price (LMP) for different system buses, variance of the LMPs, and the generators’ emission. Finally, the operator’s preferred strategy is selected using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The proposed procedure is applied to the IEEE reliability 24-bus test system and the results are analyzed.
competitive electricity markets, various longterm and short-term contracts based on spot price ar... more competitive electricity markets, various longterm and short-term contracts based on spot price are implemented by independent market operator (IMO). An accurate forecasting technique for spot price facilitates the market participants to develop bidding strategies in order to maximize their benefit. Neural-Wavelet is a powerful method for forecasting problems under the condition of nonlinearity as well as uncertainty. In this paper, a new methodology based upon radial basis function (RBF) network is proposed to the forecasting spot price problem. To train the network, in order to apply historical information of the price behavior, some other effective parameters are used. Load level, fuel price, generation and transmission location as well as conditions are the effective parameters which are associated with general well known parameters. All these parameters are applied for learning process to an assumed neural wavelet network (NWN). Simulation results are presented in details in this paper, where these results indicate the effectiveness of the proposed forecasting tool as an accurate technique.
Abstract Under competitive electricity markets, various long-term and short-term contracts based ... more Abstract Under competitive electricity markets, various long-term and short-term contracts based on spot price are implemented by independent market operator (IMO) An accurate forecasting technique for spot price facilitates the market participants to develop bidding strategies in ...
In this paper a new approach for loss allocation is presented. The main idea is voltage angle all... more In this paper a new approach for loss allocation is presented. The main idea is voltage angle allocation, i.e. determining the contribution of each contract on the voltage angle of each bus. DC power flow is used to compute a primary solution for angle decomposition. To consider the impacts of system non-linearity on angle decomposition, the primary solution is corrected in different iterations of decoupled Newton-Raphson power flow. Then, the contribution of each contract in power flow of each transmission line is computed based on angle decomposition. The loss of each transmission line is allocated among different contracts proportional to the square of their contributions in the line flow. The presented approach is applied to the IEEE 30-bus test system.
In this paper a new approach for transmission pricing is presented. The main idea is voltage angl... more In this paper a new approach for transmission pricing is presented. The main idea is voltage angle allocation, i.e. determining the contribution of each contract on the voltage angle of each bus. DC power flow is used to compute a primary solution for angle decomposition. To consider the impacts of system non-linearity on angle decomposition, the primary solution is corrected in different iterations of decoupled Newton-Raphson power flow. Then, the contribution of each contract on power flow of each transmission line is computed based on angle decomposition. Contract-related flows are used as a measure for "extent of use" of transmission network capacity and consequently transmission pricing. The presented approach is applied to a 4-bus test system and IEEE 30-bus test system.
International Journal of Electrical Power & Energy Systems, 2008
In this paper a new approach for transmission pricing is presented. The contribution of a contrac... more In this paper a new approach for transmission pricing is presented. The contribution of a contract on power flow of a transmission line is used as extent-of-use criterion for transmission pricing. In order to determine the contribution of each contract on power flow of each transmission line, first the contribution of each contract on each voltage angle is determined, which is called voltage angle decomposition. To this end, DC power flow is used to compute a primary solution for voltage angle decomposition. To consider the impacts of system non-linearity on voltage angle decomposition, a method is presented to determine the share of different terms of sine argument in sine value. Then the primary solution is corrected in different iterations of decoupled Newton-Raphson power flow using the presented sharing method. The presented approach is applied to a 4-bus test system and IEEE 30-bus test system and the results are analyzed.
Proceedings of the XVII International Conference on Computer and Information Science and Engineering, Cairo, Egypt
In this paper a new approach for transmission pricing is presented. The main idea is voltage angl... more In this paper a new approach for transmission pricing is presented. The main idea is voltage angle allocation, i.e. determining the contribution of each contract on the voltage angle of each bus. DC power flow is used to compute a primary solution for angle decomposition. To consider the impacts of system non-linearity on angle decomposition, the primary solution is corrected in different iterations of decoupled Newton-Raphson power flow. Then, the contribution of each contract on power flow of each transmission line is computed based on angle decomposition. Contract-related flows are used as a measure for "extent of use" of transmission network capacity and consequently transmission pricing. The presented approach is applied to a 4-bus test system and IEEE 30-bus test system.
In this paper a new approach for loss allocation is presented. The main idea is voltage angle all... more In this paper a new approach for loss allocation is presented. The main idea is voltage angle allocation, i.e. determining the contribution of each contract on the voltage angle of each bus. DC power flow is used to compute a primary solution for angle decomposition. To consider the impacts of system non-linearity on angle decomposition, the primary solution is corrected in different iterations of decoupled Newton-Raphson power flow. Then, the contribution of each contract in power flow of each transmission line is computed based on angle decomposition. The loss of each transmission line is allocated among different contracts proportional to the square of their contributions in the line flow. The presented approach is applied to the IEEE 30-bus test system.
International Journal of Electrical Power and Energy Systems
In this paper a new approach for transmission pricing is presented. The contribution of a contrac... more In this paper a new approach for transmission pricing is presented. The contribution of a contract on power flow of a transmission line is used as extent-of-use criterion for transmission pricing. In order to determine the contribution of each contract on power flow of each transmission line, first the contribution of each contract on each voltage angle is determined, which is called voltage angle decomposition. To this end, DC power flow is used to compute a primary solution for voltage angle decomposition. To consider the impacts of system non-linearity on voltage angle decomposition, a method is presented to determine the share of different terms of sine argument in sine value. Then the primary solution is corrected in different iterations of decoupled Newton-Raphson power flow using the presented sharing method. The presented approach is applied to a 4-bus test system and IEEE 30-bus test system and the results are analyzed.
European Journal of Engineering Education
In the Iranian higher education system, including engineering education, effective implementation... more In the Iranian higher education system, including engineering education, effective implementation of cooperative learning is difficult because classrooms are usually crowded and the students never had a formal group working background in their previous education. In order to achieve the benefits of cooperative learning in this condition, this paper proposes a combination of cooperative learning and inquiry method. The method is implemented by grouping students in a way that the learning procedure is done in non-official class sessions by each group, while the inquiry method is done in the regular programmed class sessions. The study is performed in Islamic Azad University and the methods are implemented in two engineering economic classes with different numbers of students in each working group. The results are compared with a control class in which traditional teaching style is implemented. The results of analysis show simultaneous improvement of learning and behavioural attitudes of the students with cooperative learning plus inquiry method in the classroom with a fewer number of students in each working group.
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Papers by Mohammad Reza Salehizadeh