Penn State University

Research Assistant

Worked on several research projects related to policy analysis in transmission-constrained electricity markets

Arizona State University

Post-Doctoral Scholar

Transmission switching
Network topology optimization
High performance computing - Parallel programming

Arizona State University

Faculty Associate

Teaching EEE202 - Circuits I

University of Utah

Assistant Professor

Mostafa worked at University of Utah as a Assistant Professor

Niroo Research Institute

Research Engineer

Involved in designing reserve ancillary services market for Iran's electricity market.

Seven Lakes Technologies

Data Analyst

Developed statistical machine learning models to predict down time for oil and has industry.

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Distributional impacts of state-level energy efficiency policies in regional electricity markets

Elsevier - Energy Policy

A number of U.S. states have passed legislation targeting energy efficiency and peak demand reduction. We study one such state, Pennsylvania, within the context of PJM, a regional electricity market covering numerous different states. Our focus is on the distributive impacts of this policy—specifically how the policy is likely to impact electricity prices in different areas of Pennsylvania and in the PJM market more generally. Such spatial differences in policy impacts are difficult to model and the transmission system is often ignored in policy studies. Our model estimates supply curves on a “zonal” basis within regional electricity markets and yields information on price and fuel utilization within each zone. We use the zonal supply curves estimated by our model to study regional impacts of energy-efficiency legislation on utilities both inside and outside of Pennsylvania. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. It would also save 2.1 to 2.8 percent of total energy cost in Pennsylvania in a year similar to 2009. The savings are lower than 0.5 percent in other PJM states and the prices may slightly increase in Washington, DC area.

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Distributional impacts of state-level energy efficiency policies in regional electricity markets

Elsevier - Energy Policy

A number of U.S. states have passed legislation targeting energy efficiency and peak demand reduction. We study one such state, Pennsylvania, within the context of PJM, a regional electricity market covering numerous different states. Our focus is on the distributive impacts of this policy—specifically how the policy is likely to impact electricity prices in different areas of Pennsylvania and in the PJM market more generally. Such spatial differences in policy impacts are difficult to model and the transmission system is often ignored in policy studies. Our model estimates supply curves on a “zonal” basis within regional electricity markets and yields information on price and fuel utilization within each zone. We use the zonal supply curves estimated by our model to study regional impacts of energy-efficiency legislation on utilities both inside and outside of Pennsylvania. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. It would also save 2.1 to 2.8 percent of total energy cost in Pennsylvania in a year similar to 2009. The savings are lower than 0.5 percent in other PJM states and the prices may slightly increase in Washington, DC area.

A dynamic replicator model of the players’ bids in an oligopolistic electricity market

Elsevier - Electric Power System Research

In this paper, the replicator dynamics of the power suppliers’ bids in an oligopolistic electricity market are derived for both the fixed and variable demand cases. The replicator dynamics stability analysis is also performed. The dynamics of the electricity markets are the results of players’ decisions. The physical parameters of the power systems (such as the lines capacities, voltage limitations, etc.) also affect the market dynamics indirectly, through the changes in players’ behaviors. Assuming rational players, an optimal bidding strategy for constructing the supply function (SF) of a generating firm is presented and based on that, the dynamics of the bid replicators are studied. Both fixed demands and price sensitive demands are taken into account. The replicator model is presented in the well-known state space structure. A case study is presented to show the applicability of the developed dynamic replicator bid model, and also to show how the Nash–SFE equilibrium evolves over time.

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Distributional impacts of state-level energy efficiency policies in regional electricity markets

Elsevier - Energy Policy

A number of U.S. states have passed legislation targeting energy efficiency and peak demand reduction. We study one such state, Pennsylvania, within the context of PJM, a regional electricity market covering numerous different states. Our focus is on the distributive impacts of this policy—specifically how the policy is likely to impact electricity prices in different areas of Pennsylvania and in the PJM market more generally. Such spatial differences in policy impacts are difficult to model and the transmission system is often ignored in policy studies. Our model estimates supply curves on a “zonal” basis within regional electricity markets and yields information on price and fuel utilization within each zone. We use the zonal supply curves estimated by our model to study regional impacts of energy-efficiency legislation on utilities both inside and outside of Pennsylvania. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. It would also save 2.1 to 2.8 percent of total energy cost in Pennsylvania in a year similar to 2009. The savings are lower than 0.5 percent in other PJM states and the prices may slightly increase in Washington, DC area.

A dynamic replicator model of the players’ bids in an oligopolistic electricity market

Elsevier - Electric Power System Research

In this paper, the replicator dynamics of the power suppliers’ bids in an oligopolistic electricity market are derived for both the fixed and variable demand cases. The replicator dynamics stability analysis is also performed. The dynamics of the electricity markets are the results of players’ decisions. The physical parameters of the power systems (such as the lines capacities, voltage limitations, etc.) also affect the market dynamics indirectly, through the changes in players’ behaviors. Assuming rational players, an optimal bidding strategy for constructing the supply function (SF) of a generating firm is presented and based on that, the dynamics of the bid replicators are studied. Both fixed demands and price sensitive demands are taken into account. The replicator model is presented in the well-known state space structure. A case study is presented to show the applicability of the developed dynamic replicator bid model, and also to show how the Nash–SFE equilibrium evolves over time.

Estimating zonal electricity supply curves in transmission-constrained electricity markets

Elsevier - Energy

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal.

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Distributional impacts of state-level energy efficiency policies in regional electricity markets

Elsevier - Energy Policy

A number of U.S. states have passed legislation targeting energy efficiency and peak demand reduction. We study one such state, Pennsylvania, within the context of PJM, a regional electricity market covering numerous different states. Our focus is on the distributive impacts of this policy—specifically how the policy is likely to impact electricity prices in different areas of Pennsylvania and in the PJM market more generally. Such spatial differences in policy impacts are difficult to model and the transmission system is often ignored in policy studies. Our model estimates supply curves on a “zonal” basis within regional electricity markets and yields information on price and fuel utilization within each zone. We use the zonal supply curves estimated by our model to study regional impacts of energy-efficiency legislation on utilities both inside and outside of Pennsylvania. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. It would also save 2.1 to 2.8 percent of total energy cost in Pennsylvania in a year similar to 2009. The savings are lower than 0.5 percent in other PJM states and the prices may slightly increase in Washington, DC area.

A dynamic replicator model of the players’ bids in an oligopolistic electricity market

Elsevier - Electric Power System Research

In this paper, the replicator dynamics of the power suppliers’ bids in an oligopolistic electricity market are derived for both the fixed and variable demand cases. The replicator dynamics stability analysis is also performed. The dynamics of the electricity markets are the results of players’ decisions. The physical parameters of the power systems (such as the lines capacities, voltage limitations, etc.) also affect the market dynamics indirectly, through the changes in players’ behaviors. Assuming rational players, an optimal bidding strategy for constructing the supply function (SF) of a generating firm is presented and based on that, the dynamics of the bid replicators are studied. Both fixed demands and price sensitive demands are taken into account. The replicator model is presented in the well-known state space structure. A case study is presented to show the applicability of the developed dynamic replicator bid model, and also to show how the Nash–SFE equilibrium evolves over time.

Estimating zonal electricity supply curves in transmission-constrained electricity markets

Elsevier - Energy

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal.

A Fast LP Approach for Enhanced Utilization of Variable Impedance Based FACTS Devices

IEEE Transactions on Power Systems

Transmission systems are under stress and need to be upgraded. Better utilization of the existing grid provides a fast and cheap alternative to building new transmission. One way to improve the utilization of the transmission network is power flow control via flexible AC transmission system (FACTS) devices. While FACTS devices are used today, the utilization of these devices is limited; traditional dispatch models (e.g., security constrained economic dispatch) assume a fixed, static transmission grid even though it is rather flexible. The primary barrier is the complexity that is added to the power flow problem. The mathematical representation of the DC optimal power flow, with the added modeling of FACTS devices, is a nonlinear program (NLP). This paper presents a method to convert this NLP into a mixed-integer linear program (MILP). The MILP is reformulated as a two-stage linear program, which enforces the same sign for the voltage angle differences for the lines equipped with FACTS. While this approximation does not guarantee opti¬mality, more than 98% of the presented empirical results, based on the IEEE 118 bus and Polish system, achieved global optimality. In the case of suboptimal solutions, the savings were still significant and the solution time was dramatically reduced.

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Distributional impacts of state-level energy efficiency policies in regional electricity markets

Elsevier - Energy Policy

A number of U.S. states have passed legislation targeting energy efficiency and peak demand reduction. We study one such state, Pennsylvania, within the context of PJM, a regional electricity market covering numerous different states. Our focus is on the distributive impacts of this policy—specifically how the policy is likely to impact electricity prices in different areas of Pennsylvania and in the PJM market more generally. Such spatial differences in policy impacts are difficult to model and the transmission system is often ignored in policy studies. Our model estimates supply curves on a “zonal” basis within regional electricity markets and yields information on price and fuel utilization within each zone. We use the zonal supply curves estimated by our model to study regional impacts of energy-efficiency legislation on utilities both inside and outside of Pennsylvania. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. It would also save 2.1 to 2.8 percent of total energy cost in Pennsylvania in a year similar to 2009. The savings are lower than 0.5 percent in other PJM states and the prices may slightly increase in Washington, DC area.

A dynamic replicator model of the players’ bids in an oligopolistic electricity market

Elsevier - Electric Power System Research

In this paper, the replicator dynamics of the power suppliers’ bids in an oligopolistic electricity market are derived for both the fixed and variable demand cases. The replicator dynamics stability analysis is also performed. The dynamics of the electricity markets are the results of players’ decisions. The physical parameters of the power systems (such as the lines capacities, voltage limitations, etc.) also affect the market dynamics indirectly, through the changes in players’ behaviors. Assuming rational players, an optimal bidding strategy for constructing the supply function (SF) of a generating firm is presented and based on that, the dynamics of the bid replicators are studied. Both fixed demands and price sensitive demands are taken into account. The replicator model is presented in the well-known state space structure. A case study is presented to show the applicability of the developed dynamic replicator bid model, and also to show how the Nash–SFE equilibrium evolves over time.

Estimating zonal electricity supply curves in transmission-constrained electricity markets

Elsevier - Energy

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal.

A Fast LP Approach for Enhanced Utilization of Variable Impedance Based FACTS Devices

IEEE Transactions on Power Systems

Transmission systems are under stress and need to be upgraded. Better utilization of the existing grid provides a fast and cheap alternative to building new transmission. One way to improve the utilization of the transmission network is power flow control via flexible AC transmission system (FACTS) devices. While FACTS devices are used today, the utilization of these devices is limited; traditional dispatch models (e.g., security constrained economic dispatch) assume a fixed, static transmission grid even though it is rather flexible. The primary barrier is the complexity that is added to the power flow problem. The mathematical representation of the DC optimal power flow, with the added modeling of FACTS devices, is a nonlinear program (NLP). This paper presents a method to convert this NLP into a mixed-integer linear program (MILP). The MILP is reformulated as a two-stage linear program, which enforces the same sign for the voltage angle differences for the lines equipped with FACTS. While this approximation does not guarantee opti¬mality, more than 98% of the presented empirical results, based on the IEEE 118 bus and Polish system, achieved global optimality. In the case of suboptimal solutions, the savings were still significant and the solution time was dramatically reduced.

Day-Ahead Corrective Adjustment of FACTS Reactance: A Linear Programming Approach

IEEE Transactions on Power Systems

Reserve requirements serve as a proxy for N-1 reliability in the security-constrained unit commitment (SCUC) problem. However, there is no guarantee that the reserve is deliverable for all scenarios (post-contingency states). One cheap way to improve reserve deliverability is to harness the flexibility of the transmission network. Flexible AC transmission system (FACTS) devices are able to significantly improve the transfer capability. However, FACTS utilization is limited today due to the complexities these devices introduce to the DC optimal power flow problem (DCOPF). With a linear objective, the traditional DCOPF is a linear program (LP); when variable impedance based FACTS devices are taken into consideration, the problem becomes a nonlinear program (NLP). A reformulation of the NLP to a mixed integer linear program, for day-ahead corrective operation of FACTS devices, is presented in this paper. Engineering insight is then introduced to further reduce the complexity to an LP. Although optimality is not guaranteed, the simulation studies on the IEEE 118-bus system show that the method finds the globally optimal solution in 98.8% of the cases. Even when the method did not find the optimal solution, it was able to converge to a near-optimal solution, which substantially improved the reliability, very quickly.

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Distributional impacts of state-level energy efficiency policies in regional electricity markets

Elsevier - Energy Policy

A number of U.S. states have passed legislation targeting energy efficiency and peak demand reduction. We study one such state, Pennsylvania, within the context of PJM, a regional electricity market covering numerous different states. Our focus is on the distributive impacts of this policy—specifically how the policy is likely to impact electricity prices in different areas of Pennsylvania and in the PJM market more generally. Such spatial differences in policy impacts are difficult to model and the transmission system is often ignored in policy studies. Our model estimates supply curves on a “zonal” basis within regional electricity markets and yields information on price and fuel utilization within each zone. We use the zonal supply curves estimated by our model to study regional impacts of energy-efficiency legislation on utilities both inside and outside of Pennsylvania. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. It would also save 2.1 to 2.8 percent of total energy cost in Pennsylvania in a year similar to 2009. The savings are lower than 0.5 percent in other PJM states and the prices may slightly increase in Washington, DC area.

A dynamic replicator model of the players’ bids in an oligopolistic electricity market

Elsevier - Electric Power System Research

In this paper, the replicator dynamics of the power suppliers’ bids in an oligopolistic electricity market are derived for both the fixed and variable demand cases. The replicator dynamics stability analysis is also performed. The dynamics of the electricity markets are the results of players’ decisions. The physical parameters of the power systems (such as the lines capacities, voltage limitations, etc.) also affect the market dynamics indirectly, through the changes in players’ behaviors. Assuming rational players, an optimal bidding strategy for constructing the supply function (SF) of a generating firm is presented and based on that, the dynamics of the bid replicators are studied. Both fixed demands and price sensitive demands are taken into account. The replicator model is presented in the well-known state space structure. A case study is presented to show the applicability of the developed dynamic replicator bid model, and also to show how the Nash–SFE equilibrium evolves over time.

Estimating zonal electricity supply curves in transmission-constrained electricity markets

Elsevier - Energy

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal.

A Fast LP Approach for Enhanced Utilization of Variable Impedance Based FACTS Devices

IEEE Transactions on Power Systems

Transmission systems are under stress and need to be upgraded. Better utilization of the existing grid provides a fast and cheap alternative to building new transmission. One way to improve the utilization of the transmission network is power flow control via flexible AC transmission system (FACTS) devices. While FACTS devices are used today, the utilization of these devices is limited; traditional dispatch models (e.g., security constrained economic dispatch) assume a fixed, static transmission grid even though it is rather flexible. The primary barrier is the complexity that is added to the power flow problem. The mathematical representation of the DC optimal power flow, with the added modeling of FACTS devices, is a nonlinear program (NLP). This paper presents a method to convert this NLP into a mixed-integer linear program (MILP). The MILP is reformulated as a two-stage linear program, which enforces the same sign for the voltage angle differences for the lines equipped with FACTS. While this approximation does not guarantee opti¬mality, more than 98% of the presented empirical results, based on the IEEE 118 bus and Polish system, achieved global optimality. In the case of suboptimal solutions, the savings were still significant and the solution time was dramatically reduced.

Day-Ahead Corrective Adjustment of FACTS Reactance: A Linear Programming Approach

IEEE Transactions on Power Systems

Reserve requirements serve as a proxy for N-1 reliability in the security-constrained unit commitment (SCUC) problem. However, there is no guarantee that the reserve is deliverable for all scenarios (post-contingency states). One cheap way to improve reserve deliverability is to harness the flexibility of the transmission network. Flexible AC transmission system (FACTS) devices are able to significantly improve the transfer capability. However, FACTS utilization is limited today due to the complexities these devices introduce to the DC optimal power flow problem (DCOPF). With a linear objective, the traditional DCOPF is a linear program (LP); when variable impedance based FACTS devices are taken into consideration, the problem becomes a nonlinear program (NLP). A reformulation of the NLP to a mixed integer linear program, for day-ahead corrective operation of FACTS devices, is presented in this paper. Engineering insight is then introduced to further reduce the complexity to an LP. Although optimality is not guaranteed, the simulation studies on the IEEE 118-bus system show that the method finds the globally optimal solution in 98.8% of the cases. Even when the method did not find the optimal solution, it was able to converge to a near-optimal solution, which substantially improved the reliability, very quickly.

Electricity Restructuring Impacts in Rural Pennsylvania

The Center for Rural Pennsylvania

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Distributional impacts of state-level energy efficiency policies in regional electricity markets

Elsevier - Energy Policy

A number of U.S. states have passed legislation targeting energy efficiency and peak demand reduction. We study one such state, Pennsylvania, within the context of PJM, a regional electricity market covering numerous different states. Our focus is on the distributive impacts of this policy—specifically how the policy is likely to impact electricity prices in different areas of Pennsylvania and in the PJM market more generally. Such spatial differences in policy impacts are difficult to model and the transmission system is often ignored in policy studies. Our model estimates supply curves on a “zonal” basis within regional electricity markets and yields information on price and fuel utilization within each zone. We use the zonal supply curves estimated by our model to study regional impacts of energy-efficiency legislation on utilities both inside and outside of Pennsylvania. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. It would also save 2.1 to 2.8 percent of total energy cost in Pennsylvania in a year similar to 2009. The savings are lower than 0.5 percent in other PJM states and the prices may slightly increase in Washington, DC area.

A dynamic replicator model of the players’ bids in an oligopolistic electricity market

Elsevier - Electric Power System Research

In this paper, the replicator dynamics of the power suppliers’ bids in an oligopolistic electricity market are derived for both the fixed and variable demand cases. The replicator dynamics stability analysis is also performed. The dynamics of the electricity markets are the results of players’ decisions. The physical parameters of the power systems (such as the lines capacities, voltage limitations, etc.) also affect the market dynamics indirectly, through the changes in players’ behaviors. Assuming rational players, an optimal bidding strategy for constructing the supply function (SF) of a generating firm is presented and based on that, the dynamics of the bid replicators are studied. Both fixed demands and price sensitive demands are taken into account. The replicator model is presented in the well-known state space structure. A case study is presented to show the applicability of the developed dynamic replicator bid model, and also to show how the Nash–SFE equilibrium evolves over time.

Estimating zonal electricity supply curves in transmission-constrained electricity markets

Elsevier - Energy

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal.

A Fast LP Approach for Enhanced Utilization of Variable Impedance Based FACTS Devices

IEEE Transactions on Power Systems

Transmission systems are under stress and need to be upgraded. Better utilization of the existing grid provides a fast and cheap alternative to building new transmission. One way to improve the utilization of the transmission network is power flow control via flexible AC transmission system (FACTS) devices. While FACTS devices are used today, the utilization of these devices is limited; traditional dispatch models (e.g., security constrained economic dispatch) assume a fixed, static transmission grid even though it is rather flexible. The primary barrier is the complexity that is added to the power flow problem. The mathematical representation of the DC optimal power flow, with the added modeling of FACTS devices, is a nonlinear program (NLP). This paper presents a method to convert this NLP into a mixed-integer linear program (MILP). The MILP is reformulated as a two-stage linear program, which enforces the same sign for the voltage angle differences for the lines equipped with FACTS. While this approximation does not guarantee opti¬mality, more than 98% of the presented empirical results, based on the IEEE 118 bus and Polish system, achieved global optimality. In the case of suboptimal solutions, the savings were still significant and the solution time was dramatically reduced.

Day-Ahead Corrective Adjustment of FACTS Reactance: A Linear Programming Approach

IEEE Transactions on Power Systems

Reserve requirements serve as a proxy for N-1 reliability in the security-constrained unit commitment (SCUC) problem. However, there is no guarantee that the reserve is deliverable for all scenarios (post-contingency states). One cheap way to improve reserve deliverability is to harness the flexibility of the transmission network. Flexible AC transmission system (FACTS) devices are able to significantly improve the transfer capability. However, FACTS utilization is limited today due to the complexities these devices introduce to the DC optimal power flow problem (DCOPF). With a linear objective, the traditional DCOPF is a linear program (LP); when variable impedance based FACTS devices are taken into consideration, the problem becomes a nonlinear program (NLP). A reformulation of the NLP to a mixed integer linear program, for day-ahead corrective operation of FACTS devices, is presented in this paper. Engineering insight is then introduced to further reduce the complexity to an LP. Although optimality is not guaranteed, the simulation studies on the IEEE 118-bus system show that the method finds the globally optimal solution in 98.8% of the cases. Even when the method did not find the optimal solution, it was able to converge to a near-optimal solution, which substantially improved the reliability, very quickly.

Electricity Restructuring Impacts in Rural Pennsylvania

The Center for Rural Pennsylvania

Zonal Electricity Supply Curve Estimation with Fuzzy Fuel Switching Thresholds

USAEE

Many important policy initiatives, such as imposing carbon tax, would directly affect the operation of electric power networks. Evaluating such policies often requires models of how the proposed policy will impact system operations. Predictive modeling of electric transmission systems, particularly in the face of transmission constraints, is difficult unless the analyst possesses a detailed network model. Further, policy analysis must often be performed under time constraints, which may prevent the use of complex engineering models. Our motivation in this paper is to develop a method for estimating zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods (but not necessarily engineering) and with publicly-available data. We develop a fuzzy nonlinear statistical model that uses fuel prices and zonal electric loads to determine piecewise supply curves, each segment of which represents the influence of a particular fuel type on the zonal electricity price. The domain belonging to different fuels can overlap, which means a mixture of two fuels can be marginal. The magnitude of this overlap is a function of the relative fuel prices. Our problem thus requires the simultaneous estimation of the slope of each supply-curve segment, thresholds that define the endpoints of each segment and the level of marginal fuel overlap. We illustrate our methodology by estimating zonal supply curves for the seventeen utility zones in the PJM system. We use then our supply curves to estimate regional impacts of Pennsylvania’s legislative requirement that utilities in Pennsylvania to reduce annual and peak electric load...

Real-Time Contingency Analysis With Transmission Switching on Real Power System Data

IEEE Transactions on Power Systems

Transmission switching (TS) has shown to be an effective power flow control tool. TS can reduce the system cost, improve system reliability,and enhance the management of intermittent renewable resources. This letter addresses the state-of-the-art problem of TS by developing an AC-base d real-time contingency analysis (RTCA) package with TS. The package is tested on real power system data, taken from energy management systems of PJM, TVA, and ERCOT. The results show that post-contingency corrective switching is a ready to be implemented transformational technology that provides substantial reliability gains. The computational time and the performance of the developed RTCA package, reported in this letter, are promising.

A study of electricity market dynamics using Invasive Weed Colonization Optimization

IEEE symposium on computational intelligence and games

A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable. The IWO has also been introduced briefly and it is discussed why this method is supposed to be appropriate in such problems. Several simulation studies are presented to show how the method works. These outputs are compared with what exist in the literature. It is shown that making use of search based optimization algorithms such as IWO is necessary for consideration of all the constraints and details.

Distributional impacts of state-level energy efficiency policies in regional electricity markets

Elsevier - Energy Policy

A number of U.S. states have passed legislation targeting energy efficiency and peak demand reduction. We study one such state, Pennsylvania, within the context of PJM, a regional electricity market covering numerous different states. Our focus is on the distributive impacts of this policy—specifically how the policy is likely to impact electricity prices in different areas of Pennsylvania and in the PJM market more generally. Such spatial differences in policy impacts are difficult to model and the transmission system is often ignored in policy studies. Our model estimates supply curves on a “zonal” basis within regional electricity markets and yields information on price and fuel utilization within each zone. We use the zonal supply curves estimated by our model to study regional impacts of energy-efficiency legislation on utilities both inside and outside of Pennsylvania. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. It would also save 2.1 to 2.8 percent of total energy cost in Pennsylvania in a year similar to 2009. The savings are lower than 0.5 percent in other PJM states and the prices may slightly increase in Washington, DC area.

A dynamic replicator model of the players’ bids in an oligopolistic electricity market

Elsevier - Electric Power System Research

In this paper, the replicator dynamics of the power suppliers’ bids in an oligopolistic electricity market are derived for both the fixed and variable demand cases. The replicator dynamics stability analysis is also performed. The dynamics of the electricity markets are the results of players’ decisions. The physical parameters of the power systems (such as the lines capacities, voltage limitations, etc.) also affect the market dynamics indirectly, through the changes in players’ behaviors. Assuming rational players, an optimal bidding strategy for constructing the supply function (SF) of a generating firm is presented and based on that, the dynamics of the bid replicators are studied. Both fixed demands and price sensitive demands are taken into account. The replicator model is presented in the well-known state space structure. A case study is presented to show the applicability of the developed dynamic replicator bid model, and also to show how the Nash–SFE equilibrium evolves over time.

Estimating zonal electricity supply curves in transmission-constrained electricity markets

Elsevier - Energy

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal.

A Fast LP Approach for Enhanced Utilization of Variable Impedance Based FACTS Devices

IEEE Transactions on Power Systems

Transmission systems are under stress and need to be upgraded. Better utilization of the existing grid provides a fast and cheap alternative to building new transmission. One way to improve the utilization of the transmission network is power flow control via flexible AC transmission system (FACTS) devices. While FACTS devices are used today, the utilization of these devices is limited; traditional dispatch models (e.g., security constrained economic dispatch) assume a fixed, static transmission grid even though it is rather flexible. The primary barrier is the complexity that is added to the power flow problem. The mathematical representation of the DC optimal power flow, with the added modeling of FACTS devices, is a nonlinear program (NLP). This paper presents a method to convert this NLP into a mixed-integer linear program (MILP). The MILP is reformulated as a two-stage linear program, which enforces the same sign for the voltage angle differences for the lines equipped with FACTS. While this approximation does not guarantee opti¬mality, more than 98% of the presented empirical results, based on the IEEE 118 bus and Polish system, achieved global optimality. In the case of suboptimal solutions, the savings were still significant and the solution time was dramatically reduced.

Day-Ahead Corrective Adjustment of FACTS Reactance: A Linear Programming Approach

IEEE Transactions on Power Systems

Reserve requirements serve as a proxy for N-1 reliability in the security-constrained unit commitment (SCUC) problem. However, there is no guarantee that the reserve is deliverable for all scenarios (post-contingency states). One cheap way to improve reserve deliverability is to harness the flexibility of the transmission network. Flexible AC transmission system (FACTS) devices are able to significantly improve the transfer capability. However, FACTS utilization is limited today due to the complexities these devices introduce to the DC optimal power flow problem (DCOPF). With a linear objective, the traditional DCOPF is a linear program (LP); when variable impedance based FACTS devices are taken into consideration, the problem becomes a nonlinear program (NLP). A reformulation of the NLP to a mixed integer linear program, for day-ahead corrective operation of FACTS devices, is presented in this paper. Engineering insight is then introduced to further reduce the complexity to an LP. Although optimality is not guaranteed, the simulation studies on the IEEE 118-bus system show that the method finds the globally optimal solution in 98.8% of the cases. Even when the method did not find the optimal solution, it was able to converge to a near-optimal solution, which substantially improved the reliability, very quickly.

Electricity Restructuring Impacts in Rural Pennsylvania

The Center for Rural Pennsylvania

Zonal Electricity Supply Curve Estimation with Fuzzy Fuel Switching Thresholds

USAEE

Many important policy initiatives, such as imposing carbon tax, would directly affect the operation of electric power networks. Evaluating such policies often requires models of how the proposed policy will impact system operations. Predictive modeling of electric transmission systems, particularly in the face of transmission constraints, is difficult unless the analyst possesses a detailed network model. Further, policy analysis must often be performed under time constraints, which may prevent the use of complex engineering models. Our motivation in this paper is to develop a method for estimating zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods (but not necessarily engineering) and with publicly-available data. We develop a fuzzy nonlinear statistical model that uses fuel prices and zonal electric loads to determine piecewise supply curves, each segment of which represents the influence of a particular fuel type on the zonal electricity price. The domain belonging to different fuels can overlap, which means a mixture of two fuels can be marginal. The magnitude of this overlap is a function of the relative fuel prices. Our problem thus requires the simultaneous estimation of the slope of each supply-curve segment, thresholds that define the endpoints of each segment and the level of marginal fuel overlap. We illustrate our methodology by estimating zonal supply curves for the seventeen utility zones in the PJM system. We use then our supply curves to estimate regional impacts of Pennsylvania’s legislative requirement that utilities in Pennsylvania to reduce annual and peak electric load...