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Robust Operation Planning With Participation of Flexibility Resources Both on Generation and Demand Sides Under Uncertainty of Wind-based Generation Units

A Mansoori, A Sheikhi Fini, M Parsa Moghaddam
Journal Papers , , {Pages }

Abstract

Flexibility-constrained operation scheduling of active distribution networks

S Allahmoradi, MP Moghaddam, S Bahramara, P Sheikhahmadi
Journal Papers , , {Pages }

Abstract

Power System Robust Day-ahead Scheduling with the Presence of Fast-Response Resources Both on Generation and Demand Sides under High Penetration of Wind Generation Units

A Mansoori, AS Fini, MP Moghaddam
Journal Papers , , {Pages }

Abstract

Fast Islanding Detection of Nested Grids Including Multiple Resources Based on Phase Criteria

R Zamani, MP Moghaddam, H Panahi, M Sanaye-Pasand
Journal Papers , , {Pages }

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A novel three-stage risk-based scheme to improve power system resilience against hurricane

M Mahzarnia, MP Moghaddam, MR Haghifam
Journal Papers , , {Pages }

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Convolutional and recurrent neural network based model for short-term load forecasting

H Eskandari, M Imani, MP Moghaddam
Journal Papers , , {Pages }

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Generation expansion planning in multi electricity markets considering environmental impacts

Reza Allahdadi Mehrabadi, Mohsen Parsa Moghaddam, Mohammad Kazem Sheikh-El-Eslami
Journal PapersJournal of Cleaner Production , Volume 243 , 2020 January 10, {Pages 118611 }

Abstract

Inter-area generation expansion planning in a multi-period timescale with minimization of expansion cost and pollution is proposed in this paper. The expansion decision is made in a deregulated environment from the viewpoint of the strategic competitor. In this regard, the GENCO can expand its generation units accessing various generation technologies as candidate expansion plans in the main area. The main area consists of several buses while the adjacent areas are modeled as a single bus. The behavior of the other competitors is considered predictable by the strategic GENCO. In this study, the uncertainties of load, electricity price and wind speed are included. To confront them, rough neural network methodology is employed to forecast the

Regulatory-intervented sustainable generation expansion planning in multi-electricity markets

Reza Allahdadi Mehrabadi, Mohsen Parsa Moghaddam, Mohammad Kazem Sheikh-El-Eslami
Journal PapersSustainable Cities and Society , Volume 52 , 2020 January 1, {Pages 101794 }

Abstract

Nowadays, according to sustainable development targets in modern societies, electricity markets are gradually connecting together. In this way, in this paper, a multi-agent generation expansion planning in a joint multi-electricity market environment is proposed. The GENCO (Generation Company) agents, competing in a deregulated structure, try to obtain the most profitable investment and operation plan regarding the incentives/taxes that the regulatory sector legislates. The multi-area market assumption encourages the GENCOs to offer their energy blocks to adjacent electricity markets whenever the production capacity is higher than the local load. To confront the uncertainties such as wind speed, market price, and load demand, the Markov cha

A new hybrid model for point and probabilistic forecasting of wind power

Reza Tahmasebifar, Mohsen Parsa Moghaddam, Mohammad Kazem Sheikh-El-Eslami, Reza Kheirollahi
Journal PapersEnergy , Volume 211 , 2020 November 15, {Pages 119016 }

Abstract

The accurate and reliable forecasting of wind power is of great importance for electrical systems’ control and operation. However, the intermittent nature of wind power generation implies a complicated forecasting framework. In this paper, a new hybrid model including three steps is proposed for point and probabilistic forecasting of wind power. Within the first step, by using data preprocessing methods, proposed weighted Extreme Learning Machine (ELM) by Mutual Information, and bootstrap approach, point forecasting and variance of the model uncertainties are estimated. In the second step, by employing ELM, bootstrap approach, and an ensemble structure, the noise variance is calculated. During the final step, to improve the results of the

Correlation based Convolutional Recurrent Network for Load Forecasting

Hosein Eskandari, Maryam Imani, Mohsen Parsa Moghadam
Conference Papers2020 28th Iranian Conference on Electrical Engineering (ICEE) , 2020 August 4, {Pages 05-Jan }

Abstract

The safe and economical operation of a power grid is not possible without knowing the future load. For this reason, the first step in terms of productivity and proper management of a system will be to predict the electric load in the future. In this paper, the features that exist in the history of electric load consumption are examined and they are used as a guide for designing the proposed method. We try to predict short-term electric load by extracting the characteristics of the electric load history using deep neural networks. Long Short Term Memory (LSTM), are able to hold short and long-term memory for extracting relationships between the load values from time series. On the other hand, convolution neural networks are capable of automa

A review of the measures to enhance power systems resilience

Maedeh Mahzarnia, Mohsen Parsa Moghaddam, Payam Teimourzadeh Baboli, Pierluigi Siano
Journal PapersIEEE Systems Journal , 2020 January 29, {Pages }

Abstract

Rare and extreme climate events may result in wide power outages or blackouts. The concept of power system resilience has been introduced for focusing on high-impact and low-probability (HILP) events such as a hurricane, heavy snow, and floods. Power system resilience is the ability of a system to reduce the likelihood of blackout or wide power outages due to HILP events. Indeed, in a resilient power system, as the severity of HILP events increases, the rate (but not the amount) of unserved loads diminishes. Suitable measures for managing power system resilience can be classified into three categories in terms of time, known as “resilience-based planning,” “resilience-based response,” and “resilience-based restoration.” The most

Flexibility Enhancement in Active Distribution Networks through a Risk-based Optimal Placement of Sectionalizing Switches

Mahnaz Moradijoz, Saeed Moradijoz, Mohsen Parsa Moghaddam, Mahmoud-Reza Haghifam
Journal PapersReliability Engineering & System Safety , 2020 May 8, {Pages 106985 }

Abstract

The advent of distributed energy resources (DERs) in distribution networks, referred to as active distribution networks (ADNs), brings in new opportunities for distribution network operators (DNOs) to improve the network reliability. The contribution of DERs in reliability enhancement generally depends on the island mode operation of DERs. Optimal placement of sectionalizing switches (SSs) enables ADNs to be operated more reliably by islanding the faulted part of the system in the form of flexible micro-grids (FMGs). However, practical methods are needed to handle the complex problem of the SS placement in ADNs. This paper presents a risk-based two-stage mixed-integer linear programming (MILP) model for the optimal placement of the network-

A Novel Unknown Input Observer-based Measurement Fault Detection and Isolation scheme for Micro-Grid Systems

Hassan Haes Alhelou, MEH Golshan, Nikos D Hatziargyriou, Mohsen Parsa Moghaddam
Journal PapersIEEE Transactions on Industrial Informatics , 2020 January 29, {Pages }

Abstract

Correct measurement of different signals used in the micro-grids control center (MGCC) is crucial for their operation, control, and stability. This is especially true for micro-grids operating in island mode. To keep their operation efficient and safe, faulty sensors should be instantly isolated. To this end, novel sensor fault detection and isolation schemes are proposed in this paper that are built based on unknown input observer method (UIO). In this method, load fluctuations and output power variations of renewable energy sources are modeled as unknown inputs. Theoretical analysis and simulation scenarios are carried out on a micro-grid system which consists of different types of energy generation sources and energy storage systems to p

An Introduction to Blockchain-based Concepts for Demand Response Considering of Electric Vehicles and Renewable Energies

Mohammadreza Shekari, Mohsen Parsa Moghaddam
Conference Papers2020 28th Iranian Conference on Electrical Engineering (ICEE) , 2020 August 4, {Pages 04-Jan }

Abstract

Future of power systems and smart grids will host modern generation and consumption units, e.g., Renewable Energies (REs) and Electric Vehicles (EVs) more rather than traditional ones. Therefore, adopting a method for managing such users in electricity markets with the implementation of Demand Response (DR) programs is required and essential. In this paper, the “Blockchain-based concepts for demand response programs by efficient use of electric vehicles and renewable energies in the electricity markets” are introduced. This process can be accomplished with the utilization of different features of blockchain technology like smart contracts. Implementation of smart contracts in demand response programs could enhance the efficiency of thes

A comprehensive assessment of power system resilience to a hurricane using a two-stage analytical approach incorporating risk-based index

Maedeh Mahzarnia, Mohsen Parsa Moghaddam, Pierluigi Siano, Mahmoud-Reza Haghifam
Journal PapersSustainable Energy Technologies and Assessments , Volume 42 , 2020 December 1, {Pages 100831 }

Abstract

Sustainability of power systems is a vital need for modern societies. The occurrence of extreme weather events, such as hurricanes, may lead to blackouts. Hence, power systems resilience is a critical issue for experts. The main focus of this paper is on how to assess power system resilience comprehensively. In this regard, a two-stage framework is proposed. In the first stage, an approach is presented to evaluate power system resilience against a single intensity of a hurricane, which is called snapshot resilience assessment. The Cost of Energy Not Supplied (CENS) is regarded as a primary criterion. A risk measure called Conditional Value at Risk (CVaR) is incorporated into this approach to manage the risk of experiencing unfavorable failu

Multi-Objective Sizing of Energy Storage Systems (ESSs) and Capacitors in a Distribution System

H Delkhosh, MP Moghaddam, M Ghaedi
Journal Papers , , {Pages }

Abstract

Non-Cooperative Operation of Transmission and Distribution Systems

M Khodadadi, MEH Golshan, MP Moghaddam
Journal Papers , , {Pages }

Abstract

Electric vehicle parking lots as a capacity expansion option in distribution systems: a mixed‐integer linear programing‐based model

M Moradijoz, J Heidari, MP Moghaddam, MR Haghifam
Journal Papers , , {Pages }

Abstract

Modeling of demand response programs based on market elasticity concept

Hasan Jalili, Mohammad Kazem Sheikh-El-Eslami, M Parsa Moghaddam, Pierluigi Siano
Journal PapersJournal of Ambient Intelligence and Humanized Computing , Volume 10 , Issue 6, 2019 June 1, {Pages 2265-2276 }

Abstract

Demand response programs (DRPs) are appropriate tools to improve power system operation. Applying these programs results in a reduction in reliability cost and electricity price, transmission congestion and pollution relief, and also can determine postponements in network expansion. Therefore, developing a comprehensive model for DRPs is necessary for accurate planning and encouragement of consumers to increase their participation. In this paper, by using the market elasticity concept, a comprehensive model for DRPs is developed. Market elasticity is defined as sensitivity of electricity price on the network load. The proposed model is able to increase the consumers’ participation by providing a higher awareness about their

Robust expansion co-planning of electricity and natural gas infrastructures for multi energy-hub systems with high penetration of renewable energy sources

Shahab Karamdel, Mohsen Parsa Moghaddam
Journal PapersIET Renewable Power Generation , 2019 May 29, {Pages }

Abstract

High penetration of renewable energy sources will cause crucial challenges for future energy systems. This study presents a three-level model for adaptive robust expansion co-planning of electricity and natural gas infrastructures in multi-energy-hub networks, which is robust against uncertainties of maximum production of wind generation and gas-fired power plants as well as estimated load levels. The proposed min–max–min model is formulated as a mixed integer linear programming problem. The first level minimises the investment cost of electricity and natural gas infrastructures, the worst possible case is determined through the second level, and the third level minimises the overall operation cost under that condition. To solve this mo

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