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Prosumers play a central role in current distribution networks. Local markets provide an environment for prosumers to interact with each other, either directly through peer-to-peer (P2P) markets, or indirectly via community-based markets. In this paper, we propose a hierarchical approach for local energy and flexibility trading among prosumers in distribution networks, in which prosumers are able to trade energy via P2P manner and transact flexibility in the local energy market to maintain distribution network constraints. The proposed method enables prosumers to manage their resources and participate in a P2P market by submitting their optimal bidding and offering curves. A local market operator runs the P2P market for energy trading among prosumers, and cooperates with the distribution system operator to dispatch the flexibility provided by prosumers. Moreover, a real-world distribution network consisting of ten prosumers is considered to assess the performance of the proposed model for local energy market based on flexible behavior of prosumers in the bottom layer of the distribution network.
Amin Shokri Gazafroudi; Mohsen Khorasany; Reza Razzaghi; Hannu Laaksonen; Miadreza Shafie-Khah. Hierarchical approach for coordinating energy and flexibility trading in local energy markets. Applied Energy 2021, 302, 117575 .
AMA StyleAmin Shokri Gazafroudi, Mohsen Khorasany, Reza Razzaghi, Hannu Laaksonen, Miadreza Shafie-Khah. Hierarchical approach for coordinating energy and flexibility trading in local energy markets. Applied Energy. 2021; 302 ():117575.
Chicago/Turabian StyleAmin Shokri Gazafroudi; Mohsen Khorasany; Reza Razzaghi; Hannu Laaksonen; Miadreza Shafie-Khah. 2021. "Hierarchical approach for coordinating energy and flexibility trading in local energy markets." Applied Energy 302, no. : 117575.
The performance of electric vehicles and their abilities to reduce fossil fuel consumption and air pollution on one hand and the use of photovoltaic (PV) panels in energy production, on the other hand, has encouraged parking lot operators (PLO) to participate in the energy market to gain more profit. However, there are several challenges such as different technologies of photovoltaic panels that make the problem complex in terms of installation cost, efficiency, available output power and dependency on environmental temperature. Therefore, the aim of this study is to maximize the PLO’s operational profit under the time of use energy pricing scheme by investigating the effects of different PV panel technologies on energy production and finding the best strategy for optimal operation of PVs and electric vehicle (EV) parking lots which is achieved by means of market and EV owners’ interaction. For the accurate investigation, four different PV panel technologies are considered in different seasons, with significant differences in daylight times, in Helsinki, Finland.
Mahsa Farahmand; Sara Javadi; Sayyed Sadati; Hannu Laaksonen; Miadreza Shafie-Khah. Optimal Operation of Solar Powered Electric Vehicle Parking Lots Considering Different Photovoltaic Technologies. Clean Technologies 2021, 3, 503 -518.
AMA StyleMahsa Farahmand, Sara Javadi, Sayyed Sadati, Hannu Laaksonen, Miadreza Shafie-Khah. Optimal Operation of Solar Powered Electric Vehicle Parking Lots Considering Different Photovoltaic Technologies. Clean Technologies. 2021; 3 (2):503-518.
Chicago/Turabian StyleMahsa Farahmand; Sara Javadi; Sayyed Sadati; Hannu Laaksonen; Miadreza Shafie-Khah. 2021. "Optimal Operation of Solar Powered Electric Vehicle Parking Lots Considering Different Photovoltaic Technologies." Clean Technologies 3, no. 2: 503-518.
This paper presents a day-ahead scheduling approach for a multi-carrier residential energy system (MRES) including distributed energy resources (DERs). The main objective of the proposed scheduling approach is the minimization of the total costs of an MRES consisting of both electricity and gas energy carriers. The proposed model considers both electrical and natural gas distribution networks, DER technologies including renewable energy resources, energy storage systems (ESSs), and combined heat and power. The uncertainties pertinent to the demand and generated power of renewable resources are modeled using the chance-constrained approach. The proposed model is applied on the IEEE 33-bus distribution system and 14-node gas network, and the results demonstrate the efficacy of the proposed approach in the matters of diminishing the total operation costs and enhancing the reliability of the system.
Reza Habibifar; Hossein Ranjbar; Miadreza Shafie-Khah; Mehdi Ehsan; João P. S. Catalão. Network-Constrained Optimal Scheduling of Multi-Carrier Residential Energy Systems: A Chance-Constrained Approach. IEEE Access 2021, 9, 1 -1.
AMA StyleReza Habibifar, Hossein Ranjbar, Miadreza Shafie-Khah, Mehdi Ehsan, João P. S. Catalão. Network-Constrained Optimal Scheduling of Multi-Carrier Residential Energy Systems: A Chance-Constrained Approach. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StyleReza Habibifar; Hossein Ranjbar; Miadreza Shafie-Khah; Mehdi Ehsan; João P. S. Catalão. 2021. "Network-Constrained Optimal Scheduling of Multi-Carrier Residential Energy Systems: A Chance-Constrained Approach." IEEE Access 9, no. : 1-1.
The recent experiences of extreme weather events highlight the significance of boosting the resilience of distribution systems. In this situation, the resilience of distribution systems planning leads to an efficient solution for protecting the system from these events via line hardening and the installation of distributed generators (DGs). For this aim, this study presents a new two-stage stochastic mixed-integer linear programming model (SMILP) to hedge against natural disaster uncertainty. The first stage involves making investment decisions about line hardening and DG installation. Then, in the second stage, the dynamic microgrids are created according to a master-slave concept with the ability of integrating distributed generators to minimize the cost of loss of load in each uncertain outage scenario. In particular, this paper presents an approach to select the line damage scenarios for the SMILP. In addition, the operational strategies such as load control capability, microgrid formation and network reconfiguration are integrated into the distribution system plans for resilience improvement in both planning and emergency response steps. The simulation results for an IEEE 33-bus test system demonstrate the effectiveness of the proposed model in improving disaster-induced the resilience of distribution systems.
Mostafa Ghasemi; Ahad Kazemi; Mohammad Amin Gilani; Miadreza Shafie-Khah. A stochastic planning model for improving resilience of distribution system considering master-slave distributed generators and network reconfiguration. IEEE Access 2021, 9, 1 -1.
AMA StyleMostafa Ghasemi, Ahad Kazemi, Mohammad Amin Gilani, Miadreza Shafie-Khah. A stochastic planning model for improving resilience of distribution system considering master-slave distributed generators and network reconfiguration. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StyleMostafa Ghasemi; Ahad Kazemi; Mohammad Amin Gilani; Miadreza Shafie-Khah. 2021. "A stochastic planning model for improving resilience of distribution system considering master-slave distributed generators and network reconfiguration." IEEE Access 9, no. : 1-1.
This paper presents a risk-averse stochastic framework for virtual associations (VAs), which are dynamic clusters of prosumers. A VA, as a price taker agent, supports the active participation of prosumers in the day-ahead (DA) electricity market. In this regard, a bi-level optimization model is formulated to optimize the decision-making problem of the VA in the DA market with the main goal of maximizing VA profit and minimizing the total energy costs of prosumers. In this framework, the impacts of peer to peer (P2P) trading among the prosumers and VAs on the offering and bidding strategies of VAs are also considered. In a competition among VAs, the prosumers are able to select the most competitive VA to participate in the DA market. Moreover, due to the uncertainties of market prices, the VA should undertake the risks arising from price volatilities that may cause the VA to suffer from financial loss due to occurrence of some scenarios such as price spikes. To compensate the undesired effects of the occurrence of price spikes, the impacts of demand response (DR) actions and peer to peer (P2P) energy trading among prosumers on the decisions of VA are analyzed. Moreover, an index is defined from which the competitive condition in a retailing layer would be analyzed. Using Nordpool data as a practical test system, the undesired effects of occurrence of price spikes are compensated using demand response (DR) actions and peer to peer (P2P) energy trading among prosumers. Moreover, an index is defined from which the competitive condition in a retailing layer would be analyzed.
Homa Rashidizadeh-Kermani; Mostafa Vahedipour-Dahraie; Miadreza Shafie-Khah; Pierluigi Siano. Optimal bidding of profit-seeking virtual associations of smart prosumers considering peer to peer energy sharing strategy. International Journal of Electrical Power & Energy Systems 2021, 132, 107175 .
AMA StyleHoma Rashidizadeh-Kermani, Mostafa Vahedipour-Dahraie, Miadreza Shafie-Khah, Pierluigi Siano. Optimal bidding of profit-seeking virtual associations of smart prosumers considering peer to peer energy sharing strategy. International Journal of Electrical Power & Energy Systems. 2021; 132 ():107175.
Chicago/Turabian StyleHoma Rashidizadeh-Kermani; Mostafa Vahedipour-Dahraie; Miadreza Shafie-Khah; Pierluigi Siano. 2021. "Optimal bidding of profit-seeking virtual associations of smart prosumers considering peer to peer energy sharing strategy." International Journal of Electrical Power & Energy Systems 132, no. : 107175.
During the ongoing evolution of energy systems toward increasingly flexible, resilient, and digitalized distribution systems, many issues need to be developed. In general, a holistic multi-level systemic view is required on the future enabling technologies, control and management methods, operation and planning principles, regulation as well as market and business models. Increasing integration of intermittent renewable generation and electric vehicles, as well as industry electrification during the evolution, requires a huge amount of flexibility services at multiple time scales and from different voltage levels, resources, and sectors. Active use of distribution network-connected flexible energy resources for flexibility services provision through new marketplaces will also be needed. Therefore, increased collaboration between system operators in operation and planning of the future power system will also become essential during the evolution. In addition, use of integrated cyber-secure, resilient, cost-efficient, and advanced communication technologies and solutions will be of key importance. This paper describes a potential three-stage evolution path toward fully flexible, resilient, and digitalized electricity distribution networks. A special focus of this paper is the evolution and development of adaptive control and management methods as well as compatible collaborative market schemes that can enable the improved provision of flexibility services by distribution network-connected flexible energy resources for local (distribution system operator) and system-wide (transmission system operator) needs.
Hannu Laaksonen; Hosna Khajeh; Chethan Parthasarathy; Miadreza Shafie-Khah; Nikos Hatziargyriou. Towards Flexible Distribution Systems: Future Adaptive Management Schemes. Applied Sciences 2021, 11, 3709 .
AMA StyleHannu Laaksonen, Hosna Khajeh, Chethan Parthasarathy, Miadreza Shafie-Khah, Nikos Hatziargyriou. Towards Flexible Distribution Systems: Future Adaptive Management Schemes. Applied Sciences. 2021; 11 (8):3709.
Chicago/Turabian StyleHannu Laaksonen; Hosna Khajeh; Chethan Parthasarathy; Miadreza Shafie-Khah; Nikos Hatziargyriou. 2021. "Towards Flexible Distribution Systems: Future Adaptive Management Schemes." Applied Sciences 11, no. 8: 3709.
The concept of smart cities has emerged as an ongoing research in recent years. In this case, there is a proven association between the smart cities and the smart devices, which have caused the power systems to become more flexible, controllable and detectable. Along with these promising results, many disputes have been generated over the cyber-attacks as unpredictable destructive threats, if not properly repelled, which could seriously endanger the power system. With this in mind, this paper explores a novel stochastic virtual assignment (SVA) method based on a directed acyclic graph (DAG) approach, where the essential data of the system sections are broadcasted decentralized through the data blocks, as a worthwhile step to deal with the cyber attacks' risk. To do so, an additional security layer is added to the data blocks aiming to enhance the security of the data against the long lasting data sampling by virtually assigning the hash addresses (HAs) to the data blocks, which are randomly changed based on a stochastic process. The basic network architecture is based on a Provchain structure as a new framework to constantly monitor data operation. Two pivotal strategies also represented to deal with the energy and time needed for the HAs generation process, which have improved the proposed method. In this paper, the proposed security framework is implemented in a smart city environment to provide a secure energy transaction platform. Results show the authenticity of this model and demonstrate the effectiveness of the SVA method in decreasing the successful probability of cyber threat, increasing the time needed for the cyber attacker to decrypt and manipulate the data block.
Morteza Sheikh; Jamshid Aghaei; Hossein Chabok; Mahmoud Roustaei; Taher Niknam; Abdollah Kavousi-Fard; Miadreza Shafie-Khah; Joao P. S. Catalao. Synergies Between Transportation Systems, Energy Hub and the Grid in Smart Cities. IEEE Transactions on Intelligent Transportation Systems 2021, PP, 1 -15.
AMA StyleMorteza Sheikh, Jamshid Aghaei, Hossein Chabok, Mahmoud Roustaei, Taher Niknam, Abdollah Kavousi-Fard, Miadreza Shafie-Khah, Joao P. S. Catalao. Synergies Between Transportation Systems, Energy Hub and the Grid in Smart Cities. IEEE Transactions on Intelligent Transportation Systems. 2021; PP (99):1-15.
Chicago/Turabian StyleMorteza Sheikh; Jamshid Aghaei; Hossein Chabok; Mahmoud Roustaei; Taher Niknam; Abdollah Kavousi-Fard; Miadreza Shafie-Khah; Joao P. S. Catalao. 2021. "Synergies Between Transportation Systems, Energy Hub and the Grid in Smart Cities." IEEE Transactions on Intelligent Transportation Systems PP, no. 99: 1-15.
A large amount of renewable energy sources and electric vehicles will be integrated into future electricity distribution and transmission systems. New flexibility services from distribution network are needed to manage the related challenges. This paper proposes a local flexible capacity market (LFCM) in the distribution network providing system-wide and local flexibility services for transmission (TSO) and distribution system operators (DSO). The TSO and the DSO play the role of buyers, whereas prosumers connected to the distribution network are the sellers. The LFCM consists of three stages. At the first stage, the offers of flexibility sellers are matched with the bids of flexibility buyers aiming to maximize the social welfare of all participants. At the second stage, the accepted flexible capacities are checked by the DSO not to violate the constraints of the local network. The third stage accepts the offers of the sellers based on the results of the previous stage. The results related to the chosen case study demonstrate that the local flexible resources can help the DSO control the voltage and manage periods of congestion. Besides, the owners of the resources can obtain revenues by selling flexibility services while improving electricity supply reliability.
Hosna Khajeh; Hooman Firoozi; Mohammad Reza Hesamzadeh; Hannu Laaksonen; Miadreza Shafie-Khah. A Local Capacity Market Providing Local and System-Wide Flexibility Services. IEEE Access 2021, 9, 52336 -52351.
AMA StyleHosna Khajeh, Hooman Firoozi, Mohammad Reza Hesamzadeh, Hannu Laaksonen, Miadreza Shafie-Khah. A Local Capacity Market Providing Local and System-Wide Flexibility Services. IEEE Access. 2021; 9 (99):52336-52351.
Chicago/Turabian StyleHosna Khajeh; Hooman Firoozi; Mohammad Reza Hesamzadeh; Hannu Laaksonen; Miadreza Shafie-Khah. 2021. "A Local Capacity Market Providing Local and System-Wide Flexibility Services." IEEE Access 9, no. 99: 52336-52351.
Distribution network connected distributed energy resources (DER) are able to provide various flexibility services for distribution system operators (DSOs) and transmission system operators (TSOs). These local and system-wide flexibility services offered by DER can support the frequency (f) and voltage (U) management of a future power system with large amounts of weather-dependent renewable generation and electric vehicles. Depending on the magnitude of frequency deviation, other active network management-based frequency control services for TSOs could also be provided by DSOs in coordination with adaptive control of DER. This paper proposes utilisation of demand response based on frequency-dependent HV/MV transformer on-load tap-changer (OLTC) operation in case of larger frequency deviations. The main principle underlying the proposed scheme lies in the voltage dependency of the distribution network connected loads. In this paper, it is also proposed to, simultaneously with frequency-dependent OLTC control, utilise reverse reactive power -voltage (QU) - and adaptive active power -voltage (PU) -droops with distribution network connected DER units during these larger frequency deviations, in order to enable better frequency support service for TSOs from DSO networks. The effectivity and potential of the proposed schemes are shown through PSCAD simulations. In addition, this paper also presents a holistic and collaborative view of potential future frequency control services which are provided by DSO network-connected resources for TSOs at different frequency deviation levels.
Hannu Laaksonen; Chethan Parthasarathy; Hosna Khajeh; Miadreza Shafie-Khah; Nikos Hatziargyriou. Flexibility Services Provision by Frequency-Dependent Control of On-Load Tap-Changer and Distributed Energy Resources. IEEE Access 2021, 9, 45587 -45599.
AMA StyleHannu Laaksonen, Chethan Parthasarathy, Hosna Khajeh, Miadreza Shafie-Khah, Nikos Hatziargyriou. Flexibility Services Provision by Frequency-Dependent Control of On-Load Tap-Changer and Distributed Energy Resources. IEEE Access. 2021; 9 (99):45587-45599.
Chicago/Turabian StyleHannu Laaksonen; Chethan Parthasarathy; Hosna Khajeh; Miadreza Shafie-Khah; Nikos Hatziargyriou. 2021. "Flexibility Services Provision by Frequency-Dependent Control of On-Load Tap-Changer and Distributed Energy Resources." IEEE Access 9, no. 99: 45587-45599.
This study presents the optimal model of the coordinated flexible energy and self‐healing management (C‐FE&SH‐M) in the active distribution network (ADN) including renewable energy sources (RESs), electric vehicles (EVs) and demand response program (DRP).The flexible energy management (FEM) is extracted using coordination between the RESs, EVs and DRP. The self‐healing method (SHM) is related to multi‐agent system‐based restoration process (MAS‐based RP) that finds the optimal restoration pattern at the fault condition according to the different zone agents (ZAs) distributing along with the network. This method minimizes the difference between energy cost and flexibility benefit related to the FEM part and difference between the number of switching operation and priority loads restored based on the SHM part. Also, this problem subjects to power flow equations, RESs and active loads constraints, restoration process formulation and system operation limits. Stochastic programming is used to model the uncertainty of loads, energy prices, RESs and EVs. Hereupon, the suggested strategy is implemented on the 33‐bus radial distribution network and it is solved by the crow search algorithm (CSA). Ultimately, the obtained results imply the high flexibility and security of the operation, incorporating the proposed strategy, and delineate the optimal restoration scheme for the ADN.
Leila Bagherzadeh; Hossein Shayeghi; Sasan Pirouzi; Miadreza Shafie‐Khah; João P. S. Catalão. Coordinated flexible energy and self‐healing management according to the multi‐agent system‐based restoration scheme in active distribution network. IET Renewable Power Generation 2021, 15, 1765 -1777.
AMA StyleLeila Bagherzadeh, Hossein Shayeghi, Sasan Pirouzi, Miadreza Shafie‐Khah, João P. S. Catalão. Coordinated flexible energy and self‐healing management according to the multi‐agent system‐based restoration scheme in active distribution network. IET Renewable Power Generation. 2021; 15 (8):1765-1777.
Chicago/Turabian StyleLeila Bagherzadeh; Hossein Shayeghi; Sasan Pirouzi; Miadreza Shafie‐Khah; João P. S. Catalão. 2021. "Coordinated flexible energy and self‐healing management according to the multi‐agent system‐based restoration scheme in active distribution network." IET Renewable Power Generation 15, no. 8: 1765-1777.
The problem of electricity load forecasting has emerged as an essential topic for power systems and electricity markets seeking to minimize costs. However, this topic has a high level of complexity. Nevertheless, CNN architecture design remains a challenging problem. Moreover, designing an optimal architecture for CNNs leads to improve their performance in the prediction process. This paper proposes an effective approach for the electricity load forecasting problem using a deep neuroevolution algorithm to automatically design the CNN structures using a novel modified evolutionary algorithm called EGWO. The architecture of CNNs and its hyperparameters are optimized by the novel discrete EGWO algorithm for enhancing its load forecasting accuracy. The proposed method is evaluated on real time data obtained from data sets of Australian Energy Market Operator in the year 2018. The simulation results demonstrated that the proposed method outperforms other compared forecasting algorithms based on different evaluation metrics.
Seyed Mohammad Jafar Jalali; Sajad Ahmadian; Abbas Khosravi; Miadreza Shafie-Khah; Saeid Nahavandi; Joao P. S. Catalao. A Novel Evolutionary-Based Deep Convolutional Neural Network Model for Intelligent Load Forecasting. IEEE Transactions on Industrial Informatics 2021, 17, 8243 -8253.
AMA StyleSeyed Mohammad Jafar Jalali, Sajad Ahmadian, Abbas Khosravi, Miadreza Shafie-Khah, Saeid Nahavandi, Joao P. S. Catalao. A Novel Evolutionary-Based Deep Convolutional Neural Network Model for Intelligent Load Forecasting. IEEE Transactions on Industrial Informatics. 2021; 17 (12):8243-8253.
Chicago/Turabian StyleSeyed Mohammad Jafar Jalali; Sajad Ahmadian; Abbas Khosravi; Miadreza Shafie-Khah; Saeid Nahavandi; Joao P. S. Catalao. 2021. "A Novel Evolutionary-Based Deep Convolutional Neural Network Model for Intelligent Load Forecasting." IEEE Transactions on Industrial Informatics 17, no. 12: 8243-8253.
This paper proposes a data-driven chance-constrained optimal gas-power flow (OGPF) calculation method without any prior assumption on the distribution of uncertainties of wind power generation. The Gaussian mixture model is employed to fit the uncertainty distribution, where the Bayesian nonparametric Dirichlet process is adopted to tune the component number. To facilitate the online application of the proposed methods, an online-offline double-track distribution construction approach is established, where the frequency of training the relatively time-consuming Dirichlet process Gaussian mixture model can be reduced. On account of the quadratic gas consumption expression of gas-fired generators as well as the linear decision rule based uncertainty mitigation mechanism, the chance constraints would become quadratic ones with quadratic terms of uncertainties, which makes the proposed model more intractable. An equivalent linear separable counterpart is then provided for the quadratic chance constraints, after which the intractable chance constraints could be converted into traditional linear ones. The convex-concave procedure is used to crack the nonconvex Weymouth equation in the gas network and the auxiliary quadratic equalities. Simulation results on two test systems validate the effectiveness of the proposed methods.
Jingyao Wang; Cheng Wang; Yile Liang; Tianshu Bi; Miadreza Shafie-Khah; Joao P. S. Catalao. Data-Driven Chance-Constrained Optimal Gas-Power Flow Calculation: A Bayesian Nonparametric Approach. IEEE Transactions on Power Systems 2021, 36, 4683 -4698.
AMA StyleJingyao Wang, Cheng Wang, Yile Liang, Tianshu Bi, Miadreza Shafie-Khah, Joao P. S. Catalao. Data-Driven Chance-Constrained Optimal Gas-Power Flow Calculation: A Bayesian Nonparametric Approach. IEEE Transactions on Power Systems. 2021; 36 (5):4683-4698.
Chicago/Turabian StyleJingyao Wang; Cheng Wang; Yile Liang; Tianshu Bi; Miadreza Shafie-Khah; Joao P. S. Catalao. 2021. "Data-Driven Chance-Constrained Optimal Gas-Power Flow Calculation: A Bayesian Nonparametric Approach." IEEE Transactions on Power Systems 36, no. 5: 4683-4698.
Mostafa Vahedipour-Dahraie; Homa Rashidizadeh-Kermani; Miadreza Shafie-Khah; Joao P. S. Catalao. Risk-Averse Optimal Energy and Reserve Scheduling for Virtual Power Plants Incorporating Demand Response Programs. IEEE Transactions on Smart Grid 2021, 12, 1405 -1415.
AMA StyleMostafa Vahedipour-Dahraie, Homa Rashidizadeh-Kermani, Miadreza Shafie-Khah, Joao P. S. Catalao. Risk-Averse Optimal Energy and Reserve Scheduling for Virtual Power Plants Incorporating Demand Response Programs. IEEE Transactions on Smart Grid. 2021; 12 (2):1405-1415.
Chicago/Turabian StyleMostafa Vahedipour-Dahraie; Homa Rashidizadeh-Kermani; Miadreza Shafie-Khah; Joao P. S. Catalao. 2021. "Risk-Averse Optimal Energy and Reserve Scheduling for Virtual Power Plants Incorporating Demand Response Programs." IEEE Transactions on Smart Grid 12, no. 2: 1405-1415.
The generation mix of Portugal now contains a significant amount of variable renewable energy sources (RES) and the amount of RES is expected to grow substantially. This has led to concerns being raised regarding the security of the supply of the Portuguese electric system as well as concerns relating to system inertia. Deploying and efficiently using various flexibility options is proposed as a solution to these concerns. Among these flexibility options proposed is the use of battery energy storage systems (BESSs) as well as relaxing system inertia constraints such as the system nonsynchronous penetration (SNSP). This article proposes a stochastic mixed-integer linear programming problem formulation, which examines the effects of deploying BESS in a power system. The model is deployed on a real-world test case and results show that the optimal use of BESS can reduce system costs by as much as 10% relative to a baseline scenario and the costs are reduced further when the SNSP constraint is relaxed. The amount of RES curtailment is also reduced with the increased flexibility of the power system through the use of BESS. Thus, the efficiency of the Portuguese transmission system is greatly increased by the use of flexibility measures, primarily the use of BESS.
Sergio F. Santos; Matthew Gough; Desta Z. Fitiwi; Andre F. P. Silva; Miadreza Shafie-Khah; Joao P. S. Catalao. Influence of Battery Energy Storage Systems on Transmission Grid Operation With a Significant Share of Variable Renewable Energy Sources. IEEE Systems Journal 2021, PP, 1 -12.
AMA StyleSergio F. Santos, Matthew Gough, Desta Z. Fitiwi, Andre F. P. Silva, Miadreza Shafie-Khah, Joao P. S. Catalao. Influence of Battery Energy Storage Systems on Transmission Grid Operation With a Significant Share of Variable Renewable Energy Sources. IEEE Systems Journal. 2021; PP (99):1-12.
Chicago/Turabian StyleSergio F. Santos; Matthew Gough; Desta Z. Fitiwi; Andre F. P. Silva; Miadreza Shafie-Khah; Joao P. S. Catalao. 2021. "Influence of Battery Energy Storage Systems on Transmission Grid Operation With a Significant Share of Variable Renewable Energy Sources." IEEE Systems Journal PP, no. 99: 1-12.
Solar energy usage is thriving day by day. These solar panels are installed to absorb solar energy and produce electrical energy. As a result, the efficiency of solar panels depends on different environmental factors, namely, air temperature, dust (aerosols and accumulated dust), and solar incidence, and photovoltaic panel angles. The effects of real conditions factors on power and efficiency of photovoltaic panels are studied in this paper through testing the panel in real environmental tests. To study the mentioned parameters precisely, two panels with different angles are used. The case study is regarding a region of Tehran, Iran, in summer and winter seasons. The results show that panel efficiency during winter is higher than summer due to air temperature decrement. It is discovered that among air pollutants, Al and Fe have the most share in polluting the air that affect the photovoltaic efficiency. Moreover, measuring the accumulated dust on the panels shows more amount in winter in comparison with summer. The important point in studying the effect of tilt angle is that inconformity between solar incidence and photovoltaic panel angles would result in solar radiation absorption and eventually panel efficiency loss and also, photovoltaic panel installation angle would affect the amount of dust deposited on its surface.
Mahsa Farahmand; M. Nazari; S. Shamlou; Miadreza Shafie-Khah. The Simultaneous Impacts of Seasonal Weather and Solar Conditions on PV Panels Electrical Characteristics. Energies 2021, 14, 845 .
AMA StyleMahsa Farahmand, M. Nazari, S. Shamlou, Miadreza Shafie-Khah. The Simultaneous Impacts of Seasonal Weather and Solar Conditions on PV Panels Electrical Characteristics. Energies. 2021; 14 (4):845.
Chicago/Turabian StyleMahsa Farahmand; M. Nazari; S. Shamlou; Miadreza Shafie-Khah. 2021. "The Simultaneous Impacts of Seasonal Weather and Solar Conditions on PV Panels Electrical Characteristics." Energies 14, no. 4: 845.
Microgrids active characteristics such as grid-connected or islanded operation mode, the distributed generators with an intermittent nature, and bidirectional power flow in active distribution lines lead to malfunction of traditional protection schemes. In this article, an impedance-based fault detection scheme is proposed as the main protection of microgrids by applying the proposed equivalent circuits for doubly-fed lines. In this scheme, relay location data and positive sequence voltage absolute value of the other end of the line are used. It can detect even high impedance faults in grid-connected and islanded modes. It is robust against load and generation uncertainties and network reconfigurations. Low sampling rate and minimum data exchange are among the advantages of the proposed scheme. Moreover, a backup protection scheme based on the conductance variations is suggested. No requirement for the communication link is a distinguished advantage of the proposed backup protection scheme. The proposed schemes have been simulated using PSCAD and MATLAB software and the results confirmed their validity.
Seyyed Mohammad Nobakhti; Abbas Ketabi; Miadreza Shafie-Khah. A New Impedance-Based Main and Backup Protection Scheme for Active Distribution Lines in AC Microgrids. Energies 2021, 14, 274 .
AMA StyleSeyyed Mohammad Nobakhti, Abbas Ketabi, Miadreza Shafie-Khah. A New Impedance-Based Main and Backup Protection Scheme for Active Distribution Lines in AC Microgrids. Energies. 2021; 14 (2):274.
Chicago/Turabian StyleSeyyed Mohammad Nobakhti; Abbas Ketabi; Miadreza Shafie-Khah. 2021. "A New Impedance-Based Main and Backup Protection Scheme for Active Distribution Lines in AC Microgrids." Energies 14, no. 2: 274.
This paper proposes a unified solution to address the energy issues in net zero energy building (ZEB), as a new contribution to earlier studies. The multi carrier energy system including hydro-wind-solar-hydrogen-methane-carbon dioxide-thermal energies is integrated and modeled in ZEB. The electrical sector is supplied by hydro-wind-solar, combined heat and power, and pumped hydro storage. The purpose is to minimize the released CO2 to the atmosphere while all the electrical-thermal load demands are successfully supplied following events and disruptions. The model improves the energy resilience and minimizes the environmental pollutions simultaneously. The results demonstrate that the developed model reduces the CO2 pollution by about 33451 kg per year. The model is a resilient energy system that can handle all failures of components and supply both the thermal and electrical loads following events. The model can efficiently handle 26% increment in the electrical loads and 110% increment in the thermal loads.
Hasan Mehrjerdi; Reza Hemmati; Miadreza Shafie-Khah; Joao P. S. Catalao. Zero Energy Building by Multicarrier Energy Systems including Hydro, Wind, Solar, and Hydrogen. IEEE Transactions on Industrial Informatics 2020, 17, 5474 -5484.
AMA StyleHasan Mehrjerdi, Reza Hemmati, Miadreza Shafie-Khah, Joao P. S. Catalao. Zero Energy Building by Multicarrier Energy Systems including Hydro, Wind, Solar, and Hydrogen. IEEE Transactions on Industrial Informatics. 2020; 17 (8):5474-5484.
Chicago/Turabian StyleHasan Mehrjerdi; Reza Hemmati; Miadreza Shafie-Khah; Joao P. S. Catalao. 2020. "Zero Energy Building by Multicarrier Energy Systems including Hydro, Wind, Solar, and Hydrogen." IEEE Transactions on Industrial Informatics 17, no. 8: 5474-5484.
The distribution networks can convincingly break down into small-scale self-controllable areas, namely microgrids to substitute microgrids arrangements for effectively coping with any perturbations. To achieve these targets, this paper examines a novel spatiotemporal algorithm to split the existing network into a set of self-healing microgrids. The main intention in the grid-tied state is to maximize the microgrids profit while equilibrating load and generation at the islanded state by sectionalizing on-fault area, executing resources rescheduling, network reconfiguration and load shedding when the main grid is interrupted. The proposed problem is formulated as an exact computationally efficient mixed integer linear programming problem relying on the column & constraint generation framework and an adjustable interval optimization is envisaged to make the microgrids less susceptible against renewables variability. Finally, the effectiveness of the proposed model is adequately assured by performing a realistic case study.
Farhad Samadi Gazijahani; Javad Salehi; Miadreza Shafie-Khah; Joao P. S. Catalao. Spatiotemporal Splitting of Distribution Networks Into Self-Healing Resilient Microgrids Using an Adjustable Interval Optimization. IEEE Transactions on Industrial Informatics 2020, 17, 5218 -5229.
AMA StyleFarhad Samadi Gazijahani, Javad Salehi, Miadreza Shafie-Khah, Joao P. S. Catalao. Spatiotemporal Splitting of Distribution Networks Into Self-Healing Resilient Microgrids Using an Adjustable Interval Optimization. IEEE Transactions on Industrial Informatics. 2020; 17 (8):5218-5229.
Chicago/Turabian StyleFarhad Samadi Gazijahani; Javad Salehi; Miadreza Shafie-Khah; Joao P. S. Catalao. 2020. "Spatiotemporal Splitting of Distribution Networks Into Self-Healing Resilient Microgrids Using an Adjustable Interval Optimization." IEEE Transactions on Industrial Informatics 17, no. 8: 5218-5229.
In this study, a privacy-based demand response (DR) trading scheme among end-users and DR aggregators (DRAs) is proposed within the retail market framework and by distribution platform optimiser. This scheme aims to obtain the optimum DR volume to be exchanged while considering both DRAs' and customers' preferences. A bi-level programming model is formulated in a day-ahead market within retail markets. In the upper-level problem, the total operation cost of the distribution system is minimised. The production volatility of renewable energy resources is also taken into account in this level through stochastic two-stage programming and Monte–Carlo simulation method. In the lower-level problem, the electricity bill for customers is minimised for customers. The income from DR selling is maximised based on DR prices through secure communication of household energy management systems and DRA. To solve this convex and continuous bi-level problem, it is converted to an equivalent single-level problem by adding primal and dual constraints of lower level as well as its strong duality condition to the upper-level problem. The results demonstrate the effectiveness of different DR prices and different number of DRAs on hourly DR volume, hourly DR cost and power exchange between the studied network and the upstream network.
Saber Talari; Miadreza Shafie‐Khah; Nadali Mahmoudi; Pierluigi Siano; Wei Wei; João P.S. Catalão. Optimal management of demand response aggregators considering customers' preferences within distribution networks. IET Generation, Transmission & Distribution 2020, 14, 5571 -5579.
AMA StyleSaber Talari, Miadreza Shafie‐Khah, Nadali Mahmoudi, Pierluigi Siano, Wei Wei, João P.S. Catalão. Optimal management of demand response aggregators considering customers' preferences within distribution networks. IET Generation, Transmission & Distribution. 2020; 14 (23):5571-5579.
Chicago/Turabian StyleSaber Talari; Miadreza Shafie‐Khah; Nadali Mahmoudi; Pierluigi Siano; Wei Wei; João P.S. Catalão. 2020. "Optimal management of demand response aggregators considering customers' preferences within distribution networks." IET Generation, Transmission & Distribution 14, no. 23: 5571-5579.
With the mushrooming of distributed renewable generation, energy storage unit (ESU) is becoming increasingly important in residential energy systems. This letter proposes a fractional programming model to determine the optimal power and energy capacities of residential ESUs, aiming at minimizing the ratio between the reduced electricity tariff and the investment cost of ESU, ensuring the minimal payback time. A decomposition algorithm is developed to solve the fractional program based on convex optimization; the subproblem is a dual convex quadratic program which provides cutting planes, and the master problem comes down to a small linear program after variable transformations. Compared to the widely used cost-minimum method, the proposed model is cost-efficient: it enjoys a higher rate of return which is usually welcomed by smaller consumers.
Wei Wei; Zhaojian Wang; Feng Liu; Miadreza Shafie-Khah; Joao P. S. Catalao. Cost-Efficient Deployment of Storage Unit in Residential Energy Systems. IEEE Transactions on Power Systems 2020, 36, 525 -528.
AMA StyleWei Wei, Zhaojian Wang, Feng Liu, Miadreza Shafie-Khah, Joao P. S. Catalao. Cost-Efficient Deployment of Storage Unit in Residential Energy Systems. IEEE Transactions on Power Systems. 2020; 36 (1):525-528.
Chicago/Turabian StyleWei Wei; Zhaojian Wang; Feng Liu; Miadreza Shafie-Khah; Joao P. S. Catalao. 2020. "Cost-Efficient Deployment of Storage Unit in Residential Energy Systems." IEEE Transactions on Power Systems 36, no. 1: 525-528.