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Mousa Marzband
Department of Mathematics, Physics, and Electrical Engineering, Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne NE1 8ST, UK

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Review
Published: 29 July 2021 in Processes
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Optimal power flow (OPF), a mathematical programming problem extending power flow relationships, is one of the essential tools in the operation and control of power grids. To name but a few, the primary goals of OPF are to meet system demand at minimum production cost, minimum emission, and minimum voltage deviation. Being at the heart of power system problems for half a century, the OPF can be split into two significant categories, namely optimal active power flow (OAPF) and optimal reactive power flow (ORPF). The OPF is spontaneously a complicated non-linear and non-convex problem; however, it becomes more complex by considering different constraints and restrictions having to do with real power grids. Furthermore, power system operators in the modern-day power networks implement new limitations to the problem. Consequently, the OPF problem becomes more and more complex which can exacerbate the situation from mathematical and computational standpoints. Thus, it is crucially important to decipher the most appropriate methods to solve different types of OPF problems. Although a copious number of mathematical-based methods have been employed to handle the problem over the years, there exist some counterpoints, which prevent them from being a universal solver for different versions of the OPF problem. To address such issues, innovative alternatives, namely heuristic algorithms, have been introduced by many researchers. Inasmuch as these state-of-the-art algorithms show a significant degree of convenience in dealing with a variety of optimization problems irrespective of their complexities, they have been under the spotlight for more than a decade. This paper provides an extensive review of the latest applications of heuristic-based optimization algorithms so as to solve different versions of the OPF problem. In addition, a comprehensive review of the available methods from various dimensions is presented. Reviewing about 200 works is the most significant characteristic of this paper that adds significant value to its exhaustiveness.

ACS Style

Ehsan Naderi; Hossein Narimani; Mahdi Pourakbari-Kasmaei; Fernando Cerna; Mousa Marzband; Matti Lehtonen. State-of-the-Art of Optimal Active and Reactive Power Flow: A Comprehensive Review from Various Standpoints. Processes 2021, 9, 1319 .

AMA Style

Ehsan Naderi, Hossein Narimani, Mahdi Pourakbari-Kasmaei, Fernando Cerna, Mousa Marzband, Matti Lehtonen. State-of-the-Art of Optimal Active and Reactive Power Flow: A Comprehensive Review from Various Standpoints. Processes. 2021; 9 (8):1319.

Chicago/Turabian Style

Ehsan Naderi; Hossein Narimani; Mahdi Pourakbari-Kasmaei; Fernando Cerna; Mousa Marzband; Matti Lehtonen. 2021. "State-of-the-Art of Optimal Active and Reactive Power Flow: A Comprehensive Review from Various Standpoints." Processes 9, no. 8: 1319.

Journal article
Published: 17 July 2021 in Applied Energy
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This paper focuses on cooperative scheduling of the integrated plug-in hybrid electric vehicle fleets and wind farm system (IWPHEVS) in the day-ahead wholesale market (DWM), as well as its effects on the market outcomes and price, as a price-maker player. In this regard, a multi-objective two-stage bi-level hybrid stochastic-robust offering/bidding and scheduling strategy is developed. The upper-level problem, which is that of the IWPHEVS operator, encompasses two objectives, namely cost and emission. The cost objective is comprised of operational costs and the cost of power that is purchased in DWM. Additionally, the plug-in hybrid electric vehicles (PHEVs) are congregated into distinct fleets through k-means clustering. To inscribe PHEVs’ battery erosion, a comprehensive battery erosion model is comprehended, which is linearized by semi-integer variables. The uncertain data sets, such as vehicle fleets arrival/departure timings and their travelled miles are represented as scenarios according to their empirical distribution, which is acquired from the National household travel survey (NHTS). On the flip side, the wind power, which is a more unpredictable parameter, is designed as a robust optimization (RO) set, as it is apt to enhance the reliability issues regarding wind volatilities. The lower-level, embodies the wholesale market operator that has the objective of maximizing social welfare. Conclusively, different case studies of dump, smart and multi-objective charging are meticulously investigated to testify the potency of the proposed method. Based on the obtained findings on the proposed smart multi-objective framework, the IWPHEVS as a price-maker player, can manipulate locational marginal price as much as 4.4%, while the emissions can be curtailed by 40%.

ACS Style

Saeed Zeynali; Nima Nasiri; Mousa Marzband; Sajad Najafi Ravadanegh. A hybrid robust-stochastic framework for strategic scheduling of integrated wind farm and plug-in hybrid electric vehicle fleets. Applied Energy 2021, 300, 117432 .

AMA Style

Saeed Zeynali, Nima Nasiri, Mousa Marzband, Sajad Najafi Ravadanegh. A hybrid robust-stochastic framework for strategic scheduling of integrated wind farm and plug-in hybrid electric vehicle fleets. Applied Energy. 2021; 300 ():117432.

Chicago/Turabian Style

Saeed Zeynali; Nima Nasiri; Mousa Marzband; Sajad Najafi Ravadanegh. 2021. "A hybrid robust-stochastic framework for strategic scheduling of integrated wind farm and plug-in hybrid electric vehicle fleets." Applied Energy 300, no. : 117432.

Journal article
Published: 13 July 2021 in Sustainability
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With a goal of achieving net-zero emissions by developing Smart Cities (SCs) and industrial decarbonization, there is a growing desire to decarbonize the renewable energy sector by accelerating green buildings (GBs) construction, electric vehicles (EVs), and ensuring long-term stability, with the expectation that emissions will need to be reduced by at least two thirds by 2035 and by at least 90% by 2050. Implementing GBs in urban areas and encouraging the use of EVs are cornerstones of transition towards SCs, and practical actions that governments can consider to help with improving the environment and develop SCs. This paper investigates different aspects of smart cities development and introduces new feasible indicators related to GBs and EVs in designing SCs, presenting existing barriers to smart cities development, and solutions to overcome them. The results demonstrate that feasible and achievable policies such as the development of the zero-energy, attention to design parameters, implementation of effective indicators for GBs and EVs, implementing strategies to reduce the cost of production of EVs whilst maintaining good quality standards, load management, and integrating EVs successfully into the electricity system, are important in smart cities development. Therefore, strategies to governments should consider the full dynamics and potential of socio-economic and climate change by implementing new energy policies on increasing investment in EVs, and GBs development by considering energy, energy, techno-economic, and environmental benefits.

ACS Style

Armin Razmjoo; Meysam Nezhad; Lisa Kaigutha; Mousa Marzband; SeyedAli Mirjalili; Mehdi Pazhoohesh; Saim Memon; Mehdi Ehyaei; Giuseppe Piras. Investigating Smart City Development Based on Green Buildings, Electrical Vehicles and Feasible Indicators. Sustainability 2021, 13, 7808 .

AMA Style

Armin Razmjoo, Meysam Nezhad, Lisa Kaigutha, Mousa Marzband, SeyedAli Mirjalili, Mehdi Pazhoohesh, Saim Memon, Mehdi Ehyaei, Giuseppe Piras. Investigating Smart City Development Based on Green Buildings, Electrical Vehicles and Feasible Indicators. Sustainability. 2021; 13 (14):7808.

Chicago/Turabian Style

Armin Razmjoo; Meysam Nezhad; Lisa Kaigutha; Mousa Marzband; SeyedAli Mirjalili; Mehdi Pazhoohesh; Saim Memon; Mehdi Ehyaei; Giuseppe Piras. 2021. "Investigating Smart City Development Based on Green Buildings, Electrical Vehicles and Feasible Indicators." Sustainability 13, no. 14: 7808.

Journal article
Published: 10 July 2021 in Sustainable Cities and Society
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In recent years, multi-energy microgrid (MEM) has gained increasing interest, which could use clean and efficient electro-thermal resources, multi-energy storages (MESs) and demand response potential to improve the flexibility of MEM. However, maximizing the flexibility potential of MEM and alongside managing the electrical parameters (EPs) is a challenging modeling problem. In this paper, a probabilistic nonlinear model is presented to maximize the flexibility with all the power grid constraints taking into account EPs constraints using power flow. To this end, voltage profile and congestion improvement, robust thermal comfort provision during reserve call and MESs utilization are the key properties of the proposed model. The outcome of suggested model ensures sustainability in the MEM performance, which is an essential feature in modern smart cities. The presented model is applied to a distribution network in the UK and results illustrate how equipment scheduling and demand response leads to observe the EPs limitation and maximizes MEM flexibility. The achieved results show a decrease in MEM revenue (decrease of 34% and 24% without and with reserve commitment, respectively) and in contrast, a significant increase in flexibility compared to non-compliance with EPs constraints.

ACS Style

S. Mahdi Kazemi-Razi; Hossein Askarian Abyaneh; Hamed Nafisi; Zunaib Ali; Mousa Marzband. Enhancement of flexibility in multi-energy microgrids considering voltage and congestion improvement: Robust thermal comfort against reserve calls. Sustainable Cities and Society 2021, 74, 103160 .

AMA Style

S. Mahdi Kazemi-Razi, Hossein Askarian Abyaneh, Hamed Nafisi, Zunaib Ali, Mousa Marzband. Enhancement of flexibility in multi-energy microgrids considering voltage and congestion improvement: Robust thermal comfort against reserve calls. Sustainable Cities and Society. 2021; 74 ():103160.

Chicago/Turabian Style

S. Mahdi Kazemi-Razi; Hossein Askarian Abyaneh; Hamed Nafisi; Zunaib Ali; Mousa Marzband. 2021. "Enhancement of flexibility in multi-energy microgrids considering voltage and congestion improvement: Robust thermal comfort against reserve calls." Sustainable Cities and Society 74, no. : 103160.

Journal article
Published: 30 April 2021 in Journal of Cleaner Production
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With the ever-increasing growth of electric vehicles (EV)s in the power industry, their significance as a flexible load has increased drastically. On the other hand, uncontrolled charging of these vehicles can cause serious problems in the grid, such as a peak in demand, a decrease in the life expectancy of transformers and as a result, an increase in charging costs of EVs for the EV owners. In this paper, a framework for day-ahead optimal charging of EVs is proposed which through optimization of active and reactive power exchange at each time interval, could prevent the problems mentioned above and at the same time increase the benefit of EV owners and network operators simultaneously. Furthermore, taking into account the effective factors on electrical energy consumption of EVs and the driving pattern of their owners, a route mapping algorithm is developed based on the proposed framework, so as to provide the EV owners with better services. The simulations are carried out using a hybrid interior-point optimization approach, based on traffic and geographic data collected from the city of Kowloon and a standard IEEE 33 bus system is used. The simulation results show that integrating optimal charging of EVs with a route mapping algorithm into the proposed framework can reduce the loss costs of the network during the hours of EVs’ presence in the framework and the selling price of electricity to EV owners by 24.93% and 33.6%, respectively in comparison with the uncontrolled mode. Also, the average life expectancy of power transformers is increased by 2.97% in the optimal charging mode compared to the uncontrolled mode.

ACS Style

Arian Shahkamrani; Hossein Askarian-Abyaneh; Hamed Nafisi; Mousa Marzband. A framework for day-ahead optimal charging scheduling of electric vehicles providing route mapping: Kowloon case study. Journal of Cleaner Production 2021, 307, 127297 .

AMA Style

Arian Shahkamrani, Hossein Askarian-Abyaneh, Hamed Nafisi, Mousa Marzband. A framework for day-ahead optimal charging scheduling of electric vehicles providing route mapping: Kowloon case study. Journal of Cleaner Production. 2021; 307 ():127297.

Chicago/Turabian Style

Arian Shahkamrani; Hossein Askarian-Abyaneh; Hamed Nafisi; Mousa Marzband. 2021. "A framework for day-ahead optimal charging scheduling of electric vehicles providing route mapping: Kowloon case study." Journal of Cleaner Production 307, no. : 127297.

Journal article
Published: 01 January 2021 in Energy
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ACS Style

Morteza Zare Oskouei; Mohammad Amin Mirzaei; Behnam Mohammadi-Ivatloo; Mahmood Shafiee; Mousa Marzband; Amjad Anvari-Moghaddam. A hybrid robust-stochastic approach to evaluate the profit of a multi-energy retailer in tri-layer energy markets. Energy 2021, 214, 1 .

AMA Style

Morteza Zare Oskouei, Mohammad Amin Mirzaei, Behnam Mohammadi-Ivatloo, Mahmood Shafiee, Mousa Marzband, Amjad Anvari-Moghaddam. A hybrid robust-stochastic approach to evaluate the profit of a multi-energy retailer in tri-layer energy markets. Energy. 2021; 214 ():1.

Chicago/Turabian Style

Morteza Zare Oskouei; Mohammad Amin Mirzaei; Behnam Mohammadi-Ivatloo; Mahmood Shafiee; Mousa Marzband; Amjad Anvari-Moghaddam. 2021. "A hybrid robust-stochastic approach to evaluate the profit of a multi-energy retailer in tri-layer energy markets." Energy 214, no. : 1.

Journal article
Published: 17 October 2020 in Applied Sciences
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This paper investigates the linear quadratic integral (LQI)-based control of Z-source inverters in the presence of uncertainties such as parameter perturbation, unmodeled dynamics, and load disturbances. These uncertainties, which are naturally available in any power system, have a profound impact on the performance of power inverters and may lead to a performance degradation or even an instability of the system. A novel robust LQI-based design procedure is presented to preserve the performance of the inverter against uncertainties while a proper level of disturbance rejection is satisfied. The stability robustness of the system is also studied on the basis of the maximum sensitivity specification. Moreover, the bat algorithm is adopted to optimize the weighting matrices. Simulation results confirm the effectiveness of the proposed controller in terms of performance and robustness.

ACS Style

Amirhossein Ahmadi; Behnam Mohammadi-Ivatloo; Amjad Anvari-Moghaddam; Mousa Marzband. Optimal Robust LQI Controller Design for Z-Source Inverters. Applied Sciences 2020, 10, 7260 .

AMA Style

Amirhossein Ahmadi, Behnam Mohammadi-Ivatloo, Amjad Anvari-Moghaddam, Mousa Marzband. Optimal Robust LQI Controller Design for Z-Source Inverters. Applied Sciences. 2020; 10 (20):7260.

Chicago/Turabian Style

Amirhossein Ahmadi; Behnam Mohammadi-Ivatloo; Amjad Anvari-Moghaddam; Mousa Marzband. 2020. "Optimal Robust LQI Controller Design for Z-Source Inverters." Applied Sciences 10, no. 20: 7260.

Journal article
Published: 01 October 2020 in International Journal of Electrical Power & Energy Systems
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Power network operators have recently faced new challenges due to an increase in the penetration of non-dispatchable renewable energy sources in power grids. Incorporating emerging flexible resources like electric vehicle parking lots (EVPLs) and demand response programs (DRPs) into power systems, could be a good solution to deal with inherent uncertainties imposed by these resources to the power grid. EVPLs can improve power system operating conditions by active and reactive power injection capabilities. The participation of consumers in DRPs can also improve energy consumption management by decreasing or shifting loads to other periods. This paper proposes a hybrid information gap decision theory (IGDT)- stochastic method to solve a transmission-constrained AC unit commitment model integrated with electric vehicle (EV), incentive-based DRP, and wind energy. The behavioural uncertainty related to EV owners is modelled using a scenario-based method. Additionally, an IGDT method is applied to manage wind energy uncertainty under a two-level optimization model. Verification of the proposed model is done under several case studies. Based on the results achieved, the proposed risk-based hybrid model allows the operator to differentiate between the risk level of existing uncertainties and apply a high-flexibility decision-making model to deal with such difficulties. Additionally, the role of the aforementioned flexible resources in the reduction of power system running costs and wind power uncertainty handling are evaluated. Numerical results confirm a 3.7% reduction in the daily operating costs as a consequence of coordinated scheduling of EVPL and DRP. Moreover, Taking advantage of reactive power injection of EVPL provides more cost savings.

ACS Style

Masoumeh Ahrabi; Mehrdad Abedi; Hamed Nafisi; Mohammad Amin Mirzaei; Behnam Mohammadi-Ivatloo; Mousa Marzband. Evaluating the effect of electric vehicle parking lots in transmission-constrained AC unit commitment under a hybrid IGDT-stochastic approach. International Journal of Electrical Power & Energy Systems 2020, 125, 106546 .

AMA Style

Masoumeh Ahrabi, Mehrdad Abedi, Hamed Nafisi, Mohammad Amin Mirzaei, Behnam Mohammadi-Ivatloo, Mousa Marzband. Evaluating the effect of electric vehicle parking lots in transmission-constrained AC unit commitment under a hybrid IGDT-stochastic approach. International Journal of Electrical Power & Energy Systems. 2020; 125 ():106546.

Chicago/Turabian Style

Masoumeh Ahrabi; Mehrdad Abedi; Hamed Nafisi; Mohammad Amin Mirzaei; Behnam Mohammadi-Ivatloo; Mousa Marzband. 2020. "Evaluating the effect of electric vehicle parking lots in transmission-constrained AC unit commitment under a hybrid IGDT-stochastic approach." International Journal of Electrical Power & Energy Systems 125, no. : 106546.

Journal article
Published: 15 September 2020 in Renewable Energy
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Reduction of carbon dioxide (CO2) emissions will have a positive impact on the environment by preventing adverse effects of global warming. To achieve an eco-environment, the primary source of energy needs to shift from fossil fuels to clean renewable energy. Thus, increased utilization of renewable energy overtime reduces air pollution and contributes to securing sustainable energy supply to satisfy future energy needs. The main purpose of this study is to investigate several sustainable hybrid renewable systems for electricity production in Iran. In this regard, critical indicators that have the strongest impact on the environment and energy sustainability are presented in this study. After a comprehensive review of environmental issues, data was collected from the meteorological organization and a techno-economic assessment was performed using HOMER software. It was concluded that the hybrid configuration composed of photovoltaic (PV), wind turbine, diesel generator and battery produced the best outcome with an energy cost of 0.151$/kWh and 15.6% return on investment. In addition, the results showed that with a higher renewable fraction exceeding 72%, this hybrid system can reduce more than 2000 Kg of CO2 emission per household annually. Although excess electricity generation is a challenge in stand-alone systems, by using the fuel cell, an electrolyzer, and a hydrogen tank unit, the amount of energy loss was reduced to less than one-sixth. These results show that selecting useful indicators such as appropriate implementation of policies of new enabling technologies and investments on renewable energy resources, has three potential benefits namely: CO2 reduction, greater sustainable electricity generation and provides an economic justication for stakeholders to invest in the renewable energy sector.

ACS Style

A. Razmjoo; L. Gakenia Kaigutha; M.A. Vaziri Rad; M. Marzband; Afshin Davarpanah; M. Denai. A Technical analysis investigating energy sustainability utilizing reliable renewable energy sources to reduce CO2 emissions in a high potential area. Renewable Energy 2020, 164, 46 -57.

AMA Style

A. Razmjoo, L. Gakenia Kaigutha, M.A. Vaziri Rad, M. Marzband, Afshin Davarpanah, M. Denai. A Technical analysis investigating energy sustainability utilizing reliable renewable energy sources to reduce CO2 emissions in a high potential area. Renewable Energy. 2020; 164 ():46-57.

Chicago/Turabian Style

A. Razmjoo; L. Gakenia Kaigutha; M.A. Vaziri Rad; M. Marzband; Afshin Davarpanah; M. Denai. 2020. "A Technical analysis investigating energy sustainability utilizing reliable renewable energy sources to reduce CO2 emissions in a high potential area." Renewable Energy 164, no. : 46-57.

Journal article
Published: 08 September 2020 in International Journal of Hydrogen Energy
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The operation of energy systems considering a multi-carrier scheme takes several advantages of economical, environmental, and technical aspects by utilizing alternative options is supplying different kinds of loads such as heat, gas, and power. This study aims to evaluate the influence of power to hydrogen conversion capability and hydrogen storage technology in energy systems with gas, power, and heat carriers concerning risk analysis. Accordingly, conditional value at risk (CVaR)-based stochastic method is adopted for investigating the uncertainty associated with wind power production. Hydrogen storage system, which can convert power to hydrogen in off-peak hours and to feed generators to produce power at on-peak time intervals, is studied as an effective solution to mitigate the wind power curtailment because of high penetration of wind turbines in electricity networks. Besides, the effect constraints associated with gas and district heating network on the operation of the multi-carrier energy systems has been investigated. A gas-fired combined heat and power (CHP) plant and hydrogen storage are considered as the interconnections among power, gas and heat systems. The proposed framework is implemented on a system to verify the effectiveness of the model. The obtained results show the effectiveness of the model in terms of handling the risks associated with multi-carrier system parameters as well as dealing with the penetration of renewable resources.

ACS Style

Morteza-Nazari Heris; Mohammad Amin Mirzaei; Somayeh Asadi; Behnam Mohammadi-Ivatloo; Kazem Zare; Houtan Jebelli; Mousa Marzband. Evaluation of hydrogen storage technology in risk-constrained stochastic scheduling of multi-carrier energy systems considering power, gas and heating network constraints. International Journal of Hydrogen Energy 2020, 45, 30129 -30141.

AMA Style

Morteza-Nazari Heris, Mohammad Amin Mirzaei, Somayeh Asadi, Behnam Mohammadi-Ivatloo, Kazem Zare, Houtan Jebelli, Mousa Marzband. Evaluation of hydrogen storage technology in risk-constrained stochastic scheduling of multi-carrier energy systems considering power, gas and heating network constraints. International Journal of Hydrogen Energy. 2020; 45 (55):30129-30141.

Chicago/Turabian Style

Morteza-Nazari Heris; Mohammad Amin Mirzaei; Somayeh Asadi; Behnam Mohammadi-Ivatloo; Kazem Zare; Houtan Jebelli; Mousa Marzband. 2020. "Evaluation of hydrogen storage technology in risk-constrained stochastic scheduling of multi-carrier energy systems considering power, gas and heating network constraints." International Journal of Hydrogen Energy 45, no. 55: 30129-30141.

Journal article
Published: 07 September 2020 in Sustainability
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The high penetration rate of renewable energy sources (RESs) in smart energy systems has both threat and opportunity consequences. On the positive side, it is inevitable that RESs are beneficial with respect to conventional energy resources from the environmental aspects. On the negative side, the RESs are a great source of uncertainty, which will make challenges for the system operators to cope with. To tackle the issues of the negative side, there are several methods to deal with intermittent RESs, such as electrical and thermal energy storage systems (TESSs). In fact, pairing RESs to electrical energy storage systems (ESSs) has favorable economic opportunities for the facility owners and power grid operators (PGO), simultaneously. Moreover, the application of demand-side management approaches, such as demand response programs (DRPs) on flexible loads, specifically thermal loads, is an effective solution through the system operation. To this end, in this work, an air conditioning system (A/C system) with a TESS has been studied as a way of volatility compensation of the wind farm forecast-errors (WFFEs). Additionally, the WFFEs are investigated from multiple visions to assist the dispatch of the storage facilities. The operation design is presented for the A/C systems in both day-ahead and real-time operations based on the specifications of WFFEs. Analyzing the output results, the main aims of the work, in terms of applying DRPs and make-up of WFFEs to the scheduling of A/C system and TESS, will be evaluated. The dispatched cooling and base loads show the superiority of the proposed method, which has a smoother curve compared to the original curve. Further, the WFFEs application has proved and demonstrated a way better function than the other uncertainty management techniques by committing and compensating the forecast errors of cooling loads.

ACS Style

Ali Dargahi; Khezr Sanjani; Morteza Nazari-Heris; Behnam Mohammadi-Ivatloo; Sajjad Tohidi; Mousa Marzband. Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs. Sustainability 2020, 12, 7311 .

AMA Style

Ali Dargahi, Khezr Sanjani, Morteza Nazari-Heris, Behnam Mohammadi-Ivatloo, Sajjad Tohidi, Mousa Marzband. Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs. Sustainability. 2020; 12 (18):7311.

Chicago/Turabian Style

Ali Dargahi; Khezr Sanjani; Morteza Nazari-Heris; Behnam Mohammadi-Ivatloo; Sajjad Tohidi; Mousa Marzband. 2020. "Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs." Sustainability 12, no. 18: 7311.

Journal article
Published: 31 August 2020 in IEEE Transactions on Transportation Electrification
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The global transport sector has a significant share of greenhouse gas emissions. Thus, plug-in electric vehicles (PEVs) can play a vital role in the reduction of pollution. However, high penetration of PEVs can pose severe challenges to power systems, such as an increase in energy losses and a decrease in the transformers expected life. In this paper, a new day-ahead co-optimization algorithm is proposed to reduce the unwanted effects of PEVs on the power system. The aim of the proposed algorithm is minimizing the cost of energy losses as well as transformer operating cost by the management of active and reactive powers simultaneously. Moreover, the effect of harmonics, which are produced by the charger of PEVs, are considered in the proposed algorithm. Also, the transformer operating cost is obtained from a method that contains the purchase price, loading, and losses cost of the transformer. Another advantage of the proposed algorithm is that it can improve power quality parameters, e.g., voltage and power factor of the distribution network by managing the reactive power. Afterward, the proposed algorithm is applied to a real distribution network. The results show that the proposed algorithm optimizes the daily operating cost of the distribution network efficiently. Finally, the robustness of the proposed algorithm to the number and distribution of PEVs is verified by simulation results.

ACS Style

Seyed Soroush Karimi Madahi; Hamed Nafisi; Hossein Askarian Abyaneh; Mousa Marzband. Co-Optimization of Energy Losses and Transformer Operating Costs Based on Smart Charging Algorithm for Plug-In Electric Vehicle Parking Lots. IEEE Transactions on Transportation Electrification 2020, 7, 527 -541.

AMA Style

Seyed Soroush Karimi Madahi, Hamed Nafisi, Hossein Askarian Abyaneh, Mousa Marzband. Co-Optimization of Energy Losses and Transformer Operating Costs Based on Smart Charging Algorithm for Plug-In Electric Vehicle Parking Lots. IEEE Transactions on Transportation Electrification. 2020; 7 (2):527-541.

Chicago/Turabian Style

Seyed Soroush Karimi Madahi; Hamed Nafisi; Hossein Askarian Abyaneh; Mousa Marzband. 2020. "Co-Optimization of Energy Losses and Transformer Operating Costs Based on Smart Charging Algorithm for Plug-In Electric Vehicle Parking Lots." IEEE Transactions on Transportation Electrification 7, no. 2: 527-541.

Journal article
Published: 08 June 2020 in IEEE Systems Journal
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This article proposes a new two-stage hybrid stochastic–information gap-decision theory (IGDT) based on the network-constrained unit commitment framework. The model is applied for the market clearing of joint energy and flexible ramping reserve in integrated heat- and power-based energy systems. The uncertainties of load demands and wind power generation are studied using the Monte Carlo simulation method and IGDT, respectively. The proposed model considers both risk-averse and risk-seeker strategies, which enables the independent system operator to provide flexible decisions in meeting system uncertainties in real-time dispatch. Moreover, the effect of feasible operating regions of the combined heat and power (CHP) plants on energy and flexible ramping reserve market and operation cost of the system is investigated. The proposed model is implemented on a test system to verify the effectiveness of the introduced two-stage hybrid framework. The analysis of the obtained results demonstrates that the variation of heat demand is effective on power and flexible ramping reserve supplied by CHP units.

ACS Style

Mohammad Amin Mirzaei; Morteza Nazari-Heris; Behnam Mohammadi-Ivatloo; Kazem Zare; Mousa Marzband; Miadreza Shafie-Khah; Amjad Anvari-Moghaddam; João P. S. Catalão. Network-Constrained Joint Energy and Flexible Ramping Reserve Market Clearing of Power- and Heat-Based Energy Systems: A Two-Stage Hybrid IGDT–Stochastic Framework. IEEE Systems Journal 2020, 15, 1547 -1556.

AMA Style

Mohammad Amin Mirzaei, Morteza Nazari-Heris, Behnam Mohammadi-Ivatloo, Kazem Zare, Mousa Marzband, Miadreza Shafie-Khah, Amjad Anvari-Moghaddam, João P. S. Catalão. Network-Constrained Joint Energy and Flexible Ramping Reserve Market Clearing of Power- and Heat-Based Energy Systems: A Two-Stage Hybrid IGDT–Stochastic Framework. IEEE Systems Journal. 2020; 15 (2):1547-1556.

Chicago/Turabian Style

Mohammad Amin Mirzaei; Morteza Nazari-Heris; Behnam Mohammadi-Ivatloo; Kazem Zare; Mousa Marzband; Miadreza Shafie-Khah; Amjad Anvari-Moghaddam; João P. S. Catalão. 2020. "Network-Constrained Joint Energy and Flexible Ramping Reserve Market Clearing of Power- and Heat-Based Energy Systems: A Two-Stage Hybrid IGDT–Stochastic Framework." IEEE Systems Journal 15, no. 2: 1547-1556.

Journal article
Published: 27 April 2020 in IEEE Transactions on Power Electronics
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Losses in light-emitting-diode (LED) driver cause increasing temperature and shorten their lifespan. Therefore, improving the efficiency of LED drivers not only saves energy but also is indispensable to increase their lifespan. In this study, a new LED driver topology is proposed to improve the performance of valley switching by decreasing the MOSFET switching losses. The proposed topology is designed in a way that the MOSFET works at the significantly lower switching and conduction losses in compared with conventional LED drivers. It elaborates how the proposed topology also improves the overall efficiency by decreasing power losses in other main elements of the driver including inductance, and diode. In addition, a new valley switching implementation is introduced for the new converter which decreases the cost and dimension of the LED drivers. The experimental results confirm the high efficient operation of the proposed LED driver by reaching the efficiency up to 97% at a wide range of operating voltage.

ACS Style

Reza Sangrody; Mobina Pouresmaeil; Mousa Marzband; Edris Pouresmaeil. Resonance-Based Optimized Buck LED Driver Using Unequal Turn Ratio Coupled Inductance. IEEE Transactions on Power Electronics 2020, 35, 13068 -13076.

AMA Style

Reza Sangrody, Mobina Pouresmaeil, Mousa Marzband, Edris Pouresmaeil. Resonance-Based Optimized Buck LED Driver Using Unequal Turn Ratio Coupled Inductance. IEEE Transactions on Power Electronics. 2020; 35 (12):13068-13076.

Chicago/Turabian Style

Reza Sangrody; Mobina Pouresmaeil; Mousa Marzband; Edris Pouresmaeil. 2020. "Resonance-Based Optimized Buck LED Driver Using Unequal Turn Ratio Coupled Inductance." IEEE Transactions on Power Electronics 35, no. 12: 13068-13076.

Journal article
Published: 20 March 2020 in IEEE Systems Journal
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In a power system with high penetration of renewable power sources, gas-fired units can be considered as a back-up option to improve the balance between generation and consumption in short-term scheduling. Therefore, closer coordination between power and natural gas systems is anticipated. This article presents a novel hybrid information gap decision theory (IGDT)-stochastic cooptimization problem for integrating electricity and natural gas networks to minimize total operation cost with the penetration of wind energy. The proposed model considers not only the uncertainties regarding electrical load demand and wind power output, but also the uncertainties of gas load demands for the residential consumers. The uncertainties of electric load and wind power are handled through a scenario-based approach, and residential gas load uncertainty is handled via IGDT approach with no need for the probability density function. The introduced hybrid model enables the system operator to consider the advantages of both approaches simultaneously. The impact of gas load uncertainty associated with the residential consumers is more significant on the power dispatch of gas-fired plants and power system operation cost since residential gas load demands are prior than gas load demands of gas-fired units. The proposed framework is a bilevel problem that can be reduced to a one-level problem. Also, it can be solved by the implementation of a simple concept without the need for Karush–Kuhn–Tucker conditions. Moreover, emerging flexible energy sources such as the power to gas technology and demand response program are considered in the proposed model for increasing the wind power dispatch, decreasing the total operation cost of the integrated network as well as reducing the effect of system uncertainties on the total operating cost. Numerical results indicate the applicability and effectiveness of the proposed model under different working conditions.

ACS Style

Mohammad Amin Mirzaei; Morteza Nazari-Heris; Behnam Mohammadi-Ivatloo; Kazem Zare; Mousa Marzband; Amjad Anvari-Moghaddam. A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies. IEEE Systems Journal 2020, 14, 3598 -3608.

AMA Style

Mohammad Amin Mirzaei, Morteza Nazari-Heris, Behnam Mohammadi-Ivatloo, Kazem Zare, Mousa Marzband, Amjad Anvari-Moghaddam. A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies. IEEE Systems Journal. 2020; 14 (3):3598-3608.

Chicago/Turabian Style

Mohammad Amin Mirzaei; Morteza Nazari-Heris; Behnam Mohammadi-Ivatloo; Kazem Zare; Mousa Marzband; Amjad Anvari-Moghaddam. 2020. "A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies." IEEE Systems Journal 14, no. 3: 3598-3608.

Journal article
Published: 11 March 2020 in IEEE Transactions on Industrial Electronics
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Multi carrier energy systems create new challenges as well as opportunities in future energy systems. One of these challenges is the interaction among multiple energy systems and energy hubs on different energy markets. The proposed new concept of the energy hub, which is named as the VEH in this paper, is referred to a new physical structure beside the proposed self-scheduling approach. The VEH is a new structure of the energy hub systems, which is operated, based on the different energy carriers and facilities as well as maximization its revenue by participation on the various local energy markets. The proposed virtual energy hub (VEH) optimizes its revenue from participating in the electrical and thermal energy markets by examining both local markets. Participation a player in the energy markets by using the integrated point of view can be reach to a higher benefit and optimal operation of the facilities in comparison with independent energy systems. In a competitive energy market, a VEH optimizes its self-scheduling problem in order to maximize its benefit considering uncertainties related to renewable resources. To handle the problem under uncertainty, a non-probabilistic information gap method is implemented in this study.

ACS Style

Mohammad Jadidbonab; Behnam Mohammadi-Ivatloo; Mousa Marzband; Pierluigi Siano. Short-Term Self-Scheduling of Virtual Energy Hub Plant Within Thermal Energy Market. IEEE Transactions on Industrial Electronics 2020, 68, 3124 -3136.

AMA Style

Mohammad Jadidbonab, Behnam Mohammadi-Ivatloo, Mousa Marzband, Pierluigi Siano. Short-Term Self-Scheduling of Virtual Energy Hub Plant Within Thermal Energy Market. IEEE Transactions on Industrial Electronics. 2020; 68 (4):3124-3136.

Chicago/Turabian Style

Mohammad Jadidbonab; Behnam Mohammadi-Ivatloo; Mousa Marzband; Pierluigi Siano. 2020. "Short-Term Self-Scheduling of Virtual Energy Hub Plant Within Thermal Energy Market." IEEE Transactions on Industrial Electronics 68, no. 4: 3124-3136.

Journal article
Published: 17 December 2019 in Energies
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According to the European Union Emissions Trading Scheme, energy system planners are encouraged to consider the effects of greenhouse gases such as CO 2 in their short-term and long-term planning. A decrease in the carbon emissions produced by the power plant will result in a tax decrease. In view of this, the Dynamic carbon-constrained Equilibrium programming equilibrium constraints (DCC-EPEC) Framework is suggested to explore the effects of distinct market models on generation development planning (GEP) on electricity markets over a multi-period horizon. The investment incentives included in our model are the firm contract and capacity payment. The investment issue, which is regarded as a set of dominant producers in the oligopolistic market, is developed as an EPEC optimization problem to reduce carbon emissions. In the suggested DCC-EPEC model, the sum of the carbon emission tax and true social welfare are assumed as the objective function. Investment decisions and the strategic behavior of producers are included at the first level so as to maximize the overall profit of the investor over the scheduling period. The second-level issue is market-clearing, which is resolved by an independent system operator (ISO) to maximize social welfare. A real power network, as a case study, is provided to assess the suggested carbon-constrained EPEC framework. Simulations indicate that firm contracts and capacity payments can initiate the capacity expansion of different technologies to improve the long-term stability of the electricity market.

ACS Style

Jaber Valinejad; Mousa Marzband; Michael Elsdon; Ameena Saad Al-Sumaiti; Taghi Barforoushi. Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO2 Emissions. Energies 2019, 12, 4813 .

AMA Style

Jaber Valinejad, Mousa Marzband, Michael Elsdon, Ameena Saad Al-Sumaiti, Taghi Barforoushi. Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO2 Emissions. Energies. 2019; 12 (24):4813.

Chicago/Turabian Style

Jaber Valinejad; Mousa Marzband; Michael Elsdon; Ameena Saad Al-Sumaiti; Taghi Barforoushi. 2019. "Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO2 Emissions." Energies 12, no. 24: 4813.

Journal article
Published: 23 October 2019 in Applied Energy
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Electric vehicles and renewable energy sources are collectively being developed as a synergetic implementation for smart grids. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are seen as a way forward to achieve economic, technical and environmental benefits. The implementation of these technologies requires the cooperation of the end-electricity user, the electric vehicle owner, the system operator and policy makers. These stakeholders pursue different and sometime conflicting objectives. In this paper, the concept of multi-objective-techno-economic-environmental optimisation is proposed for scheduling electric vehicle charging/discharging. End user energy cost, battery degradation, grid interaction and CO2 emissions in the home micro-grid context are modelled and concurrently optimised for the first time while providing frequency regulation. The results from three case studies show that the proposed method reduces the energy cost, battery degradation, CO2 emissions and grid utilisation by 88.2%, 67%, 34% and 90% respectively, when compared to uncontrolled electric vehicle charging. Furthermore, with multiple optimal solutions, in order to achieve a 41.8% improvement in grid utilisation, the system operator needs to compensate the end electricity user and the electric vehicle owner for their incurred benefit loss of 27.34% and 9.7% respectively, to stimulate participation in energy services.

ACS Style

Ridoy Das; Yue Wang; Ghanim Putrus; Richard Kotter; Mousa Marzband; Bert Herteleer; Jos Warmerdam. Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services. Applied Energy 2019, 257, 113965 .

AMA Style

Ridoy Das, Yue Wang, Ghanim Putrus, Richard Kotter, Mousa Marzband, Bert Herteleer, Jos Warmerdam. Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services. Applied Energy. 2019; 257 ():113965.

Chicago/Turabian Style

Ridoy Das; Yue Wang; Ghanim Putrus; Richard Kotter; Mousa Marzband; Bert Herteleer; Jos Warmerdam. 2019. "Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services." Applied Energy 257, no. : 113965.

Journal article
Published: 09 October 2019 in Journal of Cleaner Production
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Integration of renewable energy sources in electrical energy networks, is significantly increased due to economic and environmental issues in recent years and has appeared new challenges in the operation of power systems. Additionally, the power to gas (P2G) technology is a practical solution for accommodating the variability of the power output of wind energy sources, which are effective in reducing pollutant gas emissions considering their gas or power injection to the network at on-peak time intervals. Moreover, natural gas (NG)-fired generation plants can be introduced as practical solutions for decreasing power output variations of renewable sources due to their high ramp rates and quick response. This study proposes a multi-objective two-stage stochastic unit commitment scheme for integrated gas and electricity networks taking into account novel flexible energy sources such as P2G technology and demand response (DR) programs as well as high penetration of wind turbines. In this paper, P2G technology is introduced as a promising option for increasing the wind power dispatch in power systems. In addition, DR program as a cost-environmental effective method is modeled as a price-responsive bidding mechanism that is influential in decreasing the operation cost of the integrated network by shifting load from on-peak time intervals to off-peak time intervals. The introduced scheme has been implemented on an integrated 6-bus power system with 6-node gas networks by analyzing the performance of the framework in terms of operation cost and release of environmental pollutant gases. The results show that the simultaneous consideration of power-to-gas technology and demand response program reduces environmental pollution in addition to reducing costs. The investigation of the operation cost of the whole integrated system shows that application of both P2G and DR is beneficial in decreasing cost by 2.42% and 1.78% with respect to consideration of each of the P2G and DR, respectively.

ACS Style

Morteza Nazari-Heris; Mohammad Amin Mirzaei; Behnam Mohammadi-Ivatloo; Mousa Marzband; Somayeh Asadi. Economic-environmental effect of power to gas technology in coupled electricity and gas systems with price-responsive shiftable loads. Journal of Cleaner Production 2019, 244, 118769 .

AMA Style

Morteza Nazari-Heris, Mohammad Amin Mirzaei, Behnam Mohammadi-Ivatloo, Mousa Marzband, Somayeh Asadi. Economic-environmental effect of power to gas technology in coupled electricity and gas systems with price-responsive shiftable loads. Journal of Cleaner Production. 2019; 244 ():118769.

Chicago/Turabian Style

Morteza Nazari-Heris; Mohammad Amin Mirzaei; Behnam Mohammadi-Ivatloo; Mousa Marzband; Somayeh Asadi. 2019. "Economic-environmental effect of power to gas technology in coupled electricity and gas systems with price-responsive shiftable loads." Journal of Cleaner Production 244, no. : 118769.

Journal article
Published: 01 October 2019 in Energy
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ACS Style

Houman Jamshidi Monfared; Ahmad Ghasemi; Abdolah Loni; Mousa Marzband. A hybrid price-based demand response program for the residential micro-grid. Energy 2019, 185, 274 -285.

AMA Style

Houman Jamshidi Monfared, Ahmad Ghasemi, Abdolah Loni, Mousa Marzband. A hybrid price-based demand response program for the residential micro-grid. Energy. 2019; 185 ():274-285.

Chicago/Turabian Style

Houman Jamshidi Monfared; Ahmad Ghasemi; Abdolah Loni; Mousa Marzband. 2019. "A hybrid price-based demand response program for the residential micro-grid." Energy 185, no. : 274-285.