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Seyed Mehdi Hakimi
Electrical Engineering Department and Renewable Energy Research Center, Damavand Branch, Islamic Azad University, Damavand, Iran

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Journal article
Published: 08 June 2021 in Applied Energy
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This paper presents a stochastic planning algorithm to plan an operation of a multi-microgrid (MMG) in an electricity market considering the integration of stochastic renewable energy resources (RERs). The proposed planning algorithm investigates the optimal operation of resources (i.e., wind turbine (WT), fuel cell (FC), Electrolyzer, photovoltaic (PV) panel, and microturbine (MT)) and energy storage (ES). Various uncertainties (e.g., the power production of WT, the power production of PV, the departure time of electric vehicle (EV), the arrival time of EV, and the traveled distance of EV) are initially forecasted according to the observed data. The prediction error is estimated by fitting the forecasted data and observed data using a Copula method. A Cournot equilibrium and game theory (GT) are applied to model the real-time electricity market and its interactions with the MMG. The proposed algorithm is examined in a sample MMG to determine the operation of uncertain resources and ES. The obtained results are compared with a baseline and the other conventional optimization methods to verify the effectiveness of the proposed algorithm. The obtained results authenticate the importance of modeling the interaction between the MMG and electricity market, especially under the high integration of uncertain RERs, resulting in above 8% cost reduction in the MMG.

ACS Style

Seyed Mehdi Hakimi; Arezoo Hasankhani; Miadreza Shafie-Khah; João P.S. Catalão. Stochastic planning of a multi-microgrid considering integration of renewable energy resources and real-time electricity market. Applied Energy 2021, 298, 117215 .

AMA Style

Seyed Mehdi Hakimi, Arezoo Hasankhani, Miadreza Shafie-Khah, João P.S. Catalão. Stochastic planning of a multi-microgrid considering integration of renewable energy resources and real-time electricity market. Applied Energy. 2021; 298 ():117215.

Chicago/Turabian Style

Seyed Mehdi Hakimi; Arezoo Hasankhani; Miadreza Shafie-Khah; João P.S. Catalão. 2021. "Stochastic planning of a multi-microgrid considering integration of renewable energy resources and real-time electricity market." Applied Energy 298, no. : 117215.

Chapter
Published: 06 April 2021 in Numerical Methods for Energy Applications
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In this chapter, a novel methodology is proposed for optimization of an energy hub in Iran (Ganje) to satisfy the electricity, thermal, and cooling loads of a sample residential sector. Different types of distributed generation units and energy storage systems are considered in the mentioned energy hub. The heat water load and heating/cooling loads are considered as thermal demand in the studied system. The produced heat of fuel cell is implemented to provide the thermal energy of energy hub. In this work, the absorption chiller is applied to supply the cooling demand in the energy hub. When the produced heat of fuel cells is more than loads, the extra heat is utilized to store in thermal storages. In addition, when the supplied thermal energy of fuel cells and available energy in thermal storages cannot satisfy thermal loads, waste and natural gas are used to supply thermal energy. Minimizing the studied energy hub’s costs is considered as the main objective of this chapter. The reliability indices are also considered in the mentioned energy hub.

ACS Style

Hamid HassanzadehFard; Arezoo Hasankhani; Seyed Mehdi Hakimi. Optimal Planning and Design of Multi-carrier Energy Networks. Numerical Methods for Energy Applications 2021, 209 -234.

AMA Style

Hamid HassanzadehFard, Arezoo Hasankhani, Seyed Mehdi Hakimi. Optimal Planning and Design of Multi-carrier Energy Networks. Numerical Methods for Energy Applications. 2021; ():209-234.

Chicago/Turabian Style

Hamid HassanzadehFard; Arezoo Hasankhani; Seyed Mehdi Hakimi. 2021. "Optimal Planning and Design of Multi-carrier Energy Networks." Numerical Methods for Energy Applications , no. : 209-234.

Chapter
Published: 06 April 2021 in Numerical Methods for Energy Applications
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In this chapter, a modern smart energy management system (SEMS) for a multi-carrier microgrid including renewable energy resources, storage system, combined heat and power system, and consumers has been proposed. This microgrid has the capability of exchanging energy with distribution grid and contains both the controllable and uncontrollable loads. For the controllable loads by presenting new operation controlling methods, the consumption of the loads is changing or postponing to another time, with regard to uncertainties of wind and solar generation or energy cost of distribution grid and of course by considering the social welfare of consumer. This operation controlling is done by courage or a rebate in the cost of consumption power. For the optimized operation of the microgrid in the next 24 h, an objective function is maximized. This is done by utilizing the partial swarm optimization method from the point of view of manager of microgrid. At the end, the operation scheduling for optimized beneficiary of microgrid is presented and the results have been analyzed.

ACS Style

Mohammad Saadatmandi; Seyed Mehdi Hakimi; Pegah Bahrevar. An Optimal Operation Model for Multi-carrier Energy Grids. Numerical Methods for Energy Applications 2021, 59 -85.

AMA Style

Mohammad Saadatmandi, Seyed Mehdi Hakimi, Pegah Bahrevar. An Optimal Operation Model for Multi-carrier Energy Grids. Numerical Methods for Energy Applications. 2021; ():59-85.

Chicago/Turabian Style

Mohammad Saadatmandi; Seyed Mehdi Hakimi; Pegah Bahrevar. 2021. "An Optimal Operation Model for Multi-carrier Energy Grids." Numerical Methods for Energy Applications , no. : 59-85.

Review article
Published: 09 February 2021 in International Journal of Electrical Power & Energy Systems
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Development of the smart grids (SGs) has led to many changes in the current power grid structure. Application of new devices, technologies, renewable energy resources, and electric vehicles (EVs) increases the need for decentralized energy management and the data transactions, i.e., the secure and economic transactions are realized through the decentralized networks. The blockchain technology can be used as a solution for these modifications, so a comparative literature review is presented to identify all possible applications of blockchain in SG. The renewable energy development and its interaction with the blockchain technology are investigated, so the blockchain technology is verified as a promising option to increase the renewable energy share. Then, the applications of blockchain technology in SG are categorized in different areas, including the smart contracts and demand response (DR), EVs, the Internet of Things (IoT), the decentralized energy management, the energy trading, the financial transactions, the cybersecurity, the testbeds, and the environmental issues. Therefore, all possible opportunities and challenges of blockchain’s applications in SG are identified. A comprehensive literature review is done to introduce the current improvements related to the blockchain technology’s applications in SG, while the future opportunities and current challenges of blockchain are discussed. This paper aims to present a structure of SG according to the blockchain application and discuss all benefits and drawbacks caused by blockchain in different areas of SG.

ACS Style

Arezoo Hasankhani; Seyed Mehdi Hakimi; Mojtaba Bisheh-Niasar; Miadreza Shafie-Khah; Hasan Asadolahi. Blockchain technology in the future smart grids: A comprehensive review and frameworks. International Journal of Electrical Power & Energy Systems 2021, 129, 106811 .

AMA Style

Arezoo Hasankhani, Seyed Mehdi Hakimi, Mojtaba Bisheh-Niasar, Miadreza Shafie-Khah, Hasan Asadolahi. Blockchain technology in the future smart grids: A comprehensive review and frameworks. International Journal of Electrical Power & Energy Systems. 2021; 129 ():106811.

Chicago/Turabian Style

Arezoo Hasankhani; Seyed Mehdi Hakimi; Mojtaba Bisheh-Niasar; Miadreza Shafie-Khah; Hasan Asadolahi. 2021. "Blockchain technology in the future smart grids: A comprehensive review and frameworks." International Journal of Electrical Power & Energy Systems 129, no. : 106811.

Journal article
Published: 07 January 2021 in Sustainable Energy, Grids and Networks
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Increasing the implementation of distributed generation and introducing multi-carrier energy systems highlight the need for energy hub systems. The energy hub is a new idea implemented in multi-carrier energy systems, sending, receiving, and storing different energy types. Therefore, the present paper proposes an improved energy hub consisting of different types of renewable energy-based DG units considering electricity and heating storage systems, which models the system’s operation and planning aspects. Furthermore, optimal planning and scheduling of multi-carrier energy hub system is modeled considering the stochastic behavior of wind and photovoltaic units. The operation section’s main challenge is determining the optimal interaction between different resources for supplying other loads in the system. The presented model is solved using a robust method based on a Quantum Particle Swarm Optimization (QPSO) approach to minimize the energy hub system’s total cost. The minimization of fuel consumption and pollutant emissions due to implementing the residential energy hub’s thermal storage system is evaluated. Simulation results show that the amount of consumed natural gas reduces by 48% after using CHP units produced heat to supply heating and cooling loads. After installing CHP and thermal storages in the energy hub system, the amount of CO2 has reduced by about 904 tons during a year. It can be concluded that the produced power of CHP is at the highest, which is equal to 61%, as it can generate electricity at all times during the day. Moreover, to evaluate the efficiency of the proposed methodology, the Genetic Algorithm (GA) and PSO algorithm are also implemented for optimization of the mentioned energy hub system. The performance of the mentioned algorithms is compared with each other, and the results depicted that the QPSO algorithm is the best and the convergence speed and global search ability of the QPSO algorithm are significantly better than PSO and GA algorithms The obtained numerical results verify the efficiency of the proposed method in the optimal scheduling and planning of the energy hub system in the presence of stochastic renewable energy systems.

ACS Style

Elnaz Shahrabi; Seyed Mehdi Hakimi; Arezoo Hasankhani; Ghasem Derakhshan; Babak Abdi. Developing optimal energy management of energy hub in the presence of stochastic renewable energy resources. Sustainable Energy, Grids and Networks 2021, 26, 100428 .

AMA Style

Elnaz Shahrabi, Seyed Mehdi Hakimi, Arezoo Hasankhani, Ghasem Derakhshan, Babak Abdi. Developing optimal energy management of energy hub in the presence of stochastic renewable energy resources. Sustainable Energy, Grids and Networks. 2021; 26 ():100428.

Chicago/Turabian Style

Elnaz Shahrabi; Seyed Mehdi Hakimi; Arezoo Hasankhani; Ghasem Derakhshan; Babak Abdi. 2021. "Developing optimal energy management of energy hub in the presence of stochastic renewable energy resources." Sustainable Energy, Grids and Networks 26, no. : 100428.

Journal article
Published: 24 December 2020 in Energy
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Stochastic energy management of smart microgrids (MGs) is an important subject due to the high integration of intermittent resources, including wind turbine (WT) and photovoltaic (PV) units. The complexity of the multi MGs management algorithm increases, considering their participation in an electricity market. In this paper, we proposed a stochastic energy management algorithm to address the participation of smart MGs in the electricity market, which minimizes the total cost and finds the optimal size of different components, including WT, PV unit, fuel cell, Electrolyzer, battery, and microturbine. The intermittencies in the PV output power, WT output power, and electric vehicle (EV) are modeled and integrated into the management algorithm using the Copula method. The market clearing price (MCP) is found using a game theory (GT) model and Cournot equilibrium. To verify the efficiency of the proposed method, it is tested on a sample three-MG, where the optimal size of various components is obtained. The obtained results verify that the total cost of MG decreases and the better performance can be obtained after participation in the electricity market. A sensitivity analysis is also done to evaluate the effects of various parameter changes (e.g., capital cost, replacement cost, and operation and maintenance cost) in various scenarios, where the obtained results verify that the cost reduction is obtained over different scenarios.

ACS Style

Arezoo Hasankhani; Seyed Mehdi Hakimi. Stochastic energy management of smart microgrid with intermittent renewable energy resources in electricity market. Energy 2020, 219, 119668 .

AMA Style

Arezoo Hasankhani, Seyed Mehdi Hakimi. Stochastic energy management of smart microgrid with intermittent renewable energy resources in electricity market. Energy. 2020; 219 ():119668.

Chicago/Turabian Style

Arezoo Hasankhani; Seyed Mehdi Hakimi. 2020. "Stochastic energy management of smart microgrid with intermittent renewable energy resources in electricity market." Energy 219, no. : 119668.

Chapter
Published: 21 January 2020 in Electric Vehicles in Energy Systems
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For decades, fossil fuels are the main source of energy in the world, but concerns caused by price fluctuations, energy security, and environmental issues such as greenhouse gas emissions from burning these fuels have led that various industries to seek to replace fossil fuels. Transportation is one of the main consumers of fossil fuels, especially oil. The transportation share of the world’s total oil consumed in 2012 was 63.7%. Also, 23% of carbon dioxide produced by fossil fuels in 2012 was related to this sector. Replacing conventional vehicles with hybrid electric vehicles is among the best solutions for environmental and economic issues in the transportation sector. Considering the advantages of electric vehicles, their number is expected to increase rapidly over the next few decades. In 2022, more than 35 million electric cars are expected to be on the road. Electric vehicles must be connected to the power grid to charge their batteries. Therefore, with the widespread presence of these cars, the performance of the power system will change especially in the distribution network. Uncontrolled battery charging can cause undesirable effects such as overload, overvoltage, loss increase, unbalanced load, harmonic, and instability. Demand side management can prevent these problems, and it also flattens the demand curve. In order to solve the problems caused by the use of gasoline cars, it is expected that electric vehicles will gradually replace these cars. Lack of control in charging process will have adverse effects on the network. In this study, after modeling the electric car charging curve, its influence on network demand has been investigated in two uncontrolled charging and controlled charging scenarios. In this study, the controlled charge with the goal of minimizing household electricity consumption costs is investigated. The results show that the lack of control on the car charging time increases the peak demand, while the controllable charge does not increase the peak, and flattens the demand curve. The current chapter will discuss the application of electric vehicles in power grid and its role in demand response in order to improve the demand curve especially in smart homes.

ACS Style

Arezoo Hasankhani; Seyed Mehdi Hakimi. Optimal Charge Scheduling of Electric Vehicles in Smart Homes. Electric Vehicles in Energy Systems 2020, 359 -383.

AMA Style

Arezoo Hasankhani, Seyed Mehdi Hakimi. Optimal Charge Scheduling of Electric Vehicles in Smart Homes. Electric Vehicles in Energy Systems. 2020; ():359-383.

Chicago/Turabian Style

Arezoo Hasankhani; Seyed Mehdi Hakimi. 2020. "Optimal Charge Scheduling of Electric Vehicles in Smart Homes." Electric Vehicles in Energy Systems , no. : 359-383.

Chapter
Published: 21 January 2020 in Electric Vehicles in Energy Systems
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During the past few years, the growth of the greenhouse gas emissions and the global warming from fossil fuels to produce the electrical power, transportation, as well as the finiteness of these resources have become the most critical concern of governments to find the alternative resources for fossil fuels. Solar energy is one of these resources which are clean, unlimited, and completely free resource. However widespread use of that needs to make some changes in the power system thus due to its random production of electrical power, solar energy will be a great uncertainty in power system. Therefore, the power grid will be required to the reliable compensator, which compensate the lack of power by help to the generation sector when the production and consumption is imbalanced. The solution of this problem is energy storage and the flexible loads which have the ability to adjust power consumption and reducing it in the real time. Also transportation is one of the main sources of environmental pollution, to this end, PHEV is presented, but the widespread use of them will be creating a significant load on the grid. For this reason, the managing of these loads is required in order to increase permeability of renewable energy resources (solar energy) in a smart distribution grid and decrease the consumers’ dependence on conventional power grids with fossil fuels. Additionally, the chapter develops a charging management program to increase from renewable resources for penetration. The finding show that, this program is made to increase use of renewable energy resources by consumers and reducing received power of the conventional generation.

ACS Style

Mohammad Saadatmandi; Seyed Mehdi Hakimi. Optimal Utilization of Solar Energy for Electric Vehicles Charging in a Typical Microgrid. Electric Vehicles in Energy Systems 2020, 129 -164.

AMA Style

Mohammad Saadatmandi, Seyed Mehdi Hakimi. Optimal Utilization of Solar Energy for Electric Vehicles Charging in a Typical Microgrid. Electric Vehicles in Energy Systems. 2020; ():129-164.

Chicago/Turabian Style

Mohammad Saadatmandi; Seyed Mehdi Hakimi. 2020. "Optimal Utilization of Solar Energy for Electric Vehicles Charging in a Typical Microgrid." Electric Vehicles in Energy Systems , no. : 129-164.

Journal article
Published: 15 October 2019 in Journal of Cleaner Production
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The energy interaction between smart homes can be a solution for developing renewable energy systems in residential sections and optimal energy consumption in homes. The main objectives of such energy interactions are to increase consumer participation in energy management‘ boost economic efficiency‘ increase the user’s satisfaction by choosing between electricity sellers and buyers‘ and reduce the electricity purchased from the grid especially at peak hours. Thus, the innovations of this study includes defining an energy exchange method between smart buildings in an off-grid mode considering renewable energy systems, considering both thermal and electrical equilibrium and studying the lightning loads. it is assumed, here, that smart homes are off-grid‘ and the critical loads are supplied by the energy transfer between the homes using mixed integer linear programming. A compromise between the cost and time interval for using home appliances is considered to provide consumer’s comfort. An objective function is introduced considering programmable and non-programmable loads‘ thermal and electrical storages and lighting loads aiming to optimize the cost of energy between different smart buildings. Based on the method, which is tested in two different cases not only does the total cost of the smart buildings decrease but also the cost is reduced significantly when lightning loads are managed.

ACS Style

Seyed Mehdi Hakimi; Arezoo Hasankhani. Intelligent energy management in off-grid smart buildings with energy interaction. Journal of Cleaner Production 2019, 244, 118906 .

AMA Style

Seyed Mehdi Hakimi, Arezoo Hasankhani. Intelligent energy management in off-grid smart buildings with energy interaction. Journal of Cleaner Production. 2019; 244 ():118906.

Chicago/Turabian Style

Seyed Mehdi Hakimi; Arezoo Hasankhani. 2019. "Intelligent energy management in off-grid smart buildings with energy interaction." Journal of Cleaner Production 244, no. : 118906.

Journal article
Published: 07 February 2019 in Applied Sciences
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This paper develops modeling and describes a control strategy for a modular multilevel converter (MMC) for grid-connected renewable energy systems. The proposed model can be used to simulate MMC activity during normal and faulty situations. Firstly, a dynamic model of a grid-connected MMC (GC-MMC), based upon the symmetrical component of voltages and currents, was designed. Then an adaptive robust control approach was established in order to follow the reference currents of the converter and stabilize the submodule (SM) capacitor voltage. The positive and negative sequences of reference currents that were given from the demanded active and reactive power during grid voltage disturbance and a normal situation were then utilized in control loops. Finally, the numerical results for the performance of the MMC throughout voltage sag conditions and the effect of uncertainties on the filter parameters during changing power demands were evaluated. The results specified that the current control strategy is more potent under voltage sag situations and able to fulfill the stability requirements of the MMC.

ACS Style

Seyed Mehdi Hakimi; Amin Hajizadeh. Voltage Ride through Control Strategy of Modular Multilevel Converter under Unbalanced Voltage Sag. Applied Sciences 2019, 9, 551 .

AMA Style

Seyed Mehdi Hakimi, Amin Hajizadeh. Voltage Ride through Control Strategy of Modular Multilevel Converter under Unbalanced Voltage Sag. Applied Sciences. 2019; 9 (3):551.

Chicago/Turabian Style

Seyed Mehdi Hakimi; Amin Hajizadeh. 2019. "Voltage Ride through Control Strategy of Modular Multilevel Converter under Unbalanced Voltage Sag." Applied Sciences 9, no. 3: 551.

Journal article
Published: 15 October 2018 in Energies
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With the growing of using photovoltaic (PV) units in power distribution systems, the role of high-performance power electronic converters is increasing. In this paper, modelling and control of Modular Multilevel Converter (MMC) are addressed for grid integration of PV units. Designing a proper controller for MMC is crucial during faulty conditions to make the converter stable and provide proper dynamic performance. To achieve this goal, a dynamic model of MMC is presented which it includes symmetrical components of voltage and current. Then, adaptive robust current controllers are developed based on sliding mode and fuzzy controllers for MMC and then the robustness and stability of the controllers are proved by the Lyapunov theory. To implement the proposed controllers under unbalanced grid voltage fault, positive and negative sequences current controllers are implemented to compensate the effect of grid voltage fault and load power variation. Finally, numerical results are shown to evaluate the performance of MMC. In the end, the experimental results are given to prove the controller performance. The outcome indicates that the proposed current controllers are more effective under voltage disturbance conditions and could satisfy the stability of MMC.

ACS Style

Seyed Mehdi Hakimi; Amin Hajizadeh. Integration of Photovoltaic Power Units to Power Distribution System through Modular Multilevel Converter. Energies 2018, 11, 2753 .

AMA Style

Seyed Mehdi Hakimi, Amin Hajizadeh. Integration of Photovoltaic Power Units to Power Distribution System through Modular Multilevel Converter. Energies. 2018; 11 (10):2753.

Chicago/Turabian Style

Seyed Mehdi Hakimi; Amin Hajizadeh. 2018. "Integration of Photovoltaic Power Units to Power Distribution System through Modular Multilevel Converter." Energies 11, no. 10: 2753.

Journal article
Published: 30 September 2017 in Industrial Engineering & Management Systems
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This paper presents an approach for optimal sizing and sitting of distribution generation units in smart microgrid under pool electricity market to reduce total cost and power loss of whole smart microgrid. The costs comprise capital cost, replacement cost, operation and maintenance cost, fuel cost, reliability cost, power loss cost and selling and buying electricity cost. The new idea of this paper is the investigation of pool electricity market aspects in optimization of smart microgrid. On the other hand, cost minimization of smart microgrid is related to their bidding strategies. Therefore two different optimization tools are considered. First, a game-theoretical (GT) model has been used for bidding strategy of smart microgrid as a price-maker, in a long-term electricity market. Secondly, a particle swarm optimization (PSO) algorithm is employed to obtain the best cost value of smart microgrids construction. This study was performed for the Ekbatan residential complex in Tehran, Iran. It has three smart microgrids consist of renewable energy resources. They participate in a long-term electricity market as a price maker. The results show that the proposed method is more effective and has lower cost in finding optimum size and location of distribution generation in smart microgrids.

ACS Style

Seyed Mehdi Hakimi; Amin Hajizadeh. Optimal Sizing and Sitting of Smart Microgrid Units under Pool Electricity Market. Industrial Engineering & Management Systems 2017, 16, 427 -436.

AMA Style

Seyed Mehdi Hakimi, Amin Hajizadeh. Optimal Sizing and Sitting of Smart Microgrid Units under Pool Electricity Market. Industrial Engineering & Management Systems. 2017; 16 (3):427-436.

Chicago/Turabian Style

Seyed Mehdi Hakimi; Amin Hajizadeh. 2017. "Optimal Sizing and Sitting of Smart Microgrid Units under Pool Electricity Market." Industrial Engineering & Management Systems 16, no. 3: 427-436.

Journal article
Published: 01 October 2016 in Sustainable Cities and Society
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The present paper, investigates the stochastic modeling of the domestic electrical load profile in a residential area. The Domestic Load Modeling (DLM) methodologies are more complicated compared to the industrial, commercial and agricultural load modeling. Domestic loads contain a wide diversity of loads that exist in every household consuming a remarkable portion of the overall domestic consumption. Diversity of domestic loads has created different consumption patterns with variable usage timing and duration caused by miscellaneous factors. The intuitive uncertainty in DLM is the main motivation to apply Domestic Loads Stochastic Modeling (DLSM) in the present paper. This study uses multivariable probability distribution function. Additionally, simultaneous correlation between different weekdays and different hours of a day has been performed. Monte Carlo technique is applied in order to generate different samples for domestic electrical load profile. As a result, the behavior of domestic electrical load profile for all residents in a region was estimated based on a limited number of questionnaires using DLSM. The study was performed for the Ekbatan residential complex in Tehran, Iran.

ACS Style

Seyed Mehdi Hakimi. Multivariate stochastic modeling of washing machine loads profile in Iran. Sustainable Cities and Society 2016, 26, 170 -185.

AMA Style

Seyed Mehdi Hakimi. Multivariate stochastic modeling of washing machine loads profile in Iran. Sustainable Cities and Society. 2016; 26 ():170-185.

Chicago/Turabian Style

Seyed Mehdi Hakimi. 2016. "Multivariate stochastic modeling of washing machine loads profile in Iran." Sustainable Cities and Society 26, no. : 170-185.

Journal article
Published: 01 May 2016 in Journal of Energy Storage
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This paper presents novel methods for Demand Response (DR) programs in order to deal with operational uncertainties, such as wind energy and energy price of upstream network, within the framework of a smart Microgrid. Respectively, total loads of a typical Microgrid are classified into three major categories, each of which is represented by a typical load. The First category involves loads with energy storage capability, which is represented by heater loads. In this category, virtual energy storage capability are considered for some special loads. Second group comprises loads with shifting capability that represents by washing machines and the third category consists loads with curtailment capability, which is represented by lighting loads. Using the proposed DR methods, energy consumptions of all mentioned loads are coupled to amounts of wind energy and energy price of upstream network. These methods are applied to the operation of a typical Microgrid, which consists of a dispatchable supplier (microturbine), a non-dispatchable supplier (wind turbine) and an energy storage system. Moreover, the Microgrid has the capability of exchanging energy with upstream distribution network. In order to consider uncertainties, Monte-Carlo simulation method is used, in which various scenarios are generated and applied in the operation of the Microgrid. Finally, simulation results on the Microgrid demonstrate that implementing the proposed DR methods would lead to increasing the total operational profit of the Microgrid from $92 to $108 and also decreasing the risk of low profit.

ACS Style

R. Roofegari Nejad; S.M. Hakimi; Seyed Masoud Moghaddas Tafreshi. Smart virtual energy storage control strategy to cope with uncertainties and increase renewable energy penetration. Journal of Energy Storage 2016, 6, 80 -94.

AMA Style

R. Roofegari Nejad, S.M. Hakimi, Seyed Masoud Moghaddas Tafreshi. Smart virtual energy storage control strategy to cope with uncertainties and increase renewable energy penetration. Journal of Energy Storage. 2016; 6 ():80-94.

Chicago/Turabian Style

R. Roofegari Nejad; S.M. Hakimi; Seyed Masoud Moghaddas Tafreshi. 2016. "Smart virtual energy storage control strategy to cope with uncertainties and increase renewable energy penetration." Journal of Energy Storage 6, no. : 80-94.