List of Articles پاسخگویی بار

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  1 - Optimal Economic Scheduling of Islanding Microgrid Considering Renewable Energy Sources (Wind Turbine and Photovoltaic System), Battery and Hydrogen Storage System in the Presence of the Demand Response Program
  A. Mehdizadeh N. Taghizadegan
  Microgrid (MG) supplied its local load with distributed energy resources at the low voltage system in distribution networks. Microgrid can be used in parts that are not allowed access to the electricity network with low investment cost. The used islanding MG in this res More

  Microgrid (MG) supplied its local load with distributed energy resources at the low voltage system in distribution networks. Microgrid can be used in parts that are not allowed access to the electricity network with low investment cost. The used islanding MG in this research includes wind turbine and photovoltaic systems as renewable energy sources and hydrogen storage system (HSS). This paper proposes a new energy management strategy (EMS) for MG in the presence of the HSS considering the power uncertainties of renewable energy sources. The objective of proposed EMS is to minimize the operating costs of batteries, HSS and the costs associated with excess and undelivered energy considering the supplied load constraints. The considered technical constraints in this paper contain renewable energy sources limits and battery and HSS constraints. HSS includes electrolyzer (EL), hydrogen tanks and fuel cell (FC). Demand response program (DRP) is used to flat the load curve and optimal operation of MG. The proposed model on a MG is been implemented in GAMS software. The simulation results show that the operation cost of MG reduced by using of HSS and DRP. Manuscript profile
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  2 - Assessment of Demand Side Resources Potential in Presence of Cooling and Heating Equipment Using Data Mining Method Based Upon K-Means Clustering Algorithm
  fatemeh sheibani M. Mollahassani-pour هنگامه کشاورز
  Under the smart power systems, determining the amount of Demand Response Resources(DRRs) potential is considered as a crucial issue due to affecting in all energy policy decisions. In this paper, the potential of DRRs in presence of cooling and heating equipment are ide More

  Under the smart power systems, determining the amount of Demand Response Resources(DRRs) potential is considered as a crucial issue due to affecting in all energy policy decisions. In this paper, the potential of DRRs in presence of cooling and heating equipment are identified using k-means clustering algorithm as a data mining technique. In this regard, the energy consumption dataset are categorized in different clusters by k-means algorithm based upon variations of energy price and ambient temperature during peak hours of hot (Spring and Summer) and cold (Autumn and Winter) periods. Then, the clusters with the possibility of cooling and heating equipment’s commitment are selected. After that, the confidence interval diagram of energy consumption in elected clusters is provided based upon energy price variations. The nominal potential of DRRs, i.e. flexible load, will be obtained regarding the maximum and minimum differences between the average of energy consumption in upper and middle thresholds of the confidence interval diagram. The energy consumption, ambient temperature and energy price related to BOSTON electricity network over a six-year horizon time is utilized to evaluate the proposed model. Manuscript profile
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  3 - Multi-Objective Economic-Environment Scheduling of Microgrids in the Presence of Hybrid Electric Vehicles and Demand Response to Smooth the Distribution Nodal Prices
  ali mirzaei NAVID TAGHIZADEGAN KALANTARI Sajad Najafi Ravadanegh
  Today, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper int More

  Today, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper introduces a new multi-objective optimization model, which in the first objective, minimizes the total operation cost of the microgrid, and in the second objective, improves the reliability index by reducing the amount of energy not supplied. Due to these two objectives, a multi-objective evolutionary seagull optimization algorithm is used to find the optimal global solutions. In this regard, hybrid electric vehicles and demand response programs are used to smooth out distribution nodal prices and reduce CO2 emissions. The 69-bus distribution network has been used to evaluate the efficiency of the proposed method. Manuscript profile