INVESTIGATION AND MODELLING OF LOAD SHEDDING AND ITS MITIGATION USING HYBRID RENEWABLE ENERGY SYSTEM

This paper outlines a solution to the problem of load shedding by integrating the renewable energy source (RES) with the conventional power grid. The case study is presented for the electricity sector of Pakistan having energy crisis. The proposed method provides a localized and practical solution to mitigate the effect of load shedding that arises due to an imbalance between the power supply and the demand. Grid stability is ensured by the assistance of photovoltaic (PV) and battery banks to avoid critical frequency disturbance. Investigations are carried out to provide an uninterrupted supply of electricity by dynamic frequency control with the help of a centralized energy management system (CEMS). It is envisaged that the proposed solution can be applied to increase the generation capacity on an immediate basis which is not possible through conventional sources.

[1]  P. M. Anderson,et al.  A low-order system frequency response model , 1990 .

[2]  Chen Chen,et al.  Study on a system frequency response model for a large industrial area load shedding , 2005 .

[3]  Iftikhar A. Lodhi Pakistan's energy crisis: Challenges and opportunities , 2008 .

[4]  K. C. Divya,et al.  Battery Energy Storage Technology for power systems-An overview , 2009 .

[5]  David Infield,et al.  Domestic electricity use: A high-resolution energy demand model , 2010 .

[6]  Kashif Ishaque,et al.  Accurate MATLAB Simulink PV System Simulator Based on a Two-Diode Model , 2011 .

[7]  U Rudez,et al.  Analysis of Underfrequency Load Shedding Using a Frequency Gradient , 2011, IEEE Transactions on Power Delivery.

[8]  Lu Zhang,et al.  Optimal sizing study of hybrid wind/PV/diesel power generation unit , 2011 .

[9]  Kashif Ishaque,et al.  An improved modeling method to determine the model parameters of photovoltaic (PV) modules using differential evolution (DE) , 2011 .

[10]  Sajjad Ali Haider,et al.  Solar energy potential in Pakistan , 2012 .

[11]  G. Andersson,et al.  Generation of Domestic Load Profiles-an Adaptive Top-Down Approach , 2012 .

[12]  Turan Gonen,et al.  Electric Power Distribution Engineering , 2014 .

[13]  Kinjal G. Shah,et al.  A Low Order System Frequency ResponseModel for Large Power System and AdaptiveLoad Shedding , 2015 .

[14]  Kashif Ishaque,et al.  Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review , 2015 .

[15]  Shahrin Md. Ayob,et al.  Perturbative methods for maximum power point tracking (MPPT) of photovoltaic (PV) systems: a review , 2015 .

[16]  Z. Salam,et al.  An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency , 2015 .

[17]  Pierre-Francois Marty Design of a hybrid power PV – Genset – Battery storage system for a remote off-grid application in Malaysia , 2016 .

[18]  Zainal Salam,et al.  A critical review of electric vehicle charging using solar photovoltaic , 2016 .

[19]  Emanuela Colombo,et al.  Novel procedure to formulate load profiles for off-grid rural areas , 2016 .

[20]  S. C. Kaushik,et al.  A review on modeling, design methodology and size optimization of photovoltaic based water pumping, standalone and grid connected system , 2016 .

[21]  Yang Zhang,et al.  Battery sizing and rule-based operation of grid-connected photovoltaic-battery system : A case study in Sweden , 2017 .

[22]  S. Rehman,et al.  National energy scenario of Pakistan - Current status, future alternatives, and institutional infrastructure: An overview , 2017 .

[23]  Ziping WU,et al.  State-of-the-art review on frequency response of wind power plants in power systems , 2018 .

[24]  M. S. Khalil,et al.  An overview of implemented renewable energy policy of Pakistan , 2018 .

[25]  Zainal Salam,et al.  A rule-based energy management scheme for uninterrupted electric vehicles charging at constant price using photovoltaic-grid system , 2018, Renewable Energy.

[26]  Bingtuan Gao,et al.  A Bottom-Up Model for Household Load Profile Based on the Consumption Behavior of Residents , 2018, Energies.