This page has only limited features, please log in for full access.

Unclaimed
Ghulam Mohy-Ud-Din
Faculty of Engineering and Information Sciences, School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, New South Wales, Australia, 2522

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 04 February 2021 in IEEE Transactions on Industry Applications
Reads 0
Downloads 0

Virtual power plants (VPPs) have become a driving force for the decentralized energy industry, due to their efficient management and control of distributed energy resources. Most of the operation strategies for VPPs are designed based on the day-ahead forecasts. However, the prediction errors of the renewable energy sources (RES) and loads in the power dispatch schedule can lead to a sub-optimal operation. In this paper, an adaptive and predictive energy management strategy for a real-time optimal operation of VPPs is proposed based on the model predictive control technique with a feedback correction (FC) to compensate for the prediction error. This strategy has two parts: a) receding-horizon optimization (RHO), and b) FC. In the first part, a hybrid prediction algorithm based on the integration of the time series model and the Kalman filter is used to forecast the output powers of RES and the loads. Based on the prediction, the RHO model schedules the operation following the latest forecast information. In the second part, the receding schedule is adjusted based on the fast-rolling grey model's ultra-short-term error prediction. The FC is applied to minimize the adjustments for compensating the prediction error. The proposed strategy is implemented on a VPP in a real electricity distribution system in New South Wales, Australia. The simulation results demonstrate the effectiveness of the proposed strategy with a better tracking of the actual available resources and a minimal mismatch between demand and supply.

ACS Style

Ghulam Mohy-Ud-Din; Kashem M. Muttaqi; Danny Sutanto. Adaptive and Predictive Energy Management Strategy for Real-Time Optimal Power Dispatch From VPPs Integrated With Renewable Energy and Energy Storage. IEEE Transactions on Industry Applications 2021, 57, 1958 -1972.

AMA Style

Ghulam Mohy-Ud-Din, Kashem M. Muttaqi, Danny Sutanto. Adaptive and Predictive Energy Management Strategy for Real-Time Optimal Power Dispatch From VPPs Integrated With Renewable Energy and Energy Storage. IEEE Transactions on Industry Applications. 2021; 57 (3):1958-1972.

Chicago/Turabian Style

Ghulam Mohy-Ud-Din; Kashem M. Muttaqi; Danny Sutanto. 2021. "Adaptive and Predictive Energy Management Strategy for Real-Time Optimal Power Dispatch From VPPs Integrated With Renewable Energy and Energy Storage." IEEE Transactions on Industry Applications 57, no. 3: 1958-1972.

Journal article
Published: 07 January 2020 in IEEE Transactions on Industry Applications
Reads 0
Downloads 0

Many modern industries are equipped with on-site renewable generation and are normally connected to the grid. A battery energy storage system (BESS) can complement the intermittency of the available on-site renewable generation. The combination of the BESS and the renewable generation can operate as a microgrid. If the microgrid is properly sized and managed, it is possible to reduce the electricity-bill to have a huge saving in the electricity-cost. This paper proposes an energy management system for such industrial microgrids. The decisions to charge and discharge the BESS in the proposed energy management are usually constrained by the size of the energy storage. The proposed energy management strategy aims to optimize the operation of the industrial microgrid subject to the scalability of the BESS under uncertainties. The proposed optimization involves two-stages. In the first-stage of optimization, it determines the optimum size of the energy storage taking into account the cost of the BESS, and in the second-stage, it minimizes the cost of the microgrid operation based on the decision made in the first-stage. This proposed two-stage energy management strategy is formulated as a single-stage linear program that incorporates stochastic scenarios for addressing uncertainties. In addition, the proposed strategy also considers the various operating limits of the energy storage such as the efficiency, the charging and the discharging rates and considers the fading effect of the batteries of the BESS. The proposed strategy is then validated using two typical data-sets from two different industrial units in New South Wales, Australia.

ACS Style

Ghulam Mohy-Ud-Din; Dao Hoang Vu; Kashem M. Muttaqi; Danny Sutanto. An Integrated Energy Management Approach for the Economic Operation of Industrial Microgrids Under Uncertainty of Renewable Energy. IEEE Transactions on Industry Applications 2020, 56, 1062 -1073.

AMA Style

Ghulam Mohy-Ud-Din, Dao Hoang Vu, Kashem M. Muttaqi, Danny Sutanto. An Integrated Energy Management Approach for the Economic Operation of Industrial Microgrids Under Uncertainty of Renewable Energy. IEEE Transactions on Industry Applications. 2020; 56 (2):1062-1073.

Chicago/Turabian Style

Ghulam Mohy-Ud-Din; Dao Hoang Vu; Kashem M. Muttaqi; Danny Sutanto. 2020. "An Integrated Energy Management Approach for the Economic Operation of Industrial Microgrids Under Uncertainty of Renewable Energy." IEEE Transactions on Industry Applications 56, no. 2: 1062-1073.

Journal article
Published: 22 October 2019 in IEEE Transactions on Industrial Electronics
Reads 0
Downloads 0
ACS Style

Kai Zou; Ghulam Mohy-Ud-Din; Ashish P. Agalgaonkar; Kashem M. Muttaqi; Sarath Perera. Distribution System Restoration With Renewable Resources for Reliability Improvement Under System Uncertainties. IEEE Transactions on Industrial Electronics 2019, 67, 8438 -8449.

AMA Style

Kai Zou, Ghulam Mohy-Ud-Din, Ashish P. Agalgaonkar, Kashem M. Muttaqi, Sarath Perera. Distribution System Restoration With Renewable Resources for Reliability Improvement Under System Uncertainties. IEEE Transactions on Industrial Electronics. 2019; 67 (10):8438-8449.

Chicago/Turabian Style

Kai Zou; Ghulam Mohy-Ud-Din; Ashish P. Agalgaonkar; Kashem M. Muttaqi; Sarath Perera. 2019. "Distribution System Restoration With Renewable Resources for Reliability Improvement Under System Uncertainties." IEEE Transactions on Industrial Electronics 67, no. 10: 8438-8449.

Conference paper
Published: 01 September 2019 in 2019 IEEE Industry Applications Society Annual Meeting
Reads 0
Downloads 0

Many modern industries are equipped with on-site renewable generation and are normally connected to the grid. A battery energy storage system (BESS) can complement the intermittency of the available on-site renewable generation. The combination of the BESS and the renewable generation can operate as a microgrid. If the microgrid is properly sized and managed, it is possible to reduce the electricity bill to have a huge saving in the electricity cost. This paper proposes an energy management system for such an industrial microgrids. The decisions to charge and discharge the BESS in the proposed energy management are usually constrained by the size of the energy storage. The proposed energy management strategy aims to optimize the operation of the industrial microgrids subject to the scalability of the BESS under uncertainties. The proposed optimization involves two stages. In the first stage of optimization, it determines the optimum size of the energy storage taking into account the cost of the BESS, and in the second stage, it minimizes the cost of the microgrid operation based on the decision made in the first stage. This proposed two-stage energy management strategy is formulated as a single stage linear program that incorporates stochastic scenarios for addressing uncertainties. In addition, the proposed strategy also considers the various operating limits of the energy storage such as the efficiency, the charging and the discharging rates and considers the fading effect of the batteries of the BESS. The proposed strategy is then validated using two typical data sets from two different industrial units in New South Wales, Australia. The simulation results show that the proposed strategy effectively calculates the optimum size of the BESS and reduces the operational cost.

ACS Style

Ghulam Mohy-Ud-Din; D. H. Vu; K. M. Muttaqi; D. Sutanto. An Integrated Energy Management Approach for the Economic Operation of Industrial Microgrids under Uncertainty of Renewable Energy. 2019 IEEE Industry Applications Society Annual Meeting 2019, 1 -8.

AMA Style

Ghulam Mohy-Ud-Din, D. H. Vu, K. M. Muttaqi, D. Sutanto. An Integrated Energy Management Approach for the Economic Operation of Industrial Microgrids under Uncertainty of Renewable Energy. 2019 IEEE Industry Applications Society Annual Meeting. 2019; ():1-8.

Chicago/Turabian Style

Ghulam Mohy-Ud-Din; D. H. Vu; K. M. Muttaqi; D. Sutanto. 2019. "An Integrated Energy Management Approach for the Economic Operation of Industrial Microgrids under Uncertainty of Renewable Energy." 2019 IEEE Industry Applications Society Annual Meeting , no. : 1-8.

Book chapter
Published: 29 July 2019 in Variability, Scalability and Stability of Microgrids
Reads 0
Downloads 0

A microgrid (MG) is a distinct energy system consisting of distributed energy resources (DERs) and loads having the ability to operate in parallel with, or independently from, the main power grid. MGs, which were initially introduced to ensure smooth operation and control of DERs in distribution networks, offer unprecedented economic and reliability benefits to electricity consumers with minimal carbon emission. These benefits, however, must be analysed and compared with the capital investment cost of the MG to ensure a complete return on investment and to justify the MG deployment. The biggest obstacle for the widespread and rapid deployment of MGs is the high capital investment cost of MGs. A true assessment of MGs economic benefits is a challenging task due to the significant uncertainties involved in the assessment. These uncertainties may include the intermittency of the renewable generation, the varying states of charge (SoC) of battery energy storage system (BESS), the uncertain demands, the varying market price, the probability of the MG islanding, the level of developer's risk-aversion and the unpredictably of the user preferences in the smart load management system. Moreover, some of the assessment metrics, such as the measure of reliability improvements are difficult to comprehend for consumers when represented in terms of the supply availability. Thus, efficient and optimum planning models are required to ensure the economic feasibility of MG deployments and to justify the investments based on cost-to-profit analysis under uncertain conditions. This chapter demonstrates a detailed model for the optimum sizing of MG components under the uncertainties involved in the system. The proposed model is validated with the simulation of several case studies conducted on a system depicting a similar MG in a medium-voltage (MV)-distribution system derived from electricity network of a power utility in New South Wales, Australia. The results from the case studies demonstrate the efficacy of the proposed model for the optimum sizing of the MG components to justify the MG deployment.

ACS Style

Ghulam Mohy-Ud-Din; Kashem M. Muttaqi; Danny Sutanto. Sizing of microgrid components. Variability, Scalability and Stability of Microgrids 2019, 221 -262.

AMA Style

Ghulam Mohy-Ud-Din, Kashem M. Muttaqi, Danny Sutanto. Sizing of microgrid components. Variability, Scalability and Stability of Microgrids. 2019; ():221-262.

Chicago/Turabian Style

Ghulam Mohy-Ud-Din; Kashem M. Muttaqi; Danny Sutanto. 2019. "Sizing of microgrid components." Variability, Scalability and Stability of Microgrids , no. : 221-262.

Article
Published: 16 April 2019 in IET Generation, Transmission & Distribution
Reads 0
Downloads 0

Virtual power plants (VPPs) are emerging as a source of flexibility to the power systems because of their potential to provide a cost-effective solution in the real time to complement the power mismatch due to intermittent renewable energy generation and avoid expensive upgrades to the network infrastructure to meet the peak demands. These features of the VPPs best fit in the transactive energy environment. Since the VPPs are driven through the wholesale energy market, a two-stage transactive energy-based planning framework for the integrated VPPs in a co-optimised energy and ancillary services market is proposed in this study. At the first stage, during the day-ahead market, a co-optimised combined optimum schedule is obtained for the power system and the VPPs including the ancillary services. Flexible demand bids are proposed at this stage as a source of flexibility in the operation of the power system. At the second stage, a transactive energy-based real-time market balancing scheme is proposed. Furthermore, the proposed framework is validated on a modified 24-bus IEEE RTS and 118-bus IEEE power system with integrated VPPs. The simulation results show that the proposed approach results in a reduction of the locational marginal prices, congestion and reserve costs.

ACS Style

Ghulam Mohy‐Ud‐Din; Kashem M. Muttaqi; Danny Sutanto. Transactive energy‐based planning framework for VPPs in a co‐optimised day‐ahead and real‐time energy market with ancillary services. IET Generation, Transmission & Distribution 2019, 13, 2024 -2035.

AMA Style

Ghulam Mohy‐Ud‐Din, Kashem M. Muttaqi, Danny Sutanto. Transactive energy‐based planning framework for VPPs in a co‐optimised day‐ahead and real‐time energy market with ancillary services. IET Generation, Transmission & Distribution. 2019; 13 (11):2024-2035.

Chicago/Turabian Style

Ghulam Mohy‐Ud‐Din; Kashem M. Muttaqi; Danny Sutanto. 2019. "Transactive energy‐based planning framework for VPPs in a co‐optimised day‐ahead and real‐time energy market with ancillary services." IET Generation, Transmission & Distribution 13, no. 11: 2024-2035.

Conference paper
Published: 01 September 2018 in 2018 IEEE Industry Applications Society Annual Meeting (IAS)
Reads 0
Downloads 0

In this paper, an effective, three-stage day-ahead (DA) scheduling strategy for a wind farm (WF) with integrated multi-unit battery energy storage systems (BESSs) is proposed. In the first stage, a statistical flexible dispatch margin (FDM) based on the long-term wind forecast error-data is calculated to deal with the uncertainty of the wind power forecast. The FDM is modeled in such a manner that it not only compensates for the shortage of the wind power but also takes in account the expected excess amount of the wind power due to forecast errors. The conservativeness of the margin-based solution is addressed through the dynamic reliability evaluation of FDM. This FDM is realized using the multi-unit BESSs. At the second stage, a robust optimization formulation is presented that makes this strategy cost-effective in terms of revenue. Finally, at the third stage, a multi-unit BESS scheduling algorithm is presented that ensures equal cycles of charge and discharge avoiding the abrupt switching between the charging and the discharging modes to enhance the lifetime of BESS. The proposed scheduling strategy is compared with scenario-based stochastic and worst-case realization based robust optimization scheduling frameworks. The simulation studies, utilizing the real data, suggest that the proposed strategy is better in terms of the uncertainty mitigation, the total revenue obtained, the enhanced BESS lifetime and the computational time.

ACS Style

Ghulam Mohy-Ud-Din; Kashem M. Muttaqi; Darmawan Sutanto. An Effective Power Dispatch Strategy to Improve Generation Schedulability by Mitigating Wind power Uncertainty with a Data Driven flexible Dispatch Margin for a Wind Farm using a Multi-Unit Battery Energy Storage System. 2018 IEEE Industry Applications Society Annual Meeting (IAS) 2018, 1 -8.

AMA Style

Ghulam Mohy-Ud-Din, Kashem M. Muttaqi, Darmawan Sutanto. An Effective Power Dispatch Strategy to Improve Generation Schedulability by Mitigating Wind power Uncertainty with a Data Driven flexible Dispatch Margin for a Wind Farm using a Multi-Unit Battery Energy Storage System. 2018 IEEE Industry Applications Society Annual Meeting (IAS). 2018; ():1-8.

Chicago/Turabian Style

Ghulam Mohy-Ud-Din; Kashem M. Muttaqi; Darmawan Sutanto. 2018. "An Effective Power Dispatch Strategy to Improve Generation Schedulability by Mitigating Wind power Uncertainty with a Data Driven flexible Dispatch Margin for a Wind Farm using a Multi-Unit Battery Energy Storage System." 2018 IEEE Industry Applications Society Annual Meeting (IAS) , no. : 1-8.

Conference paper
Published: 01 May 2018 in 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA)
Reads 0
Downloads 0

This paper suggests an innovative scheme for examining the optimized power flow problem based on optimum position and configuration setting of Unified power flow controller (UPFC) by utilizing the artificial algae algorithm (AAA) technique. Flexible AC Transmission system (FACTS) devices have the ability to provide flexibility and control for complex power transmission systems. Unified power flow controller is proficient fellow of FACTS which has the capacity to regulate power system constraints (line impedance, voltage profile and phase angle). The core aim of this research is to solve the optimal power flow problem by curtailing or removing the over-loaded of lines and the bus voltage violations created under contingency circumstances. In first round, the contingency analysis and raking process is performed while taking the transmission line loading and voltage violations as a decision parameter (DP=NOVL+NVVB). Afterwards, the proposed technique (AAA) is exercised to discover the solution of optimal power flow issue based on optimal location of UPFC with its parameters setting under the generated single contingency of line scenarios. The simulations studies are practiced on IEEE standard benchmark-5 bus system to check the performance of this novel scheme.

ACS Style

Muhammad Zahid; Jinfu Chen; Yinhong Li; Boya Shan; Ghulam Mohy-Ud-Din; Asad Waqar. Application of AAA for optimized placement of UPFC in power systems. 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA) 2018, 30 -35.

AMA Style

Muhammad Zahid, Jinfu Chen, Yinhong Li, Boya Shan, Ghulam Mohy-Ud-Din, Asad Waqar. Application of AAA for optimized placement of UPFC in power systems. 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA). 2018; ():30-35.

Chicago/Turabian Style

Muhammad Zahid; Jinfu Chen; Yinhong Li; Boya Shan; Ghulam Mohy-Ud-Din; Asad Waqar. 2018. "Application of AAA for optimized placement of UPFC in power systems." 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA) , no. : 30-35.

Journal article
Published: 30 October 2017 in Energies
Reads 0
Downloads 0

Operation of power system within specified limits of voltage and frequency are the major concerns in power system stability studies. As power system is always prone to disturbances, which consequently affect the voltage instability and optimal power flow, and therefore risks the power systems stability and security. In this paper, a novel technique based on the “Artificial Algae Algorithm” (AAA) is introduced, to identify the optimal location and the parameters setting of Unified Power Flow Controller (UPFC) under N-1 contingency criterion. In the first part, we have carried out a contingency operation and ranking process for the most parlous lines outage contingencies while taking the transmission lines overloading (NOLL) and voltage violation of buses (NVVB) as a performance parameter (PP = NOLL + NVVB). As UPFC possesses too much prohibitive cost and larger size, its optimal location and size must be identified before the actual deployment. In the second part, we have applied a novel AAA technique to identify the optimal location and parameters setting of UPFC under the discovered contingencies. The simulations have been executed on IEEE 14 bus and 30 bus networks. The results reveals that the location of UPFC is significantly optimized using AAA technique, which has improved the stability and security of the power system by curtailing the overloaded transmission lines and limiting the voltage violations of buses.

ACS Style

Muhammad Zahid; Jinfu Chen; Yinhong Li; Xianzhong Duan; Qi Lei; Wang Bo; Ghulam Mohy-Ud-Din; Asad Waqar. New Approach for Optimal Location and Parameters Setting of UPFC for Enhancing Power Systems Stability under Contingency Analysis. Energies 2017, 10, 1738 .

AMA Style

Muhammad Zahid, Jinfu Chen, Yinhong Li, Xianzhong Duan, Qi Lei, Wang Bo, Ghulam Mohy-Ud-Din, Asad Waqar. New Approach for Optimal Location and Parameters Setting of UPFC for Enhancing Power Systems Stability under Contingency Analysis. Energies. 2017; 10 (11):1738.

Chicago/Turabian Style

Muhammad Zahid; Jinfu Chen; Yinhong Li; Xianzhong Duan; Qi Lei; Wang Bo; Ghulam Mohy-Ud-Din; Asad Waqar. 2017. "New Approach for Optimal Location and Parameters Setting of UPFC for Enhancing Power Systems Stability under Contingency Analysis." Energies 10, no. 11: 1738.

Journal article
Published: 01 January 2017 in Journal of Renewable and Sustainable Energy
Reads 0
Downloads 0

Increasing environmental concerns have led to a push for renewable energy sources to be extensively used to reduce emissions. In this paper, we investigate a hybrid dynamic economic emission dispatch (HDEED) problem involving thermal, wind, and photovoltaic(PV)generation systems. Our formulation considers the stochastic nature of both wind and PVgenerated power, and differences because of mismatches between the actual and allocated wind and PV power. A hybrid backtracking search algorithm with sequential quadratic programming was used to minimize the total operational costs and emissions, while dispatching power to the committed generation units subject to all operational constraints. To verify the efficacy, we applied the proposed technique to solve the dynamic economic emission dispatch problem on five and ten unit test systems. The proposed technique was also used to solve the HDEED problem on IEEE 30 bus, 6-unit and IEEE 57 bus, 7-unit test systems, with and without renewable generation. The results of our numerical simulations show the efficiency of the proposed technique with respect to reducing operational costs and emissions. Moreover, our results show that by incorporating renewable energy into existing power systems, we can reduce operational costs and emissions.

ACS Style

Ghulam Mohy-Ud-Din. Hybrid dynamic economic emission dispatch of thermal, wind, and photovoltaic power using the hybrid backtracking search algorithm with sequential quadratic programming. Journal of Renewable and Sustainable Energy 2017, 9, 15502 .

AMA Style

Ghulam Mohy-Ud-Din. Hybrid dynamic economic emission dispatch of thermal, wind, and photovoltaic power using the hybrid backtracking search algorithm with sequential quadratic programming. Journal of Renewable and Sustainable Energy. 2017; 9 (1):15502.

Chicago/Turabian Style

Ghulam Mohy-Ud-Din. 2017. "Hybrid dynamic economic emission dispatch of thermal, wind, and photovoltaic power using the hybrid backtracking search algorithm with sequential quadratic programming." Journal of Renewable and Sustainable Energy 9, no. 1: 15502.