A hybrid approach to balance the variability and intermittency of renewable generation

Hug-Glanzmann, Gabriela

doi:10.1109/ptc.2011.6019448

Cited by 10 publications

(4 citation statements)

References 14 publications

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“…It can be observed from the research work conducted by the authors in [35] that apart from shedding the load demand, there are scenarios where the load demand could be increased to retain the output of RES near the maximum power point (when the SBS is completely charged). The uncertainties in RES power generation have been considered in the development of various DRM algorithms in [36, 37]. In the above research, the power consumed by the loads is assumed to be maintained constant at their rated power during their operation without any cycling or variations.…”

Section: Literature Surveymentioning

confidence: 99%

“…2, pp. [31][32][33][34][35][36][37][38][39] This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/) residential refrigerators, since residential refrigerators cannot be considered as physical thermal energy storage systems such as the ones described in [19,20].…”

Section: Introductionmentioning

confidence: 99%

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Virtual energy storage capacity estimation using ANN‐based kWh modelling of refrigerators

2018

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Prolific integration of renewable energy sources (RESs) such as solar photovoltaic systems into the distribution network will result in various issues associated with their intermittent nature. Energy storage is a vital component for overcoming issues associated with the intermittent nature of such RES. Though stationary battery systems are used as energy storage for such applications, smart energy storage (SES) systems are also becoming popular owing to various advantages and advent of smart grid systems. SES can be achieved by aggregating electric vehicles (EVs) or by using demand response management for loads with large time constants. Aggregated residential refrigerators are potential candidates for creating SES which has virtual storage capacity, unlike EVs. In this study, residential refrigerators are modelled analogously to energy capacity and selfdischarge of electro-chemical batteries using the artificial neural network based kWh modelling. The model is further extended to estimate the virtual energy storage (VES) capacity with aggregated residential refrigerators; particularly in high-rise residential buildings. Simulation results are presented for scenarios covering the complete range of thermal capacity of typical refrigerators applicable in Singapore's climatic condition. Furthermore, a brief description of the possible applications for the estimated VES, pertaining to smart grid architecture and cyber-attack is also presented.

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Section: Literature Surveymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Virtual energy storage capacity estimation using ANN‐based kWh modelling of refrigerators

2018

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“…Among various types of RES [1], wind and solar photovoltaic based energy sources are the most adopting technologies even at the end-user level. The benefits of using RES over fossil fuels are like (1) reduced active power losses, (2) improved voltage profile, (3) increased overall energy efficiency, (4) congestion relief across the system elements and (5) potential increase of service quality to the end-customers etc., In spite of the outstanding advantages of RES, certain shortcomings exist and among those the intermittency is the major issue and the solutions to the intermittency problem has been addressed in [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Transmission Security Enhancement under (N−1) Contingency Conditions with Optimal Unified Power Flow Controller and Renewable Energy Sources Generation

Kavuturu

Narasimham

2020

J. Electr. Eng. Technol.

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Introduction Transmission system security management under (N−1) line contingency is one of the typical and essential tasks in power system operation and control. This paper examines the impact of the optimal unified power flow controller (OUPFC) and renewable energy sources (RES) on the severity of (n−1) line contingency on transmission system security. Materials and methods To test the performance of OUPFC device under single line contingency conditions, an optimal power flow (OPF) based multi-objective function is formulated using real power loss and line collapse proximity indicator (LCPI). Primarily, the optimal location of the OUPFC is determined using LCPI index and then (n−1) contingency analysis is performed by considering OUPFC device at different RES generation levels. Here, the control variables of OUPFC, tapchangers, VAr injections, output power of conventional energy sources (CES), bus voltages and bus angles are optimized with two different variants of the cuckoo search algorithm (CSA) namely (1) dynamically increasing switching parameter in power of three (CSA1) and (2) exponentially increasing switching parameter (CSA2). Conclusion The simulation results of various case studies on a standard IEEE-30 bus test system have shown the superiority of CSA2 in solving the multi-objective, non-linear complex optimization problem over CSA1 and time-varying acceleration coefficient-particle swarm optimization (TVAC-PSO). Also, the ability of OUPFC for managing the impact of (n−1) line contingency and variable RES generation is shown in terms of decreased real power loss, improved voltage profile and enhanced security margin.

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“…The inherent intermittent generation characteristics of solar PVs have not been considered in these research works. Although the uncertainties in solar PV generation have been considered in the development of various DRM algorithms in [14,15], the power consumed by the loads is assumed to be maintained constant at their rated power during their operation without any cycling or variations.…”

Section: Introductionmentioning

confidence: 99%

Virtual storage capacity using demand response management to overcome intermittency of solar PV generation

Kandasamy

Tseng

Soong

2017

IET Renewable Power Generation

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The integration of solar photovoltaic (PV) systems into the distribution network creates various stability and reliability issues associated with the intermittency of solar PV power generation. Energy storage is a vital component required for overcoming the intermittency of solar PV. This study presents a priority-based demand response management (DRM) for loads with large time constants to create virtual energy storage. The virtual energy storage thus created can be used for partial levelling of intermittent output from solar PVs. The proposed DRM algorithm involves controlling loads with large time constants such as air conditioning systems and refrigerators based on the forecasted solar PV generation. The proposed method is evaluated using data-driven simulations, weather data and mathematical models. The proposed algorithm is highly suitable for megacities that have high number of multi-storey residential buildings. Utilising the virtual storage capacity available from the appliances will reduce the investment as well as the operation cost of renewable energy such as solar PV. Analyses on impact on temperature, percentage of interruptions, cost savings and impact on energy storage sizing are also presented for evaluating the performance of the proposed algorithm. Nomenclature T n ac, on(max) usual turn ON time of the nth air conditioner T n ac, off(max) usual turn OFF time of the nth air conditioner T n ref, on(max) usual turn ON time of the nth refrigerator T n ref, off(max) usual turn OFF time of the nth refrigerator x ac, on , x ac, off proportion of turn ON and turn OFF time for air conditioners x ref, on , x ref, off proportion of turn ON and turn OFF time for refrigerators T n ac, on current turn ON time of the nth air conditioner T n ac, off current turn OFF time of the nth air conditioner T n ref, on current turn ON time of the nth refrigerator T n ref, off current turn OFF time of the nth refrigerator p j vsc, c estimated virtual storage capacity (charging) during jth interval p j vsc, d estimated virtual storage capacity (discharging) during the jth interval p j bpd power required from the battery during the jth interval p ave_pv_op average solar PV output on a given day N off ref number of refrigerators that can be turned off N off ac number of air conditioners that can be turned off N on ref number of refrigerators that can be turned on N on ac number of air conditioners that can be turned on

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A hybrid approach to balance the variability and intermittency of renewable generation

Cited by 10 publications

References 14 publications

Virtual energy storage capacity estimation using ANN‐based kWh modelling of refrigerators

Virtual energy storage capacity estimation using ANN‐based kWh modelling of refrigerators

Transmission Security Enhancement under (N−1) Contingency Conditions with Optimal Unified Power Flow Controller and Renewable Energy Sources Generation

Virtual storage capacity using demand response management to overcome intermittency of solar PV generation

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