An Equivalent Aggregated Model of Large-Scale Flexible Loads for Load Scheduling

Tu, Jiyuan; Zhou, Ming; Cui, Hantao; Li, Fangxing

doi:10.1109/access.2019.2944233

Cited by 18 publications

(7 citation statements)

References 31 publications

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“…In most cases, no better options than curtailment could be found [12], [13], [14]. In some cases, the load is shifted or the peak is shaved by load shedding [15], [16], [17]. These measures would reduce customer comfort, and result in extra costs due to violation of customer contracts.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Control of Power Exchange at Primary Substations: An OPF-Based Solution

Estebsari

Patti

Bottaccioli

2020

2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Syst

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Nowadays, integration of more renewable energy resources into distribution systems to inject more clean energy introduces new challenges to power system planning and operation. The intermittent behaviour of variable renewbale resources such as wind and PV generation would make the energy balancing more difficult, as current forecasting tools and existing storage units are insufficient. Transmission system operators may withstand some level of power imbalance, but fluctuations and noise of profiles are undesired. This requires local management performed or encouraged by distribution system operators. They could try to involve aggregators to exploit flexibility of loads through demand response schemes. In this paper, we present an optimal power flow-based algorithm written in Python which reads flexibility of different loads offered by the aggregators from one side, and the power flow deviation with respect to the scheduled profile at transmission-distribution coupling point from the other side, to define where and how much load to adjust. To demonstrate the applicability of this core, we setup a realtime simulation-based test bed and realised the performance of this approach in a real-like environment using real data of a network.

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Section: Introductionmentioning

confidence: 99%

Real-Time Control of Power Exchange at Primary Substations: An OPF-Based Solution

Estebsari

Patti

Bottaccioli

2020

2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Syst

View full text Add to dashboard Cite

show abstract

“…In most cases, no better options than curtailment could be found [21], [22], [23]. In some cases, the load is shifted or the peak is shaved by load shedding [24], [25], [26]. These measures would reduce customer comfort, and result in extra costs due to violation of customer contract.…”

Section: Introductionmentioning

confidence: 99%

IoT-Enabled Real-Time Management of Smart Grids With Demand Response Aggregators

Estebsari

Mazzarino

Bottaccioli

et al. 2022

IEEE Trans. on Ind. Applicat.

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Integration of widely distributed small-scale Renewable Energy Sources like rooftop Photovoltaic panels and emerging loads like plug-in Electric Vehicles would cause more volatility in total net demand of distribution networks. Utility-owned storage units and control devices like tap changers and capacitors may not be sufficient to manage the system in real-time. Exploitation of available flexibility in demand side through aggregators is a new measure that distribution system operators are interested in. In this paper, we present a developed real-time management schema based on Internet of Things solutions which facilitate interactions between system operators and aggregators for ancillary services like power balance at primary substation or voltage regulation at secondary substations. Two algorithms for power balance and voltage regulation are developed based on modified Optimal Power Flow and voltage sensitivity matrix, respectively. To demonstrate the applicability of the schema, we set-up a real-time simulationbased test bed and realised the performance of this approach in a real-like environment using real data of a network with residential buildings.

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“…Equivalent models of loads with flexible schedules would make the systems more robust and require less computational resources for operation making demand side management easier [28], [29]. While such models can be efficiently implemented in urban areas, the demand side management of rural areas may require a different approach of processing data [30].…”

Section: Introductionmentioning

confidence: 99%

Development of regional load management system based on rural, semi urban and urban loads-a critical analysis

Ganguly

Sil

2022

Bulletin EEI

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The sharp rise in population during the last half century has created immense pressure on the resources required for generation of energy essential to lead a comfortable and healthy lifestyle. The drive towards 100% electrification in developing countries like India has also contributed to this increase in demand. Till recently, fossil fuel was use to supply the bulk of this power. Now, the world is moving more and more towards renewable energy. This paper presents a model where several regions are combined together based on the demand profile of the regions segregated as urban, semi urban and rural along with the flexibility to schedule loads on the basis of availability of renewable energy sources within the area of the regions. The main focus is on detailed neural-networking based load forecasting and developing a load management system to manage load based on availability of distributed generation capacity and available tariff system. A solution is proposed in this paper based on a new approach to answer load management on the basis of region, population demographics and per capita energy consumption. A considerable amount of improvement to manage demand is intended to be attained and has been demonstrated in this research work.

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An Equivalent Aggregated Model of Large-Scale Flexible Loads for Load Scheduling

Cited by 18 publications

References 31 publications

Real-Time Control of Power Exchange at Primary Substations: An OPF-Based Solution

Real-Time Control of Power Exchange at Primary Substations: An OPF-Based Solution

IoT-Enabled Real-Time Management of Smart Grids With Demand Response Aggregators

Development of regional load management system based on rural, semi urban and urban loads-a critical analysis

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