Model-Based Estimation of Energy Savings in Load Control Events for Thermostatically Controlled Loads

Perfumo, Cristian; Braslavsky, Julio H.; Ward, John

doi:10.1109/tsg.2014.2298840

Cited by 50 publications

(14 citation statements)

References 22 publications

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“…In this method, to mitigate the voltage issues with high PV penetration, authors utilized the thermostatic controlled loads (TCLs) with demand response programs (DRs) [112]. As air conditioners belong to the category of TCLs, they received much attention thanks to their fast responses with minimum end user disturbances [113,114]. They are also energy hungry appliances in summer as per the Ausgrid investigation [115].…”

Section: Discussion and Future Research Directionsmentioning

confidence: 99%

A Review of Strategies to Increase PV Penetration Level in Smart Grids

Aleem

Hussain²,

Ustun³

2020

Energies

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Due to environmental concerns, power system generation is shifting from traditional fossil-fuel resources to renewable energy such as wind, solar and geothermal. Some of these technologies are very location specific while others require high upfront costs. Photovoltaic (PV) generation has become the rising star of this pack, thanks to its versatility. It can be implemented with very little upfront costs, e.g., small solar home systems, or large solar power plants can be developed to generate MWs of power. In contrast with wind or tidal generation, PV can be deployed all around the globe, albeit with varying potentials. These merits have made PV the renewable energy technology with highest installed capacity around the globe. However, PV penetration into the grid comes with its drawbacks. The inverter-interfaced nature of the PV systems significantly impacts the power system operation from protection, power flow and stability perspectives. There must be strategies to mitigate these negative impacts so that PV penetration into the grid can continue. This paper gives a thorough overview of such strategies from different research fields: such as communication, artificial intelligence, power electronics and electric vehicle charging coordination. In addition, possible research directions are given for future work.

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Section: Discussion and Future Research Directionsmentioning

confidence: 99%

A Review of Strategies to Increase PV Penetration Level in Smart Grids

Aleem

Hussain²,

Ustun³

2020

Energies

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“…Calculation of robust PID controller requires defining desired transfer function, which is given as (5) where the parameter can be chosen empirically with respect to the system's requirements. Transfer function of pre-filter is recommended to be identical to the desired transfer function .…”

Section: Control System Designmentioning

confidence: 99%

Application of PID controller based on the localization method for ancillary service provision

Hlava

Zemtsov

Frantsuzova

2016

2016 International Siberian Conference on Control and Communications (SIBCON)

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The work deals with usage of classical PID controller to maintain balance between electricity consumption and production using concepts of smart grid and virtual power plant. Aggregated control of large groups of thermostatically controlled loads can be used for ancillary services provision. The focus is on secondary control and peak-shaving, which are a part of the power balance problem. Calculation of PID controller parameters are based on the localization method. The main idea of the localization method is using a derivatives vector of the controlled variable for manipulated variable calculation. The highest derivative implicitly contains full information about plant's state at the current moment. The dynamics of individual building with heaters is described by second order equivalent thermal parameters (ETP) model. The obtained results show that aggregate response of large population of electrical space heaters can meet the requirements on both of the problems. Nevertheless, there are still a lot of issues remaining open: influence of the hysteresis parameter, and using suitable sampling time in order to lower demand on the communication infrastructure.

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“…To have an accurate STLF method, several approaches estimate the load patterns and non-stationary part of load signal by modeling the user behavior and use signal decomposition to extract the non-stationary part of load signal. The user behavior model is built to estimate the exact load signals by considering various inputs, such as user daily schedules, as investigated by Stephen et al [4] and Sajjad et al [5], while Perfumo et al [6] used specific temperature formulation. Another way to investigate user behavior is by using non-intrusive load monitoring to know status of each set of appliances as proposed by Welikala et al [7].…”

Section: Introductionmentioning

confidence: 99%

Optimal Decomposition and Reconstruction of Discrete Wavelet Transformation for Short-Term Load Forecasting

2019

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To achieve high accuracy in prediction, a load forecasting algorithm must model various consumer behaviors in response to weather conditions or special events. Different triggers will have various effects on different customers and lead to difficulties in constructing an adequate prediction model due to non-stationary and uncertain characteristics in load variations. This paper proposes an open-ended model of short-term load forecasting (STLF) which has general prediction ability to capture the non-linear relationship between the load demand and the exogenous inputs. The prediction method uses the whale optimization algorithm, discrete wavelet transform, and multiple linear regression model (WOA-DWT-MLR model) to predict both system load and aggregated load of power consumers. WOA is used to optimize the best combination of detail and approximation signals from DWT to construct an optimal MLR model. The proposed model is validated with both the system-side data set and the end-user data set for Independent System Operator-New England (ISO-NE) and smart meter load data, respectively, based on Mean Absolute Percentage Error (MAPE) criterion. The results demonstrate that the proposed method achieves lower prediction error than existing methods and can have consistent prediction of non-stationary load conditions that exist in both test systems. The proposed method is, thus, beneficial to use in the energy management system.

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Model-Based Estimation of Energy Savings in Load Control Events for Thermostatically Controlled Loads

Cited by 50 publications

References 22 publications

A Review of Strategies to Increase PV Penetration Level in Smart Grids

A Review of Strategies to Increase PV Penetration Level in Smart Grids

Application of PID controller based on the localization method for ancillary service provision

Optimal Decomposition and Reconstruction of Discrete Wavelet Transformation for Short-Term Load Forecasting

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