109 research outputs found
Wind Farms and Flexible Loads Contribution in Automatic Generation Control: An Extensive Review and Simulation
With the increasing integration of wind energy sources into conventional power systems, the demand for reserve power has risen due to associated forecasting errors. Consequently, developing innovative operating strategies for automatic generation control (AGC) has become crucial. These strategies ensure a real-time balance between load and generation while minimizing the reliance on operating reserves from conventional power plant units. Wind farms exhibit a strong interest in participating in AGC operations, especially when AGC is organized into different regulation areas encompassing various generation units. Further, the integration of flexible loads, such as electric vehicles and thermostatically controlled loads, is considered indispensable in modern power systems, which can have the capability to offer ancillary services to the grid through the AGC systems. This study initially presents the fundamental concepts of wind power plants and flexible load units, highlighting their significant contribution to load frequency control (LFC) as an important aspect of AGC. Subsequently, a real-time dynamic dispatch strategy for the AGC model is proposed, integrating reserve power from wind farms and flexible load units. For simulations, a future Pakistan power system model is developed using Dig SILENT Power Factory software (2020 SP3), and the obtained results are presented. The results demonstrate that wind farms and flexible loads can effectively contribute to power-balancing operations. However, given its cost-effectiveness, wind power should be operated at maximum capacity and only be utilized when there is a need to reduce power generation. Additionally, integrating reserves from these sources ensures power system security, reduces dependence on conventional sources, and enhances economic efficiency
Optimal Ensemble Control of Loads in Distribution Grids with Network Constraints
Flexible loads, e.g. thermostatically controlled loads (TCLs), are
technically feasible to participate in demand response (DR) programs. On the
other hand, there is a number of challenges that need to be resolved before it
can be implemented in practice en masse. First, individual TCLs must be
aggregated and operated in sync to scale DR benefits. Second, the uncertainty
of TCLs needs to be accounted for. Third, exercising the flexibility of TCLs
needs to be coordinated with distribution system operations to avoid
unnecessary power losses and compliance with power flow and voltage limits.
This paper addresses these challenges. We propose a network-constrained,
open-loop, stochastic optimal control formulation. The first part of this
formulation represents ensembles of collocated TCLs modelled by an aggregated
Markov Process (MP), where each MP state is associated with a given power
consumption or production level. The second part extends MPs to a multi-period
distribution power flow optimization. In this optimization, the control of TCL
ensembles is regulated by transition probability matrices and physically
enabled by local active and reactive power controls at TCL locations. The
optimization is solved with a Spatio-Temporal Dual Decomposition (ST-D2)
algorithm. The performance of the proposed formulation and algorithm is
demonstrated on the IEEE 33-bus distribution model.Comment: 7 pages, 6 figures, accepted PSCC 201
Efficient Desynchronization of Thermostatically Controlled Loads
This paper considers demand side management in smart power grid systems
containing significant numbers of thermostatically controlled loads such as air
conditioning systems, heat pumps, etc. Recent studies have shown that the
overall power consumption of such systems can be regulated up and down
centrally by broadcasting small setpoint change commands without significantly
impacting consumer comfort. However, sudden simultaneous setpoint changes
induce undesirable power consumption oscillations due to sudden synchronization
of the on/off cycles of the individual units. In this paper, we present a novel
algorithm for counter-acting these unwanted oscillations, which requires
neither central management of the individual units nor communication between
units. We present a formal proof of convergence of homogeneous populations to
desynchronized status, as well as simulations that indicate that the algorithm
is able to effectively dampen power consumption oscillations for both
homogeneous and heterogeneous populations of thermostatically controlled loads.Comment: 6 pages, 8 Figure
A unified control strategy for active distribution networks via demand response and distributed energy storage systems
AbstractAs part of the transition to a future power grid, distribution systems are undergoing profound changes evolving into Active Distribution Networks (ADNs). The presence of dispersed generation, local storage systems and responsive loads in these systems incurs severe impacts on planning and operational procedures. This paper focuses on the compelling problem of optimal operation and control of ADNs, with particular reference to voltage regulation and lines congestion management. We identify the main challenges and opportunities related to ADNs control and we discuss recent advances in this area. Finally, we describe a broadcast-based unified control algorithm designed to provide ancillary services to the grid by a seamless control of heterogeneous energy resources such as distributed storage systems and demand-responsive loads
Fast and Reliable Primary Frequency Reserves From Refrigerators with Decentralized Stochastic Control
Due to increasing shares of renewable energy sources, more frequency reserves
are required to maintain power system stability. In this paper, we present a
decentralized control scheme that allows a large aggregation of refrigerators
to provide Primary Frequency Control (PFC) reserves to the grid based on local
frequency measurements and without communication.
The control is based on stochastic switching of refrigerators depending on
the frequency deviation. We develop methods to account for typical lockout
constraints of compressors and increased power consumption during the startup
phase. In addition, we propose a procedure to dynamically reset the thermostat
temperature limits in order to provide reliable PFC reserves, as well as a
corrective temperature feedback loop to build robustness to biased frequency
deviations. Furthermore, we introduce an additional randomization layer in the
controller to account for thermostat resolution limitations, and finally, we
modify the control design to account for refrigerator door openings.
Extensive simulations with actual frequency signal data and with different
aggregation sizes, load characteristics, and control parameters, demonstrate
that the proposed controller outperforms a relevant state-of-the-art
controller.Comment: 44 pages, 17 figures, 9 Tables, submitted to IEEE Transactions on
Power System
Natural Heterogeneity Prevents Synchronization of Fridges With Deterministic Frequency Control
Appliances that cycle on and off throughout the day, such as fridges, freezers, and air-conditioners can collectively provide second-by-second electricity supply-demand balancing known as frequency response. Previous studies have shown that deterministic temperature set-point control of a homogeneous population of such appliances can cause herding behavior with detrimental effects on the system. Here, we use computational modeling to establish the minimum population heterogeneity required to prevent herding problems without requiring centralized or stochastic control. We discover a linear relationship between the benefits that fridges can provide and their number. The impact on system benefits and on fridge temperatures of varying fridge frequency sensitivity is also explored, and a viable range for sensitivity (the control parameter) is proposed. Our approach involves simulating a large heterogeneous population of frequency-sensitive fridges using 12 months' GB system data from National Grid. We compare the historic frequency response from other response providers with their response in our fridge simulations to determine the benefits of the fridge population response. We find that a fridge population can offer a valuable demand-side response service to the electricity system operator, requiring neither the expensive infrastructure of centralized control nor the regular intervention of stochastic control for temperature cycle desynchronization
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