Load Control Strategy Research Articles

Towards green data center microgrids by leveraging data center loads in providing frequency regulation

In an electricity grid, imbalance between generation and load need be corrected within seconds so that frequency deviations will not threaten the stability and security. This is especially important for a low inertia microgrid operated in islanded mode, which is equipped with a limited number of synchronous generators in regulating frequency. To this end, for data center microgrid with limited on-site generators and increased green energy, when isolated from the utility grid, frequency deviation due to generation-load imbalance could be potentially corrected by conventional generating units as well as data center loads. Focusing on high PV penetrated data center microgrid operated in islanded mode, this paper explores effective control strategies for data center loads to participate in primary frequency response. By analyzing unique operational characteristics of traditional and PV generation units, uninterruptible power supply (UPS) units, and power consumption characteristics of IT components and cooling systems, the proposed load control strategy design effectively utilizes primary FR capabilities while not compromising data center quality of service (QoS) requirements. Numerical simulations via MATLAB/Simulink illustrate effectiveness of the proposed load control strategy in enhancing renewable energy penetration without compromising the system stability and security, providing a viable solution for future green data centers.

Thermostatic Load Control for System Frequency Regulation Considering Daily Demand Profile and Progressive Recovery

Large-scale wind and solar power integration are likely to cause a short-term mismatch between generation and load demand because of the intermittent nature of the renewables. System frequency is therefore challenged. In recent years, it has been proposed that a part of the residential load can be controlled for frequency regulation with little impact on customer comfort. This paper proposes a thermostatic load control strategy for primary and secondary frequency regulation, in particular, using heating, ventilation, and air-conditioning units and electric water heaters. First, daily demand profile modeling indicates that these two loads are complementary in the daytime and can provide a relatively stable frequency reserve. Second, the progressive load recovery is specifically considered in the control scheme. The random switching and cycle recovery method is proposed for mitigating power rebound after switching the air conditioners on again. The proposed control strategy can organize a large population of thermostatic loads for the provision of a frequency reserve. Consequently, the requirement of a spinning reserve is reduced. Finally, the proposed control strategy is verified by the dynamic simulation of IEEE RTS 24-bus system.

Distributed Control With Virtual Capacitance for the Voltage Restorations, State of Charge Balancing, and Load Allocations of Heterogeneous Energy Storages in a DC Datacenter Microgrid

This paper proposes a distributed coordination control strategy for load sharing and energy balancing between heterogeneous energy storages. These control objectives are satisfied through a two-level control structure. At the primary level, the decentralized virtual impedance control, without the requirement of communication links, allocates the low frequency component of the loads to batteries, while the high frequency component is allocated to ultracapacitors. Distributed control strategy, introduced at the secondary level over a sparse communication network, achieves battery state of charge balancing and regulation of the local bus voltages. Two sets of data are exchanged via the communication links, the local bus voltages, and state of charges of batteries. The distributed controller for the restoration of local bus voltages implements an average consensus protocol, while the controller for energy balancing uses a cooperative protocol. In addition, the ultracapacitor voltages are locally restored at a slower time-scale. The proposed control strategy is resilient to communication link failures and features plug-and-play capability. Presented results demonstrate performance of the proposed control strategy for an islanded 380 VDC datacenter with variable loads. Different operating conditions are verified through the RTDS Technologies real-time digital power system simulator using switching converter models and nonlinear battery models.

Control Strategy of Central Air-conditioning Load Participate in Peak Adjustment

At present, the proportion of air-conditioning load on the user side is increasing, and the air-conditioning loads have the ability to store thermal energy. By reasonable controlling air-conditioning loads to participate in peak adjustment, the potential of air-conditioning load regulation can be effectively played. In this paper, a temperature control model of central air-conditioning loads is established based on the calculation method of building cooling load. Fully the periodic paused control strategy for central air-conditioning load is proposed to release the conflict between electricity supplying and demanding in the period of peak load, considering the heat storage and heat dissipation characteristics of buildings and the heat dissipation characteristics of changing flow rate of people, without affecting or less affecting the users comfort. Then, taking a business district as an example, the feasibility of temperature control model of central air-conditioning and the hierarchical strategies periodic paused control strategy is verified.

Control Strategy of Electric Heating Loads for Reducing Power Shortage in Power Grid

With the development of demand response technology, it is possible to reduce power shortages caused by loads participating in power grid dispatching. Based on the equivalent thermal parameter model, and taking full account of the virtual energy storage characteristics presented during electro-thermal conversion, a virtual energy storage model suitable for electric heating loads with different electrical and thermal parameters is proposed in this paper. To avoid communication congestion and simplify calculations, the model is processed by discretization and linearization. To simplify the model, a control strategy for electric heating load, based on the virtual state ofcharge priority list, is proposed. This paper simulates and analyzes a control example, explores the relevant theoretical basis affecting the control effect, and puts forward an optimization scheme for the control strategy. The simulation example proved that the proposed method in this paper can reduce power storage in the grid over a long period of time and can realize a power response in the grid.

Stochastic optimized chiller operation strategy based on multi-objective optimization considering measurement uncertainty

Chillers are responsible for nearly 30–40% of the energy consumption of an HVAC system. To enhance the efficiency of HVAC systems, it is necessary to optimize the operation of chillers. Conventional chiller operation strategies are mostly intended to save energy by suitably distributing the chiller cooling load in accordance with the measured cooling system data, which is typically considered noise-free. In other words, the uncertainty of the cooling system measurement and the necessity of customized optimization—as different buildings require different tradeoffs between energy-saving and indoor comfort—are usually not considered. This paper proposes a stochastic optimized chiller operation strategy based on multi-objective optimization and measurement uncertainty. The strategy consists of five steps: (1) Quantify the indoor comfort utility and energy consumption utility by using utility functions; (2) integrate these two utilities into one comprehensive utility using user-defined weights; (3) specify the measurement uncertainty distribution in the cooling system; (4) traverse each possible operation plan, and calculate the mean value (i.e., mathematical expectation) of its corresponding comprehensive utility (expected utility, EU); and (5) determine the optimal operation plan to be the one corresponding to the maximum EU value. The performance of the proposed strategy is validated by establishing a cooling system model on TRNSYS and comparing the findings with those of two conventional chiller operation strategies commonly adopted in Shanghai: the cooling load control strategy and coefficient of performance (COP) optimization strategy. Moreover, the robustness of the proposed strategy is validated by performing a comparison with the deterministic multi-objective strategy, which assumes that the measured system data is noise-free. The simulation results suggest that the proposed strategy can be customized to satisfy different optimization requirements such as less energy consumption or a high level of indoor comfort.

Economic Operation Modeling and Optimization of an Island Micro Grid Considering Load Control

This paper proposes an optimization control of micro-grid system economy operation model. It coordinates the new energy and storage operation with diesel generator output, so as to achieve the economic operation purpose of micro-grid. In this paper, the micro-grid network economic operation model is transformed into mixed integer programming problem, which is solved by the mature commercial software, and the new model is proved to be economical, and the load control strategy can reduce the charge and discharge times of energy storage devices, and extend the service life of the energy storage device to a certain extent.

Adjustable loads control and stochastic stability analysis for multi-energy generation system based on Markov model

This paper mainly addresses the issue of the power generation fluctuations due to the stochastic characteristics of the renewable energies, which threaten the stability of the power grid. First, the multi-energy generation system with integration of wind and photovoltaic power is modeled in the framework of Markov model to describe the dynamic changes. Second, to weaken the active power fluctuation of renewable energies generation and improve the utilization of renewable energies, the flexible loads are added for local consumption and an adjustable load control strategy is proposed to guarantee the output power continuous stability of the renewable energies generation. Then, the stochastic stability is analyzed by using Markov stability theory. Finally, the simulation results and analysis are provided to illustrate the effectiveness of the proposed schemes.

A loading control strategy for electric load simulator based on new mapping approach and fuzzy inference in Cerebellar Model Articulation Controller

To improve surplus torque suppression and loading performance of electric load simulators, this paper presents a loading control strategy based on the new mapping approach and fuzzy inference scheme in the fuzzy Cerebellar Model Articulation Controller. The proposed mapping approach and fuzzy inference scheme in the fuzzy Cerebellar Model Articulation Controller, designed free from the mathematical model of system, comprises a mapping fuzzy Cerebellar Model Articulation Controller and a fuzzy inference controller, in which the former is the main controller. By introducing the new mapping approach in mapping fuzzy Cerebellar Model Articulation Controller, the proposed control strategy is actually a global network with local weight updating and its continuity has been enhanced. The fuzzy inference controller is used as a fuzzy compensator. As a torque controlled system, electric load simulator takes the loading error as the performance index. The results of dynamic simulation and experiments indicate that the proposed loading control strategy can achieve favorable control performance.

Combining the Flexibility From Shared Energy Storage Systems and DLC-Based Demand Response of HVAC Units for Distribution System Operation Enhancement

In this study, a direct load control strategy for procuring flexibility from residential heating, ventilation, and air conditioning (HVAC) units and the optimal management of shared energy storage systems connected at different buses of a distribution system is proposed, as a new contribution with respect to earlier studies, aiming to minimize the energy demand during DR event periods. Moreover, an additional objective related to the minimization of the end-users’ discomfort induced by the interruption of the HVAC units is considered, leading to the formulation of a bi-level optimization problem based on a second-order conic programming representation of the AC power flow equations. The effectiveness of the proposed methodology is demonstrated by performing simulations on a test system and comparisons with other approaches.

A bilayer interaction strategy for air‐conditioning load aggregators considering market‐based demand response

With considerable portion of air-conditioning load in total power consumption, air-conditioning load aggregators are authorised to participate in power market by aggregating large amounts of air-conditioning load with or without ice storage system. This paper studies on a bilayer interaction strategy for air-conditioning load aggregators considering market-based demand response, on the basis of a hierarchical deregulated day-ahead market architecture. In the upper layer, load aggregators submit their bids to independent system operator (ISO), after evaluating their load regulation potential. With the aim of minimising load dispatch cost, ISO optimises the dispatch schedule and informs each LA of its bid-winning capacity under a pay-as-bid pricing scheme. In the lower layer, air-conditioning load aggregator adopts a flexible control strategy to optimise the control actions in an effort to maximise its own benefits, as well as keeping indoor temperature within the temperature range in the contract and achieving the desired aggregated demand response capacity allocated by ISO in the upper layer. Thermal dynamic characteristics and corresponding power consumption characteristics of air-conditioning load control strategies are analysed. The resulting model is a mixed-integer non-linear optimisation problem. Finally, simulation verifies the feasibility and effectiveness of the proposed strategy.

Effects of upstream buildings on the performance of a synergistic roof-and-diffuser augmentation system for cross flow wind turbines

In a previous work we investigated the effectiveness of combining the concentration effects generated by a dual-pitched roof and a convergent-divergent semi-diffuser placed over a cross flow turbine (CFT), which is rooftop mounted with horizontal shaft running close to the roof ridge. By means of 2D CFD we now assess the effects of the upstream buildings on the performance of this concentration system. Three different urban layouts are simulated via a challenging fully-resolved URANS approach that gives unprecedented insight into the complex interactions of the flow around buildings, diffuser and turbine's blades. A promising power augmentation of 40% with respect to the case without diffuser are obtained and the mechanism behind this performance enhancement are analysed. The beneficial effect of the diffuser on the torque fluctuations damping (∼60%) is also discussed. Important remarks on the load control strategy for diffuser-augmented CFT are finally presented.

Appliance level data analysis of summer demand reduction potential from residential air conditioner control

Residential air-conditioner loads are known to be a key driver of summer demand peaks for some electricity industries. Such demand peaks occur infrequently but have potentially severe implications for network and peaking generation plant investment, and hence electricity prices for end users. Detailed assessments of air-conditioner peak demand have, however, been hampered by limited residential consumption data, and even when interval meter data is available, the complexities of other household loads and behavior. This study utilizes data from a significant appliance level consumption monitoring project in Sydney, Australia, to analyze the actual contribution of air-conditioners to regional summer demand peaks. K-means clustering is used to characterize air-conditioner load profiles across a large number of households at times of these overall demand peaks. These clustered air-conditioning load profiles, combined with a number of possible load control strategies, are then used to estimate possible peak load reductions from air-conditioner demand response across the Australian State of New South Wales. Our findings suggest that residential air-conditioning presents a significant demand response opportunity, approaching perhaps 9% of total peak demand in some circumstances.

Control of Energy-Intensive Load for Power Smoothing in Wind Power Plants

Uncertainty of the wind power output is the main influence factor for wind power utilization in the bulk power system. Because of the large capacity and the load characteristic, energy-intensive load holds great potentials to share the burden of wind power fluctuation smoothing. In this paper, a direct control scheme of the energy-intensive load power is proposed to smooth the wind power fluctuation. Based on the characteristic of the energy-intensive load production technology, the feasibility of energy-intensive load control and its influence on the production are discussed. A feedback control is designed to regulate the saturable reactor and transformer tap changer when the power support from the bulk power system is limited. Regulation capacity is analyzed quantitatively based on the energy-intensive load equivalent circuit model. A grid-connected energy-intensive enterprise driven by self-generation wind power plants and thermal power plants is studied as an example case. By the proposed energy-intensive load control scheme, power fluctuation of the wind farms can be smoothed with the minimum control cost. Besides, the regulation requirement of the bulk power system is eased correspondingly so that the utilization capacity of the power system can be improved significantly. Simulation is done on the real-time digital simulator to verify the effectiveness of the proposed control method.

Improved Boiler-Turbine Coordinated Control of CHP Units with Heat Accumulators by Introducing Heat Source Regulation

It is significant for power system stability to improve the operation flexibility of grid-connected units. Such improvement has always been a hot topic, especially for coal-fired units. In recent decades, it has become increasingly urgent and challenging as large-scale fluctuant renewable energy is connected to the power grid. Boiler-turbine coordinated control strategy (CCS), which is employed to perform unit load control according to automatic generation control (AGC), has a slow ramp rate in general on account of large delay and inertia of boiler, so to improve the unit operating flexibility, it is necessary to explore usable heat storage and optimize the control strategy. In combined heat and power (CHP) units with heat accumulators, their heat and power are decoupled. Therefore the extraction steam that goes to the heating station can be regulated flexibly even operating in “heat-led mode”. The change of extraction steam flow has a significant influence on the turbine power output, so we propose to improve the load-following capability of CHP units by regulating the heat source flow. In this paper, the influencing model is set up, and it is about heat source flow variations on the electric power output. The load control strategy is further optimized and designed through combinations of CCS and heat source regulation. Finally simulations and analysis are performed on a 330MW CHP unit, and the results reveal that the power ramp rate with our strategy is two times faster than that with traditional strategy.

Sparse and Resilient Hierarchical Direct Load Control for Primary Frequency Response Improvement and Inter-Area Oscillations Damping

The aim of this paper is to define and develop an optimal hierarchical demand-side power-system primary-frequency control structure in order to provide a reliable complement to generator inertia and governor response while improving inter-area oscillation damping. This resilient optimal load control strategy utilizes both wide-area and local signals to guarantee that the system remains stable in the case of communication failures. In the device layer, we deal with demand-response and frequency regulation by minimizing the total disutility of consumers subject to power balance and frequency regulation over the network. In the supervisory layer, we handle the power system's electromechanical oscillations using an linear-quadratic regulator (LQR)-based state feedback scheme with sparsity promotion to achieve the necessary tradeoff between complexity and performance. Since the wide-area feedback loops are built on top of an existing decentralized load control strategy, this design approach creates a decentralized/hierarchical demand-side load-control structure with significant advantages in terms of reliability and operational flexibility. Our study clearly shows by simulation that a demand-side hierarchical load-control strategy has a significant potential for improving the dynamic performance of power systems, even when implemented with a limited number of measurement units and controlling less than $1\%$ of the total base load.

Current-based MPC for operating-safety analysis of a reduced-order solid oxide fuel cell system

One of the key issues for integrated solid oxide fuel cell (SOFC) systems, which is a high-temperature power-generation plant, is the cooperative control of safe operating during load tracking. As the operating safety, especially the fuel exhaustion rejection and thermal management, are the key challenging for long-time implementation during load following. To this end, these above problems are studied in this dissertation from the aspects of thermo-electrical modeling, operating-safety analysis and controller development. This paper mainly focus on the cooperative control of the issues such as temperature constrains, fuel exhaustion rejection and external load tracing. Based on the reduced order model, a current-based model predictive controller (MPC) is proposed, and the transient performance associated with simultaneous dynamic operating-safety performance and current rate are addressed. Simulation results show the competition of the control design by demonstrating the fast load following ability while maintaining the safe operation. Namely the control strategy of fast load following is on the premise of operating safety under normal working conditions. All these control analysis results in this work can provide an important reference on the solutions of thermo-electrical control for SOFC system.

Multiobjective Autonomous Intelligent Load Control for Hybrid Single-/Three-Phase AC/DC Smart Buildings

Modern distribution grids and smart buildings comprise unbalanced single-phase, three-phase, DC, and constant power loads and battery energy storage systems (BESSs). This paper presents a hybrid single/three-phase multiobjective automated/autonomous intelligent load (MAIL1) control for smart buildings. The main focus is to autonomously and automatically respond to grid disturbances and power imbalances and unbalances by adaptive demand adjustment of various loads. Also, it can realize regulation objectives of a supervisory operator to enable fast building demand control to participate in performance-based frequency regulation markets. Moreover, it is a unified load control strategy for both grid-connected and islanded hybrid single/three-phase AC/DC grids with smooth transition between them without a need for the strategy reconfiguration. The MAIL1 renders an adaptive and continuous demand for single-phase AC and DC loads. The MAIL1 is based on a fundamentally new controller for single-phase voltage source converters (VSCs) by introducing single-phase DC-source synchronous current converter technology, with extra functionalities such as auto-synchronization with single-phase grids and virtual inertia. Extensive real-time hardware-in-loop results are presented to demonstrate the MAIL1 performance.

Interactive Energy-Saving Dispatch Considering Generation and Demand Side Uncertainties: A Chinese Study

The energy-saving dispatch is becoming one of the most important smart grid components in China, which asks for both generation and demand side resources' participation. In smart electricity grid, the uncertainties related with variable renewable energy outputs on the generation side, as well as the deviations between the scheduled demand response (DR) resources and their actual availabilities on the demand side should be simultaneously taken care of. In this paper, a new energy-saving dispatch problem is studied considering the uncertainties from both generation and demand sides. A bi-level optimization model is established to address the generation and demand side's interactions considering economic dispatch of thermal units and load control schemes of end users in the new energy-saving dispatch problem. The upper-level minimizes the electric transmission company's power generation and carbon emission costs while maintaining the system reliability, and the lower-level minimizes the expected total load dispatch cost paid by the electric distribution company to DR providers and the demand side emission cost. An iterative algorithm is adopted to solve the proposed bi-level model. In addition, improved NSGA-II method is used to solve the lower-level multi-objective optimization problem for seeking optimal compromise solution. Numerical case studies on the practical energy-saving dispatch problem of Guangdong Province in China illustrate the effectiveness of the proposed approach.

A Loading Control Strategy for Electric Load Simulators Based on Proportional Resonant Control

In order to effectively suppress surplus torque, realizing high precision loading, this paper applies proportional resonant (PR) control to the load torque control of electric load simulator (ELS), and analyzes and optimizes the stability and dynamic performance of ELS. The mathematical model of ELS is built in z -domain first in this paper, to establish foundation for designing and analyzing PR controller. The stability of the ELS with PR controller is analyzed through Nyquist diagrams, and optimized by reasonably designing the phase compensation angle of PR controller. The dynamic performance is analyzed through pole–zero plots, and the resonant gain of PR controller is designed based on the pole–zero plots to optimize the dynamic performance. Experimental results on ELS are provided, and the proposed method is compared with other typical methods, validating the effectiveness of the proposed method.