Interruptible Load Management Research Articles

Control strategies for large industrial users to participate in interruptible load response considering production characteristics

The interruptible cost benefit of large industrial users is an important factor to decide whether to participate in interruptible load management, which has a direct impact on users’ interruption and the choice of interruption strategy. Different industrial users have different production processes and electricity consumption characteristics. This paper first analyzes the production and power consumption characteristics of users, then analyzes the cost and benefit of large industrial users participating in interruptible load response, as the basis for judging whether users are willing to participate in interruptible load response. Finally, the case study can provide some guidance for enterprises to formulate the response strategy of interruptible load.

Research on interruptible load supply curve simulation based on industrial classification

Recently, with the adjustment of industrial structure, peak power load is getting sharper in China. Interruptible Load Management (ILM) enables power system to gain deterministic access to Interruptible Load (IL) provided by power consumers, which can use a more economical way to ensure real-time balance and safe operation of power system. This paper proposes a simulation method of interruptible load supply curve of lager industrial power consumers based on industrial classification, which can predict capacity of interruptible load that lager industrial power consumers are willing to provide under different interruptible load prices. An example towards a China’s eastern province shows that, if government wants to acquire interruptible load capacity of 10 million kW, the interruptible price should be priced higher than 0.7 RMB/kWh.

Smart Distribution Boards (Smart DB), Non-Intrusive Load Monitoring (NILM) for Load Device Appliance Signature Identification and Smart Sockets for Grid Demand Management.

Traditionally, the choices to balance the grid and meet its peaking power needs are by installing more spinning reserves or perform load shedding when it becomes too much. This problem becomes worse as more intermittent renewable energy resources are installed, forming a substantial amount of total capacity. Advancements in Energy Storage System (ESS) provides the utility new ways to balance the grid and to meet its peak demand by storing un-used off peak energy for peak usage. Large sized ESS—mega watt (MW) level—are installed by different utilities at their substations to provide the high speed grid stabilization to balance the grid to avoid installing more capacity or triggering any current load shedding schemes. However, such large sized ESS systems and their required inverters are costly to install, require much space and their efficacy could also be limited due to network fault current limits and impedances. In this paper, we propose a novel approach and trial for 3000+ homes in Singapore of achieving a large capacity of demand management by developing a smart distribution board (DB) in each home with the high speed metering sensors (>6 kHz sampling rate) and non-intrusive load monitoring (NILM) algorithm, that can assist home users to perform the load/appliance profile identification with daily usage patterns and allow targeted load interruption using the smart sockets/plugs provided. By allowing load shedding at device or appliance level, while knowing their usage profile and preferences, this can allow such an approach to become part of a new voluntary interruptible load management system (ILMS) that requires little user intervention, while minimizing disruption to them, allowing ease of mass participation and thus achieving the intended MW demand management capacities for the grid. This allows for a more cost effective way to better balance the grid without the need for generation capacity growth, large ESS investment while improving the way to perform load shedding without disruptions to entire districts. Simply, home users can now know and participate with the grid in interruptible load (IL) schemes to target specific home appliance, such as water heaters or air conditioning, allowing interruptions during certain times of the day, instead of the entire house, albeit with the right incentives. This allows utilities to achieve MW capacity load shedding with millions of appliances with their preferences, and most importantly, with minimal disruptions to their consumers quality of life. In our paper, we will also consider coupling a small sized Home Energy Storage System (HESS) to amplify the demand management capacity. The proposed approach does not require any infrastructure or wiring changes and is highly scalable. Simulation results demonstrate the effectiveness of the NILM algorithm and achieving high capacity grid demand management. This approach of taking user preferences for appliance level load shedding was developed from the results of a survey of 500 households that indicates >95% participation if they were able to control their choices, possibly allowing this design to be the most successful demand management program than any large ESS solution for the utility. The proposed system has the ability to operate in centralized as part of a larger Energy Management System (EMS) Supervisory Control And Data Acquisition (SCADA) that decide what to dispatch as well as in autonomous modes making it simpler to manage than any MW level large ESS setup. With the availability of high-speed sampling at the DB level, it can rely on EMS SCADA dispatch or when disconnected, rely on the decaying of the grid frequency measured at the metering point in the Smart DB. Our simulation results demonstrate the effectiveness of our proposed approach for fast grid balancing.

Research on Interruptible Load Management of Electric Vehicle Charging Considering Price Risk

The rapid development of electric vehicle industry promotes the construction of charging infrastructure and charging station. In the operation of charging station, how to ensure the stable profit of charging equipment under the condition of excessive charging load has become a crucial issue. Based on this, this paper focuses on how charging stations sign interruptible load contracts with users during peak load period and consider their risk coefficients to formulate optimal competition strategies so as to maximize expected profits. Finally, the problems and conclusions are summarized.

Designing interruptible load management scheme based on customer performance using mechanism design theory

Interruptible load management (ILM), as an important incentive-based demand response (DR) program, plays a critical role in power system operation. An improved ILM scheme design method is proposed in the paper. From the perspective of social welfare, the scheme design is described as an optimization problem, and then mechanism design theory is adopted for solving. The novel idea presented in the paper is that the customer baseline load (CBL) is used to parameterize the type of customer (TOC), which is fundamental information for application of mechanism design theory. Being private information, TOC is not directly attainable, but CBL can be estimated based on historical load data (namely the customer performance), and it can reflect the customers’ rational judgments in self-benefit decisions. Firstly, the validity of adopting CBL to determine TOC is demonstrated. Then, the load curtailing potential constraints and the objective function are rebuilt in the expression of CBL correspondingly, so that the mechanism design theory successfully works with CBL instead of TOC. Moreover, adjustment strategies are also proposed to cope with the possible unenforceable scheme scenarios, thus the practicability of the designed scheme is ensured. Finally, simulations are carried out to validate the effectiveness of the proposed method.

Economic Dispatch and Interruptible Load Management with Renewable Energy using Particle Swarm Optimization

Economic Dispatch and Interruptible Load Management with Renewable Energy using Particle Swarm Optimization

Transmission Capability of the Grid Cross Section Considering the Interruptible Load Management

This paper proposes a mathematical model of power grid section transmission limit under the constraints of N-1 contingency analysis and interruptible load management. By loosen the conditions of traditional N-1 analysis with the interruptible load management on demand side, an improved power grid section transmission limit model considering the interruptible load and power flow constraints is established. The opposite-quantities-adjusted in pairs method based on branch sensitivity is studied and proposed to solve the model. The quantitative relationship between the increments of the grid section transmission limit and the load interrupted quantities is tested with the IEEE39–bus testing system. The simulation result shows that the application of interruptible load can improve the grid section transmission limit, as well as improving the operation economy while the security of the power system is guaranteed.

Stochastic Optimization-Based Economic Dispatch and Interruptible Load Management With Increased Wind Penetration

In this paper, stochastic optimization of economic dispatch (ED) and interruptible load management is investigated using short-term distributional forecast of wind farm generation. Specifically, using the statistical information of wind farm generation extracted from historical data, a Markov chain-based distributional forecast model for wind farm generation is developed in a rigorous optimization framework, in which the diurnal nonstationarity and the seasonality of wind generation are accounted for by constructing multiple finite-state Markov chains for each epoch of 3 h and for each individual month. Based on this distributional forecast model, the joint optimization of ED and interruptible load management is cast as a stochastic optimization problem. Additionally, a robust ED is formulated using an uncertainty set constructed based on the proposed distributional forecast, aiming to minimize the system cost for worst cases. The proposed stochastic ED is compared with four other ED schemes: 1) the robust ED; 2) deterministic ED using the persistence wind generation forecast model; 3) scenario-based stochastic ED; and 4) deterministic ED, in which perfect wind generation forecasts are used. Numerical studies, using the IEEE Reliability Test System-1996 and realistic wind measurement data from an actual wind farm, demonstrate the significant benefits obtained by leveraging the Markov chain-based distributional forecast and the interruptible load management.

The Combined Generation-Consumption Scheduling Mode Considering Price-Responsive and Interruptible Loads

In order to provide reserve power supply, consumption dispatch can be integrated into the conventional generation dispatch model. This serves as a feasible approach in connecting intermittent power sources such as hydropower into the power grid. An integrated generation-consumption dispatch model with hydropower is presented considering the consumption dispatch mode, such as consumption stimulation, interruptible load management, and price response, etc. Practical case studies show that price-responsive loads and interruptible loads tend to exert great influence on the load distribution which lead to a reallocation of generation among thermal generation units, run-of-river and storage hydropower generation units, which favours the total reservoir storage of the system so that the overall system operational economy can be improved.

New Impact Factors-Based Transmission Congestion Management

Abstract. By utilizing interruptible load management can be quickly and flexibly to eliminate the root causes of congestion on the line, based on lowbidding interruptible load have priority in electricity markets. This paper selects the interrupt interruptible load at the same time taking into account the sensitivity and interruptible load costs factor. By building mathematical models of congestion sensitivity, and combined with interruptible load costs form the new impact factors, as the basis of choice of interruptible load adjustments needed. A congestion management model was proposed with the goal of minimizing the congestion elimination cost, and has attempted to find the solution to it. Finally, a practical case is designed to validate the economic and validity of the method. And have achieved the expected effect.

Interruptible Load Risk Analysis Based on Portfolio Theory

Due to the uncertain price and stochastic load, power supply companies will face the trade-off between profits and risks when exercising Interruptible Load Management (ILM). Customers of different type are looked as sub-markets with different risk and benefit. A model is established for Interruptible Load (IL) in the framework of portfolio theory, with the object of maximizing the expected profits and risks of conditional value at risk (CVaR). Genetic Algorithm (GA), is adopted to solve the model. Finally, a numerical example is served for demonstrating the market property of high profits accompanied by high risks and the feasibility of the proposed model, thus a reference is provided to a power supply company to manage risks.

Application of Intelligent Algorithms to Interruptible Load Dispatch Model

Interruptible load management plays an important role in maintaining the reliability and security of power systems and reducing price spike of power markets, thus has been widely used in power systems. Interruptible loads dispatch problem with multi-period and multi-interruptible-load is usually a multi-objective, combinatorial optimization problem, and its solution method needs to be carefully investigated. Application of intelligent optimization algorithms to the multi-period interruptible load dispatch problem is discussed in this paper. Multi objectives, such as minimizing the interruption payments and interruption frequency, can be included in the proposed interruptible load dispatch model. The characteristics of different interruptible loads are also considered. Numerical simulations using discrete binary particle swarm optimization (BPSO) and the genetic algorithm (GA) show that the BPSO can obtain better solutions than that of the GA. Thus the BPSO presents better potentials in solving the interruptible load dispatch problem.

Research of Interruptible Load Management Model via Incentive Compatibility

In this paper interruptible load management model via incentive compatibility is researched. Simulated the interruptible load capacity and disruption of economic compensation of the interruptible load management with using MATLAB and compare the cost of interruptible load management and construction of standby units, find that interruptible load management can reduce the cost of electricity companies. But it should be noted that when the interrupt the load is too large, the implementation of interruptible load management will increase the operating costs of the utilities.

Integrating Direct Load Control With Interruptible Load Management to Provide Instantaneous Reserves for Ancillary Services

This paper presents a novel adaptive control strategy for integrating direct load control (DLC) with interruptible load management (ILM) to provide instantaneous reserves for ancillary services in deregulated power systems. Fuzzy dynamic programming is used to satisfy customers' requirements and yields a near optimal pre-scheduling of the DLC. Then, the energy payback associated with the DLC is further eliminated by the adaptive control strategy, which exploits interruptible loads to modify the DLC schedule in real-time. Through the developed adaptive control strategy, the influences of the load uncertainties and forecasting errors on the pre-scheduling of the DLC can also be excluded. The proposed algorithm was practically tested on the Taiwan power (Taipower) 38-unit system with 20 air-conditioner loads and 15 interruptible loads. The outcomes reveal that an exact amount of instantaneous reserves can be successfully acquired, and the results are robust against dynamic disturbances of the power system.

A Model Reference Adaptive Control Strategy for Interruptible Load Management

This paper presents a model reference adaptive control (MRAC) strategy for interruptible load management (ILM). The proposed MRAC strategy consists of fuzzy dynamic programming (FDP) and priority-based heuristics inference rule (PBHIR) to offer a flexible solution and a real-time adjusting scheme for the ILM problem. The customers' requirements can be dealt with by the fuzzy variables, and the optimal or near optimal schedule of interrupted load can be acquired through DP search scheme. Additionally, a PBHIR is further employed as a regulator for the MRAC to modulate the schedule of the interrupted load in real time. The influences of the load variations and forecasting errors on the outputs of the FDP can be eliminated by the MRAC. The proposed MRAC strategy is tested practically on the Dar-Gun substation in Taiwan power (Taipower) system. The test results demonstrate the feasibility and effectiveness of applying the proposed method to the ILM problem.

Interruptible load management using optimal power flow analysis

An interruptible load management (ILM) scheme is proposed using dynamic optimal power flow analysis. It enables real-time selection of interruptible loads incorporating power network constraints and dynamic restriction on generation, viz. ramp-rate limits. The model provides an analytical framework for addressing several important issues associated with optimal selection of load curtailment, e.g. advance notification for load curtailment, short-term price discounts and long-term discounts on demand-charges, power factor of the load and customer-cost associated with the load to be curtailed, and power system security. A six-bus example illustrates the proposed methodology.