Load Management System Using Intelligent Monitoring and Control System for Commercial and Industrial Sectors

Eissa, M.M.; Wasfy, S. M.; Sallam, Mohamed

doi:10.5772/51850

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…13 When the conditions exist for approaching the demand set-point, the device sequentially switches off interruptible (or controllable) loads according to a priority. 13 When the conditions exist for approaching the demand set-point, the device sequentially switches off interruptible (or controllable) loads according to a priority.…”

Section: Demand Measurement and Controlmentioning

confidence: 99%

“…In PDC systems, the disconnection of the controllable load is performed by means of devices that optimize power reduction or disconnection from the grid on the basis of a preestablished limit regarding the maximum load. 13 When the conditions exist for approaching the demand set-point, the device sequentially switches off interruptible (or controllable) loads according to a priority. 13 A demand control systems typically is composed of the following components: (a) a programmable logic controller (PLC) or microprocessor with input channels to detect the electrical energy (kWh) pulses and output channels for sending ON/OFF commands to the controllable loads and (a) a human-machine interface (HMI) for visualization and entering parameters; see Figure 3.…”

Section: Demand Measurement and Controlmentioning

confidence: 99%

“…13 When the conditions exist for approaching the demand set-point, the device sequentially switches off interruptible (or controllable) loads according to a priority. 13 A demand control systems typically is composed of the following components: (a) a programmable logic controller (PLC) or microprocessor with input channels to detect the electrical energy (kWh) pulses and output channels for sending ON/OFF commands to the controllable loads and (a) a human-machine interface (HMI) for visualization and entering parameters; see Figure 3. The PDC typically is implemented as real-time controller using the PLC scan time as a cycle time to compute and execute the control commands to the controllable loads.…”

Section: Demand Measurement and Controlmentioning

confidence: 99%

See 2 more Smart Citations

Power demand control algorithm for single controllable load with parametric and variable load factors

Martell

Sánchez‐Chávez

Peña‐Cruz

et al. 2019

Int Trans Electr Energ Syst

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Summary Power demand control is required at steelmaking plants and other energy intensive industrial plants where the electrical bills include high demand charges and are subject to demand limit contracts. This paper introduces a novel and simplified algorithm for the implementation of a power demand controller. The presented algorithm does not require a model of the electrical load since it is based on a geometrical approach for the estimation of the disconnection time of the controllable load and only requires the nominal power values and the load factors of both the total (full) load and the noncontrollable (base) load as parameters. The power demand control method presented is verified with a computational simulation, and precise control of the demand limit is achieved under random variations of the base and full loads. The proposed control algorithm is simpler than commercial methods and achieves a competitive performance. Simulation results show a better performance by calculating the disconnection times based on load parameters specified as mean values between the average and nominal powers of the full and base loads. Some considerations to tune‐up the load factor parameters are also discussed. The presented control method has been successfully implemented on industrial controllers in two steelmaking facilities in Mexico, having an electric arc furnace as controllable load in both cases. This novel demand control is adequate for industrial plants with electrical loads that can be disconnected without affecting the quality of the product and with minor impact on productivity.

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Section: Demand Measurement and Controlmentioning

confidence: 99%

Section: Demand Measurement and Controlmentioning

confidence: 99%

Section: Demand Measurement and Controlmentioning

confidence: 99%

See 1 more Smart Citation

Power demand control algorithm for single controllable load with parametric and variable load factors

Martell

Sánchez‐Chávez

Peña‐Cruz

et al. 2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…Meeting consumer demand for electric power is one of the major glitches faced by Power utilities [16]. Due to prohibitive costs in the addition of new generation capacity, Power utilities have designed programs and techniques in order to balance demand and supply within their generating capacity [17]; hence load management has come in as an important approach in providing electric power proportional in times of peak demands.…”

Section: Load Management Techniques In Power Gridmentioning

confidence: 99%

An Algorithm for using Internet of Things (IoTs) to Improve Load Management in Electric Power Grid

Mahlangu¹,

Musungwini²,

Nleya³

2018

IJCA

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Several new technologies, for example, the Internet of Things (IoTs) continue to surface in the frontage of ubiquitous and pervasive computing. Internet of things is slowly being embraced in different domains to support control and monitoring systems. The advent of microprocessors embedded with communication facilities has enabled the possibility of integrating ICTs within people and their environments. With the power utilities industry grappling with serious issues like load management which has a potential of damaging their equipment, first movers are turning to advanced technologies such as the IoTs to achieve demandside management. The purpose of this study was to conduct a theoretical and empirical review on the approaches used by Power utilities to manage load in order to determine how IoTs can be used particularly by Zimbabwe's Power utility to solve the supply-demand problem. Currently, the load management approaches used by the Power utility in Zimbabwe are load shifting and load shedding. A conceptual model was developed using C++ guided by the algorithm for load management. The model development was motivated by the research gap establish from the literature review and the problem faced by the Power utility in Zimbabwe in balancing demand and supply during peak periods. The idea is modelled around continuous monitoring of the feeder or substation, activating the automatic control and carrying out load allocation procedure based on priority settings, connection, and re-connection timings. The proposed model is also based on the dependence of demand and consumer priority perception. The model will ensure that electricity is available for basic and essential use in times of increased demand. It requires that load demand is constantly monitored to trigger automatic control and appliances should connect to the electric power grid using smart plugs.

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“…Flexible demand acts as distributed storage and is fundamental and increasingly important in accommodating variability in RES supply while transitioning to low or zero-carbon electric power. Fortunately, the roles of flexible commercial and industrial processes in modulating demand on the grid are expanding (Eissa, Wasfy, and Sallam 2012;Ma et al 2017). Unfortunately, though forecast with increasing accuracy (Zhang et al 2015;Shaker, Manfre, and Zareipour 2020), residential electric loads are inflexible, operated autonomously as requested with neither regard for geographic transmission and distribution constraints nor the time-varying costs and CO 2 emissions of generating electricity.…”

Section: Introductionmentioning

confidence: 99%

Estimating the value of jointly optimized electric power generation and end use: a study of ISO-scale load shaping applied to the residential building stock

Cruickshank¹,

Henze

Florita

et al. 2021

Journal of Building Performance Simulation

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A generation-to-load simulation estimated the impact, in terms of production costs and CO2 emissions, attributable to the joint optimization of electric power generation and flexible end uses to support increasing penetrations of renewable energy. Newly conceived, evaluated, and foundational in developing a U.S. National Standard was a transaction-less yet continuous demand response system based on a day-ahead optimum load shape (OLS) designed to encourage Internet-connected devices to autonomously and voluntarily explore options to favour lowest cost generators -without requiring two-way communications, personally identifiable information, or customer opt-in. Boundary conditions used for model calibration included historical weather, residential building stock construction attributes, home appliance and device empirical operating schedules, prototypical power distribution feeder models, thermal generator heat rates, startup and ramping constraints, and fuel costs. Results of an hourly-based annual case study of Texas indicate a 1/3 reduction in production costs and a 1/5 reduction in CO2 emissions are possible.

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Load Management System Using Intelligent Monitoring and Control System for Commercial and Industrial Sectors

Cited by 6 publications

References 9 publications

Power demand control algorithm for single controllable load with parametric and variable load factors

Power demand control algorithm for single controllable load with parametric and variable load factors

An Algorithm for using Internet of Things (IoTs) to Improve Load Management in Electric Power Grid

Estimating the value of jointly optimized electric power generation and end use: a study of ISO-scale load shaping applied to the residential building stock

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