concept

peak load

Also known as: Dpeak, peak load demands, peak load demand, peak load times

Facts (21)

Sources

A comprehensive overview on demand side energy management ... link.springer.com Springer Mar 13, 2023 16 facts

claimDemand response systems can schedule interruptible loads to shift energy usage from peak to off-peak hours based on power costs or financial incentives, thereby reducing peak load demand.

claimZhu et al. (2012) proposed an integer linear programming (LP) system to schedule electrical appliances, power sources, and operating times based on user preferences to decrease peak loads.

claimDemand Side Management (DSM) strategies aim to lessen peak load demands and maintain synchronization between network operators and customers.

claimThe primary goal of Demand Side Management (DSM) methods is to decrease peak load demands and achieve advanced synchronization between network operators and customers through the application of power-saving technologies, financial incentives, energy pricing, and government regulations.

claimRahim et al. (2016) employed ant colony optimization (ACO) based on time-of-use (TOU) and inclining block rates (IBR) to decrease residential energy usage, successfully lowering peak load, peak-to-average ratio (PAR), and energy expenditures without negatively impacting customer satisfaction.

referenceDemand Side Management (DSM) can analyze and reshape load profiles and load market patterns in Smart Grids (SG), which lowers energy prices, carbon emissions, and grid running costs by reducing peak load demands, while increasing system sustainability, security, and stability (Awais et al. 2015).

referenceDemand-side management (DSM) strategies have recommended optimal charging methods for plug-in electric vehicles (PHEV) and battery energy storage systems (BESS) to reduce peak load demand, as noted by Mou et al. (2014).

claimRahim et al. (2016) employed Ant Colony Optimization (ACO) based on Time-of-Use (TOU) and Inclining Block Rates (IBR) to decrease residential energy usage, successfully lowering peak load, peak-to-average ratio (PAR), and energy expenditures without affecting customer satisfaction.

measurementThe Genetic Harmony Search Algorithm (GHSA) reduces peak load to 3.73 kWh, compared to 13.84 kWh achieved by present heuristic methods.

referenceFreeman R (2005) discussed managing energy, specifically reducing peak load and managing risk through demand response and demand-side management strategies.

measurementYang et al. (2015) found that the Improved Particle Swarm Optimization (IPSO) algorithm reduced peak load by approximately 30.26%, while the Genetic Algorithm (GA) reduced it by 25.78%.

measurementPriya Esther et al. (2016) utilized the bacterial foraging optimization (BFO) algorithm to reduce peak load by 7% and energy expenditures by 10% for various consumer loads, outperforming earlier evolutionary algorithms.

claimDemand Side Management (DSM) lowers energy prices, carbon emissions, and grid running costs by reducing customer peak load demands, while increasing system sustainability, security, and stability (Awais et al. 2015).

measurementThe GHSA algorithm reduces peak load to 3.73 kWh compared to 13.84 kWh achieved by present heuristic methods.

referenceDemand-side management (DSM) has recommended optimal charging methods for plug-in electric vehicles (PHEV) and battery energy storage systems (BESS) to reduce peak load demand, as noted by Mou et al. (2014).

referenceFreeman (2005) discussed strategies for managing energy, specifically focusing on reducing peak load and managing risk through demand response and demand side management.

Comprehensive framework for smart residential demand side ... nature.com Nature Mar 22, 2025 3 facts

claimThe residential energy management strategy reduces overall energy costs, enhances grid stability by flattening peak loads, and increases system reliability by integrating renewable energy sources, energy storage devices, and electric vehicles.

claimBy strategically operating appliances during off-peak hours, Residential Energy Management (REM) systems enable users to reduce electricity expenses and alleviate peak load demands on the grid.

procedureIn the REM framework's Case II (Vehicle to Home), electric vehicles act as storage devices, discharging energy to the home during peak load times to reduce grid dependence and lower energy costs.

Demand side management using optimization strategies for efficient ... journals.plos.org PLOS ONE Mar 21, 2024 2 facts

procedureThe Slime Mould Algorithm for Demand Side Management proceeds in the following steps: (1) Initialization: Generate an initial population of slime moulds with random positions within the permissible DSM strategy space. (2) Fitness Evaluation: Evaluate the fitness of each slime mould based on the objective function (Dpeak). (3) Loop Until Convergence: For each iteration, update positions based on fitness, simulate rhythmic contraction and expansion (oscillation phase), reinforce strategies yielding lower peak loads (positive feedback), adjust search strategy based on stochastic oscillation (adaptation), and retain the best-found solutions (selection). (4) Output the Best Solution: Display the best-found solution upon reaching the final iteration.

procedureThe Cuckoo Search algorithm for Demand Side Management (DSM) proceeds in the following steps: (1) Initialization: Generate initial nests, each representing a DSM schedule. (2) Fitness Evaluation: Calculate the fitness of each nest based on the peak load (Dpeak) for its DSM schedule. (3) Loop Until Convergence: For each generation, generate a new solution (Xi) using Lévy flights for a randomly chosen cuckoo, choose a nest randomly and compare its fitness with (Xi), apply a discovery rate (Pa) to determine if eggs are discovered (if discovered, the nest is abandoned and a new one is built), retain the best nests and perform local searches, abandon a fraction (Pa) of worse nests and build new ones via Lévy flights, rank the nests to find the best, and terminate if maximum generations or convergence criteria are met.