A New Approach to Determine Base, Intermediate and Peak-Demand in an Electric Power System

Salimi-beni, A.; Farrokhzad, D.; Fotuhi-Firuzabad, M.; Alemohammad, Seyed Hamidreza

doi:10.1109/icpst.2006.321928

Cited by 7 publications

(7 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…peak, intermediate, and base. By applying the K-mean clustering technique [30] to the hourly generation data of Thailand, the base, intermediate, and peak ranges are set as 0-35%, 35-80%, and 80-100% of the peak demand, respectively. When renewable generation is integrated, it can be seen from Table 10 that the penetration level of renewable resources is less than 7% in the intermediate-load and base-load groups and less than 4% in the peak-load group.…”

Section: Impact On Load and Plant Groupsmentioning

confidence: 99%

Impact assessment of renewable generation on electricity demand characteristics

Chaiamarit

Nuchprayoon

2014

Renewable and Sustainable Energy Reviews

View full text Add to dashboard Cite

Section: Impact On Load and Plant Groupsmentioning

confidence: 99%

Impact assessment of renewable generation on electricity demand characteristics

Chaiamarit

Nuchprayoon

2014

Renewable and Sustainable Energy Reviews

View full text Add to dashboard Cite

“…The constant power demand turns the system more predictable and easier to manage, and the cost of energy more regular during the day [36]. The proposed methodology tries to minimize the difference between the average and the maximum power demand.…”

Section: Power Demand Curve Optimizationmentioning

confidence: 99%

Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

Morais

Sousa

Vale

et al. 2014

Energy Conversion and Management

124

View full text Add to dashboard Cite

a b s t r a c tSmart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

show abstract

“…These load levels are typically met by three groups of generation units, each with characteristics that align with the behavior of the corresponding load level. For instance, base load units, such as thermal or nuclear power plants [9] usually have the lowest operating cost and need to be operated continuously at or near their rated output [42]. Intermediate load units, like combined cycle power plants, are positioned between peaking units and base load units.…”

Section: B Literature Reviewmentioning

confidence: 99%

Enhancing Generation Expansion Planning With Integration of Variable Renewable Energy and Full-Year Hourly Multiple Load Levels Balance Constraints

Diewvilai,

Audomvongseree

2024

IEEE Access

View full text Add to dashboard Cite

This paper proposes a method for generation expansion planning that incorporates full-year hourly multiple load levels balance constraints, providing sufficient flexibility to address load fluctuations and intermittency associated with variable renewable energy sources. Typically, ensuring that the generation system possesses enough flexibility to manage this intermittency involves considering the operational characteristics of generators within unit commitment constraints. However, to mitigate the substantial computational burden caused by the number and type of variables, various approximation techniques are often employed. Unfortunately, these techniques can introduce unrealistic elements into the problem. Instead of considering the operational characteristics of generators, this approach classifies the system's demand into three levels: base load, intermediate load, and peak load, using the proposed load classification method. The multiple load-level balance constraints are then applied to ensure that the capacity of generation units in each level is sufficient to meet their corresponding demand, with particular emphasis on matching fast-response generation units and their corresponding demand. The resulting generation expansion plan can be obtained with significantly reduced computational effort. The proposed load classification method and generation expansion planning approach have been tested using the latest power development plan of Thailand. Compared to another method that is not taken flexibility into account, 5 Gigawatts of fast-response generation capacity are selected instead of base load generation units. With the improved computational time achieved by the proposed generation expansion planning method, it can account for input data uncertainty by solving multiple generation expansion planning problems with varying input data and distinct individual probabilities. INDEX TERMS power generation planning, power generation reliability, generation expansion planning, renewable energy NOMENCLATURE A. ACRONYMS

show abstract

A New Approach to Determine Base, Intermediate and Peak-Demand in an Electric Power System

Cited by 7 publications

References 7 publications

Impact assessment of renewable generation on electricity demand characteristics

Impact assessment of renewable generation on electricity demand characteristics

Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

Enhancing Generation Expansion Planning With Integration of Variable Renewable Energy and Full-Year Hourly Multiple Load Levels Balance Constraints

Contact Info

Product

Resources

About