scholarly journals Controlling capture plants to avoid CO2 emissions penalties during peak load demand

2021 ◽  
Vol 106 ◽  
pp. 103285
Author(s):  
Muhammad Akram ◽  
Kris Milkowski ◽  
Jon Gibbins ◽  
Mohammed Pourkashanian
Keyword(s):  
Co2 Emissions ◽  
Peak Load ◽  
Load Demand

Optimal Planning of Distribution System Considering Distributed Generators

2013 ◽  
Vol 291-294 ◽  
pp. 2022-2027
Author(s):  
Hui Shi Liang ◽  
Hai Tao Liu ◽  
Jian Su
Keyword(s):  
Distribution System ◽  
Peak Load ◽  
Optimal Planning ◽  
System Construction ◽  
Peak Shaving ◽  
Diagram Method ◽  
Distributed Generators ◽  
Load Demand ◽  
Substation Planning ◽  
The Impact

This paper presents a methodology for substation optimal planning considering DG for peak shaving. Utility can take effective demand-side management (DSM) to encourage customer-owned DG to participate in peak load shaving, and it can also construct utility DG to meet the peak load demand. In this paper, the impact of DG on peak load shaving is analyzed, and DG is taken as a complement to T&D system to meet load demand, which is considered in the substation planning. Substations sizing and location and new-built utility DG capacity is optimized using Particle Swarm Optimization (PSO), in which supply area of each substation is obtained by Voronoi diagram method. Case study shows that planning result considering DG for peak shaving can defer T&D system expansion so that considerable investment can be saved. Especially for those areas with high cost of T&D system construction, constructing DG to meet peak load demand would be a more economic way.

Energy Comparison Among Load Following, Hydro Storage and Two-Shift Operation Strategies for Intermediate Fossil Fuel Power Units

1999 ◽  
Author(s):  
M. Bianchi ◽  
E. Gadda ◽  
A. Peretto
Keyword(s):  
Gas Turbines ◽  
Fossil Fuel ◽  
Peak Load ◽  
Heat Rate ◽  
Total Efficiency ◽  
Unit Load ◽  
Load Following ◽  
Load Demand ◽  
Power Generation System ◽  
Hydro Turbines

During the night hours, to match the lowest load demand by a power generation system, many different strategies can be employed: unit load following, unit shutdown and hydro storage. Obviously, the utilized strategy influences the power production (gas turbines, hydro turbines, etc.) during the peak load demand. In this paper, the energy comparison among the above different strategies is carried out as a function of the load demand, the heat rate of the peaking units, the hydro storage total efficiency and the hydro stored energy. In particular, two sets of intermediate load fossil fuel power units (conventional and advanced) are considered. For the sets considered and relatively to the variable costs, the two-shift operation proved to be the most convenient strategy.

scholarly journals Application of Hydrosuction Sediment Removal System (HSRS) on Peaking Ponds

2012 ◽  
Vol 11 ◽  
pp. 43-48
Author(s):  
H. S. Shrestha
Keyword(s):  
Field Test ◽  
Peak Load ◽  
Load Shedding ◽  
Hydropower Plant ◽  
Dry Period ◽  
Small Hydropower ◽  
Settling Basin ◽  
Sediment Removal ◽  
Load Demand ◽  
Removal System

The value of the peaking hour energy is very high in Nepal where people are facing more than 16 hours load shedding in a day during the dry period. Currently, the peak load demand is about 90% higher than the off peak load demand. Therefore, a storage type hydropower project plays a signifi cant role in the Nepalese energy sector and decides the fate of load shedding. However, the Reservoir sedimentation studies in Nepal show that the capacity of the reservoirs has been reduced significantly; hence, preservation of these reservoirs is a vital issue.The hydrosuction sediment removal system (HSRS) is one of the methods to remove sediment from the reservoirs. A modified double layer suction head of HSRS was used in a field test of HSRS at the Settling Basin of Sunkoshi Small Hydropower Plant (SSHP) and Peaking Pond of the Sunkoshi Hydropower Plant (SHP). This paper presents field test results in the settling basin of SSHP and peaking pond of SHP and applicability of HSRS in the Kulekhani Reservoir and other peaking ponds in Nepal.DOI: http://dx.doi.org/10.3126/hn.v11i0.7162 Hydro Nepal Vol.11 2011 pp.43-48

scholarly journals A Conceptual Framework for Minimizing Peak Load Electricity using Internet of Things

2021 ◽  
Vol 10 (8) ◽  
pp. 60-71
Author(s):  
Amira Hassan Abed ◽  
Mona Nasr ◽  
Laila Abd Elhamid
Keyword(s):  
Conceptual Framework ◽  
Peak Load ◽  
Energy System ◽  
Renewable Energy Resources ◽  
Control Center ◽  
Load Demand ◽  
Production And Consumption ◽  
Electricity Load ◽  
The Impact ◽  
Varying Demand

Electricity load demand converts from time to time frequently in a day. Encountering time-varying demand particularly in peak times is considered a big challenge that faces electric utilities. Persistent growth in peak load increases the prospect of power failure and increases the electricity equipping marginal cost. Therefore, balancing production and consumption of electricity or addressing peak load has become a key attention of utilities. Most previous works and researches were focused on applying Shave/Shift peak load to solve energy scarcity. In this study, we introduce four significant technologies and techniques for achieving peak load shaving, namely “Internet of Things (IoT) in Energy System”, “On-site Generation systems (Renewable Energy Resources)”, “Demand Side Management (DSM)” applications of control center and “Energy Storage Systems (ESSs)”. The impact of these four major methods for peak load shaving to the grid has been discussed in detail. Finally, we suggest a conceptual framework as guiding tool for illustrating the presented technologies of Shave/Shift peak load in energy systems.

scholarly journals A Review on Demand Side Management Applications, Techniques, and Potential Energy and Cost saving

2021 ◽  
Vol 20 (1) ◽  
pp. 21-33
Author(s):  
Hossam Eldin Hamed Shalaby
Keyword(s):  
Dynamic Pricing ◽  
Energy Savings ◽  
Peak Load ◽  
Cost Effective ◽  
Demand Side Management ◽  
Special Focus ◽  
Demand Side ◽  
Renewable Energy Resources ◽  
Load Demand ◽  
Battery Energy

Electrical peak load demand all over the world is always anticipated to grow, which is challenging electrical utility to supply such increasing load demand in a cost effective, reliable and sustainable manner. Thus, there is a need to study some of load management (LM) techniques employed to minimize energy consumption, reduce consumers' electricity bills and decrease the greenhouse gas emissions responsible for global warming. This paper presents a review of several recent LM strategies and optimization algorithms in different domains. The review is complemented by tabulating several demand side management (DSM) techniques with a specific view on the used demand response (DR) programs, key finding and benefits gained. A special focus is directed to the communication protocols and wireless technology, incorporation of renewable energy resources (RERs), battery energy storage (BES), home appliances scheduling and power quality applications. The outcome of this review reveals that the real time pricing (RTP) is the most efficient price-based mechanism program (PBP), whilst time of use (TOU) is the basic PBP and easiest to implement. Energy efficiency programs have proved the highest influential impact on the annual energy saving over the other dynamic pricing mechanism programs. Through a forecasted proposal of future study, DSM proved tremendous potential annual energy savings, peak demand savings, and investment cost rates within different consumption sectors progressively up to year 2030.

Electricity Peak Load Demand using De-noising Wavelet Transform integrated with Neural Network Methods

2016 ◽  
Vol 6 (1) ◽  
pp. 12
Author(s):  
Pituk Bunnoon
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Power Systems ◽  
Peak Load ◽  
Electric Power System ◽  
Load Demand ◽  
The Neural Network ◽  
Forecasting Method ◽  
Neural Network Algorithm ◽  
The One

One of most important elements in electric power system planning is load forecasts. So, in this paper proposes the load demand forecasts using de-noising wavelet transform (DNWT) integrated with neural network (NN) methods. This research, the case study uses peak load demand of Thailand (Electricity Generating Authority of Thailand: EGAT). The data of demand will be analyzed with many influencing variables for selecting and classifying factors. In the research, the de-noising wavelet transform uses for decomposing the peak load signal into 2 components these are detail and trend components. The forecasting method using the neural network algorithm is used. The work results are shown a good performance of the model proposed. The result may be taken to the one of decision in the power systems operation.

scholarly journals Study on a New Operational Mode of Economic Operation of Islanded Microgrids Using Electric Springs

2018 ◽  
Vol 160 ◽  
pp. 04004
Author(s):  
Zhiyu Zhao ◽  
Keyou Wang ◽  
Guojie Li ◽  
Xiuchen Jiang ◽  
Yin Zhang
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Peak Load ◽  
Energy Storage System ◽  
Operational Cost ◽  
Operational Mode ◽  
Load Demand ◽  
Economic Operation

With the increasing penetration of intermittent renewable energy sources (RESs) into microgrids, the original operation mode of power generation determined by load demand faces severe challenges due to the uncertainties of the RESs power output. The electric springs(ESs), as an emerging technology has been verified to be effective in enabling load demand to follow power generation and stabilizing fluctuation of RESs output. This paper presents a new mode of economic operation for island microgrids including non-critical loads with embedded electric springs. Its connotation includes that i) the capacity of energy storage can be reduced through the interaction of the energy storage system (ESS) and the electric springs, ii) the electric springs reduce the stress of peak load regulation and operational cost and iii) the demand of microgrids system for ramping ability of generation units is reduced with the buffer of the electric springs. Numerical results show that the coordinated operation between electric springs and energy storage system of microgrids can bring down the investment cost for the ESS and short-term operational cost in the aspect of economic dispatch, reducing requirements for the capacity and ramp ability of the energy storage system in microgrids. Energy buffering can be achieved with lower cost and the load demand can follow power generation in the new operational mode of islanded microgrids using electric springs.

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