Demand-Side Management: Optimising Through Differential Evolution Plug-in Electric Vehicles to Partially Fulfil Load Demand

2016 ◽  
pp. 155-174 ◽  
Author(s):  
Edgar Galván-López ◽  
Marc Schoenauer ◽  
Constantinos Patsakis ◽  
Leonardo Trujillo
Keyword(s):  
Differential Evolution ◽  
Electric Vehicles ◽  
Demand Side Management ◽  
Demand Side ◽  
Load Demand

Social License to Automate: Emerging Approaches to Demand Side Management - Executive Summary

2021 ◽  
Author(s):  
Sophie Adams ◽  
Lisa Diamond ◽  
Tara Esterl ◽  
Peter Fröhlich ◽  
Rishabh Ghotge ◽  
...  
Keyword(s):  
Case Studies ◽  
Electric Vehicles ◽  
Demand Side Management ◽  
Heat Pumps ◽  
Final Report ◽  
Demand Side ◽  
Executive Summary ◽  
Air Conditioners ◽  
Social License

Executive Summary of the final report of the Users TCP Social License to Automate Task findings from a 2 year project with 16 researchers in 6 countries, 26 Case studies spanning electric vehicles, home and precinct batteries, air conditioners and other heat pumps.

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.

scholarly journals Demand-Side Management Optimization in Electric Vehicles Battery Swapping Service

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 95224-95232 ◽  
Author(s):  
Liang Zhang ◽  
Sihang Zhou ◽  
Jing An ◽  
Qi Kang
Keyword(s):  
Electric Vehicles ◽  
Demand Side Management ◽  
Demand Side ◽  
Management Optimization

Battery Management Based on Predictive Control and Demand-Side Management

2016 ◽  
pp. 149-180
Author(s):  
Deepranjan Dongol ◽  
Elmar Bollin ◽  
Thomas Feldmann
Keyword(s):  
Energy Management ◽  
Predictive Control ◽  
Management Strategy ◽  
Demand Side Management ◽  
Battery Management ◽  
Demand Side ◽  
Energy Management Strategy ◽  
Battery System ◽  
Surplus Energy ◽  
Load Demand

The chapter is intended to introduce the predictive control based energy management strategy for the grid connected renewable systems in order to achieve an effective demand side management strategy. Grid connected Photovoltaic battery system as being popular and extensively used has been discussed in this chapter .Conventionally, battery storage has been used to store surplus energy produced and meet the load demand with this stored energy. However, such systems do not respond to the grid conditions and violate grid constraints of permissible grid voltage and frequency limits. The operation of the battery depends on the forecast of photovoltaic output and the load demand and as such a predictive control based energy management strategy is needed. A simple optimization problem for such scenarios has also been formulated in great detail to provide readers with an idea for solving such problems. The results of simulations are also discussed.

Demand-Side Management Using Deep Learning for Smart Charging of Electric Vehicles

2019 ◽  
Vol 10 (3) ◽  
pp. 2683-2691 ◽  
Author(s):  
Karol Lina Lopez ◽  
Christian Gagne ◽  
Marc-Andre Gardner
Keyword(s):  
Deep Learning ◽  
Electric Vehicles ◽  
Demand Side Management ◽  
Demand Side ◽  
Smart Charging

scholarly journals Composite Reliability Evaluation of Load Demand Side Management and Dynamic Thermal Rating Systems

Energies ◽  
2018 ◽  
Vol 11 (2) ◽  
pp. 466 ◽  
Author(s):  
Jiashen Teh ◽  
Chia Ooi ◽  
Yu-Huei Cheng ◽  
Muhammad Atiqi Mohd Zainuri ◽  
Ching-Ming Lai
Keyword(s):  
Demand Side Management ◽  
Reliability Evaluation ◽  
Demand Side ◽  
Rating Systems ◽  
Load Demand ◽  
Composite Reliability
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