Smart meters as enablers for feedback information induced energy efficiency and demand response: Case analysis in Latvia

2015 ◽  
Author(s):  
Uldis Bariss ◽  
Aris Dandens ◽  
Dagnija Blumberga
Keyword(s):  
Energy Efficiency ◽  
Demand Response ◽  
Case Analysis ◽  
Smart Meters ◽  
Feedback Information

scholarly journals Online Learning Algorithms for the Real-Time Set-Point Tracking Problem

2021 ◽  
Vol 11 (14) ◽  
pp. 6620
Author(s):  
Arman Alahyari ◽  
David Pozo ◽  
Meisam Farrokhifar
Keyword(s):  
Decision Making ◽  
Power Systems ◽  
Real Time ◽  
Demand Response ◽  
Tracking Problem ◽  
Smart Meters ◽  
Set Point ◽  
Point Tracking ◽  
Power Set ◽  
Decision Making Framework

With the recent advent of technology within the smart grid, many conventional concepts of power systems have undergone drastic changes. Owing to technological developments, even small customers can monitor their energy consumption and schedule household applications with the utilization of smart meters and mobile devices. In this paper, we address the power set-point tracking problem for an aggregator that participates in a real-time ancillary program. Fast communication of data and control signal is possible, and the end-user side can exploit the provided signals through demand response programs benefiting both customers and the power grid. However, the existing optimization approaches rely on heavy computation and future parameter predictions, making them ineffective regarding real-time decision-making. As an alternative to the fixed control rules and offline optimization models, we propose the use of an online optimization decision-making framework for the power set-point tracking problem. For the introduced decision-making framework, two types of online algorithms are investigated with and without projections. The former is based on the standard online gradient descent (OGD) algorithm, while the latter is based on the Online Frank–Wolfe (OFW) algorithm. The results demonstrated that both algorithms could achieve sub-linear regret where the OGD approach reached approximately 2.4-times lower average losses. However, the OFW-based demand response algorithm performed up to twenty-nine percent faster when the number of loads increased for each round of optimization.

Improving energy efficiency in colocation data centers for demand response

2021 ◽  
Vol 29 ◽  
pp. 100476
Author(s):  
Ce Chi ◽  
Fa Zhang ◽  
Kaixuan Ji ◽  
Avinab Marahatta ◽  
Zhiyong Liu
Keyword(s):  
Energy Efficiency ◽  
Demand Response ◽  
Data Centers

Joint Production and Energy Modeling of Sustainable Manufacturing Systems: Challenges and Methods

2014 ◽  
Author(s):  
Yong Wang ◽  
Lin Li
Keyword(s):  
Decision Making ◽  
Energy Efficiency ◽  
Demand Response ◽  
Manufacturing Systems ◽  
Energy Use ◽  
System Modeling ◽  
Sustainable Manufacturing ◽  
Energy Modeling ◽  
Joint Production ◽  
Solution Technique

This paper proposes a framework for addressing challenges of joint production and energy modeling of sustainable manufacturing systems. The knowledge generated is used to improve the technological readiness of manufacturing enterprises for the transition towards sustainable manufacturing. Detailed research tasks of the framework are on the modeling of production, energy efficiency, electricity demand, cost, and demand response decision making. Specifically, the dynamics and performance measures of general manufacturing systems with multiple machines and buffers are modeled to integrate energy use into system modeling. The expressions of electrical energy efficiency and cost are then established based on the electricity pricing profile. Finally, joint production and energy scheduling problem formulations and the solution technique are discussed. New insights are acquired based on the applications of the established model in system parameter selection, rate plan switching decision making, and demand response scheduling. Appropriate implementation of this research outcome may lead to energy-efficient, demand-responsive, and cost-effective operations and thus improve the sustainability of modern manufacturing systems.

scholarly journals How Much Energy Efficient are Renewable Energy Sources Cooperatives’ Initiatives?

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1136 ◽  
Author(s):  
Nikolaos Sifakis ◽  
Tryfon Daras ◽  
Theocharis Tsoutsos
Keyword(s):  
Energy Efficiency ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Smart Meters ◽  
Green Consumption ◽  
Consumption Behavior ◽  
The Difference ◽  
Actual Energy Consumption

In this paper is provided a systematic, in-depth, behavioral analysis of renewable energy sources cooperatives’ members. The analysis proved that in, on hand, there was a noticeable difference in the portion of affection of each proposed intervention on the actual energy consumption, which may be to even ten times more in some cases, and on the other hand, the difference in energy consumption between the analyzed groups was noticeable as well. So, implementing energy efficiency interventions of various types, such as technical support, special tariffs, energy generation schemes, and smart meters, seems to lead to substantial energy reductions to even more than 10%, cumulatively, and reduces the environmental footprint. Additionally, the majority of energy efficiency interventions applied by the renewable energy sources cooperatives are proved to be effective in achieving their primary goal, sensitizing members, and leading them to a more efficient energy consumption behavior (“greener”). The results of the analysis showed that each proposed intervention had played a different but nonetheless significant role in the diminishing of the energy consumption of the members and that there was a noticeable difference in energy consumption between the analyzed groups. The results of the analysis demonstrated more than 22 GWh totally in green consumption, and almost 4500 tons of CO2 saved.

scholarly journals Demand Response Model Development for Smart Households Using Time of Use Tariffs and Optimal Control—The Isle of Wight Energy Autonomous Community Case Study

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 541 ◽  
Author(s):  
Sourav Khanna ◽  
Victor Becerra ◽  
Adib Allahham ◽  
Damian Giaouris ◽  
Jamie M. Foster ◽  
...  
Keyword(s):  
Demand Response ◽  
Large Scale ◽  
Energy Transport ◽  
Model Development ◽  
Software Tool ◽  
Load Flow ◽  
Smart Devices ◽  
Smart Meters ◽  
Isle Of Wight

Residential variable energy price schemes can be made more effective with the use of a demand response (DR) strategy along with smart appliances. Using DR, the electricity bill of participating customers/households can be minimised, while pursuing other aims such as demand-shifting and maximising consumption of locally generated renewable-electricity. In this article, a two-stage optimization method is used to implement a price-based implicit DR scheme. The model considers a range of novel smart devices/technologies/schemes, connected to smart-meters and a local DR-Controller. A case study with various decarbonisation scenarios is used to analyse the effects of deploying the proposed DR-scheme in households located in the west area of the Isle of Wight (Southern United Kingdom). There are approximately 15,000 households, of which 3000 are not connected to the gas-network. Using a distribution network model along with a load flow software-tool, the secondary voltages and apparent-power through transformers at the relevant substations are computed. The results show that in summer, participating households could export up to 6.4 MW of power, which is 10% of installed large-scale photovoltaics (PV) capacity on the island. Average carbon dioxide equivalent (CO2e) reductions of 7.1 ktons/annum and a reduction in combined energy/transport fuel-bills of 60%/annum could be achieved by participating households.

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