scholarly journals A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4336
Author(s):  
Andrew J. Satchwell ◽  
Peter A. Cappers ◽  
Jeff Deason ◽  
Sydney P. Forrester ◽  
Natalie Mims Frick ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Demand Response ◽  
Economic Value ◽  
Rapid Change ◽  
Technological Factors ◽  
Utility Systems ◽  
Strategic Approach ◽  
Utility System ◽  
Building Systems ◽  
And Performance

Energy efficiency (EE) and demand response (DR) resources provide important utility systems and ratepayer benefits. At the same time, the rapid change in the amount and type of variable renewable energy, like solar and wind, is reshaping the role and economic value of EE and DR, and will likely affect the time-dependent valuation of EE and DR measures. Utilities are increasingly interested in integrating EE and DR measures as a strategic approach to improve their collective cost-effectiveness and performance. We develop a framework to identify the EE and DR attributes, system conditions, and technological factors that are likely to drive interactions between EE and DR. We apply the framework to example measures with different technology specifics in the context of different utility system conditions. We find that EE and DR interactions are likely driven by changes in discretionary load, the addition of controls or other capabilities to shift loads, and the coincidence of savings with system peak or load building periods. Our analysis suggests increasing complexity in evaluating EE and DR interactions when moving from standalone equipment to integrated systems. The framework can be applied to research on integrated building systems by grouping measures into portfolios with different likely implications for EE and DR interactions.

scholarly journals Power and Performance Evaluation of Memory-Intensive Applications

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4089
Author(s):  
Kaiqiang Zhang ◽  
Dongyang Ou ◽  
Congfeng Jiang ◽  
Yeliang Qiu ◽  
Longchuan Yan
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Consumption ◽  
Job Scheduling ◽  
Memory System ◽  
Processor Core ◽  
Memory Efficiency ◽  
And Performance ◽  
Reasonable Use ◽  
Server System

In terms of power and energy consumption, DRAMs play a key role in a modern server system as well as processors. Although power-aware scheduling is based on the proportion of energy between DRAM and other components, when running memory-intensive applications, the energy consumption of the whole server system will be significantly affected by the non-energy proportion of DRAM. Furthermore, modern servers usually use NUMA architecture to replace the original SMP architecture to increase its memory bandwidth. It is of great significance to study the energy efficiency of these two different memory architectures. Therefore, in order to explore the power consumption characteristics of servers under memory-intensive workload, this paper evaluates the power consumption and performance of memory-intensive applications in different generations of real rack servers. Through analysis, we find that: (1) Workload intensity and concurrent execution threads affects server power consumption, but a fully utilized memory system may not necessarily bring good energy efficiency indicators. (2) Even if the memory system is not fully utilized, the memory capacity of each processor core has a significant impact on application performance and server power consumption. (3) When running memory-intensive applications, memory utilization is not always a good indicator of server power consumption. (4) The reasonable use of the NUMA architecture will improve the memory energy efficiency significantly. The experimental results show that reasonable use of NUMA architecture can improve memory efficiency by 16% compared with SMP architecture, while unreasonable use of NUMA architecture reduces memory efficiency by 13%. The findings we present in this paper provide useful insights and guidance for system designers and data center operators to help them in energy-efficiency-aware job scheduling and energy conservation.

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

scholarly journals Analysis of Cooperation Between Central Power Utility and Dispersed Cogeneration Systems Through Time-of-Use Pricing

1998 ◽  
Author(s):  
Ryohei Yokoyama ◽  
Koichi Ito
Keyword(s):  
Load Factor ◽  
Theory Approach ◽  
Power Utility ◽  
Utility Systems ◽  
Utility System ◽  
Cogeneration System ◽  
Annual Total ◽  
Upper Level ◽  
Time Of Use Pricing ◽  
Cooperative Relationship

Because of an increase in peak electricity demand during summer daytime, a decrease in the annual load factor of power generation facilities has been one of the serious problems for central power utility systems. On the other hand, utility-connected dispersed cogeneration systems have been increasingly installed for energy supply in industrial and commercial sectors. This paper analyzes the cooperative relationship between power utility and cogeneration systems through time-of-use pricing. A game-theory approach in mathematical programming, i.e., bilevel programming, is applied to attain this objective. At the upper level, a power utility system determines the time-of-use rates for demand and energy charges of electricity purchased by a cogeneration system to maximize its load factor, and at the lower level, a cogeneration system determines its design and operation to minimize its annual total cost. Through a basic case study, it has been shown how the time-of-use rates are determined to attain the cooperative relationship between power utility and cogeneration systems.

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.

Sign in / Sign up

Export Citation Format

Share Document