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22 pages, 1788 KiB

Open AccessArticle

Flexibility-Based Energy and Demand Management in Data Centers: A Case Study for Cloud Computing

by Robert Basmadjian

Energies 2019, 12(17), 3301; https://doi.org/10.3390/en12173301 - 27 Aug 2019

Cited by 29 | Viewed by 4136

The power demand (kW) and energy consumption (kWh) of data centers were augmented drastically due to the increased communication and computation needs of IT services. Leveraging demand and energy management within data centers is a necessity. Thanks to the automated ICT infrastructure empowered [...] Read more.

The power demand (kW) and energy consumption (kWh) of data centers were augmented drastically due to the increased communication and computation needs of IT services. Leveraging demand and energy management within data centers is a necessity. Thanks to the automated ICT infrastructure empowered by the IoT technology, such types of management are becoming more feasible than ever. In this paper, we look at management from two different perspectives: (1) minimization of the overall energy consumption and (2) reduction of peak power demand during demand-response periods. Both perspectives have a positive impact on total cost of ownership for data centers. We exhaustively reviewed the potential mechanisms in data centers that provided flexibilities together with flexible contracts such as green service level and supply-demand agreements. We extended state-of-the-art by introducing the methodological building blocks and foundations of management systems for the above mentioned two perspectives. We validated our results by conducting experiments on a lab-grade scale cloud computing data center at the premises of HPE in Milano. The obtained results support the theoretical model, by highlighting the excellent potential of flexible service level agreements in Green IT: 33% of overall energy savings and 50% of power demand reduction during demand-response periods in the case of data center federation. Full article

(This article belongs to the Special Issue Electricity Demand Side Management)

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13 pages, 3701 KiB

Open AccessArticle

Seasonal COP of an Air-to-Water Heat Pump when Using Predictive Control Preferring Power Production from Renewable Sources in the Czech Republic

by Jiří Pospíšil, Michal Špiláček and Pavel Charvát

Energies 2019, 12(17), 3236; https://doi.org/10.3390/en12173236 - 22 Aug 2019

Cited by 6 | Viewed by 3235

Abstract

The paper presents a parametric study evaluating the effects of various predictive controls on the operating parameters of heat pumps. The heat pump represents a significant power appliance in the residential sector. Its connection to the heat accumulator creates a system with considerable [...] Read more.

The paper presents a parametric study evaluating the effects of various predictive controls on the operating parameters of heat pumps. The heat pump represents a significant power appliance in the residential sector. Its connection to the heat accumulator creates a system with considerable potential to control electricity consumption according to the needs of the electricity grid. The air-water heat pump is considered in this study. A predictive control is used for priority operation of the heat pump at periods of peak power production from renewable sources. The following were tested as the parameters of predictive control: outdoor air temperature, photovoltaic power production and wind power production. The combination of photovoltaic and wind power production was also tested. A parametric analysis considering different sizes for the thermal accumulator and the heating capacity of the heat pump were proposed. The benefits of predictive control are evaluated based on historical records of meteorological data from 2015 to 2018 in the city of Brno, Czech Republic. The data on the historical development of the real electrical energy production from renewable sources in the Czech Republic are used for regulation control in a monitored period. The main comparison parameter is the heat pump seasonal coefficient of performance (SCOP). From the carried out study results, an increase in SCOP by 14% was identified for priority operation of heat pump (HP) at periods with highest outdoor air temperature. Priority operation of HP at periods with peak photovoltaic (PV) production increased SCOP by 10.25%. A decrease in SCOP only occurred in case with priority operation of HP at peak production of wind power plants. Increasing the size of the accumulator contributes to an increase in SCOP in all assessed modifications of predictive control. Full article

(This article belongs to the Special Issue Electricity Demand Side Management)

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19 pages, 3447 KiB

Open AccessArticle

Quantifying the Opportunity Limits of Automatic Residential Electric Load Shaping

by Robert Cruickshank, Gregor Henze, Rajagopalan Balaji, Bri-Mathias Hodge and Anthony Florita

Energies 2019, 12(17), 3204; https://doi.org/10.3390/en12173204 - 21 Aug 2019

Cited by 1 | Viewed by 2821

Abstract

Electric utility residential demand response programs typically reduce load a few times a year during periods of peak energy use. In the future, utilities and consumers may monetarily and environmentally benefit from continuously shaping load by alternatively encouraging or discouraging the use of [...] Read more.

Electric utility residential demand response programs typically reduce load a few times a year during periods of peak energy use. In the future, utilities and consumers may monetarily and environmentally benefit from continuously shaping load by alternatively encouraging or discouraging the use of electricity. One way to shape load and introduce elasticity is to broadcast forecasts of dynamic electricity prices that orchestrate electricity supply and demand in order to maximize the efficiency of conventional generation and the use of renewable resources including wind and solar energy. A binary control algorithm that influences the on and off states of end uses was developed and applied to empirical time series data to estimate price-based instantaneous opportunities for shedding and adding electric load. To overcome the limitations of traditional stochastic methods in quantifying diverse, non-Gaussian, non-stationary distributions of observed appliance behaviour, recent developments in wavelet-based analysis were applied to capture and simulate time-frequency domain behaviour. The performance of autoregressive and spectral reconstruction methods was compared, with phase reconstruction providing the best simulation ensembles. Results show spatiotemporal differences in the amount of load that can be shed and added, which suggest further investigation is warranted in estimating the benefits anticipated from the wide-scale deployment of continuous automatic residential load shaping. Empirical data and documented software code are included to assist in reproducing and extending this work. Full article

(This article belongs to the Special Issue Electricity Demand Side Management)

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19 pages, 1236 KiB

Open AccessArticle

The Multiple Benefits of the 2030 EU Energy Efficiency Potential

by Johannes Thema, Felix Suerkemper, Johan Couder, Nora Mzavanadze, Souran Chatterjee, Jens Teubler, Stefan Thomas, Diana Ürge-Vorsatz, Martin Bo Hansen, Stefan Bouzarovski, Jana Rasch and Sabine Wilke

Energies 2019, 12(14), 2798; https://doi.org/10.3390/en12142798 - 20 Jul 2019

Cited by 30 | Viewed by 4646

Abstract

The implementation of energy efficiency improvement actions not only yields energy and greenhouse gas emission savings, but also leads to other multiple impacts such as air pollution reductions and subsequent health and eco-system effects, resource impacts, economic effects on labour markets, aggregate demand [...] Read more.

The implementation of energy efficiency improvement actions not only yields energy and greenhouse gas emission savings, but also leads to other multiple impacts such as air pollution reductions and subsequent health and eco-system effects, resource impacts, economic effects on labour markets, aggregate demand and energy prices or on energy security. While many of these impacts have been studied in previous research, this work quantifies them in one consistent framework based on a common underlying bottom-up funded energy efficiency scenario across the EU. These scenario data are used to quantify multiple impacts by energy efficiency improvement action and for all EU28 member states using existing approaches and partially further developing methodologies. Where possible, impacts are integrated into cost-benefit analyses. We find that with a conservative estimate, multiple impacts sum up to a size of at least 50% of energy cost savings, with substantial impacts coming from e.g., air pollution, energy poverty reduction and economic impacts. Full article

(This article belongs to the Special Issue Electricity Demand Side Management)

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21 pages, 3032 KiB

Open AccessArticle

A Multi-Objective Optimization Model for a Non-Traditional Energy System in Beijing under Climate Change Conditions

by Xiaowen Ding, Lin Liu, Guohe Huang, Ye Xu and Junhong Guo

Energies 2019, 12(9), 1692; https://doi.org/10.3390/en12091692 - 05 May 2019

Cited by 6 | Viewed by 2628

Abstract

In recent years, with the increase of annual average temperature and the decrease of annual precipitation in Beijing, the fragility of Beijing’s energy system has become more and more prominent, especially the balance of electricity supply and demand in extreme weather. In the [...] Read more.

In recent years, with the increase of annual average temperature and the decrease of annual precipitation in Beijing, the fragility of Beijing’s energy system has become more and more prominent, especially the balance of electricity supply and demand in extreme weather. In the context of unstable supply of new and renewable energies, it is imperative to strengthen the ability of the energy system to adapt to climate change. This study first simulated climate change in Beijing based on regional climate data. At the same time, the Statistical Program for Social Sciences was used to perform multiple linear regression analysis on Beijing’s future power demand and to analyze the impact of climate change on electricity supply in both the RCP4.5 and RCP8.5 (representative concentration pathway 4.5 and 8.5) scenarios. Based on the analysis of the impact of climate change on energy supply, a multi-objective optimization model for new and renewable energy structure adjustment combined with climate change was proposed. The model was then used to predict the optimal power generation of the five energy types under different conditions in 2020. Through comparison of the results, it was found that the development amount and development ratio of various energy forms underwent certain changes. In the case of climate change, the priority development order of new and renewable energies in Beijing was: external electricity > other renewable energy > solar energy > wind energy > biomass energy. The energy structure adjustment program in the context of climate change will contribute to accelerating the development and utilization of new and renewable energies, alleviating the imbalance between power supply and demand and improving energy security. Full article

(This article belongs to the Special Issue Electricity Demand Side Management)

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16 pages, 7416 KiB

Open AccessArticle

Optimal Coordination of Aggregated Hydro-Storage with Residential Demand Response in Highly Renewable Generation Power System: The Case Study of Finland

by Arslan Ahmad Bashir and Matti Lehtonen

Energies 2019, 12(6), 1037; https://doi.org/10.3390/en12061037 - 18 Mar 2019

Cited by 8 | Viewed by 2446

Abstract

Current energy policy-driven targets have led to increasing deployment of renewable energy sources in electrical grids. However, due to the limited flexibility of current power systems, the rapidly growing number of installations of renewable energy systems has resulted in rising levels of generation [...] Read more.

Current energy policy-driven targets have led to increasing deployment of renewable energy sources in electrical grids. However, due to the limited flexibility of current power systems, the rapidly growing number of installations of renewable energy systems has resulted in rising levels of generation curtailments. This paper probes the benefits of simultaneously coordinating aggregated hydro-reservoir storage with residential demand response (DR) for mitigating both load and generation curtailments in highly renewable generation power systems. DR services are provided by electric water heaters, thermal storages, electric vehicles, and heating, ventilation and air-conditioning (HVAC) loads. Accordingly, an optimization model is presented to minimize the mismatch between demand and supply in the Finnish power system. The model considers proportions of base-load generation comprising nuclear, and combined heat and power (CHP) plants (both CHP-city and CHP-industry), as well as future penetration scenarios of solar and wind power that are constructed, reflecting the present generation structure in Finland. The findings show that DR coordinated with hydropower is an efficient curtailment mitigation tool given the uncertainty in renewable generation. A comprehensive sensitivity analysis is also carried out to depict how higher penetration can reduce carbon emissions from electricity co-generation in the near future. Full article

(This article belongs to the Special Issue Electricity Demand Side Management)

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22 pages, 5321 KiB

Open AccessArticle

Impact Analysis of Survivability-Oriented Demand Response on Islanded Operation of Networked Microgrids with High Penetration of Renewables

by Sung-Ho Park, Akhtar Hussain and Hak-Man Kim

Energies 2019, 12(3), 452; https://doi.org/10.3390/en12030452 - 31 Jan 2019

Cited by 20 | Viewed by 2642

Abstract

Microgrids have the potential to withstand the power outages due to their ability of islanding and potential to sustain the penetration of renewables. Increased penetration of renewables can be beneficial but it may result in curtailment of renewables during peak generation intervals due [...] Read more.

Microgrids have the potential to withstand the power outages due to their ability of islanding and potential to sustain the penetration of renewables. Increased penetration of renewables can be beneficial but it may result in curtailment of renewables during peak generation intervals due to the limited availability of storage capacity while shedding loads during peak load intervals. This problem can be solved by adjusting the load profiles, i.e., demand response (DR) programs. In contrast to the existing studies, where DR is triggered by market price signals, a local resource-triggered survivability-oriented demand response program is proposed in this paper. The proposed DR program is triggered by renewable and load level of the microgrid with an objective to minimize the load shedding and curtailment of renewables. The uncertainties in load and renewables are realized via a robust optimization method and the worst-case scenario is considered. The performance of the proposed method is compared with two conventional operation cases, i.e., independent operation case and interconnected operation case without DR. In addition, the impact of renewable penetration level, amount of shiftable load, and load absorption capacity on the performance of the proposed method are also analyzed. Simulation results have proved the proposed method is capable of reducing load shedding, renewable curtailment, and operation cost of the network during emergencies. Full article

(This article belongs to the Special Issue Electricity Demand Side Management)

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Review

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18 pages, 3459 KiB

Open AccessReview

Energy Savings from Feedback Systems: A Meta-Studies’ Review

by Paolo Zangheri, Tiago Serrenho and Paolo Bertoldi

Energies 2019, 12(19), 3788; https://doi.org/10.3390/en12193788 - 06 Oct 2019

Cited by 37 | Viewed by 5575

Abstract

In order to achieve the goal of the Paris Agreement and reduce energy consumption there is the need for a behavior change in energy end-users. Many studies have demonstrated that by delivering to energy users customized feedback on their energy consumption it can [...] Read more.

In order to achieve the goal of the Paris Agreement and reduce energy consumption there is the need for a behavior change in energy end-users. Many studies have demonstrated that by delivering to energy users customized feedback on their energy consumption it can encourage a change in their behavior and support investments in energy efficiency and sustainable energy use. However, the resulting impact on energy consumption can vary largely depending on how, when, and to whom the feedback is delivered. This paper aims to provide an updated overview of the energy savings for the main energy consumptions in residential buildings associated with different types of feedback and against some key determinants, i.e., geographical area, time period, type of medium. This analysis is based on a comprehensive literature review of over 70 studies. Based on the review the paper draws conclusions relevant for policymakers and stakeholders interested in developing feedback strategies and tools for their wide applications. The paper focuses also on the ongoing process implementing the EU Energy Efficiency Directive articles related to billing and metering, which will enable more proactive consumer feedback. Full article

(This article belongs to the Special Issue Electricity Demand Side Management)

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