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A baseline scheme not implementing energy savings where a UE small cell connection is established every time a UE starts receiving data.
Results are displayed for the baseline scheme not implementing energy savings (ES), as well as for the various energy savings schemes.
However, unlike the state-of-the-art algorithm in which UE throughput is sometimes severely degraded, the heuristic algorithm introduced in this paper yields throughput gains of up to 25%% with respect to a baseline scheme not implementing energy savings.
A total of five schemes are simulated: A baseline scheme not implementing energy savings where a UE small cell connection is established every time a UE starts receiving data.
Figure 14 shows the average UE throughput obtained with the various energy savings schemes using the heuristic algorithm, the baseline scheme not implementing energy savings, and the MM algorithm.
Results are displayed for the baseline scheme not implementing energy savings (ES), for the perfect database-aided scheme, and for a benchmark energy savings scheme where signalling latencies are ignored.
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The applicability of implementing energy-saving measures such as night ventilation, night set-back temperature, day lighting as well as optimal building envelope and optimal HVAC settings are addressed by investigating 24 design variables.
In this paper, we apply the game theory to analyze the optimal strategy between the government and the enterprises in the process of implementing energy-saving and emission-reduction action.
Implementing energy-saving measures cost less than buying and burning fuel or engaging in processes that emit other greenhouse gasses.
The Calculator resulted from an assignment in the Energy and Resource Productivity class taught by Dr. Sangwon Suh at the Bren School that challenged students to understand the return on investment for businesses and consumers to implement energy saving technologies.
Households may imperfectly implement energy saving measures.
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