scholarly journals Management and Activation of Energy Flexibility at Building and Market Level: A Residential Case Study

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1188 ◽  
Author(s):  
Paolo Taddeo ◽  
Alba Colet ◽  
Rafael E. Carrillo ◽  
Lluc Casals Canals ◽  
Baptiste Schubnel ◽  
...  
Keyword(s):  
Demand Response ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Test Site ◽  
Electricity Sector ◽  
Energy Sources ◽  
Multi Level ◽  
The Difference ◽  
Real Test

The electricity sector foresees a significant change in the way energy is generated and distributed in the coming years. With the increasing penetration of renewable energy sources, smart algorithms can determine the difference about how and when energy is produced or consumed by residential districts. However, managing and implementing energy demand response, in particular energy flexibility activations, in real case studies still presents issues to be solved. This study, within the framework of the European project “SABINA H2020”, addresses the development of a multi-level optimization algorithm that has been tested in a semi-virtual real-time configuration. Results from a two-day test show the potential of building’s flexibility and highlight its complexity. Results show how the first level algorithm goal to reduce the energy injected to the grid is accomplished as well as the energy consumption shift from nighttime to daytime hours. As conclusion, the study demonstrates the feasibility of such kind of configurations and puts the basis for real test site implementation.

scholarly journals Exploring the Potentialities of Deep Reinforcement Learning for Incentive-Based Demand Response in a Cluster of Small Commercial Buildings

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2933
Author(s):  
Davide Deltetto ◽  
Davide Coraci ◽  
Giuseppe Pinto ◽  
Marco Savino Piscitelli ◽  
Alfonso Capozzoli
Keyword(s):  
Reinforcement Learning ◽  
Demand Response ◽  
Control Strategy ◽  
Energy Demand ◽  
Hybrid Control ◽  
Renewable Energy Sources ◽  
Economic Benefits ◽  
Commercial Buildings ◽  
Electricity Sector ◽  
Hybrid Controller

Demand Response (DR) programs represent an effective way to optimally manage building energy demand while increasing Renewable Energy Sources (RES) integration and grid reliability, helping the decarbonization of the electricity sector. To fully exploit such opportunities, buildings are required to become sources of energy flexibility, adapting their energy demand to meet specific grid requirements. However, in most cases, the energy flexibility of a single building is typically too small to be exploited in the flexibility market, highlighting the necessity to perform analysis at a multiple-building scale. This study explores the economic benefits associated with the implementation of a Reinforcement Learning (RL) control strategy for the participation in an incentive-based demand response program of a cluster of commercial buildings. To this purpose, optimized Rule-Based Control (RBC) strategies are compared with a RL controller. Moreover, a hybrid control strategy exploiting both RBC and RL is proposed. Results show that the RL algorithm outperforms the RBC in reducing the total energy cost, but it is less effective in fulfilling DR requirements. The hybrid controller achieves a reduction in energy consumption and energy costs by respectively 7% and 4% compared to a manually optimized RBC, while fulfilling DR constraints during incentive-based events.

scholarly journals Synergies between e-Mobility and Photovoltaic Potentials—A Case Study on an Urban Medium Voltage Grid

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3795 ◽  
Author(s):  
Julia Vopava ◽  
Ulrich Bergmann ◽  
Thomas Kienberger
Keyword(s):  
Renewable Energy ◽  
Performance Indicators ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Key Performance Indicators ◽  
Load Flow ◽  
Energy Sources ◽  
Grid Model ◽  
Synergy Effects

To reduce CO2 emissions, it is necessary to cover the increasing energy demand of e-mobility with renewable energy sources. Therefore, the influence of increasing e-mobility and synergy effects between e-mobility and renewable energy sources need to be investigated. The case study presented here shows results from the analysis of grid-side and energetic synergy effects between e-mobility charged only at work and photovoltaic (PV) potentials. The basis of the grid study is a simplified cell-based grid model. Following the determination of synthetic charging profiles for e-mobility, PV potential profiles, load and production profiles, we perform load flow calculations for different scenarios and a simulation period of one year using the grid model. After the grid study, the energy analyses are carried out using four key performance indicators. The grid study shows that line overloads caused by PV production are only reduced and not avoided by increasing e-mobility and vice versa. The increase in the power peak of e-mobility, by shifting the charging processes into the peak of PV potentials, leads to a reduction of the production surplus in summer, while in winter the line utilisation increases. By modelling PV potentials on real irradiation and temperature data, the investigation of key performance indicators can identify not only seasonal fluctuations but also daily fluctuations.

scholarly journals Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response Programs

2021 ◽  
Vol 13 (14) ◽  
pp. 7756
Author(s):  
Tope Roseline Olorunfemi ◽  
Nnamdi I. Nwulu
Keyword(s):  
Demand Response ◽  
Rural Areas ◽  
Renewable Energy Sources ◽  
Operating Cost ◽  
Optimal Operation ◽  
Response Strategy ◽  
Energy Sources ◽  
Operational Cost ◽  
Multi Agent

Electricity is an indispensable commodity on which both urban and rural regions heavily rely. Rural areas where the main grid cannot reach make use of distributed energy resources (DER), especially renewable energy sources (RES), in an islanded microgrid. Therefore, it is necessary to make sure there is a sufficient power supply to balance the demand and supply curve and meet people’s demands. The work done in this paper aims to minimize the daily operating cost of the hybrid microgrid while incorporating a demand response strategy built on an incentive-based demand response (IBDR) model. Three case studies were constructed and analyzed to derive the best, most reduced daily operational cost. This was achieved using the CPLEX solver embedded in algebraic modeling language in the Advanced Interactive Multidimensional Modeling Systems (AIMMS) software with multi-agent system (MAS); the MAS was used to make sure that the developed intelligent-based agents work independently to achieve an optimal microgrid system. The sensitivity analysis employed established that case study 2 gave the most reduced daily operation cost (USD 119), which represents an 8% reduction in the daily operational cost from case study 1 and a 9% reduction from case study 3. Then, we achieved 17% and 25% reductions, as compared to specific other approaches.

scholarly journals The Concept of Multiple Impacts of Renewable Energy Sources: A Critical Review

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3183
Author(s):  
Michaela Makešová ◽  
Michaela Valentová
Keyword(s):  
Renewable Energy ◽  
Energy Policy ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
The European Union ◽  
Multiple Impacts ◽  
Energy Field ◽  
Full Picture ◽  
The Difference ◽  
Social Environmental

Reaching climate neutrality by 2050 is one of the main long-term objectives of the European Union climate and energy policy, and renewable energy sources (RES) are integral parts of this transition. RES development results in many effects, direct and indirect, linked to each other, societal, local and individual, i.e., “multiple impacts of RES” (MI RES). These effects need to be carefully assessed and evaluated to obtain the full picture of energy field transformation and its context, and enable further development of RES. Nevertheless, the MI RES concept is often presented misleadingly and its scope varies throughout the literature. This paper provides a literature overview of the methodologies of this concept and presents a new concept of MI RES, respecting the difference between effects resulting from the implementation of RES and ultimate multiple impacts. We have summarized the effects into four groups: economic, social, environmental, and technical, which all lead to group of ultimate multiple impacts. Finally, we provide the complex overview of all MI RES and present the framework, which is used to analyze the multiple impacts and effects of RES and to show how the RES development leads and contributes to these impacts and effects. The concept is recommended to be considered in designing a robust energy policy by decision-makers.

scholarly journals Portfolio optimization of power plants by using renewable energy in Iran

2020 ◽  
Author(s):  
Seyedeh Asra Ahmadi ◽  
Seyed Mojtaba Mirlohi ◽  
Mohammad Hossein Ahmadi ◽  
Majid Ameri
Keyword(s):  
Renewable Energy ◽  
Portfolio Optimization ◽  
Energy Supply ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Modern Society ◽  
Sustainable Growth ◽  
Electricity Sector ◽  
Capital Costs

Abstract Lack of investment in the electricity sector has created a huge bottleneck in the continuous flow of energy in the market, and this will create many problems for the sustainable growth and development of modern society. The main reason for this lack of investment is the investment risk in the electricity sector. One way to reduce portfolio risk is to diversify it. This study applies the concept of portfolio optimization to demonstrate the potential for greater use of renewable energy, which reduces the risk of investing in the electricity sector. Besides, it shows that investing in renewable energies can offset the risk associated with the total input costs. These costs stem from the volatility of associated prices, including fossil fuel, capital costs, maintenance, operation and environmental costs. This case study shows that Iran can theoretically supply ~33% of its electricity demand from renewable energy sources compared to its current 15% share. This case study confirms this finding and predicts that Iran, while reducing the risk of investing in electricity supply, can achieve a renewable energy supply of ~9% with an average increase in supply costs. Sensitivity analysis further shows that with a 10% change in input cost factors, the percentage of renewable energy supply is only partially affected, but basket costs change according to the scenario of 5–32%. Finally, suggestions are made that minimize risk rather than cost, which will bring about an increase in renewable energy supply.

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