scholarly journals KPI Evaluation Framework and Tools Performance: A Case Study from the inteGRIDy Project

2021 ◽  
Vol 11 (1) ◽  
pp. 23
Author(s):  
Chris Ogwumike ◽  
Huda Dawood ◽  
Tariq Ahmed ◽  
Bjarnhedinn Gudlaugsson ◽  
Nashwan Dawood

This paper presents an assessment of the impacts of the different tools implemented within the inteGRIDy project through the analysis of key performance indicators (KPIs) that appropriately reflect the technical and economic domains of the inteGRIDy thematic pillars, comprising demand response and battery storage systems. The evaluation is based on improvements brought about by individual components of the inteGRIDy-enabled smart solution across the Isle of Wight (IOW) pilot site. The analyses and the interpretation of findings for the pilot use case evaluation are presented. The results indicate that the smart solution implementation across the IOW pilot site resulted in achieving the inteGRIDy set objectives. Overall, a 93% reduction in energy consumption, equivalent to 643 kWh was achieved, via the M7 energy storage system and heat pumps developed as part of inteGRIDy solution. Additionally, the grid efficiency and demand flexibility contribution to the distribution network operator (DNO)-triggered DR services, based on a 10% increase/decrease in demand, resulted in stabilizing the grid efficiency.

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 883 ◽  
Author(s):  
Jeseok Ryu ◽  
Jinho Kim

This work focuses on the demand response (DR) participation using the energy storage system (ESS). A probabilistic Gaussian mixture model based on market operating results Monte, Carlo Simulation (MCS), is required to respond to an urgent DR signal. However, there is considerable uncertainty in DR forecasting, which occasionally fails to predict DR events. Because this failure is attributable to the intermittency of the DR signals, a non-cooperative game model that is useful for decision-making on DR participation is proposed. The game is conducted with each player holding a surplus of energy but incomplete information. Consequently, each player can share unused electricity during DR events, engaging in indirect energy trading (IET) under a non-cooperative game framework. The results of the game, the Nash equilibrium (N.E.), are verified using a case study with relevant analytical data from the campus of Gwangju Institute of Science and Technology (GIST) in Korea. The results of the case study show that IET is useful in mitigating the uncertainty of the DR program.


2021 ◽  
Vol 13 (8) ◽  
pp. 4549
Author(s):  
Sara Salamone ◽  
Basilio Lenzo ◽  
Giovanni Lutzemberger ◽  
Francesco Bucchi ◽  
Luca Sani

In electric vehicles with multiple motors, the torque at each wheel can be controlled independently, offering significant opportunities for enhancing vehicle dynamics behaviour and system efficiency. This paper investigates energy efficient torque distribution strategies for improving the operational efficiency of electric vehicles with multiple motors. The proposed strategies are based on the minimisation of power losses, considering the powertrain efficiency characteristics, and are easily implementable in real-time. A longitudinal dynamics vehicle model is developed in Simulink/Simscape environment, including energy models for the electrical machines, the converter, and the energy storage system. The energy efficient torque distribution strategies are compared with simple distribution schemes under different standardised driving cycles. The effect of the different strategies on the powertrain elements, such as the electric machine and the energy storage system, are analysed. Simulation results show that the optimal torque distribution strategies provide a reduction in energy consumption of up to 5.5% for the case-study vehicle compared to simple distribution strategies, also benefiting the battery state of charge.


2021 ◽  
Vol 16 (3) ◽  
pp. 1273-1284
Author(s):  
Hye Ji Kim ◽  
Hosung Jung ◽  
Young Jun Ko ◽  
Eun Su Chae ◽  
Hyo Jin Kim ◽  
...  

AbstractThis paper proposes an algorithm for the cooperative operation of air conditioning facilities and the energy storage system (ESS) in railway stations to minimize electricity. Unlike traditional load patterns, load patterns of an urban railway station can peak where energy charge rates are not high. Due to this possibility, if applying the traditional peak-reduction algorithm to railway loads, energy changes can increase, resulting in higher electricity bills. Therefore, it is required to develop a new method for minimizing the sum of capacity charges and energy charges, which is a non-linear problem. To get a feasible solution for this problem, we suggest an algorithm that optimizes the facility operation through two optimizations (primary and secondary). This method is applied to the air-quality change model for operating air conditioning facilities as demand-response (DR) resources in railway stations. This algorithm makes it possible to estimate operable DR capacity every hour, rather than calculating the capacity of DR resources conservatively in advance. Finally, we perform a simulation for the application of the proposed method to the operation of DR resources and ESS together. The simulation shows that electricity bills become lowered, and the number of charging and discharging processes of ESS is also reduced.


Energy ◽  
2021 ◽  
pp. 122156
Author(s):  
Mohammad MansourLakouraj ◽  
Majid Shahabi ◽  
Miadreza Shafie-khah ◽  
João P.S. Catalão

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2649 ◽  
Author(s):  
Jiashen Teh

The demand response and battery energy storage system (BESS) will play a key role in the future of low carbon networks, coupled with new developments of battery technology driven mainly by the integration of renewable energy sources. However, studies that investigate the impacts of BESS and its demand response on the adequacy of a power supply are lacking. Thus, a need exists to address this important gap. Hence, this paper investigates the adequacy of a generating system that is highly integrated with wind power in meeting load demand. In adequacy studies, the impacts of demand response and battery energy storage system are considered. The demand response program is applied using the peak clipping and valley filling techniques at various percentages of the peak load. Three practical strategies of the BESS operation model are described in this paper, and all their impacts on the adequacy of the generating system are evaluated. The reliability impacts of various wind penetration levels on the generating system are also explored. Finally, different charging and discharging rates and capacities of the BESS are considered when evaluating their impacts on the adequacy of the generating system.


Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2048 ◽  
Author(s):  
Rodrigo Martins ◽  
Holger Hesse ◽  
Johanna Jungbauer ◽  
Thomas Vorbuchner ◽  
Petr Musilek

Recent attention to industrial peak shaving applications sparked an increased interest in battery energy storage. Batteries provide a fast and high power capability, making them an ideal solution for this task. This work proposes a general framework for sizing of battery energy storage system (BESS) in peak shaving applications. A cost-optimal sizing of the battery and power electronics is derived using linear programming based on local demand and billing scheme. A case study conducted with real-world industrial profiles shows the applicability of the approach as well as the return on investment dependence on the load profile. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, peak-power tariff, and battery aging. This underlines the need for a general mathematical optimization approach to efficiently tackle the challenge of peak shaving using an energy storage system. The case study also compares the applicability of yearly and monthly billing schemes, where the highest load of the year/month is the base for the price per kW. The results demonstrate that batteries in peak shaving applications can shorten the payback period when used for large industrial loads. They also show the impacts of peak shaving variation on the return of investment and battery aging of the system.


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