ABSTRACT
This paper describes the implementation of a hybrid platform for experimental activities in engineering courses. The proposed platform can be used as a remote or face-to-face laboratory;it may also be ideal for the new normal after the Covid 19 pandemic. The proposal has the purpose to help engineering teachers to build this hybrid laboratory without specialized knowledge, requiring little time for its implementation and practically no economic investment. To validate the proposal, the process to build the course of a hybrid laboratory for Control System course is described in this paper, which is expected to have experimental activities within the university and from home. After the implementation, the full functionality of the laboratory will be carried out both in its remote and face-to-face format. © 2023 IEEE.
ABSTRACT
Indian power system witnessed its largest very short-time demand ramping during light off event conducted to express solidarity with COVID-19 volunteers. 32 GW demand ramping was observed within 25 minutes and recorded as the highest ramping event across the globe. System operator has taken precautions and successfully handled the event with the help of hydro generation. However, system experienced severe frequency and voltage deviations due to unexpected consumer behaviour. A systematic study and an in-depth analysis of such a severe event would help system operators and planners to prepare for similar events. This paper presents a critical analysis of the activity and conducted a survey to understand consumer response during that event. It also proposes a modified Bottom-Up Approach to estimate Expected Demand Reduction (EDR) for such critical events. Proposed model is validated using data collected from the conducted survey. Proposed EDR estimation model offers better results than the Top Down and Bottom-up approach models used by system operator. © 2022 IEEE.
ABSTRACT
In load frequency control (LFC) study of a large power system, the key concept is control area, which is the segment of the system consisting of strongly interconnected buses, generator buses thereof working in unison. For accurate linearization of load frequency control problem, proper determination of control area is important. In the present work, a novel deterministic method is proposed and formulated to calculate the sharing of load changes by the generators to determine the control areas for LFC study of multimachine systems. This method is applied on a weakly interconnected two-area system and then on the 10-Machine New England Test System for area segmentation of each of the two systems. Furthermore, LFC studies are carried out with proposed Fuzzy Rule-tuned PID controllers (FRT-PID Controllers) for both the systems incorporated with Dish-Stirling Solar thermal system (DSTS) in each area. The scaling factors and the controller gains are optimized using Coronavirus Herd Immunity Optimizer Algorithm (CHIOA). Performance of the proposed FRT-PID controllers is compared with that of the Conventional PID controllers for the LFC studies of the systems. To test effectiveness of the FRT-PID controllers, effect of random step load perturbation (SLP) in load buses located in different areas are considered. © 2023 Elsevier B.V.
ABSTRACT
The paper considers a residential consumer living in Ontario, who is a customer of Hydro One, an electricity transmission and distribution service provider. The customer is the owner of a smart home with smart appliances who can participate in any demand response (DR) program by any communication medium. The customer has a solar photovoltaic set up on the roof, a battery energy storage system, and an electric vehicle with some thermostatically and non-thermostatically controlled appliances. The price tariffs of the country are rapidly changing due to the economic attack of Covid-19. These changing tariffs are considered as scenarios, and the effect of the tariffs on the customer’s electricity bill is analyzed. The scenarios are formulated as a simple mixed integer linear programming problem. All the events are optimized by different DR programs using the CPLEX solver of GAMS software for minimization of the cost. This paper also investigates the peak to average ratio of the power demand in each scenario. Different strategies for controlling the power transfer from the grid are employed as DR programs, and the results are analyzed in detail. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
COVID-19 em ergency has ca used major changes in everyday life in the la st m onths, a nd it a lso affected the management of buildings. In particular, indoor a ir quality and ventilation ha ve been considered to play a key role in the spreading of the infection, causing national and interna tional subjects to draw up specific guidelines on ventilation and air recirculation rate in AHUs. The pa per deals with the “Loccioni Leaf Lab”, a n industria l building that hosts offices a nd workers operating on test benches. The building features high performance envelope, solar photovoltaic systems, groundwater heat pumps a nd a high -technology control a nd monitoring system and it is connected to a thermal and electric smart grid. A va lidated m odel of the building, im plem ented with the software DesignBuilder a nd EnergyPlus, wa s used to carry out numerical sim ula tions to optimize the m anagement of the HVAC through the Building Management System. Different working conditions have been sim ulated, a nd the numerical output has been used together with experimental data collected from the Company monitoring system. Ithas been possible to investigate how the extra ventilation required by the new guidelines would affect the tota l energy consumption a nd to compare, in term s of energy efficiency, the different HVAC m a nagement stra tegies tha t could be used to ensure occupants hea lth safety and indoor air qua lity. © 2021 Institute of Physics Publishing. All rights reserved.
ABSTRACT
An epidemic multi-group model formed by interconnected SEIR-like structures is formulated and used for data fitting to gain insight into the COVID-19 dynamics and into the role of non-pharmaceutical control actions implemented to limit the infection spread since its outbreak in Italy. The single submodels provide a rather accurate description of the COVID-19 evolution in each subpopulation by an extended SEIR model including the class of asymptomatic infectives, which is recognized as a determinant for disease diffusion. The multi-group structure is specifically designed to investigate the effects of the inter-regional mobility restored at the end of the first strong lockdown in Italy (June 3, 2020). In its time-invariant version, the model is shown to enjoy some analytical stability properties which provide significant insights on the efficacy of the implemented control measurements. In order to highlight the impact of human mobility on the disease evolution in Italy between the first and second wave onset, the model is applied to fit real epidemiological data of three geographical macro-areas in the period March-October 2020, including the mass departure for summer holidays. The simulation results are in good agreement with the data, so that the model can represent a useful tool for predicting the effects of the combination of containment measures in triggering future pandemic scenarios. Particularly, the simulation shows that, although the unrestricted mobility alone appears to be insufficient to trigger the second wave, the human transfers were crucial to make uniform the spatial distribution of the infection throughout the country and, combined with the restart of the production, trade, and education activities, determined a time advance of the contagion increase since September 2020.