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
The COVID-19 pandemic had a tremendous impact on socioeconomics and directly impacted the electrical system. In Malaysia, Grid System Operators (GSOs) were found to lack detailed information to differentiate the total energy demand before and during a pandemic. Working from home during the pandemic has changed the way of life and daily energy management methods for the domestic sector. This paper aims to study the national energy demand during the pandemic and then look into domestic energy management. The study included 3 phases. Phase 1 involved the analysis of data from the GSO to identify differences in energy demand before and during the pandemic. Next, in phase 2, a survey will be conducted on the energy management of the domestic sector. Finally, phase 3 involves household energy-saving proposals through examples of structural improvements. During the 2020 Movement Control Order (MCO) in Malaysia, the average total decrease in energy demand compared to 2019 was 15.82%. This high percentage is due to the closure of several economic sectors, such as trade and industry. From the survey, 88 110 respondents reported that domestic electricity bills increased during the MCO. Statistical analysis using ANOVA indicated no significant link between age range and behavior, knowledge, and total bills paid by respondents. Furthermore, this study also suggested structural upgrades incorporating 5-star air conditioning that can save RM389.47 per year, which will take 4.78 years to repay. This study concluded with suggestions on changes that can be implemented to aid homeowners with energy savings. © 2022 IEEE.
ABSTRACT
The City of Zagreb in Croatia and its surroundings have experienced two strong earthquakes within nine months of 2020. Putting this in the context of the increased workload of healthcare facilities due to Covid-19, the distribution system operator (DSO) is encouraged to look for unconventional solutions such as integrating the battery energy storage system (BESS) to supply healthcare facilities during network fault conditions or other extreme network events. The BESS size and location are determined by optimization model, while the control system of the BESS converter, based on the virtual synchronous machine (VSM) concept, is define to test BESS ability to supply critical consumers in the off-grid mode. The models are tested and verified on several real world situations in Zagreb MV distribution network. Future developments and scenarios are also simulated to verify the robustness of the proposed investment. © 2022 IEEE.
ABSTRACT
With the development of technologies and the decrease of prices, the number of end-users that decide to invest in distributed energy resources (DERs) continuously grows. Despite the improvement of financial and environmental aspects of the power system operation, a growing share of DERs can cause numerous technical challenges for distribution system operators (DSOs). Besides the integration of DERs, the novel COVID-19 disease created additional challenges for DSOs in 2020 and 2021. Due to a large number of single-phase loads and DERs, the increased consumption, the number of nonlinear loads, and power electronic devices in a distribution network, many challenges are related to power quality (PQ). In this paper, realistic case studies that consider anomalies caused by the COVID-19 pandemic and integration of DERs are presented. By using pandapower and its newly developed extension, different PQ indicators are calculated and the values of voltage magnitude, voltage unbalance factor (VUF), and total harmonic distortion (THD) are compared through different scenarios. In addition, the impact of a transformer's vector group on the PQ indicators' propagation through the observed distribution network is analyzed. In a conclusion, the optimal vector group, that successfully mitigates or at least decreases the values of PQ indicators and their propagation is proposed. © 2022 IEEE.
ABSTRACT
This paper presents a proposal methodology to study the temperature dependence of the Italian electricity demand. Indeed, weather temperature has a significant influence on the electricity consumption. From a Transmission System Operator (TSO) perspective, an accurate estimation of this effect is crucial to interpret and predict demand fluctuations. Several dispatching applications consider these phenomena, as for example adequacy analysis, demand forecasting tools, and real-time operational procedures. Based on the geographical features of Italy, it was possible to identify various sensitivity behaviors at regional scale. The purpose of this study is to develop a temperature sensitivity model to be applied on electricity demand profile with different time granularity (e.g., daily, hourly). A clustering analysis on the historical input data is performed. Furthermore, a thorough investigation to identify the optimal best-fitting method for this application is described. In order to test the methodology, some relevant business cases are simulated considering also extreme scenarios. Results on COVID-19 scenario is also described. Finally, an outlook on the planned future developments of the method is provided. © 2021 AEIT.