Comprehensive Indicator Bank for Resilience of Water Supply Systems

Appropriate indicators are required to measure the resilience of water supply systems (WSSs). However, it is challenging to identify appropriate indicators since there is no comprehensive database of indicators to measure its resiliency. This study will establish a comprehensive bank of indicators to assist water corporations and decision-makers in selecting appropriate indicators for their particular system. The suggested indicator bank is comprised of three layers such as dimension, attributes, and the number of indicators resulting from 12 different indicator codes that the study has analysed. In addition, this paper presents instructions on how the indicator bank can be used and integrated with water enterprises, enabling decision-makers to pick the relevant indicators. The proposed indicator bank is an exploratory approach that should be validated in a real work setting since resilience is a challenging concept, and WSSs are complex due to their dependencies to other lifelines such as power networks with too many variables that may affect the actual outcomes.

Development of a Platform for Securing Interoperability between Components in a Carbon-Free Island Microgrid Energy Management System

The rigidity of information technology (IT) has been hindering the development of various businesses regarding energy management systems (EMSs) of power networks, although this area has become more diversified, resulting in changes of elements in the systems due to the introduction of renewable energy (RE) and the new energy industry. In order to effectively accommodate these changes, EMSs should be developed in a structure with a standard-based interface, which can secure interoperability between components in the EMS. In previous studies, the common information model (CIM) proposed by IEC TC57 has been utilized for developing EMSs of power networks, but there are gaps between the existing CIM and an information model for the EMSs of carbon-free island microgrids (MGs), which are a newly introduced form of power network covering multiple islands for reducing carbon emissions. This paper proposes a CIM-based software platform for a carbon-free island MG-EMS to efficiently operate the power network and secure interoperability between components in the MG-EMS. Concerning service restoration of the power network, use cases and business objects representing information exchanged between the components in the EMS are derived, and the existing CIM is extended based on the results of the gap analysis in order to provide necessary information on the MG-EMS. The validity of the proposed platform is verified by exchanging payloads between components in the MG-EMS based on the profile extracted from the extended CIM. Furthermore, the performance of the proposed platform regarding data size and speed of data exchange is presented. Based on the case study results, it is concluded that the proposed platform based on the extended CIM can exchange data between the components in the MG-EMS, achieving reasonable data size and speed of data exchange with the help of the interoperability between components in the carbon-free island MG-EMS.

Co-Optimizing Battery Storage for Energy Arbitrage and Frequency Regulation in Real-Time Markets Using Deep Reinforcement Learning

Battery energy storage systems (BESSs) play a critical role in eliminating uncertainties associated with renewable energy generation, to maintain stability and improve flexibility of power networks. In this paper, a BESS is used to provide energy arbitrage (EA) and frequency regulation (FR) services simultaneously to maximize its total revenue within the physical constraints. The EA and FR actions are taken at different timescales. The multitimescale problem is formulated as two nested Markov decision process (MDP) submodels. The problem is a complex decision-making problem with enormous high-dimensional data and uncertainty (e.g., the price of the electricity). Therefore, a novel co-optimization scheme is proposed to handle the multitimescale problem, and also coordinate EA and FR services. A triplet deep deterministic policy gradient with exploration noise decay (TDD–ND) approach is used to obtain the optimal policy at each timescale. Simulations are conducted with real-time electricity prices and regulation signals data from the American PJM regulation market. The simulation results show that the proposed approach performs better than other studied policies in literature.

An efficient multi-objective based squirrel search optimization for optimal placement of FACTS devices

The adoption of a new transmission line is extremely complex because of its socio-economic problems such as environmental clearances. Thus, there is a prominence of better utility over available transmission infrastructure. The Flexible Alternating Current Transmission System (FACTS) devices can offer transmission capability enhancement, power compensation, and stability as well as voltage improvement. However, the FACTS devices have a higher penetration impact of wind generation for the dynamic stability of power networks. In this work, an efficient Intellectual Control system has been proposed to stabilize the FACTS devices placement. The Squirrel Search Optimization is adapted with an intellectual control system to enhance the steady-state voltage stability of FACTS devices. The proposed system has been evaluated with the assist of IEEE 14 and 26 standard bus systems to handle the multi-objective functions like cost, reduction in power loss, reducing risks, and maximizing user’s benefit. These multi-objective functions facilitate to attain the optimal placement and load flows at various sites. The simulation can be carried out with MATLAB/SIMULINK environment and the results manifest that the proposed system outperforms well when compared with existing approaches.