scholarly journals System-Theoretic Process Analysis (STPA) for Hazard Analysis in Complex Systems: The Case of “Demand-Side Management in a Smart Grid”

Systems ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 33 ◽  
Author(s):  
Stylianos Karatzas ◽  
Athanasios Chassiakos

Inelasticity of demand along with the distributed energy sources and energy market democratization pose significant challenges which have considerable negative impacts on overall grid balance. The need for increased capacity and flexibility in the era of energy market digitalization has introduced new requirements in the energy supply network which could not be satisfied without continuous and costly local power network upgrades. Additionally, with the emergence of Smart Homes (SHs) and Home Energy Management (HEM) systems for monitoring and operating household appliances, opportunities have arisen for automated Demand Response (DR). DR is exploited for the modification of the consumer energy demand, in response to the specific conditions within the electricity system (e.g., peak period network congestion). In order to optimally integrate DR in the broader Smart Grid (SG) system, modelling of the system parameters and safety analysis is required. In this paper, the implementation of STPA (System-Theoretic Process Analysis) structured method, as a relatively new hazard analysis technique for complex systems is presented and the feasibility of STPA implementation for loss prevention on a Demand Response system for home energy management, and within the complex SG context, is examined. The applied method delivers a mechanism useful in understanding where gaps in current operational risk structures may exist. The STPA findings in terms of loss scenarios can be used to generate a variety of safeguards to ensure secure operational control and in implementing targeted strategies through standard approaches of risk assessment.

2020 ◽  
Vol 15 ◽  

Effective usage of Information and Communication Technologies (ICT) has started with a paradigm shift in the energy management and functioning of the conventional power grid. It also aids in the maintenance of the complete information about consumer usage pattern, power storage, supply and regulation. Blending of information and communication technologies with energy management creates a smart grid environment which makes it move to the next horizon. The smart grid environment, uplifts renewable energy sources and brings out novel strategies in the energy market. The new functioning of the energy market attracts more utility companies for decentralized power generation and optimizes the power price for the consumer. The consumer plays an active role in the demand response modelling to maximize the welfare of the utility and to obtain the optimized price for their demand. In this paper, a novel demand response management scheme is proposed for multi-utility environment. The utility companies function in a peer to peer manner to communicate effectively and to select a specific utility from a set of utilities for the power supply. The selection of single utility is based on a non-cooperative game theory algorithm where the demand and generated power should be balanced to maximize the welfare of the utility and the residential consumers. The power price can be updated in an equal interval to allow all the utilities to participate in the Distributed Multi-Utility Demand Response Management (DMDRM) system. The simulated results justify that the distributed noncooperative game theory algorithm certainly maximizes the welfare of the utility companies and residential consumers.


Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3299 ◽  
Author(s):  
Mohammad Shakeri ◽  
Jagadeesh Pasupuleti ◽  
Nowshad Amin ◽  
Md. Rokonuzzaman ◽  
Foo Wah Low ◽  
...  

Electricity demand is increasing, as a result of increasing consumers in the electricity market. By growing smart technologies such as smart grid and smart energy management systems, customers were given a chance to actively participate in demand response programs (DRPs), and reduce their electricity bills as a result. This study overviews the DRPs and their practices, along with home energy management systems (HEMS) and load management techniques. The paper provides brief literature on HEMS technologies and challenges. The paper is organized in a way to provide some technical information about DRPs and HEMS to help the reader understand different concepts about the smart grid, and be able to compare the essential concerns about the smart grid. The article includes a brief discussion about DRPs and their importance for the future of energy management systems. It is followed by brief literature about smart grids and HEMS, and a home energy management system strategy is also discussed in detail. The literature shows that storage devices have a huge impact on the efficiency and performance of energy management system strategies.


2013 ◽  
Vol 827 ◽  
pp. 78-83
Author(s):  
Tao Li ◽  
Kun Peng Xu ◽  
Xue Qing Qi

A Home Energy Management (HEM) system is an integral part of a smart grid that can potentially enable demand response applications for residential customers. It provides a homeowner the ability to automatically perform smart load controls based on utility signals, customers preference and load priority. This paper presents an intelligent HEM for managing high power consumption household appliances for demand response (DR) analysis. The proposed HEM manages household loads according to their preset priority and guarantees the total household power consumption below certain levels.Given the lack of understanding about DR potentials in this market, this work serves as an essential stepping-stone toward providing an insight into how much DR can be performed for residential customers.


Author(s):  
Shibily Joseph ◽  
E. A. Jasmin

Aim of demand response (DR) programs are to change the usage pattern of electricity in such a way that, beneficial to the consumers as well as to the distributors by applying some methods or technology. This way additional cost to erect new energy sources can be postponed in power grid. Best method to implement demand response (DR) program is by influencing consumer through the implementation of real time pricing scheme. To harness the benefit of DR, automated home energy management system is essential. This paper presents a comprehensive demand response system with real time pricing. The real time price is determined after considering price elasticity of various classes of consumers and their load profiles. A real time clustering algorithm suitable for big data of smart grid is devised for the segmentation of consumers. This paper is novel in its design for real time pricing and modelling and automatic scheduling of appliances for home energy management. Simulation results showed that this new real time pricing method is suitable for DR programs to reduce the peak load of the system as well as reducing the energy expenditure of houses, while ensuring profit for the retailer.


2017 ◽  
Vol 138 ◽  
pp. 154-164 ◽  
Author(s):  
Mohammad Shakeri ◽  
Mohsen Shayestegan ◽  
Hamza Abunima ◽  
S.M. Salim Reza ◽  
M. Akhtaruzzaman ◽  
...  

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