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Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

To meet the increasing challenges on global warming and customer demands, the current hierarchical structure of electric power grid is undergoing a rapid change by focusing on high efficiency, reliability and flexibility. To address such challenges, the new concept of smart grid with a sophisticated communication infrastructure has emerged. While power grid systems are based on traditional information architectures at present, the evolving smart grid has a strong need on communication connections among a huge amount of distributed elements, such as generators, substations, monitoring sensors and customers. However, the power industry is facing dilemma that communication resources are limited due to the lack of wireless spectrum resources and the restrictions of wired applications. This paper firstly provides the architecture of the wide-area monitoring system for smart grid by applying a spectrum sensing and sharing technique of cognitive radio, based on an overview of the current communication technologies. Afterwards, the paper presents the feasible application of cognitive communication architecture on the existing power quality monitoring system by combining long-term and short-term monitoring approaches.

Abstract The vision of the ‘Smart Grid’ anticipates a distributed real-time embedded system that implements various monitoring and control functions. As the reliability of the power grid is critical to modern society, the software supporting the grid must support fault tolerance and resilience of the resulting cyber-physical system. This paper describes the fault-tolerance features of a software framework called Resilient Information Architecture Platform for Smart Grid (RIAPS). The framework supports various mechanisms for fault detection and mitigation and works in concert with the applications that implement the grid-specific functions. The paper discusses the design philosophy for and the implementation of the fault tolerance features and presents an application example to show how it can be used to build highly resilient systems.

This chapter uses data on Intended Nationally Determined Contributions (INDCs) to examine the nature of climate change mitigation and adaptation actions being pursued in African countries and assesses the extent to which preferred mitigation and adaptation priorities advance the cause of sustainable development on the continent. The prospective synergies between mitigation and adaptation approaches and sustainable development are assessed. Also, the pathways through which resource constraints and institutional and policy environment affect Africa’s ability to mitigate and adapt to climate change are examined, as well as the degree to which these constraints are being addressed. It is argued that Africa’s ability to benefit from sustainable development synergies embedded in the mitigation and adaptation strategies in the INDCs will be greatly limited by institutional and policy environment that hinders funding, capacity building, and technological innovation systems development. The slow pace of efforts to address these impediments further erodes confidence that climate adaptation in Africa will be effective at sufficiently contributing to a reduction in climate change risks to the continent.

Remote metering is a key task in smart grid to collect the power load information for the pricing in power market. A wireless communication infrastructure is assumed for the smart meter network. The dynamics of the power market are assumed to be a Markov Decision Process (MDP) by modeling the power load evolution as a two-state Markov chain. The fundamental elements of the MDP are discussed and the optimal strategy is obtained from Dynamic Programming. Due to the curse of dimensions, the myopic strategy is proposed to significantly simplify the algorithm. The validity of the proposed scheduling algorithm is demonstrated using numerical simulations. For example, for price insensitive power users, the average price and power generation errors are reduced by 60% and 40% using the myopic approach, compared with the simple round robin schedule, in certain circumstances.

We describe the background and an analytical framework for a mathematical optimization model for home energy management systems (HEMS) to manage electricity demand on the smart grid by efficiently shifting electricity loads of households from peak times to off-peak times. We illustrate the flexibility of the model by modularizing various available technologies such as plug-in electric vehicles, battery storage, and automatic windows. First, the analysis shows that the end-user can accrue economic benefits by shifting consumer loads away from higher-priced periods. Specifically, we assessed the most likely sources of value to be derived from demand response technologies. Therefore, wide adoption of such modeling could create significant cost savings for consumers. Second, the findings are promising for the further development of more intelligent HEMS in the residential sector. Third, we formulated a smart grid valuation framework that is helpful for interpreting the model's results concerning the efficiency of current smart appliances and their respective prices. Finally, we explain the model's benefits, the major concerns when the model is applied in the real world, and the possible future areas that can be explored.

Abstract The electric power industry is restructuring as regulations move from states to regional and national levels. Estimates of regional fuel and input substitution are essential for practitioners and policy makers. This paper estimates substitution under static and dynamic scenarios, examining changes in technology and total factor productivity from 2001 to 2008. Two-stage estimation reveals regional characteristics and underlying elements in fuel and factor choice processes. Substitution varies widely depending on the region, coal technology, capital investment, and R&D activities.

Abstract The transition of energy structure to renewable energy is a social and systematic engineering that requires complex regional power interconnection as a support. Thus, an assessment of the economic viability of infrastructure investments for supporting such transmission expansion is crucial. This study presents a multi-regional power system optimization model to evaluate the potential economic benefits of infrastructure investments for the national inter-regional electricity network in China under various scenarios in the context of low-carbon transformation. Key factors influencing economic benefits are analyzed specifically and regulation barriers associated with inter-regional electricity trade are given particular attention. The results show that approximately 140 Giga Watt (GW) of infrastructure construction for the inter-regional electricity trade network is economically viable during the planning horizon. These new interconnections would lead to 250–440 billion RMB of economic benefits. Regional electricity trade barriers caused by imperfect market mechanisms have a negative impact on the economic benefits of transmission infrastructure investments, although they promote scale and utilization efficiency in the power sector of electricity-importing regions. Improving the national grid coordination mechanism to break the grid isolation between the State Grid Corporation of China and the China Southern Power Grid is crucial, because a large number of transmission lines connecting these two national-level power grids are economically viable.

Current smart power grids have open communication infrastructures to improve efficiency, reliability and sustainability of supply. However, their open communication architecture makes them vulnerable to cyber-attacks with potentially catastrophic consequences. Here for the first time, we propose a time-delay-switch (TDS) attack by introducing time delays in the dynamics of power systems. Such an attack will have devastating consequences on smart grids if no prevention measures are considered in the design of these power systems. We considered how a TDS attack affects the dynamic performance of a power system. To do this, we first formulated a state space model of a smart power grid system under TDS attack using a hybrid systems approach. Second, we prove by analysis and demonstrate by simulation examples how a TDS attack can be used to sabotage and destabilize a smart grid.