Electricity Journal最新文献

Valuing electric power, particularly its loss within the residential sector, has historically been a great challenge that many researchers have undertaken without reaching a consensus. Electric power can be troublesome to appraise because consumption is not the customer’s main goal, but rather a means to achieve a desired good or service that often has unquantifiable personal value. This paper proposes a market-based household production method that quantifies the customer electric service interruption costs in the residential sector. Because an individual’s personal time is necessary to replace services owing to the lack of electric power, we propose a method that estimates the weighted market cost of a person’s time in accordance with their occupation to better calculate customer outage costs. We also present a macroeconomic production method to estimate losses in the residential sector. Finally, we propose a method for calculating the true costs of electric services by factoring the outage costs with the electrical utility rate to be analyzed using reliability metrics. The proposed approach facilitates a closer estimation of the low-bound true costs of utility-supplied electrical services for consumers who have not taken mitigation measures, serving as a warning for energy regulators to impose corrective actions or appropriate penalties on unreliable utilities and/or as an indicator for customers to invest in alternative energy sources.

A physical Dodge City high voltage direct current (HVDC) electricity commodity hub would foster the kind of risk transfer that would invite the full participation of the financial industry in an interstate transmission system essential to the speedy development of renewable electricity and complementary storage technologies. Obstacles lie in the way of such a vision, however. Chief among them, paradoxically, is the administrative system that has evolved since the late 1990 s to promote regional electricity markets. That system abstracts from investment risk and the nation’s uneven geography of renewable resources. It lodges a kind of monopoly planning and scheduling power in a small group of bureaucratic centralized system operators that mimics a command economy in their own distinct regions, not the kind of market economy that has traditionally driven investment in US interstate energy infrastructure. And yet, in dealing with the vexing transmission constraints faced by the renewable generating sector (the “queue”), the Federal Energy Regulatory Commission (FERC) continues to pursue ever greater authority for those regional transmission organizations (RTOs). Such FERC action regarding its RTOs in 2022–23 represents a highly evident case of path dependency—a problem—that state or federal policy makers wishing to speed the entry of large-scale renewable generation, and complementary storage technologies, will have find a way either to confront directly or to work around.

Decarbonizing electric systems through the integration of large amounts of intermittent renewable energy complicates the balancing of demand and supply, increasing the value of storage. With the rapid expansion of short-term storage options such as batteries, flexible resources such as existing hydroelectric reservoir storage are often overlooked. Using a capacity expansion and dispatch model of the Northeastern North American power system, we draw lessons from the interconnection potential of Quebec’s large existing hydropower capacities. We find that reservoir-transmission coupling significantly decreases the cost of decarbonization, even when short-term storage costs are low, because it is used for both daily and seasonal balancing. Conversely, the value of short-term storage is compromised by the availability of reservoir-transmission coupling, even assuming high investment costs for transmission. We also describe the regional distribution of costs and benefits of storage and transmission and discuss implications for regional cooperation.

This article analyzes energy poverty in Latin America and the Caribbean and the importance of energy efficiency to address this issue. The paper also touches upon energy subsidies in Mexico and their negative environmental and social consequences. Then, the article studies the potentially detrimental billing practices of Mexico’s state electricity company, which are provoked by the enterprise’s growing past-due portfolio and losses, and the possible infringement of electricity consumers’ rights. The authors propose three courses of action for consumers to protest the company's possibly perjudicial billing. Finally, the authors suggest that a distributed electricity system in Mexico could combat energy poverty and strengthen electricity users’ rights.

International humanitarian law is a branch of public international law that seeks to moderate the conduct of wars to protect those who are not taking part in the hostilities. Under international humanitarian law, belligerents may not intentionally target civilians or installations that are indispensable to the survival of the civilian population. While collateral harm to civilians and civilian infrastructure may occur, international humanitarian law prohibits attacks that may be expected to cause incidental loss of civilian life, injury to civilians, damage to civilian objects, or a combination thereof which would be excessive in relation to the concrete and direct military advantage anticipated. In practice, these principles have not always been honored or enforced. State and non-state actors have deliberately targeted civilians and/or disregarded civilian impacts, often for the purpose of pressuring political leaders to capitulate. The increasing occurrence and severity of harm to civilians and civilian infrastructure in modern conflicts calls into question the continuing relevance of what were once viewed as fundamental protections. In this paper, we present a case study involving Russia’s 2022–23 attacks on Ukraine’s electric power infrastructure, which left millions of civilians without heat, water, or other basic services for extended periods in harsh winter conditions. Considering the scope, scale, and long-term impacts of these attacks, we conclude that Russia violated international law. We also suggest that a new international protocol may be necessary in order to more effectively deter and punish attacks on civilian infrastructure in future armed conflicts and military occupations.

Typical approaches to assessing excess generation capacity in African electricity systems have considered the nameplate capacities of existing generation plants, the planned generation capacity, and peak load. However, the omission of variables such as the condition of transmission and distribution infrastructure, the age of existing power plants, and whether generation capacity is intermittent (as in the case of wind or solar) or subject to climate impacts (as in the case of hydropower) has caused such assessments to be misleading. This can result in misguided public policy and power procurement processes that are poorly matched to the needs of evolving power systems. In this paper, we analyze the case of Kenya to show how power system planning must consider these key factors that are often ignored. Far from having excess capacity as has been repeatedly reported, the Kenyan grid has limited capacity to take up additional load at present.

The British Royal Society has recently recognized that achieving net zero emissions requires a substantial amount of energy storage in the United Kingdom by 2050, totaling about 200 TWh, to address the intermittent nature of wind and solar energy production, spanning from seconds to seasonal variations. While their assessment acknowledges that hydrogen should play a predominant role in this storage, it also highlights exceptionally high technology readiness level (TRL) and round-trip efficiency that is attributed to large-scale advanced compressed air energy storage (ACAES), which is viewed as a formidable contender. However, in this discussion, we argue that these values may be somewhat exaggerated. While ACAES certainly offers potential advantages, it also confronts a multitude of challenges, particularly when it comes to extensive, large-scale implementation.

The urgent shift towards renewable energy sources in response to climate change highlights the necessity of thoroughly examining the obstacles that impede the progress of cleaner energy efforts. This study examines the socio-political barriers that hinder the expansion of the renewable energy industry in India, a nation facing the dual challenges of rapid economic growth and environmental preservation. Amidst increasing global apprehensions regarding the environment, this study employs a comprehensive analysis encompassing ANOVA, correlation, and regression to identify crucial aspects influencing the advancement of renewable energy in India. While previous studies have recognized financial limitations such as brief loan durations and significant capital expenses as substantial obstacles, our research explores the intricate interaction of several elements in greater detail. The key findings reveal substantial variations across the groups examined, providing insight into the differing degrees of awareness and concern surrounding renewable energy. Remarkably, limited connections arise between crucial factors such as awareness of renewable energy, care for the environment, and government energy policy. The regression analysis highlights the insufficiency of the variable "Development of renewable energy in India" in accurately predicting the dependent variable, thus indicating the presence of other relevant factors. India's present renewable energy capacity is only 18%, with hydro energy contributing 14%. Our research highlights the need for specific actions to address this issue. The study continues by recommending incorporating scholarly knowledge into policy development to encourage investor attraction and promote the widespread acceptance of cleaner and renewable energy solutions at both national and international levels. This research provides a detailed and insightful viewpoint to the ongoing discussion, highlighting the crucial influence of socio-political factors in determining the future direction of India's renewable energy sector.

Demand-side flexibility is crucial for integrating variable renewable energy sources cost-effectively. Home heating systems determine the potential for flexibility in individual households. We examine different approaches to classify heating systems in Finland and find that using hourly electricity consumption time series is more effective than house and socio-demographic features. Classification based on electricity consumption data achieves higher precision (0.62) and recall (0.64) than house and socio-demographic features (0.41 and 0.43, respectively). Therefore, the availability of electricity consumption time series data should be considered from a competition policy perspective due to its value in estimating flexibility potential.

In natural language processing (NLP), transformer based models have surpassed recurrent neural networks (RNN) as state of the art, being introduced specifically to address the limitations of RNNs originating from its sequential nature. As a similar sequence modeling problem, transformer methods can be readily adapted for deep learning time series prediction. This paper proposes a sparse transformer based approach for electricity load prediction. The layers of a transformer addresses the shortcomings of RNNs and CNNs by applying the attention mechanism on the entire time series, allowing any data point in the input to influence any location in the output of the layer. This allows transformers to incorporate information from the entire sequence in a single layer. Attention computations can also be parallelized. Thus, transformers can achieve faster speeds, or trade this speed for more layers and increased complexity. In experiments on public datasets, the sparse transformer attained comparable accuracy to an RNN-based SOTA method (Liu et al., 2022) while being up to 5× faster during inference. Moreover, the proposed model is general enough to forecast the load from individual households to city levels as shown in the extensive experiments conducted.