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Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Greenhouse gas emissions from electricity production are a crucial part of the environmental impact assessments of any kind of product, service or consumption. Usually, average annual emissions are used, but lately there has been increased interest in the daily-based and hourly-based emission coefficients for electricity. In such markets, where the technology mix in the production process includes technologies with different emission factors, there is potential for large variation in hourly based emission factors and consequently this offers potential for decreasing the emissions by real-time based demand management. However, in real life the timing of electricity use in households and companies has restrictions. In this paper, we show illustrative household and company cases with realistic shifts in the timing of electricity use. We determine hourly based emission factors and give examples of how emissions may be decreased in households and companies by changing usage patterns, and consequently the timing of electricity use, with the total amount of electricity consumed remaining unchanged. The examples show decreases of emissions in the range 3–8% due to optimised timing, indicating that there is important potential for managing hourly based demand loads and the resulting emissions even with realistic assumptions of the timing of consumption. [ABSTRACT FROM AUTHOR]

In the restructured environment of the power industry, various commodities such as energy and operating reserves may be provided through simultaneous auctions. Prediction of market players' behavior in the auctions and simulation of the markets' environment can assist market decision-makers in evaluating specific policies before enforcing them in the real environment. Considering effects of the energy and varieties of reserve markets and also their interactions in the simulations is of high importance, which leads to more realistic simulation results. In this paper, an approach based on a multiagent system is proposed for simulating the simultaneous energy, spinning reserve, and replacement reserve market auctions, in which bidding of each agent is carried out based on a reinforcement learning algorithm. The proposed method is applied on a sample system, through which the impacts of considering lost opportunity cost in the payment model are examined. [ABSTRACT FROM AUTHOR]

Energy production and consumption is always accompanied with environmental and societal issues. Electricity as one final energy form plays an important role in people's activities. However, the electric utilities have focused on producing electricity in abundance and with an affordable price. The production of electricity results in undesirable emissions and environmental effects called externalities. This paper assesses the externality cost of electricity production in Indonesia by using the life cycle inventory analysis approach. In 2025, the results show that the total external costs according to the government plan are 42 billion US$. In addition, low carbon society behavior will be introduced into the Indonesian society to reduce the externality cost in the long term Indonesian electricity expansion planning. The results of low carbon society actions show that in the long term the Indonesian electricity expansion planning of 34.6 TWh of electricity demand and 7.3 GW of installed capacity can be reduced from these actions. Finally, at the end of the period, these actions are successful, and reducing the total external cost by 2 billion US$. [ABSTRACT FROM AUTHOR]

This paper will explore the Energy for ME program, funded by the Environmental Protection Agency and the National Science Foundation, which worked across formal and informal K-12 environments to bridge the gap between society, science, and the environment. Specifically, this article documents how Energy for ME integrates three experiential education pedagogies (place-based education, inquiry, and project-based learning) in combination with real-world electricity data in order to impact energy consumption within participating communities. Energy for ME schools and communities have saved over $135,000 in homeowner electricity costs, 900,000 lbs of carbon, and 1,000,000 kWh of energy) in electricity costs over the 3 years of the project. [ABSTRACT FROM AUTHOR]

We review future global demand for electricity and major technologies positioned to supply it with minimal greenhouse gas (GHG) emissions: renewables (wind, solar, water, geothermal, and biomass), nuclear fission, and fossil power with CO2 capture and sequestration. We discuss two breakthrough technologies (space solar power and nuclear fusion) as exciting but uncertain additional options for low-net GHG emissions (i.e., low-carbon) electricity generation. In addition, we discuss grid integration technologies (monitoring and forecasting of transmission and distribution systems, demand-side load management, energy storage, and load balancing with low-carbon fuel substitutes). For each topic, recent historical trends and future prospects are reviewed, along with technical challenges, costs, and other issues as appropriate. Although no technology represents an ideal solution, their strengths can be enhanced by deployment in combination, along with grid integration that forms a critical set of enabling technologies to assure a reliable and robust future low-carbon electricity system. [ABSTRACT FROM AUTHOR]

Background: Policy makers seek to understand the trade-offs needed between economic growth and climate change. This provides the context to explore low-carbon development (LCD) pathways for the West African electricity system. Methods: The study relied on both primary and secondary sources to elicit required information. These data were elicited from relevant authorities in the West African electricity system, namely, West African Power Pool and ECOWAS Regional Electricity Regulatory Authority. The objectives were to evaluate the planning processes in the West African Power Pool electricity system vis-a-vis low-carbon development strategy (LCDS), develop a System dynamics (SD) model, and assess the relevance of the developed model to examine the nonlinear relationship between generation adequacy and greenhouse gas emission (GHG) reduction. The SD model examined the tension between providing adequate supply capacity against reducing emission from the generation technologies in the West Africa electricity system. This model arranged the complexities in the system and established the basic interconnecting structure to conduct the analysis. High leverage points were identified. Results: Four high leverage points were identified: capacity factor (CF), emission factor (EF), time to adjust capacity, and expectation formation. CF and EF improvement increased efficiency in the system. The expectation formation periods were determined at 7.5 years for the base case scenario and 7 years for the low-carbon development option scenario. Time to adjust capacity was located at 21 and 20 years respectively; deduced from the average time, it will take to construct a combined cycle gas power plant (3 years) and an allowance of 2 years for delays and its decommissioning time. Between 2011 and 2012, in LCD option scenario, emission of GHG to the atmosphere dropped as generation did but began a steady rise for the simulation period to a value of 6.154 billion tCO in 2060. Conclusions: Electricity Planning-Low-Carbon Development (EP-LCD) model-with three modules, was developed for assessing WAPP in low carbon economy. High leverage points identified in the model simulation situate three policy options for overcoming poverty and mitigation targets as regards resource mix, investment cost recovery, and technical factors to reduce system's environmental footprint. [ABSTRACT FROM AUTHOR]