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This study investigates the potential application of hybridized energy system (i.e., PV/Wind/Diesel) with battery storage in the northern region of Bangladesh. A techno-economic feasibility of different system configurations is evaluated and an optimized system is selected using HOMER (Hybrid Optimization Model for Electric Renewable) software. The hybrid system is optimized to meet a remote stand-alone village community’s load demand of 242.56 kWh/day with a 51.52 kW peak load demand. The result of this study indicates that the optimized hybrid system consists of 73 kW PV arrays, a 57 kW Diesel generator, a 387 kWh nominal capacity battery bank, and 28 kW inverters have the minimum Cost of Energy (COE) of 0.37$/kWh and the Net Present Cost (NPC) of $357,284. The outcome also indicates that the optimized system reduces CO 2 emission by around 62% in comparison with the kerosene used in a current situation and 67% with the grid connected system. Furthermore, the Life Cycle Emissions-LCE (kg CO 2 -eq/yr) production is considerably lower in PV/Batt/ICE system than the other system configurations. However, this system has a lower Duty Factor (DF) compared to Wind/Batt/Diesel and Batt/Diesel based system. Although this system is not comparable with the grid tariff, the proposed method is economically feasible than solar micro utility system, Wind/Batt/Diesel system, and Diesel generator only system. Additionally, the article discusses the social and economic benefits of implementing the hybridized system along with their barriers and challenges. [ABSTRACT FROM AUTHOR]

Implementing real-time electricity pricing in residential sector is supposed to be an effective measure to balance daily electricity load and promote electricity conservation. However, due to lack of empirical evaluation, evidence about the in-field impacts of real-time electricity pricing is still lacking in China. Based on household survey and agent-based modeling, this study simulates Chinese household's 24-h electricity demand profile, and analyzes how households adjust their electricity use activities under the dynamic real-time pricing scheme. Results show that real-time pricing has the potential to shift residential electricity load from peak to off-peak periods and reduce total electricity consumption. The magnitudes of these two effects hinge on the probability of households' response to electricity price increases. Survey results indicate that such probability varies along the two dimensions of households' characteristics and the type of electricity use activities. To raise the response rates and improve real-time pricing's effects, the following strategies are proposed: 1) introduce and subsidize the purchase of economically feasible domestic electricity storage devices; 2) integrate environmental education modules in the real-time pricing policy design, so as to raise household dwellers' sensitive to the price signals. [ABSTRACT FROM AUTHOR]

Industries are a major fossil energy consumer and economic development contributor in China. The Chinese government is performing the industrial reforms to diminishing the dependence of industrial output on fossil energy consumption. To guide the present industrial policy adjustment, this study employs the Tapio decoupling index, a structural decomposition algorithm, a hybrid forecasting model, and industry-related data from 2001 to 2014 to evaluate, decompose and forecast the relationship between China's industrial output and fossil energy consumption. Empirical results show that the decoupling index of fossil energy consumption from the value added by China's industry was less than 0 in 2015. Consequently, the industrial fossil energy consumption reached its peak at that time and will gradually decrease in the future, even though the added value continuously increased. The mitigation goals set by the Chinese government for industrial fossil energy intensity by 2020 are expected to be achieved ahead of schedule. The attainment of these goals will strongly support the realization of China's fossil energy-related prospects for 2030. To reduce industrial fossil energy consumption, China should develop strategies for non-fossil energy electricity generation, implement electricity price bidding, prevent overheated investments to real estate and infrastructure, and eliminate backward capacity and establish market-access rules for acetic acid, calcium carbide, ethyl alcohol, and dimethyl ether. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) Panels, one of the more promising renewable energy technologies, are growing rapidly nowadays, especially in developed countries. However, these systems have not achieved public acceptance in some countries due to low energy efficiency and poor economic performance, especially in countries which are subsidized in energy tariffs. In this paper, the energy and economic performance of fourteen rooftop PV systems with the power of 5 kW in the hot and dry climate of Iran are assessed by monitoring the total annual energy production and simulation. The monitored data is used to analyze systems’ economic performance via Pay-Back Period (PBP), Net Present Value (NPV), Return of Investment (ROI) and Levelized Cost of Energy (LCOE). Results show that single array configuration systems have the maximum energy production while dividing the system decreases the production. Economic analysis shows that the average PBP is 11.6 years under actual price of electricity (0.21$), however it is 46.9–50.5 years under subsidized average tariffs. ROI values range from 2.6 to 3.2 with the average of 2.9 for actual prices. Under subsidized prices, the cash generated by investment cannot even offset the costs that the investment requires during its lifetime with NCF and NPV being both negative. Overall, the systems are not economically beneficial under subsidized average tariffs in Iran, which discourages private and public sectors to investment on these systems. Environmentally, each PV system can averagely reduce 500 kg CO 2 emission in the first year of installation and fourteen of them can approximately reduce 1,613,900 kg of CO 2 emission during life time of PV panels. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic control algorithm to enable an energy-aware single machine scheduling under the time-varying electricity pricing policy, in which price rates remain fixed day-to-day over the season. The key issue is to assign a set of jobs to available time periods where different electricity prices are assigned, while considering requested due dates of jobs so as to minimize total penalty costs for earliness and tardiness of jobs and total energy consumption costs, simultaneously. As the first contribution of this study, we develop a new mixed integer nonlinear programming (MINLP) model that aims at determining job arrival times and resulting earliness and tardiness of jobs and energy consumption costs for machine idle and normal processing. Second, an efficient heuristic approach based on continuous-time variable control models and algorithm is developed. The proposed heuristic adaptively changes job arrival times and due dates, which finally determine production sequence over the time periods of different electricity prices, machine turn-off, and machine idle with minimum energy consumption costs and just-in-time (JIT) penalty. Energy and JIT performance of the proposed approach is examined using real energy and machining parameters of a HAAS machine and compared to those of the metaheuristic approach. For relatively large size data groups, the proposed approach incurs about 4 ∼ 11 % higher energy consumption costs on average, which are offset by up to 99 % lower JIT costs, resulting in 10 ∼ 94 % lower total costs on average compared to the metaheuristic approach. The proposed time-scaled heuristic algorithm yields extremely short computational time, which enables production managers to flexibly select proper production strategies and to implement them for different production environments. [ABSTRACT FROM AUTHOR]

There is a growing worldwide concern regarding emissions of energy-related greenhouse gases (GHGs). Policy, technology and human awareness provide opportunities for offsetting these effects through energy conservation, efficient appliances and solar generation in households as these have been the subject of increasing attention across the world in recent years. Solar rooftop generation, in particular, could deliver significant efficiency improvements and reductions of CO2 emissions through its diffusion, which also avoids losses in electricity transmission and distribution systems; energy efficiency contributes to the achievement of a sustainable future because it reduces the energy-infrastructure needs, increases competitiveness and improves consumer welfare; conservation would also reduce CO2 emissions in households. The purpose of this paper is to assess the combined effect of the diffusion of solar rooftop generation, energy efficiency and electricity conservation in the residential sector in Colombia. Simulation results for different policy scenarios indicate that rooftop generation, energy efficiency and conservation can together lead, under certain conditions, to important reductions in both electricity prices and emissions. [ABSTRACT FROM AUTHOR]