Search

Reducing local and global emissions is one of the drivers behind the promotion of renewable energy technologies (RETs). Some RET projects (e.g. solar, marine power, and some biomass and wind) usually require supplemental income from carbon credits in order to make them economically viable. This paper presents the mathematical development of nodal marginal CO 2 emission metrics for hydrothermal systems. These metrics are obtained from optimal power flow and hydrothermal dispatch models considering hydro uncertainty. The proposed model allows a more accurate assessment of the emission reduction effect of RET projects and the provision of efficient carbon signals to the system. Modeling of hydro reservoirs and intertemporal constraints also allows incorporating the emission mitigation potential of water storage. The concepts of marginal CO 2 emissions for hydrothermal systems are first exemplified using a small test system, and then simulations on a real hydrothermal system illustrate how these metrics can inform investment and operational decisions. Theoretical and simulation results show that transmission and hydro storage constraints neglect may provide wrong signals for RET investors, missing the incentives to install in areas where the potential for emissions reduction is higher (where renewable energy displaces a larger amount of coal or diesel). Policy makers can use the proposed model to assess the cost-effectiveness of emission reduction policies. [ABSTRACT FROM AUTHOR]

• Significant levels of self-sufficiency based on renewable microgrids (MG) in Chile. • Community MGs are generally more profitable than MGs for single-dwellings. • Renewable MGs are effective at reducing the community peak demand tariff. • Better profitability and self-sufficiency levels are found in rural areas. • We recommend removing barriers to community microgrid projects. Grid-connected microgrids (MG) can offer significant benefits to electricity systems by improving the security of energy supply with clean renewable energy sources. Unlocking these benefits requires designing suitable business models that can capture the value of MGs and that help removing barriers to their uptake. In this work, we evaluate the profitability and self-sufficiency of optimally designed MGs for new proposed business models. The business models are tested in seventeen different geographical locations which offer a vast diversity of renewable resources, seasonal climatic variability and electricity tariffs. Both Net Billing and Net Metering schemes are tested, for both single-dwelling and community residential customers. Electricity tariffs include both energy volumetric and peak demand charges. We model the optimal sizing and energy management of the MGs by minimizing the total customer electricity costs. The generation mix of the MGs is the result of a bilevel optimization which take into account renewable resources and costs, diesel prices and tariffs. MGs can potentially be comprised by solar PV, wind and diesel generation, together with battery storage systems and demand response resources. We find significant levels of self-sufficiency based on solar sources across the country, and also wind power in some specific locations. The community business model, case which includes the peak demand charges, is generally more profitable than the case of single-dwellings. This shows that the MGs are effective at reducing the peak demand charge of a residential electricity bill. We therefore recommend the further promotion of community energy arrangements as a key way to improve the current very slow uptake of distributed generation in developing countries. [ABSTRACT FROM AUTHOR]