ライブラリー Annual Energy Outlook 2000

The value of investments in renewable energy (RE) technologies has increased rapidly over the last decade as a result of political pressures to reduce carbon dioxide emissions and the policy incentives to increase the share of RE in the energy mix. As the number of RE investments increases, so does the need to measure the associated risks throughout planning, constructing and operating these technologies. This paper provides a state-of-the-art literature review of the quantitative and semi-quantitative methods that have been used to model risks and uncertainties in sustainable energy system planning and feasibility studies, including the derivation of optimal energy technology portfolios. The review finds that in quantitative methods, risks are mainly measured by means of the variance or probability density distributions of technical and economical parameters; while semi-quantitative methods such as scenario analysis and multi-criteria decision analysis (MCDA) can also address non-statistical parameters such as socio-economic factors (e.g. macro-economic trends, lack of public acceptance). Finally, untapped issues recognised in recent research approaches are discussed along with suggestions for future research.

Risk-based methods for sustainable energy system planning: a review

The main purpose of this study is to highlight the continuing need of policies for subsidizing through Green Certificates, the production of electricity from renewable sources in Romania and especially wind energy. Amending legislation in 2013 by diminishing the support for the RES producers led to a significant reduction in investment in this area and eventually will cause an end. Romania met the planned capacity for 2014 with 2967 MW installed above 2880 MW planned. However, reducing the number of GC can affect the deployment of future projects in order to meet the 4000 MW expected by 2020. The European Union has set a unique path in terms of developing renewable energies by 2020, but each country has different potentials depending on geographical location, landscape, climatic influences and local policies. Romania׳s wind potential is considered to be the highest in Southeast Europe with Dobrogea region being the second highest wind potential area on the continent. RES Romanian producers benefited Green Certificates (GC) scheme upon accreditation by the National Regulatory Authority for Energy (ANRE). Green Certificates can be redeemed only in Romania within the national agreed quota. Owing to the 2010 legislative measures, installed capacity of wind power increased from 7 MW in 2009 to 976 MW peak in 2012, by 2015 reaching a total installed power of 2990 MW. Promotion of electricity from renewable sources over 2010–2013, through the national subsidy policy has led to a significant drop in greenhouse-gas emissions from the production of electricity from 438 g/kWh in 2011 to 326 g/kWh in 2015.

Wind energy in Romania: A review from 2009 to 2016

In this study, an IROM-ES (inexact regional optimization model for energy systems) is developed with considering NESs (new energy sources) under uncertainty. The IROM-ES integrates techniques of ILP (interval linear programming), MLP (mixed-integer linear programming) and CCP (chance-constrained programming). In the IROM-ES, multiple uncertainties expressed as intervals and stochastic numbers are allowed to be incorporated into the framework within the multi-period and multi-option contexts. The IROM-ES is then applied to a case study of Fengtai District, Beijing, China, in which the objective is to minimize system cost under a series of constraints with considering social, economic and environmental concerns. Solutions regarding energy-supply schemes, NESs utilization, capacity-expansion plans and air pollutants control in a cost-effective manner have been generated to satisfy the urban energy and atmosphere quality demands under different violation risks. Results reveal that the changes in violation risks would lead to different optimal planning schemes. A higher violation risk would correspond to a higher probability of system-constraint violation and a lower system cost; conversely, a lower violation risk would lead to an increased strictness of the constraints or a narrower decision space, then to a higher system cost. Moreover, results indicate that the urban electricity supply from NESs would be relatively high (suggested more than 14.40%). Furthermore, to improve the reliability of decisions, post-optimization analyses (including modeling comparisons, alternatives setting as well as system triangulation analysis) are preformed to examine which scheme could be more appropriate, which can facilitate providing strategy in different scenarios for the decision makers.

Regional planning of new-energy systems within multi-period and multi-option contexts: A case study of Fengtai, Beijing, China

Carbon emission reduction and reliable power supply equilibrium based daily scheduling towards hydro-thermal-wind generation system: A perspective from China

Demand for energy is constantly rising worldwide whereas most conventional sources of energy are depleting. Environmental issues such as excessive greenhouse gas emissions impose additional constraints on the energy industry across the globe. Therefore, raising the share of clean sources of energy in power generation is of paramount importance. Wind power has specifically attracted large-scale investments in recent years since wind power is inherently ample, widely distributed and comes with minimal environmental impact. Wind, and consequently wind generated power are stochastic in nature. Therefore, wind energy is generally used in combination with fuel-based power to maintain reliability. Obviously, designing a reliable and efficient network of several power generation sources requires capacity planning. In this paper, a probabilistic optimization model is proposed for this purpose. The stochastic model uses a combination of recourse and chance-constrained approaches to assign optimal capacities to several sources of power generation including wind. Demand and wind generated power are both assumed stochastic and possibility of energy storage, importation and exportation are also considered in the network.

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Yashar Aliari Kardehdeh

Papers

Planning for integration of wind power capacity in power generation using stochastic optimization