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This paper presents a modeling framework to address the energy, economy, emissions and land use nexus when exploiting bioenergy in developing countries. The modeling framework combines a qualitative and a quantitative element. The qualitative element integrates two components: (1) technology roadmapping to identify long-term technology targets through expert judgment and (2) scenario analysis to investigate different future storylines. The quantitative element comprises four integrated tools, namely the energy system model (ESM), the land use and trade model (LUTM), an economic model, and an external climate model. An overview of the modeling framework, scenario analysis, structure of the models, modeling techniques, mathematical formulations and assumptions is presented and discussed. The modeling framework is applied to the particular context of Colombia, as a case study of a developing country with large bioenergy potential. In this study case, the impacts that an accelerated deployment of bioenergy technologies might cause on the energy demand and supply, emissions and land use until 2030 are evaluated. Results suggest that a plan to exploit bioenergy in Colombia should prioritize the deployment of technologies for biomethane production, power generation & CHP, which can reduce more GHG emissions and more emissions per incremental hectare of land than first-generation biofuels. Moreover, while the share of bioenergy in the primary energy demand decreases in all the analyzed scenarios, it is possible to envision significant increases in the share of bioenergy in road transport energy demand, power generation and natural gas supply for scenarios implementing roadmap goals. In addition, impacts of El Niño oscillation on the dependence of hydro for power generation can be partly mitigated by exploiting the complementarity of hydro and bioenergy, which might result in a reduction of up to 5–6% in the demand for fossil fuels used in power generation in dry years. However, despite the ambitious goals proposed here, bioenergy alone cannot significantly reduce emissions by 2030 (maximum 10% reduction relative to baseline) and effective climate change mitigation requires a portfolio of additional measures. [ABSTRACT FROM AUTHOR]

[Display omitted] • A model is proposed to maximize market performance including tradable certificates. • The long-term impacts of regulations on market are discussed by fine and subsidy. • Three important objectives for government are investigated under four scenarios. • The obtained results are validated by Turkey's energy data as a real case study. • Fine policy is more effective than a subsidy to empower renewable electricity. In the last decades, due to the increasing environmental concerns such as energy-resource depletion and global warming, energy efficiency instruments and renewable energy production has been promoted more than ever. This paper investigates a comprehensive comparison between two energy markets, i.e., the tradable white certificate (TWC) market and the tradable green certificate (TGC) market. How to coordinate the two energy markets and what the coordination impacts become the main issues under a reward-penalty mechanism. This multi-agent problem is discussed in an electricity supply chain consisting of two populations of traditional energy suppliers who want to decide about using one of them under government intervention. In this regard, the behavior of the suppliers is analyzed under three different Scenarios, including traditional power generation, energy efficiency program (EEP), and renewable portfolio standards (RPSs). An evolutionary game is applied to formulate the problem. The results show that a mandatory fine policy is more useful than an energy-saving subsidy to motivate the traditional suppliers to move toward sustainable energy generation. This policy also helps governments to meet their sustainable-oriented goals, as we discussed in this work. The findings can be applied to extend sustainable-based energy projects in developing countries. [ABSTRACT FROM AUTHOR]

Demand response is increasing in popularity and many utilities are developing demand response programs. However, there exists many challenges to the deployment of demand response. One of the main barriers to widespread rollout is the uncertainty surrounding the value of demand response. In this regard, there is a real and pressing need to evaluate demand response if its full potential is to be realized. This paper presents a comprehensive review of the literature and identifies some of the key barriers to the deployment and the challenges to the evaluation of demand response and provides some recommendations on evaluation methodologies. [ABSTRACT FROM AUTHOR]

In terms of energy resources, Canada is an important player on the world scene. However, the energy systems of the Canadian provinces and territories are much diversified and a national energy strategy is missing in order to optimize the management of energy systems. The objective of this paper is twofold. First, we introduce TIMES-Canada, a new multi-regional energy model that has been developed using the most advanced TIMES optimization modeling framework, while keeping a very high level of details in the database (5000 specific technologies; 400 commodities) compared with other Canadian energy models. Second, we define and analyze possible futures for the Canadian integrated energy system on a 2050 horizon, under five different baselines: a Reference scenario as well as four alternate scenarios corresponding to different oil prices (Low and High) and socio-economic growth trends (Slow and Fast). In our Reference scenario, we show that the Canadian final energy consumption is expected to increase by 43% between 2007 and 2050. The Fast scenario leads to the maximum increase compared with the Reference scenario (21% in 2050). In all scenarios, oil products will continue to dominate on the long term, although in a decreasing proportion over time (from 43% in 2007 to 29% in 2050) in favor of electricity (31% of the additional demand in 2050) and biomass/biofuels. Regarding the corresponding optimal energy production paths, we illustrate two main trends: (1) a gradual replacement of onshore conventional oil & gas sources by unconventional and offshore sources (oil sands is expected to represent half of the production in 2050), and (2) a significant penetration of renewables in the electricity mix is shown after 2035 due to increases in oil import prices and decreases in renewable technology costs. The development and calibration of such a detailed technology-rich model represent an important contribution for Canada: TIMES-Canada is the only optimization model covering in details the large diversity of provincial energy systems on a long term horizon. [ABSTRACT FROM AUTHOR]

• The new power supply structure resulting from the new policy has been considered. • The new models project the inefficient points onto a more realistic efficient frontier. • The new models have the power to allocate the shared resources. • Results show that the power production stage is allocated less shared resources. • The power sale stage's efficiency is lower than the one of power production stage. To relieve the problems of energy shortage and environmental pollution, many countries have implemented a variety of policies to improve the energy efficiency of the power industry. To understand the impacts of such policies on energy efficiency, this paper constructs novel network data envelopment analysis models to recognize the policy-induced structural changes in the power system. Compared with previous studies, the new models project the inefficient points onto a more realistic efficient production frontier, considering how the distribution proportion of shared resources will change when the power system, modeled as a power generation stage and a power sale stage, is led by the latter stage. Our empirical study on China's power system shows that the province of Guangdong and the eastern region of China perform best, and all power production stages perform better than the corresponding power sale stages. The development of the two power subsystems in the four regions is unbalanced. More than half of the power supply systems choose to allocate more proportion of the shared resources to the sale stage rather than use a more balanced distribution between the two stages. [ABSTRACT FROM AUTHOR]