Countries differ in terms of their socio-economic development, population growth, and energy consumption. Many countries still depend on conventional energy to supply enough energy source for their demand, while some have made considerable progress in making the transition to renewable/sustainable energy sources. Owing to the increasing demand and drawbacks of conventional energy sources, policies can play a major role in encouraging and increasing the uptake of renewable energy (RE) technologies. In this paper, a general overview on the RE activities in the three leading countries—China, Brazil, and the United States of America (USA)—is presented. Moreover, a comparative analysis on the implementations of the RE support policies is conducted. The linear regression analysis technique is applied to develop several models for the three countries in order to investigate the effect of different policies on RE. The main contributions of this study are establishing a link between RE support policies and RE development (in terms of the installed capacity) in the three countries under study, and providing models that can be used in estimating RE development using RE policy data. In addition to this, some models are developed to investigate the relationship between RE installed capacity and the patents. The linear regression analyses suggest that RE policies promote the development of RE installed capacity in the three countries in different proportions. For example, it is found that each additional wind policy will increase the RE wind capacity in China, Brazil, and the USA by 1.63, 0.689, and 1.576 GW, respectively. Moreover, the economic instruments turn out to be more effective in promoting the RE installed capacity in the USA and Brazil, while the policy support and regulatory instruments are the most influential policy categories in China. Furthermore, the linear regression analyses indicate the existence of a positive significant relation between the number of patents and the total RE installed capacity in the three countries.
The merits of utilizing renewable energy sources (RESs) in electricity generation, especially in the developing countries, are to improve the electricity access, economic development and energy sustainability. Nigeria is a developing country with an acute electricity problem. The country is blessed with rich renewable energy (RE) resources. However, most of these resources are yet to be exploited. A look at the energy sector in Nigeria suggests that for the country to be energy sufficient, it must embrace domestic RESs in its energy mix. However, RE technologies are capital intensive. Hence, by using Nigeria as a motivation, this study aims at developing a general framework that can be used for any country or region in determining the optimal total capacities of RESs to be installed in different locations, to increase the use of RE in a cost-effective manner. The designed optimization problem aims to minimize the total cost of installing RE technologies while satisfying some predetermined constraints that include demand and supply, RE potential, area and system reserve requirement. To this end, three different scenarios, namely prospective off-grid, on-grid, and all-off-grid are introduced. The first scenario aims at finding the optimal cost of installing RESs in order to improve electricity access at each off-grid installation location (a distribution company (DISCO) location with electricity access level below 50%). The second scenario optimizes cost of installing RESs for on-grid installation locations (DISCO locations (DLs) with electricity access level of 50% and above). The third scenario finds the optimal cost of installing off-grid RESs for all the DLs. Linear optimization technique is used to solve the problem. The results show that the total installation costs of the first and second scenarios (which means having off-grid installations for some DLs and having on-grid installations for other DLs) are $97.46 billion and $114.03 billion respectively, with a total cost of $211.49 billion. On the other hand, the result of third installation scenario (only off-grid installations for all DLs), is found to be $244.33 billion. These results reveal that the combination of off-grid and on-grid installations (first and second scenarios) has the minimum installation cost, for the case study of Nigeria. As the framework presented in this study is used to provide the minimum RE related total installation cost and related RE planning in Nigeria, it can also be useful for other countries or regions considering RE planning.
Unit Commitment (UC) requires the optimization of the operation of generation units with varying loads, at every hour, under different technical and environmental constraints. Many solution techniques were developed for the UC problem, and the researchers are still working on improving the efficiency of these techniques. Particle swarm optimization (PSO) is an effective and efficient technique used for solving the UC problems, and it has gotten a considerable amount of attention in recent years. This study provides a state-of-the-art literature review on UC studies utilizing PSO or PSO-variant algorithms, by focusing on research articles published in the last decade. In this study, these algorithms/methods, objectives, constraints are reviewed, with focus on the UC problems that include at least one of the wind and solar technologies, along with thermal unit(s). Although, conventional PSO is one of the most effective techniques used in solving UC problem, other methods were also developed in literature to improve the convergence. In this study, these methods are grouped as extended PSO, modified PSO, and PSO with other techniques. This study shows that PSO with other techniques are utilized more than any other methods. In terms of constraints, it was observed that there are only few studies that considered Transmission Line (TL), Fuel (F), Emission (E), Storage (St) and Crew (Cr) constraints, while Power Balance (PB), Generation limit (GL), Unit minimum Up or Down Time (U/DT), Ramp Up or Ramp Down Time (R-U/DT) and system Spinning Reserve (SR) were the most utilized constraints in UC problems considering wind/solar as a renewable source. In addition, most of the studies are based on a single objective function (cost minimization) and, few of them are multi-objective (cost and emission minimization) based studies.
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