• Energy Research
• other engineering and technologies close
• 7. Clean energy close
• 13. Climate action close
• 8. Economic growth close

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

[EN]A systematic approach is developed for the conceptual optimal design of biomethane production via carbon capture. A hybrid heuristic-mathematical procedure is proposed to determine the optimal technology and operating conditions. The heuristic step consists of a literature-based screening of the available technologies. After the prescreening stage, the technologies selected are amine absorption, pressure swing adsorption (PSA), and membrane separation. The mathematical stage is composed of two steps. First, different alternatives for each technology are modeled based on first principles and rules of thumb. These models are used to select the optimal configuration for each process considered. Second, a superstructure model for biomethane production is developed integrating the pre-selected upgrading technologies to select the optimal process, as well as to determine the optimal operating conditions. Four waste sources are analyzed: cattle manure, swine manure, municipal food waste, and sludge. The results suggest that the best amine is diethanolamine (DEA), the best membrane material is the polyimide, and the suggested zeolite is 13X among the ones studied. Finally, among the three technologies, the overall results show that carbon capture using a PSA system using zeolite 13X results in lower production and investment costs, but very close to the use of membranes. The results indicate that food waste shows the lowest production cost for biomethane 0.36 €/Nm3, due to the largest organic matter content, whereas the investment costs are 67 M€, considering a biogas production rate of 0.035 kg of biomethane per kg of waste and the processing of 311 kt/yr of food waste. Credits or incentives are still needed for biomethane to be competitive with fossil natural gas. Junta de Castilla y León y USAL

In order to exploit renewable energies from tidal stream, tandem propellers of a unique counter-rotating type horizontal-axis tidal turbine was firstly designed based on the blade element momentum (BEM) theory. And then a multi-objective numerical optimization method coupled the response surface method (RSM) with the genetic algorithm (GA) was employed to obtain desirable blade profiles. The front blade pitch angle distribution was taken as optimization variable in this paper, as it plays an important role in affecting the inlet conditions of the rear blade. The numerical results show that both optimization objectives of power coefficient and thrust coefficient can be significantly improved. It was verified that the performance of the power unit with the optimized blades increases obviously by optimizing the pitch angle.

As the US biofuels market struggles in the wake of a drought crisis, conditions in Europe have improved. Major barriers to growth remain though, says Toby Cohen.

Abstract In this study, we develop indices for the overall technical efficiency (OTE) and energy-saving target ratio (ESTR) using data envelopment analysis (DEA) to calculate the relative efficiency and energy-saving potential of 30 provinces in China from 1997 to 2014. The results are as follows: (1) the OTE of China is 79.187%, indicating that there is 20.813% potential for improvement. The OTE exhibits decreasing efficiency values from the coastal areas to the inland areas and has clear geographical relationships. The average values of OTE in the east, midland and west are 0.932, 0.694 and 0.703. Theoretically, the total energy savings of CE, HE, ME and BE are 11080.60PJ, 5124.71PJ, 4729.24PJ and 6797.39PJ. (2) Regarding CE, HE, ME and BE, the provinces with the highest comprehensive ranks are Henan, Shanxi, Shaanxi, and Gansu, which simultaneously have the greatest energy-saving potentials and energy-saving targets. (3) The HE has the largest average ESTR of 38.357% and the values for BE, CE, and ME are 25.759%, 23.874%, and 22.143%, respectively. The CE category is the greatest in total energy savings (40.171%), which is followed by BE (24.150%), HE (18.384%), and ME (17.293%).

This paper deals the study of the lead-acid behavior and its modelling based on the Kinetic Battery Model. Results of experimental tests are used to realize the analysis and to estimate the model parameters. These last can serve for prediction and estimation of the battery lifetime according to the actual operating conditions.

The present paper develops a methodology to choose the best connection scheme for traction substations of a Massive Electrical Railway System (MERS) and distribution substations in urban areas using graph theory and economical optimization.

In this paper, we address the long-term system's requirement reserve sizing due to the high-level of variable renewable energy (VRE) sources penetration, inside the expansion planning model. The increase in the insertion of this kind of energy source will also bring an increase in the reserve requirements. A higher requirement will be translated into additional costs to the system since the system operator will need to allocate generators for reserve purposes. The VRE sources implicitly cause these costs, so besides the investment cost, the expansion planning models should consider those costs on the expansion decision process. The methodology proposed here aims to provide a probabilistic and dynamic evaluation of the forecast errors of VRE sources generation, translating these errors into the system's requirement reserve. This evaluation is done inside the expansion planning optimization model, treating the reserve requirement as an endogenous variable. Finally, a real case study of the Mexican system is presented, so that we can analyze the results of the methodology and the impacts of considering the reserve requirement along with the expansion planning decision.

Abstract Transportation de-carbonization is a complex problem involving the economy, population, technology and environment. Implementing the pathway simulation based on systematic methods will help to optimize the transportation sustainability plan. This study’s key motivation is that earlier research ignored the relationship between driving factors and the transmission process. To quantitatively identify the path and process of emission reduction, a hybrid system dynamics STIRPAT-SD model is proposed to explore the transportation optimization’s de-carbonization ability. This study fully considers the composition of elements and subsystems based on the STIRPAT theoretical model and visually shows the system’s feedback relationship. Transportation structural and technical optimization scenarios are set to identify the threshold reduction paths. It is found these optimization strategies have significant de-carbonization effects. And transportation structure policy has the highest de-carbonization efficiency, the emission intensity decreased by 9.1% under the TSS2 scenario (Transportation structure scenario). This study proposes a novelty model combining dynamic simulating processes with a significantly theoretical model to improve simulation and factor composition accuracy. And the joint scenario setting identifies the most effective de-carbonization pathway and clarifies the threshold of all possible pathways. Research findings can effectively track, test, predict the achievement of policy goals, and provide policy optimization references for the sustainable development related to the transportation system in practice.