Search

Differential evolution (DE) is a heuristic global search algorithm based on population. It has exhibited great adaptability in solving continuous-domain problems, but sometimes suffered from insufficient local search ability and being trapped in local optimum when dealing with complicated optimization problems. To solve these problems, an improved differential evolution algorithm with population diversity mechanism based on covariance matrix (CM-DE) is proposed. First, a new parameter adaptation strategy is used to adapt the control parameters, in which the scale factor F is updated according to the improved wavelet basis function in the early stage and Cauchy distribution in the later stage and the crossover rate C R is generated according to normal distribution. The diversity of population and convergence speed are improved by employing the method above. Second, the perturbation strategy is incorporated into crossover operator to enhance the search ability of DE. Finally, the covariance matrix of the population is constructed, where the variance in the covariance matrix is used as indicator to measure the similarity between individuals in the population in order to prevent the algorithm from falling into local optimum resulted by low population diversity. The CM-DE is compared with the state-of-art DE variants including LSHADE (Tanabe and Fukunaga, 2014), jSO [1] , LPalmDE [2] , PaDE [3] and LSHADE-cnEpSin [4] under 88 test functions from CEC2013 [5] , CEC2014 [6] and CEC2017 (Wu et al., 2017) test suites. From the experiment results, it is obvious that among 30 benchmark functions from CEC2017 on 50D optimization, the CM-DE algorithm has 22, 20, 24, 23, 28 better performances comparing with LSHADE, jSO, LPalmDE, PaDE, and LSHADE-cnEpsin. For CEC2017 on 30D optimization, the proposed algorithm secures better performance on 19 out of 30 benchmark functions in terms of convergence speed. In addition, a real-world application is also used to verify the feasibility of the proposed algorithm. The experiment results validate the highly competitive performance in terms of solution accuracy and convergence speed. • A new parameter adaptation mechanism is proposed to adjust the scale factor F and crossover rate CR. The experiment results show that the new parameter adaptation mechanism improves the exploration ability of the proposed algorithm. • In order to prevent prematureness, a perturbation strategy is incorporated into the crossover strategy, which firstly constructs a new crossover operation between the mutant vector and target vector based on the t-distribution probability density function; secondly, the information of the outstanding individuals is used to guide the search direction. • By calculating the covariance matrix of the population, the variance in the covariance matrix is used to determine the diversity of individuals in the current population. In the iterative process, a counter is set to count the number of variances in each dimension that is less than the set condition. When the counter meets the predefined threshold, a simple competition mechanism is used to increase the diversity of the population by perturbing the t-distribution or the Cauchy distribution for all stagnant individuals. [ABSTRACT FROM AUTHOR]

• Establishing a dispatch model for integrated wind-photovoltaic-thermal power system. • Dynamic carbon emissions trading system applications in power market is considered. • Comprehensive benefits of five dispatch modes are compared. • Optimal mode was investigated using case study transmission project (China). To transmit renewable energy on-grid over a large-scale power transmission system, an optimal dispatch model for a multi-energy power generation system is essential. This paper proposed a multi-energy hybrid power dispatch model for an integrated wind-photovoltaic-thermal power system. We consider five different dispatch modes and a dynamic carbon emissions trading system. Design of the modes was based on dispatch objectives. Power dispatch was based on interactive planning of power units and carbon emissions trading. To compare the modes, a comprehensive benefit evaluation index for dispatching is established. The proposed model was applied to supporting power supply system of the Tianzhong ultra-high voltage direct-current transmission project in Xinjiang, China. The results confirmed that high-efficiency mode is an optimal dispatch mode for the power transmission system, and has the most significant benefits. The impact on the optimal mode of the renewable energy penetration rate and carbon emissions trading system, as the two main factors, were further investigated. It was found that high-efficiency mode could maximize existing renewable energy generation and reduce coal consumption and carbon emission used for power generation and has a positive effect on carbon reduction. However, initial quotas need to be controlled more strictly than prices. [ABSTRACT FROM AUTHOR]

Substituting renewable energy for coal power under the carbon neutrality goal is an inevitable path for power system transformation, while the high share of renewable energy leads to a rapid rise in system flexibility demand. Currently, coal-fired power is still one of the most economical and reliable large-scale flexible resources in China. Therefore, the issue of how to mitigate the conflict between cleanliness and flexibility for coal-fired power is urgent to be solved. Accordingly, this paper established an optimization framework for the retirement and technology adoption of coal-fired power units with high spatial-temporal resolution, and the regional carbon emission budget is estimated from a top-down perspective. Secondly, a dynamic carbon quota allocation method considering technological innovation and adoption is proposed. The carbon trading cost of the units is evaluated from a bottom-up perspective, to realize the interaction between the obligatory policy constraints of the top-level target and the flexible incentives of the market mechanism. Finally, the empirical analysis was conducted in the Beijing-Tianjin-Hebei region of China. The optimal solution achieved by proposed method results in a substantial 27% reduction in total costs while keeping the increase in carbon emissions below 3%. By analyzing the dynamic evolution path of coal and the scale of diffusion of multi-type technologies, the differences in the roles coal power assuming at various stages of decarbonization are discussed. The robustness of the model and the validity of the proposed method were verified by comparing the dynamic/static carbon quota allocation. Overall, this study provides an effective optimization model for investigating the low-carbon technology adoption timing for coal power in Beijing-Tianjin-Hebei region, and offers valuable insights for other coal-dominated emerging economies seeking for power system transformation roadmap in the forthcoming net-zero carbon age. • A decision-making optimization model of CCPs low-carbon technology is proposed. • A dynamic CET system with upper-lower layer interaction is introduced. • The proposed dynamic CET system results in 27% reduction in total costs. • The high-resolution data of coal power in Beijing-Tianjin-Hebei region are used. • The strategy to solve the conflict between cleanliness and flexibility is given. [ABSTRACT FROM AUTHOR]

The objective of the traditional dispatching optimization model is to find the most economical scheduling mode, while ignoring the efficient use of renewable energy. To properly arrange thermal power generation and renewable energy power generation, this paper constructs an optimization model of the combined wind–photovoltaic (PV)–thermal dispatching system under a carbon emissions trading (CET) mechanism. The contribution of this paper is twofold. First, a dispatching optimization model is proposed, which not only considers the total cost but also takes into account the impact of the renewable energy spillage rate on the dispatching system. As a factor affecting renewable energy consumption, a carbon emissions trading mechanism has also been introduced into the dispatching system. The second contribution is to develop a model for predicting the output of renewable energy generation. Then, the optimization model is applied to the auxiliary power dispatching system of the Tianzhong ±800 kV UHV DC transmission channel in Xinjiang. The results indicate that under a carbon emissions trading mechanism, thermal power generation will be limited by the carbon emissions cost, thereby reducing the total cost of the system. Optimizing the spillage rate increases the share of renewable energy in the dispatching system, resulting in a 3.5% reduction in the actual spillage rate. The proposed model alleviates the serious problem of electricity being abandoned in the existing scheduling mode and helps to realize economical low-carbon dispatching of the power system. [ABSTRACT FROM AUTHOR]