Capacity Expansion of High Renewable Penetrated Energy Systems Considering Concentrating Solar Power for Seasonal Energy Balance

With the increasing proportion of variable renewable energy which owns fluctuation characteristics and the promotion of the Clean Heating policy, the seasonal energy imbalance of the system has been more and more challenging. There is a lack of effective means to mitigate this challenge under the background of gradual compression of the traditional thermal unit construction. Concentrating solar power (CSP) is a promising technology to replace thermal units by integrating emergency boilers to cope with extreme weather, and can meet long-time energy balance as a seasonal peak regulation source. In this paper, we propose a long-term high-resolution expansion planning model of the energy system under high renewable penetration which integrates CSP technology for seasonal energy balance. With the projection to 2050, by taking the energy system in Xinjiang province which is a typical area of the Clean Heating project with rich irradiance as a case study, it shows that the optimal deployment of CSP and electric boiler (EB) can reduce the cost, peak-valley difference of net load and renewable curtailment by 8.73%, 19.72% and 58.24% respectively at 65% renewable penetration compared to the base scenario.Comment: 17 pages, 13 figure

Collaborative planning and optimization for electric-thermal-hydrogen-coupled energy systems with portfolio selection of the complete hydrogen energy chain

Under the global low-carbon target, the uneven spatiotemporal distribution of renewable energy resources exacerbates the uncertainty and seasonal power imbalance. Additionally, the issue of an incomplete hydrogen energy chain is widely overlooked in planning models, which hinders the complete analysis of the role of hydrogen in energy systems. Therefore, this paper proposes a high-resolution collaborative planning model for electricity-thermal-hydrogen-coupled energy systems considering both the spatiotemporal distribution characteristics of renewable energy resources and the multi-scale bottom-to-top investment strategy for the complete hydrogen energy chain. Considering the high-resolution system operation flexibility, this paper proposes a hydrogen chain-based fast clustering optimization method that can handle high-dimensional data and multi-time scale operation characteristics. The model optimizes the geographical distribution and capacity configuration of the Northeast China energy system in 2050, with hourly operational characteristics. The planning optimization covered single-energy devices, multi-energy-coupled conversion devices, and electric-hydrogen transmission networks. Last but not least, this paper thoroughly examines the optimal portfolio selection of different hydrogen technologies based on the differences in cost, flexibility, and efficiency. In the Pareto analysis, the proposed model reduces CO2 emissions by 60% with a competitive cost. This paper provides a zero-carbon pathway for multi-energy systems with a cost 4% less than the social cost of carbon $44.6/ton, and the integration of the complete hydrogen energy chain reduces the renewable energy curtailment by 97.0%. Besides, the portfolio selection results indicate that the system favors the SOEC with the highest energy efficiency and the PEMFC with the fastest dynamic response when achieving zero-carbon emissionsComment: 32 pages, 17 figure

Parameter design of coal pillar in highwall mining under action of dynamic-static load

In view of the application of end slope shearer mining technology to recover a large amount of residual coal, the determination of reasonable width of supporting coal pillar is a key factor whether it can be safely and efficiently popularization and application, especially considering the influence of blasting vibration on the stability of supporting coal pillar. Based on the southern end slope at the open-pit coal mine of Pingshuo, field vibration test, theoretical analysis and numerical calculation were used to study the web pillar stability in open-pit highwall mining and its parameter design under the action of triangular load and blasting vibration on the side slope. Based on the theory of limit balance and the mutation theory, the stress distribution at the coal pillar was analyzed, combined with Mohr-Coulomb failure criterion. Besides, the ultimate strength function expression of coal pillar under the influence of mining height, mining width, load stress of overlying strata, cohesion and internal friction angle of coal pillar is established. The calculation formula of the maximum allowable plastic zone width and rational width of web pillar under different safety reserve factor conditions are established. The three-dimensional simple harmonic vibration response model of the supported coal pillar was established, and the blasting parameters such as the amount of single shot, elevation difference and horizontal distance of the blast center were studied on the response of the maximum instantaneous dynamic stress of the coal pillar, which revealed the influence mechanism of the blasting dynamic load effect on the width and stability of the plastic zone of the supported coal pillar and proposed the design method of the parameters of the supported coal pillar under the blasting dynamic load. The results show that the blasting vibration has a greater influence on the stability of coal pillar, and the instantaneous maximum dynamic stress response of coal pillar under the blasting dynamic load is positively correlated with the amount of single shot, and negatively correlated with the elevation difference and horizontal distance. With the increase of the maximum instantaneous dynamic stress response of coal pillar, the width of plastic zone of coal pillar increases proportionally, and the safety factor of coal pillar decays in an approximately linear pattern. The width of coal pillar under dynamic-static load is determined to be 5 m, and its reasonableness is verified by engineering practice

Distributed photovoltaic short‐term power forecasting using hybrid competitive particle swarm optimization support vector machines based on spatial correlation analysis

Abstract In order to further improve the accuracy of distributed photovoltaic (DPV) power prediction, this paper proposes a support vector machine (SVM) model based on hybrid competitive particle swarm optimization (HCPSO) with consideration of spatial correlation (SC), for realizing short‐term PV power prediction tasks. Firstly, the spatial correlation analysis is conducted on the distributed PV stations. The k‐means clustering method based on morphological similarity distance improvement and mutual information function is used to select the best reference station and the best delay, which generates strongly correlated PV sequences. Then, a hybrid algorithm of particle swarm optimization (PSO) and sine cosine algorithm (SCA) in a competitive framework (HCPSO) is proposed, aiming to fuse the fast convergence capability of PSO algorithm with the global search capability of SCA algorithm, while enabling the algorithm to effectively handle high‐dimensional optimization problems based on a competitive mechanism. Finally, the HCPSO algorithm is combined with SVM algorithm, which expands the applicable scenarios of the SVM model and effectively improves the accuracy of PV short‐term prediction

Coordinated chance-constrained optimization of multi-energy microgrid system for balancing operation efficiency and quality-of-service

To enhance the flexible interactions among multiple energy carriers, i.e., electricity, thermal power and gas, a coordinated programming method for multi-energy microgrid (MEMG) system is proposed. Various energy requirements for both residential and parking loads are managed simultaneously, i.e., electric and thermal loads for residence, and charging power and gas filling requirements for parking vehicles. The proposed model is formulated as a two-stage joint chance-constrained programming, where the first stage is a day-ahead operation problem that provides the hourly generation, conversion, and storage towards the minimization of operation cost considering the forecasting error of photovoltaic output and load demand. Meanwhile, the second stage is an on-line scheduling which adjusts the energy scheme in hourly time-scale for the uncertainty realizations. Simulations have demonstrated the validity of the proposed method, i.e., collecting the flexibilities of thermal system, gas system, and parking vehicles to facilitate the operation of electrical networks. Sensitivity analysis shows that the proposed scheme can achieve a compromise between the operation efficiency and service quality.Published versio