• Energy Research

The water system management problem has been widely investigated. However, the interdependencies between water and energy systems are significant and the effective co-optimization is required considering strong interconnections. This paper proposes a two-stage distributionally robust operation model for integrated water-energy nexus systems including power, gas and water systems networked with energy hub systems at a distribution level considering wind uncertainty. The presence of wind power uncertainty inevitably leads to risks in the optimization model. Accordingly, a coherent risk measure, i.e., conditional value-at-risk, is combined with the optimization objective to determine risk-averse operation schemes. This two-stage mean-risk distributionally robust optimization is solved by Bender's decomposition method. Both the day-ahead and real-time operation cost are minimized with an optimal set of scheduling the multi-energy infrastructures. Case studies focus on investigating the strong interdependencies among the four interconnected energy systems. Numerical results validate the economic effectiveness of IES through optimally coordinating the multi-energy infrastructures. The proposed model can provide system operators a powerful two-stage operation scheme to minimise operation cost under water-energy nexus considering risk caused by renewable uncertainties, thus benefiting customers with lower utility bills.

Proper selection of electric vehicle (EV) path will be helpful to improving the travel efficiency of EV users and alleviate their difficulties in charging during peak hours. In this context, a personalized fast-charging navigation strategy based on mutual effect of dynamic queuing is proposed. First, an effective charging navigation system is presented to enable the integration of EV information terminals, fast-charging stations (FCSs), intelligent transportation system, and information processing center (IPC). Next, by incorporating the real-time mutual effect of dynamic queuing as well as considering the priority reservation cost of the EV drivers who reserve charging priority before others, a dynamic reservation-waiting queue model is established. After that, on the basis of the above model, the coupling relations of the criteria that may affect the charging experience are investigated for the first time and the charging navigation plans in IPC are optimized for diverse EVs. Finally, the validity of the method is verified by conducting the simulation under the participation of 2250 EVs in the urban areas of a city. Results show that the proposed charging strategy will increase charging satisfaction on average by more than 10.9% in all analyzed cases. Additionally, the navigation can save the charging cost of EV owners while also improve the operation efficiency of FCSs.

Due to an imminent fossil energy crisis and environmental pollution, renewable energy, such as photovoltaics, has been vigorously developing. However, the output of photovoltaic energy has strong volatility and intermittency. Thus, the photovoltaic generation system cannot constantly meet the load demand. To address this problem, a virtual power plant with hydro-photovoltaic-thermal generation is proposed in this paper. This virtual power plant utilizes the complementary characteristics of the output of the power sources to ensure a smooth and stable total output curve, and the power supply quality of the virtual power plant is improved. Further, the nonlinear operating cost model of the virtual power plant, with output changing over time, is established on the weighted output of hydro, photovoltaic, and thermal power; then, the corresponding marginal cost model of the virtual power plant is obtained. In the electricity market, three typical mid- to long-term electricity decomposition methods based on average, tracking load and spot price are constructed, and the spot price is predicted by the auto regressive moving average model (ARIMA) model, while the relationship between the spot price and the marginal cost of the virtual power plant is obtained; the marginal cost could also be adjusted based on the ARIMA model. Based on above factors, the sizing model of the virtual power plant is established, considering investment and complementary benefits. Finally, a case study is undertaken, where the sizing scheme for the increasing local load in the typical scenarios of the planning year and the corresponding annual rate of return are obtained. Sensitivity analysis of the influence for the above factors on the sizing of the virtual power plant is carried out. The optimal ratio of mid- to long-term electricity and its decomposition methods, as well as the capacity of the virtual power plant and the sizing ratio of hydropower, photovoltaic, and thermal power are obtained.

Abstract Wind power generation rapidly grows worldwide with declining costs and the pursuit of decarbonised energy systems. However, the utilization of wind energy remains challenging due to its strong stochastic nature. Accurate wind power forecasting is one of the effective ways to address this problem. Meteorological data are generally regarded as critical inputs for wind power forecasting. However, the direct use of numerical weather prediction in forecasting may not provide a high degree of accuracy due to unavoidable uncertainties, particularly for areas with complex topography. This study proposes a hybrid short-term wind power forecasting method, which integrates the corrected numerical weather prediction and spatial correlation into a Gaussian process. First, the Gaussian process model is built using the optimal combination of different kernel functions. Then, a correction model for the wind speed is designed by using an automatic relevance determination algorithm to correct the errors in the primary numerical weather prediction. Moreover, the spatial correlation of wind speed series between neighbouring wind farms is extracted to complement the input data. Finally, the modified numerical weather prediction and spatial correlation are incorporated into the hybrid model to enable reliable forecasting. The actual data in East China are used to demonstrate its performance. In comparison with the basic Gaussian process, in different seasons, the forecasting accuracy is improved by 7.02%–29.7% by using additional corrected numerical weather prediction, by 0.65–10.23% after integrating with the spatial correlation, and by 10.88–37.49% through using the proposed hybrid method.

The “Power System Economics: Design and Analysis” for students majoring in electrical engineering is a graduate course to teach the basic concepts. The analysis methods and basic concepts of economic problems involved in electric power are of great significance to help students understand the content of economics of electric power system. This paper reforms and redesigns the teaching methods and teaching forms through the combination of curriculum theory and programming practice to improve the innovation and creativity of students. The students could share and show their achievement through their own designs, such as self-designed small games and WeChat small procedures, and the value of this course is greatly enhanced compared to the traditional course.

Abstract The uncertainty of wind generation brings risk to power grid due to the variability and intermittency of wind. One promising technique to address challenge is deploying hybrid energy storage system (HESS) in wind energy conversion system to shape the wind power output by coordinating the operation of multi-type storage devices. In this paper, a multi-objective operation model of HESS based on dynamic wavelet decomposition (DWD) is presented. The model is characterized by two novelties: i) Life-cycle cost of storage devices and smoothness performance of wind output are simultaneously considered in the objective; ii) Parameters of wavelet analytics need to be optimally determined in a predictive control scheme. An improved NSGA-II is designed to provide efficient solution by analyzing Pareto frontier. A realistic case is studied to validate the presented method.

AbstractIn this article, a structure optimization strategy is designed for the faulted distribution system with distributed generation. The strategy is composed of two stages: the island partition and the remaining network reconfiguration. In the first stage, single-source electrical betweenness is proposed, and a partition model is built on the basis of variable network structure characteristics and flexible load features. Then binary decision method has been introduced to transform the original partition problem into a “satisfiability problem,” which can be solved in two steps, and the initial partition results are obtained using the implicit enumeration method, followed by static survivability check, interruptible load modification, and reactive compensation calculation. In this manner, the final scheme for the island partition is obtained. After that, based on the ant colony algorithm, the remaining network is reconstructed in the second stage. The effectiveness of the proposed strategy is verified by...

AbstractWith the emergence of distributed energy resources (DER) and prosumers in the distribution networks, the traditional centralised operation structure has transformed into the decentralised operation and transaction structure, which is regarded as the transactive energy market. Furthermore, the planning problem in the distribution network is deeply affected by the transactive energy market. First, the literature and studies on distribution network planning with DERs are reviewed. Moreover, the multi‐stakeholder operation and planning framework under the transactive energy market are analysed. The transactive energy market provides a peer‐to‐peer (P2P) transaction for third‐party prosumers. Several techniques for multi‐stakeholders planning and P2P transaction are introduced. Finally, a tri‐layer distribution network expansion planning (DNEP) framework integrated with virtual P2P transactions is proposed and analysed to accommodate uncertainties and postpone investment. The key technology and difficulties are also discussed.