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The virtual power plant (VPP) plays an important role in managing distributed energy by integrating renewable energy sources, energy storage systems and dispatchable loads. It can not only provide peak regulation services as good flexible resources, but also participate in the electricity market for additional profit. This paper presents a multimarket model to develop an optimal bidding strategy for VPP. To enhance the effectiveness of demand response, a fixed time of use price is converted into a dynamic response price. The integrated consumption satisfaction is quantified from both comfort and economy perspectives. Multi-objective optimization is carried out to maximize market profit of VPP as well as consumer satisfaction. The results show that: (1) Compared to time of use prices, VPP's profit and consumers' satisfaction level increased by 12.46% and 3.26% respectively under dynamic response prices. (2) The increase in the market profit of VPP is accompanied by a gradual decline in integrated consumption satisfaction. There are two inflection points in the process of decline, occurring at satisfaction levels of 1.01 and 0.98 respectively. (3) The multi-objective optimization strategy can achieve a win-win situation for both its operator and the internal consumers. • An optimal bidding strategy for VPP in multimarket is developed. • A dynamic response price machoism is proposed based on renewable energy output. • Consumers' satisfaction is comprehensively considered by comfort and economy. • The profit and satisfaction are in equilibrium by multi-objective optimization. [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]

Developing clean energy power generation is one of the main strategies to promote a sustainable economy. With the development of clean coal power technology, it is necessary to make full use of existing power generation resources instead of blindly building renewable power plants. For this reason, a dispatching model based on renewable energy forecasting errors is proposed in this paper to analyze the operation of the existing power supply. The contributions of this paper include a comprehensive forecasting error model, constructed to introduce wind and photovoltaic (PV) power forecasting errors into the dispatching system, as well as a dynamic spinning reserve (SR) model, constructed based on conditional value at risk, which analyses the SR model at different risk levels. An adaptive analysis model is also introduced to verify stability when additional errors occur in both the renewable energy output and the load demand. The optimization model was applied to the auxiliary power dispatching system of the Tianzhong ±800 kV ultra-high voltage direct current transmission channel in Xinjiang. The results show that (1) renewable energy forecasting errors have a significant effect on the SR. By separately constraining the SR, the total SR is reduced by 6.59%; (2) through the optimization of the SR, the output ranges of the thermal power unit are expanded, and the utilization rate goes up to 73.55%; (3) it is important to set an appropriate risk level when dispatching decision making. Setting low-risk levels will make the power system unable to deal with sudden failures, whereas setting high-risk levels will limit the effective use of renewable energy. • A convolution formula was used to determine the comprehensive forecasting error distribution. • A dynamic spinning reserve model was constructed based on conditional value at risk. • Spinning reserve was divided into two parts and separately constrained. • An adaptability analysis model was used to verify the applicability of the optimization dispatching model. [ABSTRACT FROM AUTHOR]

Summary: This paper considers the co‐optimization operation problem of the multiple micro energy grids (MEGs), and proposes a novel concept of the flexible boundary. Then, a three‐level co‐optimization model of reconfiguration, dispatching, and reserve is designed considering different time scales. Furthermore, an improved ant colony algorithm based on the information entropy and the chaotic search is proposed. The Shenzhen international low‐carbon park in China is selected as an example. The results show that: (a) The capacity configuration scheme considering the flexible boundary conditions could decrease the reserve capacity of power, heating, and cooling from the upper energy grid, namely, 75%, 50%, and 75%, and delay 537 × 104¥ the investment cost of the new capacity by utilizing the complementary characteristics between different MEGs. (b) The proposed three‐level co‐optimization model could establish the multi‐level optimal cooperative operation schemes of multi‐MEGs and decrease the reserve power from the upper energy grid and incentive‐based demand response. Among them, UPG provides MEG 1, MEG 2, and MEG 3 with cooling load reserve capacity reduction of 53.95, 85.44, and 38.3 kw h. The positive reserve provided by IBDR for MEG 1, MEG 2, and MEG 3 decreased by 30.53, 20.21, and 52 kW h. (c) The proposed improved ant colony algorithm can consider the operational characteristics of each energy entity in different stages of multi‐MEGs and obtain the global optimal operation scheme. Compared the traditional ant colony algorithm, the average convergence times decrease by 18% and the optimization degree of the objective value increase by 12.38%. (d) The sensitivity analysis shows the conditional value at risk method can formulate the optimal dispatching schemes of multi‐MEGs according to the risk attitudes of decision makers. When confidence degree is between 0.3 and 0.8, the decision‐makers have a high‐risk sensitivity and are more willing to avoid uncertain risks of wind power plant and photovoltaic power. Overall, the proposed model and solution algorithm could achieve the optimal operation strategy of the micro energy grids. [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]