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Multi-energy systems (MES) make it possible to supply one load by several energy infrastructures, thus increasing the reliability of energy supply compared to separate energy systems (SES). To accurately and efficiently evaluate the reliability of MES, this paper proposes a fast MES reliability evaluation method using multi-parametric linear programming (MPLP). The energy conversion, transmission and storage in MES are compactly and linearly descried by energy hub model, making the load curtailment optimization problem of MES a linear programming (LP) problem. MPLP is introduced to avoid computational burdens caused by iteratively solving LP problems for a large number of samples during the evaluation process. Case studies are conducted on both imaginary MES and SES. The results show that the proposed method improves the evaluation efficiency by an order of magnitude compared to the traditional LP method and the reliability of energy supply is distinctly improved due to energy integration.

With the increasing penetration of variable renewable generation in power systems., planning for the effects of variability will become more important. This paper analyzed the flexibility metric that reflects the flexibility variability in its time series and the flexibility of a system to manage periods of variability. The time series of system flexibility demand and supply scenarios are established based on the proposed flexibility metric. The timing characteristics of flexibility requirements and flexibility resources are integrated into the traditional coordinated DG and network planning through a bi-level planning model. The upper-level model is a multi-objective model aimed at maximizing the balance between the system flexibility demand and supply., and the social and economic benefits. The optimal scheduling strategies for various flexibility resources can be achieved by the multiobjective particle swarm optimization algorithm based on meshing. The lower model optimizes the location of DG and demand side loads., and the line expansion decision according to previously constructed flexibility requirement scenarios and flexibility resource deployment strategies. Through this new bilevel planning method., available flexibility providers from the resources., network., loads and storage are considering into the planning of distribution system.

The fluctuations and forecasting errors of wind power require large amount of flexibility in power system operation. The flexibility is often provided by conventional thermal generating units. This paper focuses on the variations in operating cost caused by integration of an increasing amount of wind power in thermal generation system. A new chronological production simulation platform utilized for this analysis is described. Different phenomena, such as the efficiency loss at low load level, the ramping cost and the start-stop cost are modeled to achieve a more accurate estimate of the extra cost of balancing wind power using thermal generation. A modified version of IEEE RTS-79 test system and a model of the Jiangsu (China) provincial power system are used to demonstrate the proposed method. The results provide a reference for setting reasonable tariffs for recovering the extra cost incurred by thermal generating units.