Abstract
Multi-energy systems (MES) allow various energy forms, such as electricity, gas, and heat, to interact and achieve energy transfer and mutually benefit, reducing the probability of load cutting in the event of a failure, increasing the energy utilization efficiency, and improving the reliability and robustness of the overall energy supply system. Since energy storage systems can help to restore power in the case of failure and store the surplus energy to enhance the flexibility of MES, this work provides a methodology for reliability optimization, considering different energy storage configuration schemes under weather uncertainties. First of all, a reliability evaluation model of a multi-energy system under weather uncertainties based on a sequential Monte Carlo simulation is established. Then, the reliability optimization problem is formulated as a multi-objective optimization problem to minimize the reliability index, SAIDI (system average interruption duration index), and the reliability cost. Finally, a case study implemented on a typical MES layout is used to demonstrate the proposed methodology. A comparative analysis of three widely adopted multi-objective metaheuristic algorithms, including NSGA-II (non-dominated sorting genetic algorithm II), MOPSO (multiple objective particle swarm optimization), and SPEA2 (strength Pareto evolution algorithm 2), is performed to validate the effectiveness of the proposed method. The simulation results show that the NSGA-II algorithm leads to better optimal values and converges the fastest compared to the other two methods.
Highlights
Multi-energy systems refer to a new, unified view of energy systems formed by the coupling of cooling and heating in gas and electricity supplies during the transmission and distribution processes, which has the potential to make energy monitoring, generation, consumption, and maintenance more efficient
To find the optimal location of the storage device in the Multi-energy systems (MES) at the lowest possible cost to realize the highest reliability under weather uncertainty, the reliability optimization problem is formulated as a multi-objective problem
This paper proposes a methodology for reliability optimization in a multi-energy system with storage devices considering the weather uncertainties using non-dominated sorting genetic algorithm (NSGA)-II, MOPSO, and SPEA2
Summary
Multi-energy systems refer to a new, unified view of energy systems formed by the coupling of cooling and heating in gas and electricity supplies during the transmission and distribution processes, which has the potential to make energy monitoring, generation, consumption, and maintenance more efficient. Multi-energy systems can take full advantage of the interaction between various forms of energy sources to improve system economics, increase system flexibility, and enhance system reliability. It is critical to assess and improve MES reliability effectively and accurately. Multi-energy system reliability is defined as the extent to which the performance of the components in a bulk system provides the customer with electrical, thermal, and gas energy within agreed criteria [1]. Besides assessing MES reliability, improving it is essential, as it can enhance MES stability and provide energy to the customers more efficiently [2]. MES reliability can be improved by enhancing its flexibility through the optimized use of energy storage systems, which can compensate for the volatility and the uncertainty of renewable generation, such as wind and PV power generation. This study explores how to optimize the energy storage configuration schemes to optimize MES reliability
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