Abstract
Aiming at capacity optimization of an isolated microgrid, this paper establishes a bi-level capacity optimization model that considers load demand management (LDM) while comprehensively considering load and renewable generation uncertainties. The uncertainties in this paper are brought by the source and load on the same timescale, as well as by the different characteristics of uncertainty presented over different timescales. For long timescales, the problem of source/load random uncertainty is solved using the stochastic network calculus theory to meet the energy balance constraints. For short timescales, we primarily aim to resolve the problem of power balance at the operation level, considering the uncertainty of source/load prediction errors and the impact of LDM. Particularly, by controlling the interruptible and shiftable loads, the LDM can optimize load characteristics, reduce operation costs, and increase system stability. The bi-level optimization model established in this paper is analyzed with regard to energy and power balance constraints, and the proposed mixed integer linear programming (MILP) model is solved by utilizing the CPLEX solver to minimize the investment cost. A typical microgrid, comprising a wind turbine (WT), a photovoltaic panel (PV), a controllable micro generator (CMG), and an energy storage system (ESS), is taken as an example to study capacity optimization problems. The simulation results verify the rationality and effectiveness of the proposed model and method.
Highlights
A microgrid is a small-scale power distribution system composed of distributed energy, energy conversion devices, loads, and monitoring and protection devices, which can generally operate in grid-connected mode or in island mode
At the operation level, we develop controllable load models including an interruptible load and a shiftable load, and investigate the impact of load demand management (LDM) on the capacity planning for an isolated microgrid
Because there is a significant difference between the source and load prediction accuracies, the prediction errors of wind turbine (WT) and PV outputs are less than 30%, and the load demand prediction errors are less than 10%
Summary
A microgrid is a small-scale power distribution system composed of distributed energy, energy conversion devices, loads, and monitoring and protection devices, which can generally operate in grid-connected mode or in island mode. Reference [25] considers the flexibility of the DR to meet users’ comfort and applies a genetic algorithm (GA) and MILP simultaneously to solve two-stage optimization regarding utilities’ profits and customers’ satisfaction These studies do not consider the different characteristics of uncertainties presented by different sources and different timescales; LDM affects the operational characteristics of different types of power supplies at the operational level, which in turn affects the long-term capacity planning results of the system. For the stochastic uncertainty characteristics of source and load presentation for the longtimescale capacity planning problem, the stochastic network calculus theory is used to ensure energy balance in an isolated microgrid. The descriptions and models of each category are as follows
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