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However, this type of information is not available before the end of the whole period in reality.Thus, in this thesis, we also develop a simple online algorithm where the knowledge of the future demand information is not necessary.As a strategy to deal with the intermittent RES and provide demand response benefits in smart grid, integrating energy storage in the system introduces new features to the optimal power flow (OPF) problem.
We investigate the energy storage dynamics under different problem settings and verify that the distributed algorithms can converge fast to the global optimal solution by numerical simulations in IEEE test systems.
Although these decomposition algorithms are very efficient, they are offline algorithms, where the future demand information is needed.
In smart grid, the penetration of two-way flows of electricity and information makes it capable of integrating distributed renewable energy sources (RES) and a large number of demand side users much more effectively.
However, as a crucial part of smart grid, the renewable energy is intermittent and very difficult to predict, which then results in the inconsistent power in the grid.
We first formulate it as a dynamic nonconvex OPF problem.
Then we propose an efficient second order cone programming (SOCP) relaxation for this nonconvex problem.We use the competitive ratio to show the theoretical performance of the online algorithm.Through extensive simulations in the IEEE 14-bus system, we show that the algorithm can converge fast to the optimal solution.Also, to manage voltage stability in the absence of communication, a Hamiltonian approach is implemented for the voltage source rectifier.This approach resulted in a highly stable voltage and a fast response to large step changes.Moreover, the game theoretical approach is found to have poor performance in the absence of shared load information among players.It is determined that the localized optimizers should be removed to reduce cost and that the operating condition should be perturb starting from the most recently available power flow calculation or starting from the nominal value.If you are an IET member, log in to your account and the discounts will automatically be applied.Microgrid structures allow for more efficient utilization of renewable resources as well as autonomous operation.The new MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain.A clustering algorithm to manage the size of the Pareto-optimal set is imposed.