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Recent times have seen the emergence of prosumers with undispatchable renewable onsite generators, which can complicate operational planning of grids. The complication can be exacerbated when prosumers have the leeway to export excess generation to the grid, which may necessitate the development of a new paradigm for the operational planning of prosumer grids. In this paper, a computationally tractable robust microgrid operational dispatch model that uses diesel generators, a battery, and interruptible loads to handle uncertainty in prosumer generation is proposed. Using the modified version of a microgrid in Guangdong Province, China, the CPLEX solver in the Advanced Interactive Multidimensional Modeling System environment is used to validate the effectiveness of the proposed model. The proposed robust model yields a higher objective function value than its deterministic counterpart; however, it guarantees system reliability under any realization of prosumer generation within specified bounds, which the deterministic model cannot guarantee. Further analysis shows that the optimal objective function value increases with the uncertainty level of prosumer generation. [ABSTRACT FROM AUTHOR]

In composite expansion planning, improving the efficiency and power quality of power supplied from Renewable Energy Sources (RES) is highly essential. Therefore, this paper focuses on developing an optimal power flow optimization model for minimizing power loss and harmonics emanating from RES with emphasis on reducing their impact on the Locational Marginal Prices. In order to assess the magnitude of harmonics, grid modelling and simulation with RES such as wind and solar energy were carried out using the Electrical Transient Analyzer Program 12.6.0 software. The proposed mixed integer nonlinear programming mathematical model was solved using the Outer Approximation Algorithm solver in the advanced interactive multidimensional modelling system, and the efficiency of the model was tested on the modified IEEE 6 bus and 24 bus system. The results obtained from simulations reveal the efficiency of the proposed model in terms of effective cost reduction, nodal marginal price reduction, minimization of harmonic losses, and additional lines in the power system network. [ABSTRACT FROM AUTHOR]

The uncertainty introduced by intermittent renewable energy generation and prosumer energy imports makes operational planning of renewable energy-assisted prosumer microgrids challenging. This is due to the difficulty in obtaining accurate forecasts of the energy expected from these renewable energy sources and prosumers. Operators of such microgrids therefore require additional grid-balancing tools to maintain power supply and demand balance during grid operation. In this paper, the impact of demand response aggregators (DRAs) in a prosumer microgrid is investigated. This is achieved by developing and solving a deterministic mathematical formulation for the operational planning of the grid. Also, taking a cue from CAISO's proposed tariff revision which allows the state-of-charge of non-generator resources (like storage units) to be submitted as a bid parameter in the day-ahead market and permits scheduling coordinators of these resources to self-manage their energy limits and state-of-charge, the proposed formulation permits prosumers to submit the battery energy content as a bid parameter and self-manage their battery energy limits. Furthermore, a robust counterpart of the model is developed. Both formulations are constrained mixed integer optimization problems which are solved using the CPLEX solver in the Advanced Interactive Multidimensional Modelling System environment. The results obtained from tests carried out on a hypothetical prosumer microgrid show that the operating cost of the microgrid reduces in the presence of DRAs. In addition, the storage facility owner may benefit from self-managing its energy limits, but this may cut the amount of grid-balancing resource available to the microgrid operator, thereby increasing the operating cost of the microgrid. [ABSTRACT FROM AUTHOR]