Summary
This paper presents a new stochastic operation scheduling model for microgrid in day‐ahead electricity market considering the forecast uncertainties of wind generations, microgrid's load, and locational marginal price of the point of common coupling, as well as the uncertainties pertaining to availability of generation units of the microgrid. The financial risk caused by these uncertainties is modeled by conditional value‐at‐risk criterion. The proposed approach is formulated as a risk‐minimizing two‐stage stochastic model based on mixed‐integer linear programming framework. This model minimizes the expected scheduling cost together with the cost of financial risk. The impacts of different uncertainty sources on the model's results in both grid‐connected and islanded operation modes are extensively studied. Additionally, higher effectiveness of the proposed stochastic model compared with common deterministic approach, regarding total operation cost and convergence behavior, is illustrated through an out‐of‐sample analysis.
including the URL of the record and the reason for the withdrawal request. Abstract1-This paper presents a new robust self-scheduling strategy for virtual power plants (VPPs) considering the uncertainty sources of electricity prices, wind generations, and loads. Multi-horizon information-gap decision theory (MH-IGDT) as a non-deterministic and non-probabilistic uncertainty modeling framework is proposed here to specifically model the uncertainty sources considering their various uncertainty horizons. Since each uncertain parameter tends to optimize its uncertainty horizon competitively for a particular value of the uncertainty budget, the proposed MH-IGDT model is formulated as a multi-objective optimization problem. To solve this multi-objective problem, enhanced normalized normal constraint (ENNC) method is presented, which can obtain efficient uniformly-distributed Pareto optimal solutions. The proposed ENNC includes augmented normalized normal constraint method and lexicographic optimization technique to enhance the search performance in the objective space. To address the unsolved issue of being risk-averse or riskseeker for a VPP in the market, a bi-directional decision-making approach is presented. This decision maker comprises an ex-ante performance evaluation method and a forward-backward dynamic programming approach to hourly find the best Pareto solution within the generated risk-averse and risk-seeker Pareto frontiers. Simulation results of the proposed self-scheduling strategy are presented for a VPP including dispatchable/non-dispatchable units, storages, and loads.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.