Risk‐constrained energy management of PV integrated smart energy hub in the presence of demand response program and compressed air energy storage

Abstract

Multi-carrier energy systems create new challenges as well as opportunities in future energy systems. One of these challenges is the interaction among different energy hubs' facilities and various operational parameters on the scheduling of the energy hub systems. This paper deals with the problem of optimal scheduling of smart residential energy hub (SREH) considering the different uncertain parameters. The effect of the market prices, demands and solar radiation uncertainties on the SREH scheduling problem is characterised through a risk-constrained two-stage stochastic programming model. The objective of the proposed scheduling problem is to determine the least-cost 24 h operation of the facilities that would cover the cooling, thermal and electrical demands. The Monte Carlo simulation method is applied to model the inaccuracies of solar radiation, energy demands, and electricity market prices. Additionally, a proper scenario-reduction algorithm is employed to reduce the number of scenarios and simulation burden. The proposed approach evaluates the impacts of different values of risk aversion parameter and the utility of the demand response program on the optimal solution of the proposed PV integrated SREH scheduling. Finally, an illustrative example is provided to confirm the efficiency and the applicability of the proposed approach. DR participation factor of demand response program Demand E, ADR amount of demand after applying demand response program Demand E, TDR amount of increased demand Demand E, shifted shifted demand from other hours TD percentage of increased demand η s auxiliary variable which is used to compute the CVaR ζ value at risk

Natural gas unavailability, price uncertainty, and emission reduction policy in stochastic programming‐based optimal bidding of compressed air energy storage and wind units

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Energy management strategy for a short‐route hybrid cruise ship: an IGDT‐based approach

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Optimal Operation of Integrated Energy System Based on Exergy Analysis and Adaptive Genetic Algorithm

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