Probabilistic operation cost minimization of Micro-Grid

• Published in: Energy (Oxford) 2018-04, Vol.148, p.1116-1139
• Main Authors: Sharma, Sharmistha, Bhattacharjee, Subhadeep, Bhattacharya, Aniruddha
• Format: Article
• Language: English
• Subjects: Algorithms; Batteries; Battery Energy Storage; Complexity; Computer simulation; Cost engineering; Distributed Generation; Energy efficiency; Energy sources; Energy storage; Influenza; Livestock; Micro-Grid; Optimization; Pricing; Probabilistic methods; Probability distribution; Renewable energy sources; Renewable resources; Smart grid technology; Soft computing; Statistical analysis; Swine; Swine influenza; Swine Influenza Model Based Optimization with Quarantine; Uncertainty; Whale Optimization Algorithm
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2018.01.164

In recent years due to the increasing integration of Renewable Energy Sources (RES) into the Micro-Grid (MG), necessity of Battery Energy Storage (BES) has increased quickly and size of BES plays vital role in this regard. Present paper aims to minimize total operation cost of MG in presence of BES of optimal size, by considering uncertainties present in the MG. Here, 2 m point estimate method (PEM) has been applied to model the uncertainties in load demand, market prices and available power from RES in the MG, as it is computationally efficient and reliable probabilistic method. Moreover, Gram-Charlier expansion is used to provide more accurate probability distribution of MG operation cost. Classical techniques may be applied here to solve the problem, but these techniques may increase complexity of the problem and hence may affect the accuracy. As evolvement of soft computing techniques are not restricted by the complexity of system model, therefore Swine Influenza Model Based Optimization with Quarantine (SIMBO-Q) and Whale Optimization Algorithm (WOA) have been applied here to minimize operation cost of MG. Simulation results obtained by SIMBO-Q and WOA prove the effectiveness of the algorithms. Here incorporation of BES of optimum size reduces operation cost of MG effectively. •The paper aims to minimize operation cost of Micro-Grid considering uncertainties.•The problem is solved by recently developed soft computing techniques.•Performance of algorithms has been compared to different soft computing techniques.•Results show minimum operation cost of Micro-Grid is achieved by proposed methods.•Here probabilistic approach provides more realistic and efficient result.