Life cycle planning of battery energy storage system in off‐grid wind–solar–diesel microgrid

Abstract

For off-grid microgrids in remote areas (e.g., sea islands), proper configuring the battery energy storage system (BESS) is of great significance to enhance the power-supply reliability and operational feasibility. This paper presents a life cycle planning methodology for BESS in microgrids, where the dynamic factors such as demand growth, battery capacity fading, and components' contingencies are modelled under a multi-timescale decision framework. Under a yearly timescale, the optimal DER capacity allocation is carried out to meet the demand growth, while the investment decisions of BESS are made periodically to yield the optimal sizing, type selection, and replacement plans of BESS during the entire lifetime of microgrid. Then, under an hourly time-scale, the long-term probabilistic sequential simulation is adopted to comprehensively evaluate the investment decisions and derive detailed operation indicators. Moreover, a decompositioncoordination algorithm is developed to address the presented planning model, which iteratively strengthens the feasible space of investment decision model by substituting the operation indicators until an acceptable sub-optimal solution is obtained. Case studies on a wind-solar-diesel microgrid in Kythnos Island, Greece, illustrate the effectiveness of the proposed method. This study provides a practical and meaningful reference for BESS planning in off-grid microgrids.

Optimal Sizing of Battery Energy Storage for Grid-Connected and Isolated Wind-Penetrated Microgrid

“…The formulated problem inn each Scenario is based on the overall cost of operation of the microgrid and the objective function is to minimize this cost. The objective function is expressed in (12). The optimization problems are solved using the linear programming and non-linear programming (quadratically constraint optimization) in GAMS software for Scenarios (1 & 2) and Scenario 3 respectively.…”

“…min.J = C WT + C d.gen + CMG ex + IC ESS (12) Furthermore the associated constraints are listed in the following subsections.…”

“…Moreover, the study discussed the implementation of cost-effective based on communication technology for future and real-world problems. In [12], a life cycle planning methodology of BESS in microgrids was presented and the optimal sizes of BESS were obtained under multi-scaled decision parameters to meet the demand growth. The authors in [13] find the optimal values of BESS for an islanded DC microgrid using an incremental cost approach while the authors in [16] used the convex optimization technique for minimization of the unit a unit commitment problem.…”

Optimal Energy Management and Techno-economic Analysis in Microgrid with Hybrid Renewable Energy Sources

“…Subsequently, the battery sizing algorithm was applied in the second stage to find the rating of BESS. In [22], the optimal size of BESS was determined in islanded microgrid with WT/PV/DG considering load growth scenario using the decomposition coordination algorithm. The techno-economic analysis of islanded microgrid with PV+WT+BESS was presented using genetic algorithm.…”

“…The grid operators must have planned the adequate amount of reserve power capacity at strategic locations in the grid to ensure reliable power supply for 24´7 despite the intermittent nature of renewable power and the uncertainty of load demand. P resAC = r load P primeAC + r peakload -P primeAC + r wind P windAC (22) P resDC = r load P primeDC + r peakload -P primeDC + r solar P PVavg (23) H. LPSP In case the load demand is more than the generation, a situation arises that the customer energy demand is not served completely, i.e., there is loss of power supply. The LPSP is a design indicator which measures the probability of unmet energy demand, as given in (24).…”