A BESS Sizing Strategy for Primary Frequency Regulation Support of Solar Photovoltaic Plants

Abstract

This paper proposes a strategy for sizing a battery energy storage system (BESS) that supports primary frequency regulation (PFR) service of solar photo-voltaic plants. The strategy is composed of an optimization model and a performance assessment algorithm. The optimization model includes not only investment costs, but also a novel penalty function depending on the state of charge (SoC). This function avoids the existence of a potential inappropriate SoCtrajectory during BESS operation that could impede the supply of PFR service. The performance assessment algorithm, fed by the optimization model sizing results, allows the emulation of BESS operation and determines either the success or failure of a particular BESS design. The quality of a BESS design is measured through number of days in which BESS failed to satisfactorily provide PFR and its associated penalization cost. Battery lifetime, battery replacements, and SoC are also key performance indexes that finally permit making better decisions in the election of the best BESS size. The inclusion of multiple BESS operational restrictions under PFR is another important advantage of this strategy since it adds a realistic characterization of BESS to the analysis. The optimization model was coded using GAMS/CPLEX, and the performance assessment algorithm was implemented in MATLAB. Results were obtained using actual frequency data obtained from the Colombian power system; and the resulting BESS sizes show that the number of BESS penalties, caused by failure to provide PFR service, can be reduced to zero at minimum investment cost.

Site Selection Criteria for Battery Energy Storage in Power Systems

“…In the absence of BESS, a part of generator capacity performing PFR has to be reserved for this service. On top of that, the process occurs with a slow response speed [20]. As BESS has a high power capacity and lower discharge rate, it can provide a fast response and hence a better frequency imbalance handling capability [20].…”

“…On top of that, the process occurs with a slow response speed [20]. As BESS has a high power capacity and lower discharge rate, it can provide a fast response and hence a better frequency imbalance handling capability [20]. When BESS is used for PFR, it is recommended to interpret BESS location according to the most severe contingency for generation outage.…”

“…BESS can be deployed near the load centers to provide peaking capacity due to the scalability they can provide. Conventional generators usually do not provide this flexibility as they raise concerns about land use and toxic emissions [20].…”

Short-term Energy Recovery Control for Virtual Inertia Provision by Renewable Energy Sources

“…PFR [5]- [8], powersmoothing (also referred as ramp-rate limitation), [2], [9], [10], peak-shaving [11], etc. These strategies have been successfully applied to either wind [9], [11] or PV generation [2], [6], [10]. Although these studies include a State-Of-Charge (SoC) control after the AS provision, this control comes as a second priority and limited results are presented, while they mostly focus on the proper CIRES control for the AS provision.…”

“…Furthermore, the types of ESS in these studies are usually electrochemical BESS [5], [6], [10] or Hybrid ESS (HESS), [7]- [9], [11], [12] which consist of a BESS and a FESS (either SC [7], [8], [11] or FW, [12]). Regarding the BESS, although there are many research studies for the proper SoC restoration, the involved dynamics are in the order of minutes (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15). This is sufficient for low-frequency power smoothing or peakshaving, but for other AS, e.g.…”