Optimal planning of solar PV and battery storage with energy management systems for Time‐of‐Use and flat electricity tariffs

Abstract

This paper determines the optimal capacity of solar photovoltaic (PV) and battery energy storage (BES) with novel rule-based energy management systems (EMSs) under flat and time-of-use (ToU) tariffs. Four schemes are investigated based on the combinations of flat and ToU tariffs for buying and selling the electricity: (1) Flat-Flat, (2) ToU-Flat, (3) Flat-ToU, and (4) ToU-ToU. For each scheme, two configurations are evaluated: (i) PV only, and (ii) PV-BES. The optimization of the grid-connected household is evaluated based on one-year realistic data. An uncertainty analysis is presented based on the variations of insolation, temperature, and load. Sensitivity analyses are implemented based on the average daily load, the grid constraint, and the costs of PV and BES. The operational analyses for 48 h in summer and winter are carried out to evaluate the dynamic performance of the systems for high and low solar insolation. The effectiveness of the proposed model is verified by comparing the results with that of common EMS based on the net metering scheme. It is found that the COE of the proposed EMS for a PV-BES house with ToU-Flat scheme (as the best option) is 2 ¢/kWh lower than that of the net metering scheme.

Peak‐valley period partition and abnormal time correction for time‐of‐use tariffs under daily load curves based on improved fuzzy c‐means

“…It effectively guides customers to use electricity and improve system economy and reliability, and its role in the competitive market is becoming more and more obvious [1][2][3][4]. Time-of-use (ToU) tariff is a price-based demand response method which can solve the problems like rapid growth of electric load, supply that does not meet demand during the peak of electricity consumption and overgeneration during the valley period [5,6]. After the ToU implementation, the price differences between the peak and off-peak periods make customers move some electricity consumption to the off-peak for reducing their electricity costs.…”

“…One of the works of this paper is to develop a mathematical model of this experience to determine the parameters a and c. Here, the TMF is assumed to be the most conservative, and the MMF tends to be more aggressive. The fuzzy parameters a, b, and c are calculated by Equations ( 4) to (6).…”

“…According to the process in Figure 6, when 𝛼 = 0.79, the slope reaches its first local maximum value in both daily load curves, indicating that the conservativeness change is the most obvious within the conservativeness level neighbourhood. According to Equations ( 4) to (6), the values of fuzzy parameters a, b, and c of two daily load curves are shown in Table 3.…”

Controlling the Unbalanced Voltages of a Series-Connected Lead-Acid Batteries in a PV Power Storage System using Dynamic Capacitor Technique

“…In the last decade, the growth of PV power systems and the development of electric vehicles have made huge progress in adopting new technologies for manufacturing different types of batteries (Chen et al, 2020). Batteries now have more charge/discharge cycles, longer life, stronger, higher capacities, and low costs (Lipu et al, 2022;Pan et al, 2022). However, these batteries are still available in low voltage mostly 12 DC voltage that need to use more batteries in series and parallel connection combination to increase their voltages and capacities to follow the ratings of inverters in PV power systems (Manimekalai et al, 2013;Fortenbacher et al, 2017;Bagalini et al, 2019, Wu et al, 2022.…”