A review on peak load shaving in microgrid—Potential benefits, challenges, and future trend

This study aims to review the potential benefits of peak load shaving in a microgrid system. The relevance of peak shaving for a microgrid system is presented in this research review at the outset to justify the peak load shaving efficacy. The prospective benefits of peak shaving in microgrid systems, including technological, economic, and environmental advantages, are thoroughly examined. This review study also presents a cost–benefit numerical analysis to illustrate the economic viability of peak load shaving for a microgrid system. Different peak shaving approaches are briefly discussed, as well as the obstacles of putting them into practice. Finally, this review study reveals some potential future trends and possible directions for peak shaving research in microgrid systems. This review paper lays a strong foundation for identifying the potential benefits of peak shaving in microgrid systems and establishing suitable projects for practical effectuation

Peak shaving through battery storage for low-voltage enterprises with peak demand pricing

The renewable energy transition has introduced new electricity tariff structures. With the increased penetration of photovoltaic and wind power systems, users are being charged more for their peak demand. Consequently, peak shaving has gained attention in recent years. In this paper, we investigated the potential of peak shaving through battery storage. The analyzed system comprises a battery, a load and the grid but no renewable energy sources. The study is based on 40 load profiles of low-voltage users, located in Belgium, for the period 1 January 2014, 00:00-31 December 2016, 23:45, at 15 min resolution, with peak demand pricing. For each user, we studied the peak load reduction achievable by batteries of varying energy capacities (kWh), ranging from 0.1 to 10 times the mean power (kW). The results show that for 75% of the users, the peak reduction stays below 44% when the battery capacity is 10 times the mean power. Furthermore, for 75% of the users the battery remains idle for at least 80% of the time; consequently, the battery could possibly provide other services as well if the peak occurrence is sufficiently predictable. From an economic perspective, peak shaving looks interesting for capacity invoiced end users in Belgium, under the current battery capex and electricity prices (without Time-of-Use (ToU) dependency)

Peak Shaving Considering Streamflow Uncertainties

The main thrust of this paper is peak shaving with a Stochastic hydro model. In peak sharing, the amount of hydro energy scheduled may be a minimum but it serves to replace less efficient thermal units. The sample system is die Kainji hydro plant and the thermal units of the National Electric Power Authority. The random nature of the system load is re-organized by using a Markov load model. The results include a modification of the expected load to be served by the array of thermal units, and the optimum schedule for the economic operation of the plant as a peaking load.

Optimizing energy storage participation in emerging power markets

The growing amount of intermittent renewables in power generation creates challenges for real-time matching of supply and demand in the power grid. Emerging ancillary power markets provide new incentives to consumers (e.g., electrical vehicles, data centers, and others) to perform demand response to help stabilize the electricity grid. A promising class of potential demand response providers includes energy storage systems (ESSs). This paper evaluates the benefits of using various types of novel ESS technologies for a variety of emerging smart grid demand response programs, such as regulation services reserves (RSRs), contingency reserves, and peak shaving. We model, formulate and solve optimization problems to maximize the net profit of ESSs in providing each demand response. Our solution selects the optimal power and energy capacities of the ESS, determines the optimal reserve value to provide as well as the ESS real-time operational policy for program participation. Our results highlight that applying ultra-capacitors and flywheels in RSR has the potential to be up to 30 times more profitable than using common battery technologies such as LI and LA batteries for peak shaving

The Use of Plug-In Hybrid Electric Vehicles For Peak Shaving

This thesis entitled The Use of Plug-In Hybrid Electric Vehicles For Peak Shaving by Benjamin Maples, submitted to the department of Mechanical Engineering in partial fulfillment of the degree of Master of Science, performed under the supervision of Professor Frank Kreith, is a feasibility analysis of the capabilities of PHEV\u27s for peak shaving. The analysis focuses on energy availability of the PHEV fleet as well as the potential financial benefit to the vehicle owner by analyzing different charging scenarios and circuitry. The energy availability is heavily dependent on the location and availability of charging stations. The potential consumer profit is most dependent on the charging circuitry. The major findings of the study shows that under certain scenarios, such as the charge everywhere baseline case, using PHEV\u27s for peak shaving is possible and could provide vehicle owners with significant compensation for the energy stored in their vehicles batteries

Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy

We study inventory control with volume flexibility: A firm can replenish using period-dependent base capacity at regular sourcing costs and access additional supply at a premium. The optimal replenishment policy is characterized by two period-dependent base-stock levels but determining their values is not trivial, especially for nonstationary and correlated demand. We propose the Lookahead Peak-Shaving policy that anticipates and peak shaves orders from future peak-demand periods to the current period, thereby matching capacity and demand. Peak shaving anticipates future order peaks and partially shifts them forward. This contrasts with conventional smoothing, which recovers the inventory deficit resulting from demand peaks by increasing later orders. Our contribution is threefold. First, we use a novel iterative approach to prove the robust optimality of the Lookahead Peak-Shaving policy. Second, we provide explicit expressions of the period-dependent base-stock levels and analyze the amount of peak shaving. Finally, we demonstrate how our policy outperforms other heuristics in stochastic systems. Most cost savings occur when demand is nonstationary and negatively correlated, and base capacities fluctuate around the mean demand. Our insights apply to several practical settings, including production systems with overtime, sourcing from multiple capacitated suppliers, or transportation planning with a spot market. Applying our model to data from a manufacturer reduces inventory and sourcing costs by 6.7%, compared to the manufacturer's policy without peak shaving.info:eu-repo/semantics/publishedVersio