•We propose a four-stage Stackelberg game with a monopolistic storage operator.•We consider bidding on a day-ahead and a real-time electricity market.•We present a reformulation of the four-stage ...game into a single-level problem.•We compare different market designs regarding storage revenue and system costs.•We illustrate the importance of appropriate market design and bidding language.
The rapid growth of the share of energy generated via renewable sources highly challenges grid stability. Flexibility is key to balance the electricity supply and demand. As a relatively new player in the energy market, the Energy Storage System (ESS) is capable of providing such flexibility, acting as both a consumer and producer. Since the Directive (EU) 2019/944 of the European Union requires ESSs to be operated by an independent market player, ESSs are becoming an important player in different electricity markets. Crucially, it is difficult for, e.g., market-monitoring authorities, to compare the bid cost functions to the true opportunity costs of an ESS. Motivated by this, in this paper we elaborate on the potential of an ESS to exercise market power in a liberalized electricity market. In particular, we analyze how a monopolistic ESS operator may influence short-run market outcomes, e.g., prices and system costs, depending on different market designs including a nodal, a zonal, and a uniform pricing system. For this purpose, we propose a four-stage Stackelberg game where the monopolistic ESS operator first decides on its day-ahead market bids (level 1), followed by day-ahead market clearing (level 2), after which the ESS submits bids to the real-time balancing market (level 3), which is then cleared (level 4). Relying on a widely used case study, we illustrate that some market designs may be more favorable for the ESS operator, whereas other ones may be more attractive from the regulator’s point of view of minimizing the overall system costs.
This work presents two mixed-integer programming models that intend to minimize the costs of the picking and storage operation through better planning and organization of the places occupied by the ...products in the warehouse. A large customer that stores frozen goods in a Portuguese cold chain logistics company was selected for the analysis of the allocation of the products in the warehouse and of the corresponding outbound movements. Data with 8525 movements that occurred during 2021 were collected for 228 different product references. For this case study, the products that had a picking place in the initial scenario now have pallets with all the goods in the reserve area, and vice versa. The mathematical models were permitted to obtain savings for the logistics operator costs of around 30.9%. The proposed models can, in the future, be applied in other warehouse scenarios to companies in completely different sectors of activity.
Energy generation from intermittent renewable sources introduces additional variability into electrical systems, resulting in a higher cost of balancing against the increased variabilities. Ways to ...balance demand and supply for electricity include using flexible generation resources, storage operations, and curtailing intermittent generation. This paper focuses on the operational and environmental impact of curtailing intermittent generation. We construct a stochastic dynamic optimization model that captures the critical components of the system operating cost and analyze how various generation resources should operate with and without curtailing intermittent generation. We find that the system cost reduction per unit of curtailed energy is consistently significant and the presence of storage may increase the cost saving per unit of curtailed energy. We also find that curtailing intermittent generation often leads to system emission reductions.
The value of seasonal energy storage depends on how the firm operates storage to capture seasonal price spreads. Energy storage operations typically face limited operational flexibility characterized ...by the speed of storing and releasing energy, which makes the optimal policy, in general, difficult to compute. A widely used practice-based heuristic, the rolling intrinsic (RI) policy, generally performs well compared with an optimal policy but can significantly underperform in some cases. In this paper, we aim to understand the gap between the RI policy and the optimal policy and leverage the resulting insights to improve the RI policy. A new heuristic policy, the
price-adjusted rolling intrinsic
(PARI) policy, is developed based on theoretical analysis of storage options. This heuristic adjusts certain prices before applying the RI policy to provide the RI policy with estimates of the values of various storage options. We evaluate the performance of the RI and PARI polices using actual data from the natural gas industry. Our results show that, on average, the PARI policy recovers about 67% of the value loss of the RI policy. Furthermore, when the value loss of the RI policy is larger, the PARI policy tends to recover a higher fraction of that value loss.
In this paper, we are interested in defining a methodology for optimizing the storage operations in container terminals. Our approach is organized in two main stages, the first focuses on the design ...of a generic mathematical model the container storage problem. This takes into account the constraints commonly used in container terminals. In the second stage, we are interested in adapting the general study to the case of EUROGATE Tangier container terminal in Tangier-Med Transshipment hub. Our general objective is to specify the optimum locations for the set of unloaded containers upon arrival of one or more vessels in order to assist in the decision-making in the said terminal. The proposed methodological approach has been identified as an interesting track to achieve this goal.
In a container terminal, the optimal operations management faces many constraints, which makes it a complex and challenging problem. The main objective of this paper is to solve a real-life ...optimization problem, on the reduction of the length of containers unloading operations in the logistical platform MITA, located in the dry port of Casablanca in Morocco. We suggest a mixed integer programming (MIP) model based on a discrete time approach, that allows to solve this problem for the scheduling of unloading and storing operations. The model considers a new real-life constraint, which is cranes interferences. Its resolution is performed by using Cplex, and computational experiments are presented and interpreted.
In application processes like Web and databases, files and databases are manipulated on servers. Thus, both CPU and storage resources are used to perform application processes. In this paper, we ...propose a computation model to give the expected termination time of each application process. Here, computation operations and storage operations of a process are integrated into virtual computation steps. Then, we propose an SGEAG (Simple Globally-Energy-Aware for General processes) algorithm to select a server to perform a new process issued by a client, which is expected to consume the minimum electric energy to perform not only the new process but also every current process. In the evaluation, we show the electric energy consumed by servers and the average execution time of processes can be more reduced in the SGEAG algorithm than the other algorithms.
We present a method that operates an electrolyzer to meet the demand of a hydrogen refueling station in a cost-effective manner by solving a model-based optimal control problem. To formulate the ...underlying problem, we first conduct an experimental characterization of a Siemens SILYZER 100 polymer electrolyte membrane electrolyzer with 100 kW of rated power. We run experiments to determine the electrolyzer’s conversion efficiency and thermal dynamics as well as the overload-limiting algorithm used in the electrolyzer. The resulting detailed nonlinear models are used to design a real-time optimal controller, which is then implemented on the actual system. Each minute, the controller solves a deterministic, receding-horizon problem which seeks to minimize the cost of satisfying a given hydrogen demand, while using a storage tank to take advantage of time-varying electricity prices and photovoltaic inflow. We illustrate in simulation the significant cost reduction achieved by our method compared to others in the literature, and then validate our method by demonstrating it in real-time operation on the actual system.
•Experimental identification of system dynamics for Siemens SILYZER 100 electrolyzer.•Online optimal control experiments meet deterministic demand with near-optimal cost.•Performance of system with mixed integer model compares favorably to linear model.
Renewable energy sources have a huge potential to reduce greenhouse gas emissions and decrease the dependence on fossil fuels in the energy sector. However, the energy output of these sources is ...variable and raises concerns regarding the electric grid reliability. Therefore, the deployment of energy storage would play a key role in enabling the integration of these sources in the electric grid. This paper proposes methods for determining the optimal operation and sizing of energy storage systems. The main purpose of the operation strategy is to maximize the revenues of the renewable farm. The sizing model, on the other hand, has a purpose to minimize the cost of the hybrid system while meeting the service requirement. Both methods were formulated as non-linear programming optimization models. To verify the effectiveness of these methods; case studies have been presented. Finally, this paper proposes an economical analysis to determine the cost added by the storage to each KWh of stored energy.
PDF
