scholarly journals Forecast Error Sensitivity Analysis for Bidding in Electricity Markets with a Hybrid Renewable Plant Using a Battery Energy Storage System

2020 ◽  
Vol 12 (9) ◽  
pp. 3577 ◽  
Author(s):  
Jon Martinez-Rico ◽  
Ekaitz Zulueta ◽  
Unai Fernandez-Gamiz ◽  
Ismael Ruiz de Argandoña ◽  
Mikel Armendia
Keyword(s):  
Sensitivity Analysis ◽  
Energy Storage ◽  
Electricity Markets ◽  
Electricity Market ◽  
Forecast Error ◽  
Storage System ◽  
Energy Storage System ◽  
Prediction Errors ◽  
Electricity Grid ◽  
Battery Energy

Deep integration of renewable energies into the electricity grid is restricted by the problems related to their intermittent and uncertain nature. These problems affect both system operators and renewable power plant owners since, due to the electricity market rules, plants need to report their production some hours in advance and are, hence, exposed to possible penalties associated with unfulfillment of energy production. In this context, energy storage systems appear as a promising solution to reduce the stochastic nature of renewable sources. Furthermore, batteries can also be used for performing energy arbitrage, which consists in shifting energy and selling it at higher price hours. In this paper, a bidding optimization algorithm is used for enhancing profitability and minimizing the battery loss of value. The algorithm considers the participation in both day-ahead and intraday markets, and a sensitivity analysis is conducted to check the profitability variation related to prediction uncertainty. The obtained results highlight the importance of bidding in intraday markets to compensate the prediction errors and show that, for the Iberian Electricity Market, the uncertainty does not significantly affect the final benefits.

scholarly journals Turning Base Transceiver Stations into Scalable and Controllable DC Microgrids Based on a Smart Sensing Strategy

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1202
Author(s):  
Miguel Tradacete ◽  
Carlos Santos ◽  
José A. Jiménez ◽  
Fco Javier Rodríguez ◽  
Pedro Martín ◽  
...  
Keyword(s):  
Electricity Market ◽  
Low Cost ◽  
Storage System ◽  
Environmental Parameters ◽  
Weather Conditions ◽  
Energy Storage System ◽  
Electricity Grid ◽  
Dc Microgrids ◽  
Smart Sensing ◽  
Battery Energy

This paper describes a practical approach to the transformation of Base Transceiver Stations (BTSs) into scalable and controllable DC Microgrids in which an energy management system (EMS) is developed to maximize the economic benefit. The EMS strategy focuses on efficiently managing a Battery Energy Storage System (BESS) along with photovoltaic (PV) energy generation, and non-critical load-shedding. The EMS collects data such as real-time energy consumption and generation, and environmental parameters such as temperature, wind speed and irradiance, using a smart sensing strategy whereby measurements can be recorded and computing can be performed both locally and in the cloud. Within the Spanish electricity market and applying a two-tariff pricing, annual savings per installed battery power of 16.8 euros/kW are achieved. The system has the advantage that it can be applied to both new and existing installations, providing a two-way connection to the electricity grid, PV generation, smart measurement systems and the necessary management software. All these functions are integrated in a flexible and low cost HW/SW architecture. Finally, the whole system is validated through real tests carried out on a pilot plant and under different weather conditions.

scholarly journals Implementation of Optimal Scheduling Algorithm for Multi-Functional Battery Energy Storage System

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1339 ◽  
Author(s):  
Hee-Jun Cha ◽  
Sung-Eun Lee ◽  
Dongjun Won
Keyword(s):  
Energy Storage ◽  
Electricity Market ◽  
Distribution System ◽  
Wind Farm ◽  
Storage System ◽  
Energy Storage System ◽  
Optimal Scheduling ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy

Energy storage system (ESS) can play a positive role in the power system due to its ability to store, charge and discharge energy. Additionally, it can be installed in various capacities, so it can be used in the transmission and distribution system and even at home. In this paper, the proposed algorithm for economic optimal scheduling of ESS linked to transmission systems in the Korean electricity market is proposed and incorporated into the BESS (battery energy storage system) demonstration test center. The proposed algorithm considers the energy arbitrage operation through SMP (system marginal price) and operation considering the REC (renewable energy certification) weight of the connected wind farm and frequency regulation service. In addition, the proposed algorithm was developed so that the SOC (state-of-charge) of the ESS could be separated into two virtual SOCs to participate in different markets and generate revenue. The proposed algorithm was simulated and verified through Matlab and loaded into the demonstration system using the Matlab “Runtime” function.

scholarly journals Assessment of Energy Arbitrage Using Energy Storage Systems: A Wind Park’s Perspective

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4718
Author(s):  
Pavani Ponnaganti ◽  
Birgitte Bak-Jensen ◽  
Brian Vejrum Wæhrens ◽  
Jesper Asmussen
Keyword(s):  
Energy Storage ◽  
Electricity Markets ◽  
Reactive Power ◽  
Storage Systems ◽  
Storage System ◽  
Energy Storage System ◽  
Green Energy ◽  
Battery Energy Storage System ◽  
Wind Park ◽  
Battery Energy

With the growing application of green energy, the importance of effectively handling the volatile nature of these energy sources is also growing in order to ensure economic and operational viability. Accordingly, the main contribution of this work is to evaluate the revenue potential for wind parks with integrated storage systems in the day-ahead electricity markets using genetic algorithm. It is achieved by the concept of flexible charging–discharging of the Energy Storage System (ESS), taking advantage of the widespread electricity prices that are predicted using a feedforward-neural-network-based forecasting algorithm. In addition, the reactive power restrictions posed by grid code that are to be followed by the wind park are also considered as one of the constraints. Moreover, the profit obtained with a Battery Energy Storage System (BESS) is compared with that of a Thermal Energy Storage System (TESS). The proposed method gave more profitable results when utilizing BESS for energy arbitrage in day-ahead electricity markets than with TESS. Moreover, the availability of ESS at wind park has reduced the wind power curtailment.

scholarly journals Research on the Optimized Operation of Hybrid Wind and Battery Energy Storage System Based on Peak-Valley Electricity Price

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3707
Author(s):  
Miao Miao ◽  
Suhua Lou ◽  
Yuanxin Zhang ◽  
Xing Chen
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Forecast Error ◽  
Storage System ◽  
Energy Storage System ◽  
Economic Benefits ◽  
Electricity Price ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy

The combined operation of hybrid wind power and a battery energy storage system can be used to convert cheap valley energy to expensive peak energy, thus improving the economic benefits of wind farms. Considering the peak–valley electricity price, an optimization model of the economic benefits of a combined wind–storage system was developed. A charging/discharging strategy of the battery storage system was proposed to maximize the economic benefits of the combined wind–storage system based on the forecast wind power. The maximal economic benefits were obtained based on scenario analysis, taking into account the wind-power forecast error, and costs associated with the loss of battery life, battery operation, and maintenance. Case simulation results highlight the effectiveness of the proposed model. The results show that the hybrid wind–storage system is not only able to convert cheap electricity in the valley period into expensive electricity in the peak period, thus resulting in higher economic benefits, but can also balance the deviation between actual output and plans for the wind power generator to decrease the loss penalty. The analyzed examples show that, following an increase in the deviation of the forecast wind power, the profit of the combined wind–storage system can increase by up to 45% using the charging/discharging strategy, compared with a wind farm that does not utilize energy storage. In addition, the profit of the combined wind–storage system can increase by up to 16% compared with separate systems, following an increase in the deviation penalty deviation coefficient.

Study of Efficiency of Battery Energy Storage System

2016 ◽  
Vol 136 (11) ◽  
pp. 824-832 ◽  
Author(s):  
Mami Mizutani ◽  
Takenori Kobayashi ◽  
Katsunori Watabe ◽  
Tomoki Wada
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy
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