Optimal Participation of Price-Maker Battery Energy Storage Systems (BESSs) in Energy, Reserve and Pay as Performance Regulation Markets

Motivated by the need of assessing the optimal allocation of battery energy storage services across various markets and the corresponding impact on market operations, an optimization framework is proposed in this work to coordinate the operation of an independent utility-scale price-maker battery energy storage system (BESS) in the energy, spinning reserve and performance-based regulation markets. The entire problem is formulated as a bi-level optimization process, where the structure of all markets is modeled considering the joint operation limits. The strategic bidding behavior of a price-maker BESS in a pay as performance regulation market is investigated. Additionally, a specific approach is introduced for modeling automatic generation control (AGC) signals in the optimization. Although the formulated problem is non-linear, it is converted to mixed-integer linear programming (MILP) to find the optimum solution. The proposed framework is evaluated using test case scenarios created from real-world market data. Case study results show the impact of BESS's price-making behavior on the joint operation of energy, reserve, and regulation markets

Viability and value of behind-the-meter battery storage

Behind-the-meter (BTM) battery storage is a distributed, flexible technology that can support the integration of renewable generation in low-carbon power systems. This research addresses three main challenges related to the integration of BTM battery storage systems: their financial viability from the local perspective, identifying a suitable approach to account for BTM battery storage systems as autonomous decision makers in the power system and quantifying the value of BTM battery storage within low-carbon power systems. The viability of BTM battery storage was investigated from the local perspective, stacking up to three revenue streams simultaneously and accounting for battery degradation. The results indicate that single applications of BTM battery storage are unlikely to be an attractive investment but stacking more than one revenue stream improves investment viability and battery lifetime. Two approaches were compared for their suitability to account for BTM battery storage as autonomous decision makers in the power system. Additionally, the impact of retail contracts on the value of BTM battery storage to the power system was investigated. The result identifies and justifies the most suitable approach and provides insights into which retail contracts are the most beneficial from the power system perspective. The interactions between the power system and autonomous BTM batteries were studied in detail, to assess the value of BTM battery storage from the power system perspective. The results reveal BTM battery storage can have a positive or negative impact on the power system. Therefore, contract design and market structures are crucial to ensure the adoption of this technology benefits the power system

Electricity Market Participation and Investment Planning Frameworks for Energy Storage Systems

The recent trend of increasing share of renewable energy sources (RES) in the generation mix has necessitated new operational and planning studies because of the high degree of uncertainty and variability of these sources. RES such as solar photovoltaic and wind generation are not dispatchable, and when there is excess energy supply during off-peak hours, RES curtailment is required to maintain the demand-supply balance. Furthermore, RES are intermittent resources which have introduced new challenges to the provision of ancillary services that are critical to maintaining the operational reliability of power systems. Energy storage systems (ESS) play a pivotal role in facilitating the integration of RES to mitigate the aforementioned issues. Therefore, there is a growing interest in recent years to examine the potential of ESS in the future electricity grids. This research focuses on developing market participation and investment planning frameworks for ESS considering different ownership structures. First, a novel stochastic planning framework is proposed to determine the optimal battery energy storage system (BESS) capacity and year of installation in an isolated microgrid using a novel representation of the BESS energy diagram. A decomposition-based approach is proposed to solve the problem of stochastic planning of BESS under uncertainty. The optimal decisions minimize the net present value of total expected costs over a multi-year horizon considering optimal BESS operation using a novel matrix representing BESS energy capacity degradation. The proposed approach is solved in two stages as mixed integer linear programming (MILP) problems; the optimal ratings of the BESS are determined in the first stage, while the optimal installation year is determined in the second stage. Extensive studies considering four types of BESS technologies for deterministic, Monte Carlo Simulations, and stochastic cases are presented to demonstrate the effectiveness of the proposed approach. The thesis further studies the investment decisions on BESS installations by a third-party investor in a microgrid. The optimal BESS power rating, energy capacity, and the year of installation are determined while maximizing the investor's profit and simultaneously minimizing the microgrid operational cost. The multi-objective problem is solved using a goal programming approach with a weight assigned to each objective. The BESS is modeled to participate in energy arbitrage and provision of operating reserves to the microgrid, considering its performance parameters and capacity degradation over the planning horizon. Finally, in the third problem addressed in the thesis in the context of electricity markets, the non-strategic and strategic participation of a pumped hydro energy storage (PHES) facility in day-ahead energy and performance-based regulation (PBR) markets, which includes regulation capacity and mileage, are examined. The PHES is modeled with the capability of operating in hydraulic short-circuit (HSC) mode with detailed representation of its operational constraints, and integrated with an energy-cum-PBR market clearing model. For its strategic participation, a bi-level market framework is proposed to determine the optimal offers and bids of the PHES that maximize its profit. The operation of PHES is modeled at the upper level, while the market clearing is modeled in the lower level problem. The bi-level problem is formulated as a mathematical programming with equilibrium constraints (MPEC) model, which is linearized and solved as an MILP problem. Several case studies are carried out to demonstrate the impact of PHES' non-strategic and strategic operations on market outcomes. Furthermore, stochastic case studies are conducted to determine the PHES strategies considering the uncertainty of the net demand and rivals' price and quantity offers

A Review of Lithium-Ion Battery Models in Techno-economic Analyses of Power Systems

The penetration of the lithium-ion battery energy storage system (BESS) into the power system environment occurs at a colossal rate worldwide. This is mainly because it is considered as one of the major tools to decarbonize, digitalize, and democratize the electricity grid. The economic viability and technical reliability of projects with batteries require appropriate assessment because of high capital expenditures, deterioration in charging/discharging performance and uncertainty with regulatory policies. Most of the power system economic studies employ a simple power-energy representation coupled with an empirical description of degradation to model the lithium-ion battery. This approach to modelling may result in violations of the safe operation and misleading estimates of the economic benefits. Recently, the number of publications on techno-economic analysis of BESS with more details on the lithium-ion battery performance has increased. The aim of this review paper is to explore these publications focused on the grid-scale BESS applications and to discuss the impacts of using more sophisticated modelling approaches. First, an overview of the three most popular battery models is given, followed by a review of the applications of such models. The possible directions of future research of employing detailed battery models in power systems' techno-economic studies are then explored

optimizing the operation of energy storage using a non linear lithium ion battery degradation model

Abstract Given their technological and market maturity, lithium-ion batteries are increasingly being considered and used in grid applications to provide a host of services such as frequency regulation, peak shaving, etc. Charging and discharging these batteries causes degradation in their performance. Lack of data on degradation processes combined with requirement of fast computation have led to over-simplified models of battery degradation. In this work, the recent experimental evidence that demonstrates that degradation in lithium-ion batteries is non-linearly dependent on the operating conditions is incorporated. Experimental aging data of a commercial battery have been used to develop a scheduling model applicable to the time constraints of a market model. A decomposition technique that enables the developed model to give near-optimal results for longer time horizons is also proposed