Energy Storage Participation Research Articles

Optimization Operation of Power Systems with Thermal Units and Energy Storage Considering Lifetime Loss and Thermal Units Deep Peaking

Deep peak shaving achieved through the integration of energy storage and thermal power units is a primary approach to enhance the peak shaving capability of a system. However, current research often tends to be overly optimistic in estimating the operational lifespan of energy storage and lacks clear quantification of the cost changes associated with system peak shaving. This study proposes an optimized operation model for the joint operation of thermal power and energy storage while considering the lifespan degradation of energy storage and the deep peak shaving of thermal power. This model measures the cost changes due to the participation of energy storage in thermal power unit peaking. It is able to reflect the value of economic externalities of energy storage in the power system and has a positive reference effect on energy storage investment planning and energy storage subsidy pricing. First, an energy storage lifespan degradation model based on equivalent cycle counts is constructed, along with a thermal power unit peak shaving cost model based on output fluctuations. Second, an optimized joint operation model is developed. Finally, the impact of changes in energy storage capacity and renewable energy output on the system peak shaving costs and energy storage lifespan is recorded. Simulation experiments are conducted based on actual operational parameters, and the results demonstrate that the participation of energy storage in deep peak shaving can indeed effectively reduce system peak shaving costs. Additionally, the actual operational lifespan of energy storage is significantly lower than the floating lifespan.

Coordinated operation of PV/EV/Temperature controlled loads in distribution network

Abstract In order to solve the problems of voltage exceeding limits, local use, and reverse power flow due to the high proportion of distributed photovoltaic grid connections, a distributed photovoltaic uptake method considering demand-side resources and energy storage is proposed. Firstly, based on the equivalent thermal parameter (ETP) method, a load scheduling model for temperature-controlled loads is established. Secondly, with the objective function of minimizing the comprehensive operating cost of the distribution system, combined with the regulating effect of energy storage, stability and safety constraints for the distribution network, as well as the adjustable characteristics of thermal storage electric heating, air conditioning load, and electric vehicles, a demand side optimization model for the distribution network is established, which takes into account voltage safety and distributed photovoltaic uptake. Finally, based on historical data in Fengning County, Chengde City, and a certain park in Tangshan City, simulation analysis was conducted to obtain scheduling schemes and various scheduling indicators for the joint participation of demand-side resources and energy storage in the distributed photovoltaic local use of the distribution network under different permeability. The effectiveness and rationality of the proposed distributed photovoltaic consumption model were verified.

Frequency stability study of energy storage participation in new energy power system using virtual synchronous machine control

Aiming at the frequency stability of the power system under the increasing proportion of new energy sources, the study adopts the virtual synchronous machine-based energy storage adaptive control strategy and the frequency response model of the new power system. The energy storage adaptive control strategy coordinates the control of the battery’s charging state and the grid operation state by monitoring the grid operation parameters and the battery operation state in real time, so as to calculate the commanded power of the grid-connected converter. The results show that the system stability of adaptive virtual synchronization control improves when the electric transmission power increases from 205 to 510, while the system stability of virtual synchronization control decreases. The extended SFR model possesses excellent frequency matching ability when the new energy penetration rate is 8.497% and 15.66%. Virtual synchronous energy storage control strategy and the power system frequency response model can effectively predict and control the system frequency change to improve system stability under the increasing penetration rate of new energy.

[formula omitted] sampled-data load frequency control with time-varying delays considering delay compensation

Time delays in load frequency control (LFC) systems may deteriorate the control performance or cause instability. How to mitigate such adverse effects of delays in a simple but effective way is worth investigating and motivates this work. For sampled-data LFC systems with time-varying delays, this paper introduces two delay compensation techniques, namely linear and division-based methods, aimed at enhancing the robustness of LFC. A stability criterion based on H∞ is derived to ensure LFC system stability under delay compensation. Building upon this criterion, we propose an H∞ controller optimization method to tune delay compensation controller gains offline by searching for a minimum H∞ disturbance attenuation level and effectively segmenting the geometric region formed by the delays. The effectiveness of the proposed delay compensation techniques and the controller design method is verified via numerical examples on an LFC system with both generation unit and energy storage participation.

Research on the participation model of energy storage in electricity spot markets considering energy constraints and cost characteristics

In the context of power systems with a high proportion of renewable energy, energy storage plays a significant role in facilitating the consumption of renewable energy and ensuring the operational safety of power systems. However, the current power spot market's predominant power bidding model does not fully consider the physical and cost-operational characteristics of energy storage, which is not conducive to further incentivizing investment and construction of energy storage, and may indirectly affect the flexibility of energy storage in peak shaving and valley filling. This paper summarizes the key issues that need to be addressed for energy storage to participate in the spot market from two aspects: the power bidding model does not meet the requirements of the physical and cost-operational characteristics of energy storage, and the real-time market under this model cannot achieve optimal allocation of energy storage. Considering the energy constraints and cost characteristics of energy storage, a charge and discharge bidding model is proposed, which is based on the stored energy value of energy storage and is in line with the physical and cost-operational characteristics and real-time optimization needs of energy storage. Subsequently, a market clearing model for energy storage participation in the spot market under the state of energy bidding method is constructed, and based on the IEEE 39-bus test case, a comparative analysis of the nodal electricity prices, energy storage revenue, and total system costs under the proposed market participation model and the traditional power bidding model is conducted. Simulation results show that the proposed energy storage participation model in the spot market can better utilize the value of energy storage in peak shaving and valley filling compared to the conventional power bidding model, reducing the extreme electricity prices by up to 10%, increasing single cycle revenue of energy storage by 46%, and reducing the total operating costs of the system in scenarios with significant deviations in system load in the day-ahead and real-time markets.

Study on optimal scheduling of energy storage participation in power market considering source-load uncertainty

With the increasing penetration of new energy sources such as wind and light in the power grid, the selection of new energy-storage joint scheduling and operation methods can reduce the phenomenon of wind and light abandonment, but the new energy-storage joint scheduling and operation methods need to take into account the market factors, characteristics, and other aspects of a variety of problems. Given these difficulties, this paper takes into account the uncertainty of wind power, adopts the Latin hypercube sampling method to generate and consider the probabilistic distance fast reduction method, selects the typical scenarios, establishes the energy storage market operation model by minimizing the comprehensive operation cost, and responds to the source-load demand through the integrated response of the energy storage and the power grid. Finally, the effectiveness of the proposed method is demonstrated through simulation examples.

Trading strategies of energy storage participation in day-ahead joint market based on Stackelberg game

The goal of "carbon peak, carbon neutral" and the increasing expansion of new energy have helped to advance the development of energy storage. However, since the operating cost of energy storage is high, carbon emission trading and power market trading have emerged, effectively improving the efficiency. In this paper, a trading strategy and bidding framework of energy storage participation in the day-ahead joint market are studied. A market bidding model has been established in a framework based on the Stackelberg game. Finally, the "Day-Ahead and Intra-Day and Carbon Emission Trading (CET)" market clearing model has been constructed. It has been simplified to solve the equivalent mixed-integer linear programming (MILP) problem with equilibrium constraints through the use of the Karush–Kuhn–Tucker (KKT) optimality criterion and duality principle. The proposed model is validated through improved examples to obtain thermal unit output cuts of up to 32.2% during load trough periods, and up to 16.75% increase in clearing prices during peak load periods. The storage life is extended and the storage output variation is minimized.

Optimal participation and cost allocation of shared energy storage considering customer directrix load demand response

In recent years, with the increase in the proportion of new energy connected to the grid, the main goal of energy storage on the load side and energy storage users is to maximize the overall interests. Based on the poor utilization ratio and high use cost of energy storage configured on the user side, the controllability of adjustable load and the rationality of energy storage configuration are two key points that need to be considered for social welfare maximization (SWM). Hence, this paper puts forward an implementation method of large-scale demand response (DR) based on the customer directrix load (CDL), in order to give full play to the DR of the load side and improve the utilization rate of shared energy storage (SES). First, the CDL proposed in this paper gives the full-time DR regulation target, which can better guide load shaping and solve the problem of flexible load controllability. Then, an SES configuration model based on SWM is built to further shape the load and improve the utilization rate and economy of energy storage. In addition, in the market with incomplete free competition, a recent market clearing strategy based on Vickery-Clark-groves (VCG) is proposed, which encourages market members to declare true information to achieve the global optimal effect and realize the sustainability of the proposed model. The simulation results show that with the participation of SES, the similarity of users based on CDL has increased by 8.59 % and 0.99 % respectively, and the social welfare has reached 41,297.71 yuan/day. The results also show that the reasonable cost allocation through the VCG mechanism shortens the investment return period of SES by 33.33 %, which promotes the investment enthusiasm of SES.

Energy Storage Deployment and Benefits in the Chinese Electricity Market Considering Renewable Energy Uncertainty and Energy Storage Life Cycle Costs

The construction and development of energy storage are crucial areas in the reform of China’s power system. However, one of the key issues hindering energy storage investments is the ambiguity of revenue sources and the inaccurate estimation of returns. In order to facilitate investors’ understanding of revenue sources and returns on investment of energy storage in the existing electricity market, this study has established multiple relevant revenue quantification models. The research methodology employed in this paper consists of three main components: Firstly, we established a revenue model and a cost model for energy storage participation in the electricity market. These models focus on arbitrage revenue, subsidy revenue, auxiliary services revenue, investment cost, operational and maintenance cost, and auxiliary service cost of energy storage. Subsequently, we utilized an enhanced Grey Wolf Optimizer algorithm to solve the optimization problem and maximize revenue, thus obtaining the optimal capacity and revenue scale of energy storage in the electricity market. Finally, we compared the whole-lifecycle ROI of different energy storage options in various scenarios. The evaluation results demonstrate that the difference between peak and off-peak loads impacts the investment demand and charging/discharging depth of energy storage. In addition, the discrepancy between peak and off-peak prices affects the arbitrage return of energy storage. These two factors can serve as criteria for energy storage investors to assess their return expectations. When solely considering economic returns and disregarding technical factors, pumped storage energy storage emerges as the most suitable mechanical energy storage option requiring investment. The main contribution of this study lies in the estimation of the lifecycle investment returns for various energy storage technologies in the Chinese electricity market, thus providing valuable insights for the investment and operational practices of market participants.

Business decision-making of power generators in competitive electricity market

This paper presents a theoretical framework for the business decision-making process of the power generators as price takers when considering the participation of energy storage. The framework assesses rational valuation, optimal sales strategies, and hedging options for power plants with and without a gross sales constraint. The valuation and optimal sales strategy problems are analyzed using a risk-neutral pricing approach, dynamic programming principles, and the trinomial tree model suitable for the regime switching model. The formulation of a price risk hedging scheme flexible and widely used over-the-counter electricity derivative, the electricity contract for difference, as a tool for hedging electricity spot price risk. The minimum variance hedge ratio and its corresponding hedging efficiency formula are derived. In the section of numerical simulations, we first use the EM algorithm to calibrate the electricity spot model based on electricity spot price data of Nord Pool. Numerical simulations are then conducted on the operational decision-making of power generators under three different forms of energy storage. The results of the simulations provide a basis for power generators to evaluate the real-time value of power plants, to select optimal real-time power sales, and to determine the optimal timing of power plant transfer and storage methods.

Battery Energy Storage Participation in Primary Frequency Regulation Considering SOC Consistency

Abstract In recent years, battery energy storage has garnered increasing attention in the frequency regulation field due to its rapid and precise output characteristics. The focus of this paper is on the control strategy for battery energy storage that is involved in primary frequency regulation and addresses the coordination control issues of different storage units when implemented on a large scale. A control method is proposed that considers the consistency of the State of Charge (SOC) in battery energy storage, which is involved in primary frequency regulation. The control of the battery energy storage system is divided into upper-level and lower-level control. The upper-level control uses model predictive control to obtain the total frequency regulation power of the energy storage station. The lower-level control allocates the corresponding power based on the capacity of each battery energy storage unit. It introduces a proportional integral adjustment term related to the average SOC to achieve SOC consistency control for each unit. Simulation results demonstrate that, regardless of whether the capacities of various storage units are identical, the proposed method achieves good frequency regulation performance, restores SOC to the ideal range, and ensures SOC consistency among different storage units. This approach aids the efficient and safe operation of battery energy storage systems.

A joint clearing model for the participation of renewable energy and energy storage in the frequency modulation ancillary service market considering performance differences

The increasing growth in installed capacity for renewable energy sources has progressively replaced traditional thermal power units as synchronous power contributors. This transition has led to a reduction in system inertia and resources for frequency regulation, creating a need for renewable energy and energy storage to participate in system frequency modulation. Empirical studies indicate that the current market mechanism for frequency modulation auxiliary services, which predominantly rely on thermal power, is suboptimal for leveraging the unique capabilities of diverse frequency modulation resources. This inadequacy hinders the power industry’s pursuit of the “dual carbon” goals—carbon neutrality and carbon peak. Hence, this paper proposes a joint clearing model for the involvement of renewable energy and energy storage in the frequency modulation auxiliary service market. It considers performance differences and employs the Analytic hierarchy process (AHP) to guide the optimization of the weights of frequency modulation performance indicators for various frequency modulation resources. This approach allows renewable energy, energy storage, and thermal power to maximize the benefits of their own differentiated advantages in various frequency modulation performance indicators. Consequently, this fosters an increased share of renewable energy within the system while ensuring frequency stability, thereby expediting the achievement of the power industry’s “dual carbon” goals. Finally, computational analyses substantiate that the proposed joint clearing model, accounting for performance differentials, can enhance the renewable energy share in the system and simultaneously reduce the societal costs associated with frequency modulation services.

Distribution network restoration supply method considers 5G base station energy storage participation

This paper proposes a distribution network fault emergency power supply recovery strategy based on 5G base station energy storage. This strategy introduces Theil's entropy and modified Gini coefficient to quantify the impact of power supply reliability in different regions on base station backup time, thereby establishing a more accurate base station's backup energy storage capacity model that can fully utilize the base station's energy storage resources to participate in the emergency power supply of distribution network faults. First, the optimal Copula function in each cycle is determined through the Akaike information criterion and squared Euclidean distance to establish a wind power-photovoltaic output scenario. Secondly, the traditional Gini coefficient is modified using the weighted average node degree and influence rate indicators. A comprehensive vulnerability model is established through the modified Gini coefficient and Theil's entropy indicators. Based on the comprehensive vulnerability model, a backup energy storage time model and a modified backup energy storage capacity model of the base station affected by power supply reliability are established. Thus, the callable energy storage capacity of base stations in different areas is obtained. Finally, a two-stage robust optimization model is introduced to minimize system operating costs to solve the volatility of 5G base station communications and wind-solar output, thereby establishing an emergency power supply recovery model for base station energy storage and wind-solar output. Simulated with the improved IEEE-33 node model, the results show that the proposed base station's energy storage model improves the utilization of the base station energy storage resources and, at the same time, effectively reduces the loss of load during the fault phase of the distribution network and improves the absorption of the PV output.

Receding horizon dispatch of multi-period look-ahead market for energy storage integration

Although noteworthy efforts towards energy storage participation in electricity markets have been witnessed worldwide during the last decades, market mechanisms for optimal storage integration are yet to be comprehensively studied. This paper presents a novel approach wherein a multi-period look-ahead market is proposed to progressively solve the optimisation problem over a receding horizon, incorporating intertemporal constraints to enable forward planning. The focus is specifically on modelling the bidding behaviour of energy storage, and to address this, we develop two distinct models for the participation of energy storage in the market. The integrated model aims to schedule the future dispatch of the storage to minimise total operational cost, taking into account the fixed costs of the storage, while the strategic model pursues the dual ambition to maximise storage profit by formulating a bilevel optimisation problem. We validate the viability of our proposed market mechanisms through case studies on the Australian National Electricity Market. We conduct case studies which provide evidence that both the strategic and integrated bidding models effectively address the requirement for forward planning, resulting in reduced market costs and volatility. Notably, the strategic model outperforms in terms of generating higher storage revenue, while the integrated model exhibits a slight advantage in terms of lower market costs compared to the strategic model.

Operation of The Hybrid Energy Resources with Storage System Participation

This paper focused on the optimal operation of the hybrid energy resources in the off-grid state considering energy storage participation. The hybrid energy resources consist of wind turbine (WT), photovoltaic (PV), diesel generator (DG), and energy storage system for supplying energy to DC and AC load demand with maximum reliability. The operation of the proposed energy system based on energy control and energy optimization is modeled. The energy optimization and energy control are implemented by heuristic and nonlinear quadratic programming approaches via optimal power flow on the resources side. The energy control is done based on the weight sum method in different operation states of the system. Also, the impact of the energy storage system on the hybrid energy resources is considered as backup resources. The energy control modeling is implemented via mathematical simulation and numerical analysis in the two operation states in the summer and winter seasons for verifying the proposed approaches. Finally, the results of the energy control show optimal states of the energy system in supplying demand with considering the energy storage system.

A Novel Allocation Strategy Based on the Model Predictive Control of Primary Frequency Regulation Power for Multiple Distributed Energy Storage Aggregators

As the amount of distributed energy storage (DES) in a power system continues to increase, it will not be long before there are multiple DES aggregators participating in frequency regulation, and the realization of their coordinated control is a critical topic of current research. This study focused on the primary frequency regulation (PFR) power allocation strategy among multiple DES aggregators participating in PFR. This study first calculated the PFR demand according to a system frequency response model of the power system with DESs. Next, a PFR power allocation model of DES aggregators was developed based on model predictive control. The objective of this model was to minimize the overall frequency regulation cost while satisfying all of the constraints of DESs. Finally, the distributed interior point method was used to solve the model rapidly. The correctness and effectiveness of the proposed model and algorithm were verified on two unified transmission and distribution systems with DES aggregators used to supply the PFR service. The results revealed that the proposed model could effectively allocate PFR power to the various types of energy storage, with the additional benefits of slowing down the shift in the state of charge for energy storage units and ensuring the continuity of energy storage participation in frequency regulation.

Application research on energy storage in power grid supply and demand regulation based on differentiated electricity prices

To solve the problem of safe and stable grid operation caused by the uncontrollability of renewable energy power generation with a high proportion, this paper focuses on the method of energy storage participation in grid supply and demand balance regulation based on differentiated electricity prices. From the perspective of demand-side and regulable resources, the paper investigates the method of using differentiated electricity prices to improve demand-side responsiveness and expand energy storage operation revenue, so as to explore and activate the potential of regulable resources in the grid. Firstly, the necessity and feasibility of considering differentiated electricity prices are analyzed. Secondly, a demand-side response and energy storage regulation model based on differentiated electricity prices is established, and the supply–demand balance regulation method considering differentiated electricity prices is proposed. Then, the supply–demand balance regulation process under two conditions before and after the implementation of differentiated electricity prices is compared and analyzed through case simulation. Finally, via the practical example, the effectiveness of the method is verified, and the proposed method is able to reduce the demand for energy storage by half in rated power and reduce the rated capacity of the energy storage to 8.66%.

The role of electricity market design for energy storage in cost-efficient decarbonization

The role of electricity market design for energy storage in cost-efficient decarbonization

Investment decisions and strategies of China's energy storage technology under policy uncertainty: A real options approach

Energy storage technology is one of the critical supporting technologies to achieve carbon neutrality target. However, the investment in energy storage technology in China faces policy and other uncertain factors. Based on the characteristics of China's energy storage technology development and considering the uncertainties in policy, technological innovation, and market, this study proposes a sequential investment decision model under two investment strategies and uses the differential equation method to solve the investment threshold and investment opportunity value of the energy storage technology. Then, taking energy storage participation in peaking auxiliary services in China as an example, we verify the model validity and analyze the impact of uncertainty factors and investment strategies. The findings of this study are as follows: 1) The frequency of policy adjustments and the magnitude of subsidy adjustments can both influence energy storage technology investments, but the magnitude of subsidy adjustments is more significant. 2) Technological innovation can offset the adverse effects of policy uncertainty 3) In the case of a relatively certain policy, the subsidy is at least 0.0246 USD/kWh to effectively incentivize investment. In the case of uncertainty about the policy adjustment frequency and the subsidy reduction intensity, the subsidy must reach 0.0311 USD/kWh.

Changes in the electricity market under the participation of diverse participants and its supervision necessity analysis

With the demand for energy sustainability and the development of the low-carbon power system, distributed energy, energy storage, demand response, and other diverse market participants will participate in the electricity market, which brings new changes to the transaction organization process of the electricity market. This paper first introduces the changes in the electricity market under the participation of diverse market participants from two aspects of market transactions and market power. Diverse participants can provide a variety of auxiliary services in the electricity market while they have potential market power in the process. Secondly, the current supervision measures used in the foreign electricity market in the order of ex-ante, interim, and ex-post are reviewed and four common supervision indexes are introduced. Finally, the market power and the supervision necessity of the electricity market under the participation of energy storage are analyzed by case studies. As shown by the simulation results, energy storage with excellent regulating performance has market power in providing frequency regulation services, but the conventional supervision indexes fail to detect the market power of energy storage effectively. The purpose of this paper is to illustrate the necessity of the market supervision method for adapting to the changes under the participation of diverse participants.