Factoring the Cycle Aging Cost of Batteries Participating in Electricity Markets

When participating in electricity markets, owners of battery energy storage systems must bid in such a way that their revenues will at least cover their true cost of operation. Since cycle aging of battery cells represents a substantial part of this operating cost, the cost of battery degradation must be factored in these bids. However, existing models of battery degradation either do not fit market clearing software or do not reflect the actual battery aging mechanism. In this paper we model battery cycle aging using a piecewise linear cost function, an approach that provides a close approximation of the cycle aging mechanism of electrochemical batteries and can be incorporated easily into existing market dispatch programs. By defining the marginal aging cost of each battery cycle, we can assess the actual operating profitability of batteries. A case study demonstrates the effectiveness of the proposed model in maximizing the operating profit of a battery energy storage system taking part in the ISO New England energy and reserve markets

Optimized Energy Management Strategy for Wind Plants with Storage in Energy and Reserve Markets

This paper addresses the joint operation of wind plants with energy storage systemsin multiple markets to increase the value of wind energy from an economic and technical point of view. The development of an optimized energy management allows scheduling the wind generation in energymarkets, as well as contributing to the system stability through the joint participation in frequency ancillary services. The market optimization maximizes market revenuesconsidering overallstoragecosts, while avoidingenergy imbalancesand market penalties. Moreover, wind power fluctuations, forecast errors and real-time reserverequirementsare controlledby the energy storagesystem and managed afterward through the participation in continuous intraday market. Furthermore, model predictive control approach enables a high compliance of reserve requirementsand a hugereduction of energy imbalancesin real-time operation. Different energy storagecapacities are selected in order to evaluate theircost-effectiveness enhancing the wind plant operation underthe considered study case.This work was partially supported by the Basque Government under Project Road2DC (ELKARTEK Research Program KK-2018/00083)

Corrective receding horizon EV charge scheduling using short-term solar forecasting

Forecast errors can cause sub-optimal solutions in resource planning optimization, yet they are usually modeled simplistically by statistical models, causing unrealistic impacts on the optimal solutions. In this paper, realistic forecast errors are prescribed, and a corrective approach is proposed to mitigate the negative effects of day-ahead persistence forecast error by short-term forecasts from a state-of-the-art sky imager system. These forecasts preserve the spatiotemporal dependence structure of forecast errors avoiding statistical approximations. The performance of the proposed algorithm is tested on a receding horizon quadratic program developed for valley filling the midday net load depression through electric vehicle charging. Throughout one month of simulations the ability to flatten net load is assessed under practical forecast accuracy levels achievable from persistence, sky imager and perfect forecasts. Compared to using day-ahead persistence solar forecasts, the proposed corrective approach using sky imager forecasts delivers a 25% reduction in the standard deviation of the daily net load. It is demonstrated that correcting day-ahead forecasts in real time with more accurate short-term forecasts benefits the valley filling solution

Unintended Effects of Residential Energy Storage on Emissions from the Electric Power System.

In many jurisdictions, policy-makers are seeking to decentralize the electric power system while also promoting deep reductions in the emission of greenhouse gases (GHG). We examine the potential roles for residential energy storage (RES), a technology thought to be at the epicenter of these twin revolutions. We model the impact of grid-connected RES operation on electricity costs and GHG emissions for households in 16 of the largest U.S. utility service territories under 3 plausible operational modes. Regardless of operation mode, RES mostly increases emissions when users seek to minimize their electricity cost. When operated with the goal of minimizing emissions, RES can reduce average household emissions by 2.2-6.4%, implying a cost equivalent of $180 to$5160 per metric ton of carbon dioxide avoided. While RES is costly compared with many other emission-control measures, tariffs that internalize the social cost of carbon would reduce emissions by 0.1-5.9% relative to cost-minimizing operation. Policy-makers should be careful about assuming that decentralization will clean the electric power system, especially if it proceeds without carbon-mindful tariff reforms

Hydro/Battery Hybrid Systems for frequency regulation

An innovative Hydro/Battery Hybrid System (HBHS), composed of a hydropower plant (HPP) and a Battery Energy Storage System (BESS) is proposed to provide frequency regulation services in the Nordic Power System (NPS). The HBHS is envisioned to have a faster and more efficient response compared to HPPs currently providing these services, whilst retaining their high energy capacity and endurance, thus alleviating stand-alone BESS operation constraints. This Thesis aims to explore the operation and optimization of such a hybrid system in order to make it efficient and economically viable. A power plant perspective is employed, evaluating the impact different control algorithms and parameters have on the HBHS performance. Providing Frequency Containment Reserves for Normal Operation (FCR-N), to the national TSO in Sweden, is defined from technology and market analyses as the use case for the HBHS. The characteristics of HPPs suitable for HBHS implementation are found theoretically, by evaluating HPP operational constraints and regulation mechanisms. With the aim of evaluating the dynamic performance of the proposed HBHS, a frequency regulation model of the NPS is built in MATLAB and Simulink. Two different HBHS architectures are introduced, the Hydro Recharge, in which the BESS is regulating the frequency and the HPP is controlling its state of charge (SoC), and the Frequency Split, in which both elements are regulating the frequency with the HPP additionally compensating for the SoC. The dynamic performance of the units is qualitatively evaluated through existing and proposed FCR-N prequalification tests, prescribed by the TSO and ENTSO-E. Quantitative performance comparison to a benchmark HPP is performed with regards to the estimated HPP regulation wear and tear and BESS degradation during 30-day operation with historical frequency data. The two proposed HBHS architectures demonstrate significant reductions of estimated HPP wear and tear compared to the benchmark unit. Simulations consistently report a 90 % reduction in the number of movements HPP regulation mechanism performs and a more than 50 % decrease in the distance it travels. The BESS lifetime is evaluated at acceptable levels and compared for different architectures. Two different applications are identified, the first being installing the HBHS to enable the HPP to pass FCR-N prequalification tests. The second application is increasing the FCR-N capacity of the HPP by installing the HBHS. The Frequency Split HBHS shows more efficient performance when installed in the first application, as opposed to the Hydro Recharge HBHS, which shows better performance in the second application. Finally, it is concluded that a large-scale implementation of HBHSs would improve the frequency quality in the NPS, linearly decreasing the amount of time outside the normal frequency band with increasing the total installed HBHS power capacity

Techno-Economic Analysis and Optimal Control of Battery Storage for Frequency Control Services, Applied to the German Market

Optimal investment in battery energy storage systems, taking into account degradation, sizing and control, is crucial for the deployment of battery storage, of which providing frequency control is one of the major applications. In this paper, we present a holistic, data-driven framework to determine the optimal investment, size and controller of a battery storage system providing frequency control. We optimised the controller towards minimum degradation and electricity costs over its lifetime, while ensuring the delivery of frequency control services compliant with regulatory requirements. We adopted a detailed battery model, considering the dynamics and degradation when exposed to actual frequency data. Further, we used a stochastic optimisation objective while constraining the probability on unavailability to deliver the frequency control service. Through a thorough analysis, we were able to decrease the amount of data needed and thereby decrease the execution time while keeping the approximation error within limits. Using the proposed framework, we performed a techno-economic analysis of a battery providing 1 MW capacity in the German primary frequency control market. Results showed that a battery rated at 1.6 MW, 1.6 MWh has the highest net present value, yet this configuration is only profitable if costs are low enough or in case future frequency control prices do not decline too much. It transpires that calendar ageing drives battery degradation, whereas cycle ageing has less impact.Comment: Submitted to Applied Energ

Non-Wire Alternatives to Capacity Expansion

Distributed energy resources (DERs) can serve as non-wire alternatives to capacity expansion by managing peak load to avoid or defer traditional expansion projects. In this paper, we study a planning problem that co-optimizes DERs investment and operation (e.g., energy efficiency, energy storage, demand response, solar photovoltaic) and the timing of capacity expansion. We formulate the problem as a large scale (in the order of millions of variables because we model the operation of DERs over a period of decades) non-convex optimization problem. Despite its non-convexities, we find its optimal solution by decomposing it using the Dantzig-Wolfe Decomposition Algorithm and solving a series of small linear problems. Finally, we present a real planning problem at the University of Washington Seattle Campus.Comment: This document is an online supplement for a paper submitted to the 2018 Power and Energy Society General Meetin