Large-Scale Modeling and DR Control of Electric Water Heaters With Energy Star and CTA-2045 Control Types in Distribution Power Systems

The paper proposes a generalized energy storage (GES) model for battery energy storage systems (BESS), electric water heaters (EWH) and heating, ventilation, and air-conditioning (HVAC) systems to enable demand response control complying to Energy Star and CTA-2045 standards. The demand response control has been implemented in the DER integration testbed, which was originally developed by EPRI, to demonstrate that the “energy content” and “energy take” for BESS and EWH with mixing valve technology are comparable for typical residential ratings. A distribution power system was modeled using the modified IEEE 123-bus feeder system, measured residential loads, and EWH power simulated based on realistic hot water draws from CBECC-Res software. The demand response control, which complies to CTA-2045 standards was implemented to the EWHs considering the energy take values. Results demonstrate that the EWHs can be controlled to postpone the peak power at the distribution system level and provide a large amount of energy storage, while maintaining system robustness. The impact on occupant comfort was also analyzed

Optimal Scheduling for Energy Storage Systems in Distribution Networks

[EN] Distributed energy storage may play a key role in the operation of future low-carbon power systems as they can help to facilitate the provision of the required flexibility to cope with the intermittency and volatility featured by renewable generation. Within this context, this paper addresses an optimization methodology that will allow managing distributed storage systems of different technology and characteristics in a specific distribution network, taking into account not only the technical aspects of the network and the storage systems but also the uncertainties linked to demand and renewable energy variability. The implementation of the proposed methodology will allow facilitating the integration of energy storage systems within future smart grids. This paper's results demonstrate numerically the good performance of the developed methodology.This research was funded by European Regional Development Fund (Comunidad Valenciana FEDER 2014-2020 PO, CCI number: 2014ES16RFOP013) and the ITE-IVACE collaboration agreement corresponding to the annuity 2019 (file: IMDEEA-2019-38).Escoto Simó, M.; Montagud, M.; González-Cobos, N.; Belinchón, A.; Trujillo, AV.; Romero-Chavarro, JC.; Diaz-Cabrera, JC.... (2020). Optimal Scheduling for Energy Storage Systems in Distribution Networks. Energies. 13(15):1-13. https://doi.org/10.3390/en13153921S1131315The Impact of the Covid-19 Crisis on Clean Energy Progresshttps://www.iea.org/articles/the-impact-of-the-covid-19-crisis-on-clean-energy-progressSustainable Development Goalshttps://www.un.org/sustainabledevelopment/Mesarić, P., & Krajcar, S. (2015). Home demand side management integrated with electric vehicles and renewable energy sources. Energy and Buildings, 108, 1-9. doi:10.1016/j.enbuild.2015.09.001Rodrigues, E. M. G., Godina, R., Santos, S. F., Bizuayehu, A. W., Contreras, J., & Catalão, J. P. S. (2014). Energy storage systems supporting increased penetration of renewables in islanded systems. Energy, 75, 265-280. doi:10.1016/j.energy.2014.07.072Hirsch, A., Parag, Y., & Guerrero, J. (2018). Microgrids: A review of technologies, key drivers, and outstanding issues. Renewable and Sustainable Energy Reviews, 90, 402-411. doi:10.1016/j.rser.2018.03.040Clean Energy for All Europeans Packagehttps://ec.europa.eu/energy/topics/energy-strategy/clean-energy-all-europeans_enVISION 2050 Integrating Smart Networks for the Energy Transition: Serving Society and Protecting the Environmenthttps://www.etip-snet.eu/etip_publ/etip-snet-vision-2050/Staying on Course: Renewable Energy in the Time of COVID-19https://www.irena.org/newsroom/pressreleases/2020/Apr/Staying-on-Course-Renewable-Energy-in-the-time-of-COVID19ElNozahy, M. S., Abdel-Galil, T. K., & Salama, M. M. A. (2015). Probabilistic ESS sizing and scheduling for improved integration of PHEVs and PV systems in residential distribution systems. Electric Power Systems Research, 125, 55-66. doi:10.1016/j.epsr.2015.03.029Li, Y., Yang, Z., Li, G., Zhao, D., & Tian, W. (2019). Optimal Scheduling of an Isolated Microgrid With Battery Storage Considering Load and Renewable Generation Uncertainties. IEEE Transactions on Industrial Electronics, 66(2), 1565-1575. doi:10.1109/tie.2018.2840498Ciupăgeanu, D.-A., Lăzăroiu, G., & Barelli, L. (2019). Wind energy integration: Variability analysis and power system impact assessment. Energy, 185, 1183-1196. doi:10.1016/j.energy.2019.07.136Hemmati, R., Saboori, H., & Jirdehi, M. A. (2017). Stochastic planning and scheduling of energy storage systems for congestion management in electric power systems including renewable energy resources. Energy, 133, 380-387. doi:10.1016/j.energy.2017.05.167Xie, S., Hu, Z., & Wang, J. (2020). Two-stage robust optimization for expansion planning of active distribution systems coupled with urban transportation networks. Applied Energy, 261, 114412. doi:10.1016/j.apenergy.2019.114412Saboori, H., & Jadid, S. (2020). Optimal scheduling of mobile utility-scale battery energy storage systems in electric power distribution networks. Journal of Energy Storage, 31, 101615. doi:10.1016/j.est.2020.101615Kassai, M. (2017). Prediction of the HVAC Energy Demand and Consumption of a Single Family House with Different Calculation Methods. Energy Procedia, 112, 585-594. doi:10.1016/j.egypro.2017.03.1121Zheng, Y., Zhao, J., Song, Y., Luo, F., Meng, K., Qiu, J., & Hill, D. J. (2018). Optimal Operation of Battery Energy Storage System Considering Distribution System Uncertainty. IEEE Transactions on Sustainable Energy, 9(3), 1051-1060. doi:10.1109/tste.2017.2762364Jayasekara, N., Masoum, M. A. S., & Wolfs, P. J. (2016). Optimal Operation of Distributed Energy Storage Systems to Improve Distribution Network Load and Generation Hosting Capability. IEEE Transactions on Sustainable Energy, 7(1), 250-261. doi:10.1109/tste.2015.2487360Mehrjerdi, H., & Hemmati, R. (2019). Modeling and optimal scheduling of battery energy storage systems in electric power distribution networks. Journal of Cleaner Production, 234, 810-821. doi:10.1016/j.jclepro.2019.06.195Macedo, L. H., Franco, J. F., Rider, M. J., & Romero, R. (2015). Optimal Operation of Distribution Networks Considering Energy Storage Devices. IEEE Transactions on Smart Grid, 6(6), 2825-2836. doi:10.1109/tsg.2015.2419134Lunci Hua, Jia Wang, & Chi Zhou. (2014). Adaptive Electric Vehicle Charging Coordination on Distribution Network. IEEE Transactions on Smart Grid, 5(6), 2666-2675. doi:10.1109/tsg.2014.2336623Guo, X., Guo, X., & Su, J. (2013). Improved Support Vector Machine Short-term Power Load Forecast Model Based on Particle Swarm Optimization Parameters. Journal of Applied Sciences, 13(9), 1467-1472. doi:10.3923/jas.2013.1467.1472Bordin, C., Anuta, H. O., Crossland, A., Gutierrez, I. L., Dent, C. J., & Vigo, D. (2017). A linear programming approach for battery degradation analysis and optimization in offgrid power systems with solar energy integration. Renewable Energy, 101, 417-430. doi:10.1016/j.renene.2016.08.066IEEE PES AMPS DSAS Test Feeder Working Grouphttps://site.ieee.org/pes-testfeeders/resources/Lotero, R. C., & Contreras, J. (2011). Distribution System Planning With Reliability. IEEE Transactions on Power Delivery, 26(4), 2552-2562. doi:10.1109/tpwrd.2011.2167990Munoz-Delgado, G., Contreras, J., & Arroyo, J. M. (2015). Joint Expansion Planning of Distributed Generation and Distribution Networks. IEEE Transactions on Power Systems, 30(5), 2579-2590. doi:10.1109/tpwrs.2014.236496

Control and Stability of Residential Microgrid with Grid-Forming Prosumers

The rise of the prosumers (producers-consumers), residential customers equipped with behind-the-meter distributed energy resources (DER), such as battery storage and rooftop solar PV, offers an opportunity to use prosumer-owned DER innovatively. The thesis rests on the premise that prosumers equipped with grid-forming inverters can not only provide inertia to improve the frequency performance of the bulk grid but also support islanded operation of residential microgrids (low-voltage distribution feeder operated in an islanded mode), which can improve distribution grids’ resilience and reliability without purposely designing low-voltage (LV) distribution feeders as microgrids. Today, grid-following control is predominantly used to control prosumer DER, by which the prosumers behave as controlled current sources. These grid-following prosumers deliver active and reactive power by staying synchronized with the existing grid. However, they cannot operate if disconnected from the main grid due to the lack of voltage reference. This gives rise to the increasing interest in the use of grid-forming power converters, by which the prosumers behave as voltage sources. Grid-forming converters regulate their output voltage according to the reference of their own and exhibit load sharing with other prosumers even in islanded operation. Making use of grid-forming prosumers opens up opportunities to improve distribution grids’ resilience and enhance the genuine inertia of highly renewable-penetrated power systems. Firstly, electricity networks in many regional communities are prone to frequent power outages. Instead of purposely designing the community as a microgrid with dedicated grid-forming equipment, the LV feeder can be turned into a residential microgrid with multiple paralleled grid-forming prosumers. In this case, the LV feeder can operate in both grid-connected and islanded modes. Secondly, gridforming prosumers in the residential microgrid behave as voltage sources that respond naturally to the varying loads in the system. This is much like synchronous machines extracting kinetic energy from rotating masses. “Genuine” system inertia is thus enhanced, which is fundamentally different from the “emulated” inertia by fast frequency response (FFR) from grid-following converters. Against this backdrop, this thesis mainly focuses on two aspects. The first is the small-signal stability of such residential microgrids. In particular, the impact of the increasing number of grid-forming prosumers is studied based on the linearised model. The impact of the various dynamic response of primary sources is also investigated. The second is the control of the grid-forming prosumers aiming to provide sufficient inertia for the system. The control is focused on both the inverters and the DC-stage converters. Specifically, the thesis proposes an advanced controller for the DC-stage converters based on active disturbance rejection control (ADRC), which observes and rejects the “total disturbance” of the system, thereby enhancing the inertial response provided by prosumer DER. In addition, to make better use of the energy from prosumer-owned DER, an adaptive droop controller based on a piecewise power function is proposed, which ensures that residential ESS provide little power in the steady state while supplying sufficient power to cater for the demand variation during the transient state. Proposed strategies are verified by time-domain simulations

Renewable energy communities in Islands : a Maltese case study

Renewable energy communities are considered as key elements for transforming the present fossil fuel-based energy systems of islands into renewable-based energy systems. This study shows how renewable energy communities can be deployed in the Maltese context to achieve higher penetration of residential-scale photovoltaic systems. Case studies for five renewable energy communities in the Maltese LV distribution network have been analyzed in detail. A novel community battery energy storage sizing strategy was proposed to determine the optimal storage capacity at each energy community. The main objective of the community battery storage in each REC is to minimize the reverse power injection in the grid (minimize the total reverse energy and reverse peak power values), as well as to reduce the peak evening electricity demand. The optimal sizes for communal BESSs were determined to be of 57 kWh (EC 1), 55 kWh (EC 2), 31 kWh (EC 3), 37 kWh (EC 4) and 10 kWh (EC 5), respectively. The community storage systems were observed to reduce the overall impact of all five energy communities on the grid infrastructure. Power system simulations were performed for a typical spring day to evaluate the impact of communal BESS placement on the node voltages for all five energy communities. The results showed that the community storage was more effective at reducing the node rms voltage magnitudes when deployed at the end of the respective energy communities, rather than at the beginning of the community. During peak generation hours, reductions of up to 0.48% in the node rms voltage magnitudes were observed. This contrasts with reductions of only 0.19% when the community storage was deployed at the beginning of the energy communities.peer-reviewe

A fast and efficient coordinated vehicle-to-grid discharging control scheme for peak shaving in power distribution system.

This study focuses on the potential role of plug-in electric vehicles (PEVs) as a distributed energy storage unit to provide peak demand minimization in power distribution systems. Vehicle-to-grid (V2G) power and currently available information transfer technology enables utility companies to use this stored energy. The V2G process is first formulated as an optimal control problem. Then, a two-stage V2G discharging control scheme is proposed. In the first stage, a desired level for peak shaving and duration for V2G service are determined off-line based on forecasted loading profile and PEV mobility model. In the second stage, the discharging rates of PEVs are dynamically adjusted in real time by considering the actual grid load and the characteristics of PEVs connected to the grid. The optimal and proposed V2G algorithms are tested using a real residential distribution transformer and PEV mobility data collected from field with different battery and charger ratings for heuristic user case scenarios. The peak shaving performance is assessed in terms of peak shaving index and peak load reduction. Proposed solution is shown to be competitive with the optimal solution while avoiding high computational loads. The impact of the V2G management strategy on the system loading at night is also analyzed by implementing an off-line charging scheduling algorithm

Application of a simplified thermal-electric model of a sodium-nickel chloride battery energy storage system to a real case residential prosumer

Recently, power system customers have changed the way they interact with public networks, playing a more and more active role. End-users first installed local small-size generating units, and now they are being equipped with storage devices to increase the self-consumption rate. By suitably managing local resources, the provision of ancillary services and aggregations among several end-users are expected evolutions in the near future. In the upcoming market of household-sized storage devices, sodium-nickel chloride technology seems to be an interesting alternative to lead-acid and lithium-ion batteries. To accurately investigate the operation of the NaNiCl2 battery system at the residential level, a suitable thermoelectric model has been developed by the authors, starting from the results of laboratory tests. The behavior of the battery internal temperature has been characterized. Then, the designed model has been used to evaluate the economic profitability in installing a storage system in the case that end-users are already equipped with a photovoltaic unit. To obtain realistic results, real field measurements of customer consumption and solar radiation have been considered. A concrete interest in adopting the sodium-nickel chloride technology at the residential level is confirmed, taking into account the achievable benefits in terms of economic income, back-up supply, and increased indifference to the evolution of the electricity market

A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies

In a power system with high penetration of renewable power sources, gas-fired units can be considered as a back-up option to improve the balance between generation and consumption in short-term scheduling. Therefore, closer coordination between power and natural gas systems is anticipated. This article presents a novel hybrid information gap decision theory (IGDT)-stochastic cooptimization problem for integrating electricity and natural gas networks to minimize total operation cost with the penetration of wind energy. The proposed model considers not only the uncertainties regarding electrical load demand and wind power output, but also the uncertainties of gas load demands for the residential consumers. The uncertainties of electric load and wind power are handled through a scenario-based approach, and residential gas load uncertainty is handled via IGDT approach with no need for the probability density function. The introduced hybrid model enables the system operator to consider the advantages of both approaches simultaneously. The impact of gas load uncertainty associated with the residential consumers is more significant on the power dispatch of gas-fired plants and power system operation cost since residential gas load demands are prior than gas load demands of gas-fired units. The proposed framework is a bilevel problem that can be reduced to a one-level problem. Also, it can be solved by the implementation of a simple concept without the need for Karush–Kuhn–Tucker conditions. Moreover, emerging flexible energy sources such as the power to gas technology and demand response program are considered in the proposed model for increasing the wind power dispatch, decreasing the total operation cost of the integrated network as well as reducing the effect of system uncertainties on the total operating cost. Numerical results indicate the applicability and effectiveness of the proposed model under different working conditions

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