Intelligent control of PV co-located storage for feeder capacity optimization

Battery energy storage is identified as a strong enabler and a core element of the next generation grid. However, at present the widespread deployment of storage is constrained by the concerns that surround the techno-economic viability. This thesis addresses this issue through optimal integration of storage to improve the efficiency of the electricity grid. A holistic approach to optimal integration includes the development of methodologies for optimal siting, sizing and dispatch coordination of storage

An analytical method for sizing energy storage in microgrid systems to maximize renewable consumption and minimize unused storage capacity

This paper presents a novel analytical method to optimally size energy storage in microgrid systems. The method has fast calculation speeds, calculates the exact optimal, and handles non-linear models. The method first constructs a temporal storage profile of stored energy, based on how storage charges and discharges in response to renewable generation and load demand. The storage is sized according to the largest cumulative charge or discharge in the profile. In essence, the storage profile represents how storage is utilized within a given system, and the method sizes optimal storage to maximize that profile, such that storage utilization is maximized, and unutilized or wasted storage is eliminated. Maximizing storage utilization also maximizes renewable consumption and minimizes load shedding, as storage utilization is the temporal transfer of energy from renewable generation to load demand. The proposed method is extended iteratively to account for storage’s energy limits, power limits, and energy leakage. Two solar–battery case studies demonstrate the method. The first study shows that optimally sized storage does not have wasted capacity due to over-sizing, nor cause energy deficits due to under-sizing. The second case study shows increasing the storage size reduces the marginal increase in energy provided by storage, indicating diminishing returns. The diminishing return thresholds are defined by the largest daily and annual storage designs. The result shows the largest daily design only requires 3% of the annual design’s storage size, but provides 80% of the energy provided by the annual design. The proposed method can be used as a decision support tool for energy analysts, to determine required storage capacity when coupled with known renewable generation and load demand

Photovoltaics, Batteries, and Silicon Carbide Power Electronics Based Infrastructure for Sustainable Power Networks

The consequences of climate change have emphasized the need for a power network that is centered around clean, green, and renewable sources of energy. Currently, Photovoltaics (PV) and wind turbines are the only two modes of technology that can convert renewable energy of the sun and wind respectively into large-scale power for the electricity network. This dissertation aims at providing a novel solution to implement these sources of power (majorly PV) coupled with Lithium-ion battery storage in an efficient and sustainable approach. Such a power network can enable efficiency, reliability, low-cost, and sustainability with minimum impact to the environment. The first chapter illustrates the utilization of PV- and battery-based local power networks for low voltage loads as well as the significance of local DC power in the transportation sector. Chapter two focuses on the most efficient and maximum utilization of PV and battery power in an AC infrastructure. A simulated use-case for load satisfaction and feasibility analysis of 10 university-scale buildings is illustrated. The role of PV- and battery-based networks to fulfill the new demand from the electrification of the surface transportation sector discussed in Chapter three. Chapter four analyzes the PV- and battery- based network on a global perspective and proposes a DC power network with PV and complementary wind power to fulfill the power needs across the globe. Finally, the role of SiC power electronics and the design concept for an SiC based DC-to-DC converter for maximum utilization of PV/wind and battery power through enabling HVDC transmission is discussed in Chapter six

Voltage control and stability analysis in a multi-machine power system with increasing penetration of intermittent renewable energy generation.

Masters Degree. University of KwaZulu-Natal, Durban.Among multiple distributed generation (DG) supply means, photovoltaic (PV) and wind technologies are the most important and widely used renewable energy sources (RES) throughout the world. However, solar intermittency and the stochastic nature of radiation on one hand and grid integration-related issues on the other are fundamental concerns in the development and smooth deployment of solar energy contribution to conventional power systems networks. In addition, given that they modify both the structure and the operation of the distribution networks, RES increase uncertainty in power system operations, thus affecting power systems variables such as the voltage profiles and direction of network power flows. It is also largely established that a high penetration of DGs at the distribution end is associated amongst others, with voltage rises at PV buses that may lead to the violation of grid codes, if not adequately mitigated. There is a need to investigate both the effect and the impact of increasing penetration of these intermittent RES on, particularly, voltage and frequency stability power systems and the utilization thereof of such sources to improve voltage stability margins and predict voltage stability conditions. This research work investigated voltage control and stability conditions at Solar PV buses through various case studies and scenarios simulated using the Power Factory® tool, both in static and dynamic analysis modes. A modified standard IEEE 9-Bus Sub-transmission system was used to assess the voltage profile, system loadability and system stability. The comparison and discussion of the results obtained from the integration of the Solar PV and FACTS devices under various scenarios revealed that their respective impacts and abilities to improve voltage stability differ. The results confirmed that under any operating conditions, reactive power control remains the most effective method to control voltage stability and power transfer capability, especially in the context where an increasing penetration of renewable and inertia-less generating sources is planned. The results further revealed that there is a specific location and a specific siting architecture for a given size of PV that produces the best results for voltage stability, as well as improved system stability and loadability conditions for a given load distribution profile in a particular network. Lastly, the results demonstrated the effectiveness of the use of a Battery Energy Storage System (BESS) in achieving voltage control and regulation in distribution networks highly penetrated by PV generation, subsequently enabling greater RE penetration

Optimal integration of wind energy with a renewable based microgrid for industrial applications.

Wind energy in urban environments is a rapidly developing technology influenced by the terrain specifications, local wind characteristics and urban environments such as buildings architecture. The urban terrain is more complex than for open spaces and has a critical influence on wind flow at the studied site. This approach proposes an integration of the surrounding buildings in the studied site and then simulating the wind flow, considering both simple and advanced turbulence models to quantify and simulate the wind flow fields in an urban environment and evaluate the potential wind energy. These simulations are conducted with an accessible computational fluid dynamic tool (Windsim) implementing available commercial wind turbines and performed on a case study at Agder county in the southern part of Norway for an industrial facility specialized in food production. Several simulations were considered and repeated to achieve a convergence after adding the buildings to the domain, which mainly simulates the wind flow patterns, power density, and annual energy production. These simulations will be compared with previous results, which adapted different manipulation techniques applied on the same site where the elevation and roughness data were manipulated to mimic the actual conditions in the studied urban site. The current approach (adding the buildings) showed a reduction in the average wind speed and annual energy production for certain levels with increased turbulence intensity surrounding the buildings. Moreover, a feasibility study is conducted to analyze the techno-economic of the facility's hybrid system, including the planned installation of a wind energy system using commercial software (HOMER). The simulation results indicated that HOMER is conservative in estimating the annual energy production of both wind and solar power systems. Nevertheless, the analysis showed that integrating a wind turbine of 600 kW would significantly reduce the dependence on the grid and transform the facility into a prosumer with more than 1.6 GWh traded with the grid annually. However, the proposed system's net present cost would be 1.43 M USD based on installation, maintenance, and trading with the grid, without including self-consumption, which counts for approximately 1.5 GWh annually. Moreover, the proposed system has a low levelized cost of energy of 0.039$ per kWh, which is slightly above the levelized cost of wind energy but 2 to 4 times less than the installed solar panels

Smart management strategies of utility-scale energy storage systems in power networks

Power systems are presently experiencing a period of rapid change driven by various interrelated issues, e.g., integration of renewables, demand management, power congestion, power quality requirements, and frequency regulation. Although the deployment of Energy Storage Systems (ESSs) has been shown to provide effective solutions to many of these issues, misplacement or non-optimal sizing of these systems can adversely affect network performance. This present research has revealed some novel working strategies for optimal allocation and sizing of utility-scale ESSs to address some important issues of power networks at both distribution and transmission levels. The optimization strategies employed for ESS placement and sizing successfully improved the following aspects of power systems: performance and power quality of the distribution networks investigated, the frequency response of the transmission networks studied, and facilitation of the integration of renewable generation (wind and solar). This present research provides effective solutions to some real power industry problems including minimizationof voltage deviation, power losses, peak demand, flickering, and frequency deviation as well as rate of change of frequency (ROCOF). Detailed simulation results suggest that ESS allocation using both uniform and non-uniform ESS sizing approaches is useful for improving distribution network performance as well as power quality. Regarding performance parameters, voltage profile improvement, real and reactive power losses, and line loading are considered, while voltage deviation and flickers are taken into account as power quality parameters. Further, the study shows that the PQ injection-based ESS placement strategy performs better than the P injection-based approach (in relation to performance improvement), providing more reactive power compensations. The simulation results also demonstrate that obtaining the power size of a battery ESS (MVA) is a sensible approach for frequency support. Hence, an appropriate sizing of grid-scale ESSs including tuning of parameters Kp and Tip (active part of the PQ controller) assist in improving the frequency response by providing necessary active power. Overall, the proposed ESS allocation and sizing approaches can underpin a transition plan from the current power grid to a future one

Advanced models and algorithms to provide multiple grid services with battery storage systems

Battery energy storage systems (BESSs) are expected to play a major role in the power grid of the near future. These devices, capable of storing and returning electrical energy, are valuable assets to a grid that integrates more and more distributed, intermittent and renewable generation. Compared to renewable energy sources, however, battery storage systems are still in an early stage of deployment and the way to exploit them in an optimal way is still subject of research. In this respect, this thesis develops two lines of investigation to reach an optimal utilisation of these devices. In its first part, the thesis proposes a control framework to operate a utility-scale BESS connected to a distribution feeder. This control framework allows to provide a set of services: dispatch of the operation of such feeder, load levelling, frequency response. It is structured in a period-ahead and a real-time phase. The former plans the BESS operation for a given time horizon through the solution of optimization problems. These take into account the BESS state of energy as well as forecast scenarios of quantities such as the feeder prosumption and of the BESS energy needs due to the frequency response service. The real-time phase determines the BESS power injections a resolution as fast as 1 second and, in the case of the dispatch, relies on model predictive control. Moreover, the thesis proposes the formulation of a framework for the simultaneous deployment of multiple services. The objective of this is to maximise the BESS exploitation in the presence of uncertainty. All the proposed methods are validated experimentally, on the 560 kWh/720 kVA BESS installed on EPFL campus. This extensive validation demonstrates their effectiveness and deployability. In its second part, the thesis discusses the integration of electrochemical models in the control of BESSs. Such models, compared to more conventional equivalent circuits or empirical ones, can provide deeper insight in the processes occurring within Li-ion cells - the founding elements of BESSs - and by consequence a more effective operation of BESSs. The thesis proposes a method to identify the parameters of one of such models - the single particle model - and, again, validates it experimentally. Moreover, in its final chapter, the thesis provides a proof-of-concept by simulations of the advantages of the integration of electrochemical models in the control framework proposed in its first part and, in general, in BESS control

Integration of Energy Storage into a Future Energy System with a High Penetration of Distributed Photovoltaic Generation

Energy storage units (ESU) are increasingly used in electrical distribution systems because they can perform many functions compared with traditional equipment. These include peak shaving, voltage regulation, frequency regulation, provision of spinning reserve, and aiding integration of renewable generation by mitigating the effects of intermittency. As is the case with other equipment on electric distribution systems, it is necessary to follow appropriate methodologies in order to ensure that ESU are installed in a cost-effective manner and their benefits are realized. However, the necessary methodologies for integration of ESU have not kept pace with developments in both ESU and distribution systems. This work develops methodologies to integrate ESU into distribution systems by selecting the necessary storage technologies, energy capacities, power ratings, converter topologies, control strategies, and design lifetimes of ESU. In doing so, the impact of new technologies and issues such as volt-VAR optimization (VVO), intermittency of photovoltaic (PV) inverters, and the smart PV inverter proposed by EPRI are considered. The salient contributions of this dissertation follow. A unified methodology is developed for storage technology selection, storage capacity selection, and scheduling of an ESU used for energy arbitrage. The methodology is applied to make technology recommendations and to reveal that there exists a cost-optimal design lifetime for such an ESU. A methodology is developed for capacity selection of an ESU providing both energy arbitrage and ancillary services under a stochastic pricing structure. The ESU designed is evaluated using ridge regression for price forecasting; Ridge regression applied to overcome numerical stability and overfitting issues associated with the large number of highly correlated predictors. Heuristics are developed to speed convergence of simulated annealing for placement of distributed ESU. Scaling and clustering methods are also applied to reduce computation time for placement of ESU (or any other shunt-connected device) on a distribution system. A probabilistic model for cloud-induced photovoltaic (PV) intermittency of a single PV installation is developed and applied to the design of ESU