MAXIMIZING LOCAL PV UTILIZATION USING SMALL-SCALE BATTERIES AND FLEXIBLE THERMAL LOADS Evangelos Vrettos *,1 , Andreas Witzig # , Roland Kurmann # , Stephan Koch * , and Göran Andersson * * Power Systems Laboratory, ETH Zurich, Physikstrasse 3, Zurich, Switzerland # Vela Solaris AG, Stadthausstrasse 125, Winterthur, Switzerland 1 Corresponding author, phone: +41 44 632 75 06, fax: +41 44 632 12 52, email: vrettos@eeh.ee.ethz.ch ABSTRACT: High PV utilization ratios in buildings, i.e. the consumption of most of the PV energy within the building premises, can reduce the energy losses in distribution networks, and mitigate overvoltages and transformer overloadings. For this reason, some countries have adopted, or are discussing, regulatory instruments to motivate local utilization of PV energy. In this paper, we investigate the potential of maximizing the PV utilization ratio using small-scale batteries and flexible thermal loads. We propose four rule-based control algorithms for batteries and heat pumps, and calculate the building energy flows and PV self-consumption ratios on an annual basis using the commercial software Polysun. Based on the results, we provide insights on the potential of thermal and battery storage for PV self-consumption maximization and indicate synergies among them. Also, we identify the battery capacities that maximize the savings over the investment lifetime for different combinations of battery capital costs and PV feed-in tariffs (FITs). The results show that maximizing PV self-consumption can be an interesting business case due to the decreasing trends in battery costs and FITs. Keywords: PV self-consumption, battery, load management, heat pump, control strategy 1 INTRODUCTION 1.1 Motivation Large shares of photovoltaic generation (PV) have been introduced in the power system over the last years, and projections show that the worldwide installed PV capacity will continue to increase [1]. A large portion of the installed PV power is concentrated on the roofs of residential and commercial buildings. Depending on financial incentives, locally produced PV energy can be either self-consumed in the building premises or fed into the grid. Maximizing self-consumption of PV energy is preferable from a technical point of view for the following reasons [2]: (a) less overvoltages occur, (b) cable and transformer thermal limits are less likely to be violated, and (c) the losses in the distribution network are minimized. The technical advantages of PV self-consumption have been understood by power system regulators in some countries, which have adopted, or are discussing, instruments to motivate local utilization of PV energy in buildings. For example, in Germany the feed-in tariff (FIT) for PV plants has already fallen below the residential customer electricity tariff [3]. This creates an interest for self-consumption of PV electricity even in the absence of regulatory measures, such as the previously existing bonus on self-consumed PV electricity in Germany [4]. However, whether this interest translates to a business case or not needs further investigation. The financial advantages of PV self-consumption need to be taken into account in the planning phase of rooftop PV installations. For this purpose, algorithms to maximize local PV utilization should be incorporated into software for energy simulations in buildings. In this context, this paper presents four control algorithms to maximize PV self-consumption with controllable thermal loads and batteries. To illustrate their applicability, the algorithms were integrated into Polysun, a commercial software for energy simulations in buildings [5, 6], which was extended accordingly by adding new features. 1.2 Related work Optimal operation strategies for residential and commercial buildings with PV installations and battery storage have recently attracted the interest of many researchers. Some papers, for example [7-10], investigate planning and operation strategies for residential buildings with flexible thermal loads and/or battery storage to reduce electricity costs, but without explicitly addressing the problem of PV self-consumption. Other papers, such as [11, 12], study the potential of PV self-consumption increase using stationary lithium-ion batteries and/or electric vehicles. More relevant to our paper is the work presented in [13], where active demand side management and storage are compared in terms of potential for PV self-consumption optimization in residential buildings. Event-based loads such as washing machines and dishwashers were considered in [13]; however, heating and cooling loads are neglected. 1.3 Contribution This paper addresses the problem of maximizing PV self-consumption in buildings and its contribution is threefold: (a) four simple rule-based control algorithms for batteries and flexible thermal loads, e.g. heating and cooling loads, are developed and integrated into Polysun; (c) the potential for PV self-consumption maximization is evaluated and the respective cost savings are estimated via annual energy simulations, (d) the effect of uncertain parameters, such as battery costs and FITs, on the optimal building configuration are investigated. Thermal loads in buildings are considered in this work due to their inherent flexibility. Heating and cooling appliances, such as heat pumps (HPs), air conditioners and radiators, are operated using a hysteresis controller based on a temperature set-point and a dead-band. For heating loads, whenever the temperature falls below the lower dead-band limit, the appliance turns on and keeps heating the room till the temperature reaches the higher dead-band limit. At this point, the appliance turns off and a new cycle begins. To preserve the occupants’ comfort, the room temperature must be kept within the dead-band. However, the actual on/off state of the appliance at a particular instance is not important. Therefore, the appliance consumption can be shifted in time without noticeable effects on the occupants. In this work, an HP