Promoting peak shaving while minimizing electricity consumption payment for residential consumers by using storage devices

Turkish Journal of Electrical Engineering & Computer Sciences http://journals.tubitak.gov.tr/elektrik/ Turk J Elec Eng & Comp Sci (2017) 25: 3725 – 3737 c TÜBİTAK ⃝ doi:10.3906/elk-1606-152 Research Article Promoting peak shaving while minimizing electricity consumption payment for residential consumers by using storage devices Simona Vasilica OPREA1 , Adela BARA1,∗, Mahmut Erkut CEBECİ2 , Osman Bülent TÖR2 1 The Bucharest University of Economic Studies, Bucharest, Romania 2 EPRA Engineering Procurement Research Analysis, Ankara, Turkey Received: 10.06.2016 • Accepted/Published Online: 31.03.2017 • Final Version: 05.10.2017 Abstract: Nowadays, smart meters, sensors, and advanced electricity tariff mechanisms such as time-of-use (ToU), critical peak pricing tariff, and real time tariff enable electricity consumption optimization for residential consumers. The main scope of such mechanisms is to promote peak shaving, which leads to minimization of technical losses and avoidance (or delay) of grid onerous investments. This paper proposes a method to determine the optimum capacity of a storage device (SD) that significantly contributes to peak shaving of electricity consumption for residential consumers. Detailed modelling of diverse electric appliances’ behavior and consumers’ necessities is addressed in order to determine the optimum capacity of the SD. The effects of a small scale photovoltaic panel (PV) owned by residential consumers are also analyzed. Key words: Consumption optimization, storage, peak shaving, time-of-use tariff, prosumer 1. Introduction Enhancement of grid infrastructure is among the grid operator’s investments necessary to supply demand increase, upgrade lines and substations, and integrate renewable energy sources (RES). According to the Ten Years Network Development Plan (TYNDP) developed by ENTSO-E countries, 150 billion Euros were proposed for CAPEX in 2014 just for grid expansion at European level (European Network of Transmission System Operators for Electricity. 10-Year Network Development Plan 2014). In Romania, over 1 billion Euros are necessary for transmission grid expansion according to the Transmission grid development plan for 2014–2023 elaborated by Transelectrica. Advanced electricity tariff mechanisms are aimed to contribute to peak shaving, as practically proven worldwide. The literature shows that an electricity consumer can save up to 50% of the electricity payment since the off-peak electricity tariff is one-third of the peak tariff [1]. This paper presents a method to determine the optimum capacity of a storage device (SD) that contributes to the peak shaving of a residential consumer. Therefore, the SD is proposed to be supplied by the grid operator for free, since the residential consumer is interested in a time-of-use (ToU) tariff mechanism that incentivizes minimization of his/her electricity bill. However, the ToU tariff will increase the demand peak of the consumer at certain hours when the tariff is low (e.g., after midnight). In response, charging and discharging cycles of the SD are proposed to be programmed by the grid operator (manually or remotely) in such way that the SD ∗ Correspondence: 3725 OPREA et al./Turk J Elec Eng & Comp Sci operates in order to shave the peak. The more the consumer pays attention to schedule his/her consumption at low tariff rates, the more both the consumer and grid operator benefit. The literature includes many studies that address minimization of electricity bills and peak shaving mechanisms by means of SDs. In [2], the authors describe a simulator that optimizes electricity consumption of residential consumers that have controllable and uncontrollable devices, SDs, and generation sources. The objective function of the optimization process is to minimize payment by optimally connecting/disconnecting the controllable devices based on the electricity tariff. A drawback of this approach could be that most of the consumers might tend to response to the incentive, which would lead to new load peaks. In [3], the authors apply stochastic optimization based on a scenario approach by Monte Carlo simulation for minimization of estimated payment for the entire day and mixed integer linear programing (MILP) algorithm for optimal management of electricity residential consumption taking into account real time tariffs. In [4], problems regarding the private sensible information related to electricity consumption that could appear while managing the recorded consumption by means of smart metering systems are addressed. The authors of [5] and [6] perform consumption optimization by using genetic algorithms. The optimization method is easy and presents a higher accuracy compared with traditional methods. In [7], the authors foresee major obstacles regarding the advanced tariff systems, such as consumers’ lack of information related to the tariff variations and lack of automatic systems for consumption management. In response, the authors propose an optimal and automatic framework for planning residential electricity consumption by making a balance between minimizing the payment and minimizing the waiting time before the operation of each device. In [8], an optimization demand response through peak shaving is proposed. It uses an efficient linear programming formulation for prosumers’ demand change. This approach is focused on peak minimization of electricity consumption based on fuel supply for self-generation. In [9], the author proposes a peak shaving energy management system that adapts the house appliances to the available power such as RES and SDs with the help of sensors by monitoring and controlling algorithms. In [10], the effects of energy management are analyzed from the residential consumer perspective. The authors proposed a prototype for a house with PV, lead–acid batteries, controllable appliances, and smart metering and showed the nonlinear relation between electricity flows and SDs’ capacity. Different from the literature, this paper proposes a model for electricity consumption optimization for residential consumers with different modern consumption appliances. The proposed model takes into account a dual approach that considers two objective functions: minimization of consumption peak and minimization of electricity payment. Based on the results of the two approaches, the optimum capacity of a SD, which can effectively improve the consumption optimization process, is determined. The paper is organized as follows. Problem definition is addressed in Section 2, along with the flowchart of the proposed methodology. Section 3 presents formulation of the optimization problem and its simulation results. Calculation of the optimum capacity of the SD, which might be provided by the grid operator for free to ensure peak shaving in order to avoid new peaks, is described in Section 4. The effects of PV on optimizing electricity consumption of residential consumers are addressed in Section 5. Conclusion (...truncated)