Rooftop Photovoltaic Units Research Articles

Community Battery Storage Systems Planning for Voltage Regulation in Low Voltage Distribution Systems

The regulation of the grid voltage within operational limits becomes increasingly challenging as residential photovoltaic (PV) adoption rises. Therefore, this study proposes a method for the efficient planning of multiple community battery energy storage systems (BESS) in low voltage distribution systems embedded with high residential rooftop PV units. A bi-level optimization method based on a Neural Network Optimization Algorithm is developed to regulate the voltage in grid-connected solar PV. Since BESS characteristics are crucial for the reliable operation of the distribution networks, the objective of the bi-level optimization problem is to optimally place and operate BESS collectively at a distributed system level. The charging/discharging protocol of the batteries management system is obtained utilizing linear programming that minimizes the daily voltage signal. Simulations were carried out on a modified IEEE low voltage test feeder to examine the impact of PV integration and BESS installation on the voltage profile. Experimental results show the efficacy of the proposed method in enabling the utility to determine the optimal location, capacity, and number of BESS in the distribution system to keep the network voltage magnitude within acceptable bounds. In addition, results demonstrate that the network topology, load profiles, and amount of PV power highly influence the BESS characteristics.

Predictive energy management of residential buildings while self-reporting flexibility envelope

In recent years, renewable energy resources have been increasingly embedded in the distribution grids, raising new issues such as reverse power flows, and challenging the traditional distribution system operation. In order to mitigate these issues, it has been proposed to operate the distribution system more flexibly. For instance, residential buildings are ideal candidates to offer energy flexibility locally and defer avoidable and expensive system expansions. Due to advances in smart meter technologies and trends towards digitalization, it becomes more and more common that electrical appliances in residential buildings are equipped with remote communication and control capabilities. This paper aims at quantifying a flexibility envelope of actively controlled flexible buildings and at analyzing the sensitivity of flexibility levels with respect to system configuration, control strategy and objective function settings. We consider rooftop photovoltaic units, air-sourced heat pumps for space heating and domestic hot water, thermal energy storage and electric vehicles. The results show that an optimal control aiming at minimizing energy costs while limiting peak power can lead to savings of up to 25% compared to the existing rule-based control. When carbon emissions are considered in the cost function, the optimized controller leads to an emission reduction of up to 21%. The time-dependent quantification of the flexibility envelope further reveals that high and low power levels can only be sustained for a limited period, whereas medium power levels can be sustained the longest.

Framework of virtual microgrids formation using community energy storage in residential networks with rooftop photovoltaic units

This paper presents a framework for forming Virtual Microgrids (VMs) centered around Community Energy Storage (CES) in residential networks with Photovoltaic (PV) units. The framework considers major revenue streams for CES to justify the economic viability and operational feasibility of the VMs. In this framework, a methodology is introduced to optimally cluster a residential distribution grid into VMs. Subsequently, a cost-benefit analysis considering a new business model is conducted to identify the optimal location, size and operational characteristic of CES in each VMs. The proposed framework is tested on IEEE 33-bus test distribution grid, which reflects a typical residential network. Numerical results demonstrated that the proposed framework enables power utility or third party companies to cluster a residential network with rooftop PV into a specified number of VMs and identify the optimal allocation of CES in each VM for maximizing the total net present value of CES deployment. Furthermore, the presented business model generates a profit of almost 35% of the total financial benefit of CES and effectively assist in reducing consumers’ electricity bills.

Dynamic voltage stability of unbalanced DNs with high penetration of roof‐top PV units

Dynamic voltage instability (DVI) issue is one of the primary concerns in distribution networks (DNs) due to the growing integration of low-inertia compressor motor loads. Moreover, the inherent unbalanced nature of DNs as a result of unbalanced load could make the DVI issues more severe. Furthermore, with the way rooftop photo-voltaic (PV) units are integrated, often in the form of single-phase units, DVI issues might be a threat to secure operation of DNs (both low and medium voltage) in the future. Though dynamic voltage stability (DVS) has been researched well in DNs, how imbalance system would influence the phenomena yet to be fully understood, especially with growing number of PV units. Although the roof-top PV units are connected at low-voltage DNs, their impacts on the DVS can propagate to the immediate medium-voltage DNs. Hence, this paper systematically examines the impacts of imbalance on the DVS of medium-voltage DNs with high PV penetrations first. The degree of unbalance is defined, and then DVS is thoroughly investigated considering various unbalance scenarios. Two indices, namely Voltage Nadir (VN) and Rate of Change of Voltage Recovery (ROCOVR) are proposed for clear understanding of the issue. It is observed that the increment of system imbalance can significantly influence the DVS in a deprived way. Finally, this paper has discussed and compared mitigation strategies with respect to cost and DVS improvement. Case studies are conducted on two IEEE benchmark test systems, namely, IEEE 4 bus and IEEE 15 bus systems. It is revealed that reactive power injection by rooftop PV inverters would be the most cost-effective solution to avoid a potential instability problem while mitigating the impacts of imbalance.

Short-Term Voltage Stability Enhancement in Residential Grid With High Penetration of Rooftop PV Units

Short-term voltage instability (STVI) imposes a severe threat to modern distribution networks (DNs) where a large number of intermittent distributed generator (DG) units, like rooftop photovoltaic (PV), is being integrated. Consequently, most of the international standards have been revised by incorporating the requirement of the dynamic voltage support (DVS) through DG units, which is a promising approach to alleviate the STVI. In this paper, a novel DVS strategy is proposed to improve the short-term voltage stability (STVS) in residential grids. In comparison with other DVS strategies, the proposed DVS scheme maximizes the active power support from PV units following a contingency utilizing the maximum allowable current of the PV inverters. Moreover, the inverter design margin is taken into account in designing the proposed scheme to limit the injected grid current within the maximum allowable inverter current. The impact of the inverter design margin on the STVS is explained, and the effectiveness of the proposed strategy compared with the conventional DVS is demonstrated. The feasibility of the DVS control strategies in practical application is studied. Several case studies are carried out on benchmark IEEE 4 bus and IEEE 13 node test feeder systems, and finally, on a ring-type DN. The results show that the proposed DVS scheme is feasible, and achieved superior performance compared to the other strategies. Furthermore, it has been shown that implementation of the proposed DVS scheme can avoid the installation of an expensive 1200-kVA D-STATCOM for STVS improvement in the target system.

Deploying residential rooftop PV units for office building use: a case study in Shanghai

The utilization of distributed power generation system plays an essential role in the design of resilient cities. With the ever increasing of efficiency and decreasing of production cost, Photovoltaic (PV) system is becoming a globally welcomed city component. During the design of PV systems, the matching of demand and supply power curve is critical. This paper evaluates the PV usage potential in different neighborhoods of Shanghai through matching the rooftop PV generation profile with the electricity demands of office buildings. The typical electricity use pattern of an office building is calculated by clustering method with data from a sub-metering platform, and PV generation curve is generated through simulation approach. Case studies were done in 140 neighborhoods of Shanghai City, and theoretical self-utilization ratio and PV utilization of each neighborhood were calculated.

Optimal Residential Load Scheduling Under Utility and Rooftop Photovoltaic Units

With the rapid advancement in technology, electrical energy consumption is increasing rapidly. Especially, in the residential sector, more than 80% of electrical energy is being consumed because of consumer negligence. This brings the challenging task of maintaining the balance between the demand and supply of electric power. In this paper, we focus on the problem of load balancing via load scheduling under utility and rooftop photovoltaic (PV) units to reduce electricity cost and peak to average ratio (PAR) in demand-side management. For this purpose, we adopted genetic algorithm (GA), binary particle swarm optimization (BPSO), wind-driven optimization (WDO), and our proposed genetic WDO (GWDO) algorithm, which is a hybrid of GA and WDO, to schedule the household load. For energy cost estimation, combined real-time pricing (RTP) and inclined block rate (IBR) were used. The proposed algorithm shifts load from peak consumption hours to off-peak hours based on combined pricing scheme and generation from rooftop PV units. Simulation results validate our proposed GWDO algorithm in terms of electricity cost and PAR reduction while considering all three scenarios which we have considered in this work: (1) load scheduling without renewable energy sources (RESs) and energy storage system (ESS), (2) load scheduling with RESs, and (3) load scheduling with RESs and ESS. Furthermore, our proposed scheme reduced electricity cost and PAR by 22.5% and 29.1% in scenario 1, 47.7% and 30% in scenario 2, and 49.2% and 35.4% in scenario 3, respectively, as compared to unscheduled electricity consumption.

Analytical approach to assess the loadability of unbalanced distribution grid with rooftop PV units

Photovoltaic (PV) power is a promising source of renewable energy, which is expected to provide a significant share of electrical energy in the near future. However, a stable voltage condition of the system must be always insured even with a high level of PV penetration. It should be noted that a large portion of PV systems are single-phase and they are being integrated into distribution network (DN). In addition, the DNs are unbalanced due to their loads and line characteristics. As a result, it is necessary to investigate the impact of power from both single and three phase PV units on the voltage stability of unbalanced DN. This paper has proposed an analytical methodology to investigate the static voltage stability of unbalanced DN with high PV penetration considering both single and three phase connections. For this purpose, the loadability of general unbalanced distribution system and how it is affected by PV power is analytically investigated for both single and three phase PV integration scenarios. In addition, the impact of reactive power capability of PV systems on the loadability has been assessed. Analytical outcomes are further studied and justified using results from IEEE 37-bus DN. Presented results conclude that both unbalanced system, and single and three phase PV penetrations must be taken into account to accurately assess the static voltage stability of practical DN.

Strategic allocation of community energy storage in a residential system with rooftop PV units

The electrical power sector has entered an era of decarbonizing energy generation by accommodating more Renewable Energy Sources (RES), especially solar energy in the power grid. However, high penetration of such a resource has negative impacts on the power network such as power fluctuations, reverse power flows and voltage rises. Energy Storage (ES) offers an effective solution to addressing those challenges while improving the load factor as well as the utilization of network infrastructures. This paper proposes a new framework to integrate Community Energy Storage (CES) units in an existing residential community system with rooftop solar Photovoltaic (PV) units. In this framework, three analytical approaches are respectively developed to handle three important parameters of the CES integration (i.e. locations, sizes and operational characteristics) to enhance network performances. Firstly, a simple approach is developed on the basis of a Center of Gravity (COG) theory to determine the location of CES for minimizing the annual energy loss. Secondly, a new analytical formulation based on a load following control method is presented to identify the proper rated capacity of CES and its hourly dispatch strategy for achieving a desired annual load factor. Lastly, a technique to estimate the optimal operational characteristic of CES is proposed for flattening the daily demand profile and improving the voltage profile. The proposed framework is tested on a 19-bus test system while considering the probability of PV generation along with load variations. The numerical results show that the developed framework can bring the system load factor to a maximum of 0.76, at which the penetration levels of CES and PV are at 22% and 5% respectively while reducing the energy loss by 24.21% and enhancing the voltage profile significantly. The results also indicate that 22% CES penetration can reduce the annual purchased energy cost from the grid by 11.1% and the annual energy loss cost by 36.88%, where the system accommodates respective PV penetration levels of 5% and 50%.