PV Curtailment Research Articles

Collaborative operation of active distribution network considering PV-storage-charging-compensation

Abstract With the conjunction of clean energy generation and electric cars, the power distribution network is gradually shifting from a traditional one-way radiative network to an active network. Coordinated control of these controllable elements of “source-grid-load-storage” can improve the operating voltage level and economic benefits, and reduce the load peak and off-peak difference. A collaborative dispatch model for active power distribution networks including PV-storage-charging-compensation is constructed in this paper, with the goal of minimizing network losses and PV curtailment costs. The cone transformation is used to handle non-linear constraints of power flow. Compared with existing ordered charging control methods, the constructed model can maximize the control efficiency of the distribution grid, enhance the PV absorption capacity, and effectively slow down the upgrading and renovation of the distribution network.

Solar-hydro cable pooling – Utilizing the untapped potential of existing grid infrastructure

Over the years, the coupling of various variable renewable energy sources has emerged as a convenient way to partially or fully overcome their highly intermittent nature and low-capacity factors. In literature as well as in practical implementations, the coupling of solar and wind power systems is gaining special attention thanks to their advantageous complementarity in time. However, an area of yet not well-documented potential is the coupling of solar PV plants with non-dispatchable run-of-river hydropower plants. In this study, Poland, which still has significant untapped hydropower potential, is used as a case study. The objective of the work is to quantify the coupling potential with special attention paid to the unavoidable curtailment of solar generation due to the limited grid connection capacity. A simulation model was developed that uses input runoff, irradiation, and temperature hourly data covering the period 01.01.2008–31.12.2022 for 236 selected sites in Poland. Hydrological data were obtained from field measurements, while the remaining meteorological parameters were downloaded from the ERA5 reanalysis database. Hydropower generation was simulated assuming a constant head and a Kaplan turbine operating at different efficiencies depending on the flow rate through the turbine. The available flow was calculated considering environmental flow (e-flows) constraints. The design flow was determined based on the average multi-year flow in the considered river. The complementarity in time of these two renewable energy sources in each location was assessed by considering the grid connection capacity and resulting curtailment in case of too high simultaneous generation from both sources. The analysis showed that the average PV curtailment is about 10.7 % (or 13.2 % when it is solar PV capacity weighted) when the ratio of solar to hydro is equal. Still, it can be as high as 19.7 % in individual cases. To ensure that PV curtailment is no more than arbitrarily (in that case) selected threshold of 5 %, the solar-PV capacity should be between 58 % − 120 % of the designed hydropower plant capacity. The curtailment threshold can be further investigated as an expansion of a techno-economic analysis that fell out of the scope of this work. The additional analysis conducted by means of daily flow data showed a significant underestimation of solar curtailment in individual cases (i.e., up to 7 pp.) and, on average, lower by 0.24 pp. could be expected. Due to interannual flow variations, although the expected mean solar curtailment can be no more than 5 %, there are individual years when it is as low as 2 % and as high as 12 % of this year’s solar generation. The lessons learned from this study shed light on the potential maximization of local power generation through coupling with PV systems and the simultaneous reduction of environmental impacts by releasing higher quantities of e-flows offset by the integration of PV systems.

Coordinated planning for flexible interconnection and energy storage system in low-voltage distribution networks to improve the accommodation capacity of photovoltaic

The increasing proportion of distributed photovoltaics (DPVs) and electric vehicle charging stations in low-voltage distribution networks (LVDNs) has resulted in challenges such as distribution transformer overloads and voltage violations. To address these problems, we propose a coordinated planning method for flexible interconnections and energy storage systems (ESSs) to improve the accommodation capacity of DPVs. First, the power-transfer characteristics of flexible interconnection and ESSs are analyzed. The equipment costs of the voltage source converters (VSCs) and ESSs are also analyzed comprehensively, considering the differences in installation and maintenance costs for different installation locations. Second, a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity. Within this framework, the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs, whereas the lower-level model optimizes the operating power of the VSCs and ESSs. The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy (NSGA-II). The effectiveness of the proposed planning method is validated through an actual LVDN scenario, which demonstrates its advantages in enhancing PV accommodation capacity. In addition, the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed, demonstrating the adaptability of the proposed coordinated planning method.

Technical Impacts of Virtual Clean Hydrogen Plants: Promoting Energy Balance and Resolving Transmission Congestion Challenges

This paper presents the VCHP platform as a solution to address PV curtailment and line congestion in scenarios of increasing renewable energy penetration. Solar PV generation profiles and load profiles were generated for three scenarios (2025, 2030, and 2035) using data provided by KPX. Modifications were made to the IEEE 30 Bus model to accurately reflect the Korean power system, including the introduction of PCA and LCA at relevant buses. Line congestion was evaluated using metrics such as TUR, STUR, and TLR. The research findings indicate that integrating the VCHP platform in all scenarios effectively alleviates line congestion, as shown by the TUR remaining below 1. Importantly, the reduction in line losses exceeds the decrease in power flow, demonstrating the effectiveness of VCHP in reducing power losses. The results suggest that as renewable energy sources increase, line congestion issues may arise in the existing power system. However, integrating the proposed VCHP platform is a valuable solution for effectively utilizing surplus PV energy and improving the stability of the power grid. The adoption of such a platform can significantly enhance the operation and management of the power system.

Optimal planning of mobile energy storage in active distribution network

AbstractMobile energy storage (MES) has the flexibility to temporally and spatially shift energy, and the optimal configuration of MES shall significantly improve the active distribution network (ADN) operation economy and renewables consumption. In this study, an optimal planning model of MES is established for ADN with a goal of minimising the annual cost of a distribution system. Firstly, the annual cost of a distribution system is set up with consideration of the investment cost and operation cost of MES, wind and PV curtailment cost, network loss cost and the peak‐valley arbitrage income of MES. Then, the distributed photovoltaic and wind power access constraints, power conservation constraints of ADN, power generation constraint, system security constraint, energy coupling and displacement constraints of MES are further tailored to establish the MES planning model. Afterwards, the proposed model is solved by the second‐order cone relaxation combined with the large M algorithm. Finally, the simulation results of the modified IEEE 33‐bus distribution network validate the effectiveness of the proposed model.

Can Locational Disparity of Prosumer Energy Optimization Due to Inverter Rules Be Limited?

To mitigate issues related to the growth of variable smart loads and distributed generation, distribution system operators (DSO) now make it binding for prosumers with inverters to operate under pre-set rules. In particular, the maximum active and reactive power set points for prosumers are based on local voltage measurements to ensure that inverter output does not cause voltage violations. However, such actions, as observed in this work, restrict the range available for local energy management, with more adverse losses on arbitrage profits for prosumers located farther away from the substation. The goal of the paper is three-fold: (a) to develop an optimal local energy optimization algorithm for activation of load flexibility and inverter-interfaced solar PV and energy storage under time-varying electricity prices; (b) to quantify the locational impact on prosumer arbitrage gains due to inverter injection rules prevalent in different energy markets; (c) to propose a computationally efficient hybrid inverter control policy which provides voltage regulation while substantially reducing locational disparity. Using numerical simulations on three identical prosumers located at different parts of a radial feeder, we show that our control policy is able to minimize locational disparity in arbitrage gains between customers at the beginning and end of the feeder to 1.4%, while PV curtailment is reduced by 91.7% compared to the base case with restrictive volt-Var and volt-watt policy.

Assessment of offshore wind-solar energy potentials and spatial layout optimization in mainland China

Developing offshore wind and solar energy presents a promising solution to reduce carbon emissions. Yet, there has been little focus on the co-location of offshore wind and solar energy, and an absence of methods for optimizing their spatial layout for regional integration. To this end, this study introduces a framework to assess both the technical and economic potential using geographic information system technology, and to seek the optimal spatial layout by combining electricity dispatch simulation and multi-objective optimization. Our results reveal that China's offshore wind-solar generation potential amounts to ∼15.7 × 103 TWh/year, half of which is accessible at a cost of less than €86/MWh. This potential could satisfy 100% of the coastal electricity demands, but the proportion of offshore generation delivered to the grid and the share of load addressed are contingent on specific constraints. We demonstrate that co-located wind-solar farms diminish generation variability and that energy storage markedly reduces PV curtailment during dispatch. Our study underscores the importance of site selection in distant offshore and decentralized placement among locations with varying characteristics. Our study serves as a foundation for offshore wind-solar energy endeavors and offer crucial considerations for the spatial layout optimization of ocean renewable energy utilization.

Peak shaving auxiliary service analysis for the photovoltaic and concentrating solar power hybrid system under the planning-dispatch optimization framework

Concentrating solar power (CSP), being one of the key stakeholders in the peak shaving auxiliary service (AS) market, possesses distinct advantages due to its characteristics of energy storage, sustainability, and adjustability. Nevertheless, the market mechanism for CSP in the peak shaving AS is still in its nascent stage, particularly in the northwest region of China where thermal power dominates and there are bundled large-scale photovoltaic developments. Exploring strategies to capitalize on the peak shaving benefits of CSP, mitigate system operation costs, and enhance the revenue generation of CSP entities has emerged as a prominent area of research. This study establishes a planning-dispatch double-layer optimization model. Two mechanisms respectively based on the unit load rate (ULR) and peak shaving contribution (PSC) are proposed and examined, and the bidding range and quotation range for peak shaving of CSP under the two mechanisms are suggested according to the cost of the peak shaving capacity of CSP. The proposed model is analyzed using the improved IEEE 30-bus system. The results show that the capacity ratio of photovoltaic and CSP determines the functional position of CSP. Optimizing TES capacity and installed capacity of PV power can maximize the peak shaving capacity of CSP, while simultaneously reducing the peak shaving demand on thermal power plants, power system dispatching costs, and the LCOE of the CSP–PV hybrid system. The comprehensive economic benefit of the hybrid system increases by 2.93% under the PSC-based mechanism than that under the ULR-based mechanism. In comparison to the nonpeak shaving case under the ULR-based mechanism, the CSP–PV hybrid system exhibited a 3.74% increase in net revenue in the high peak shaving demand scenario. Furthermore, the comprehensive economic benefit of the CSP–PV hybrid system improved by 3.80% over the full life cycle, while the PV curtailment experienced a 2.50% decrease.

Microgrid source-network-load-storage master-slave game optimization method considering the energy storage overcharge/overdischarge risk

--This paper selects the whole microgrid system as the master and renewable energy, energy storage, and load as the game's slave. It builds a master-slave game optimization model for coordinating the microgrid's source-network-load-storage. The master's goal in the microgrid game is to minimize the overall operation cost. The slave in the renewable energy game aims to minimize the operation cost of renewable energy while considering penalties for wind and PV curtailment. The slave in the energy storage game focuses on optimizing energy storage regulation performance and considers overcharge/discharge risks. Meanwhile, in the load game, the slave aims for the highest power quality and improves load power quality as much as possible while preserving demand response capability to enhance system flexibility. The case analysis shows after 45 games, all game participants can achieve Stackelberg equilibrium, effectively balancing multi-party benefits and improving safety and regulation capabilities of energy storage operations. The microgrid operation scheme based on this method maintains the existing microgrid operation mode and ensures safe and stable system operation.

Contribution to net zero emissions of integrating hydrogen production in wastewater treatment plants

The reliability of renewable hydrogen supply for off-take applications is critical to the future sustainable energy economy. Integrated water electrolysis can be deployed at distributed municipal wastewater treatment plants (WWTP), creating opportunity for reduction in carbon emissions through direct and indirect use of the electrolysis output. A novel energy shifting process where the co-produced oxygen is compressed and stored to enhance the utilisation of intermittent renewable electricity is analysed. The hydrogen produced can be used in local fuel cell electric buses to replace incumbent diesel buses for public transport. However, quantifying the extent of carbon emission reduction of this conceptual integrated system is key. In this study, the integration of hydrogen production at a case study WWTP of 26,000 EP capacity and using the hydrogen in buses was compared with two conventional systems: the base case of a WWTP with grid electricity consumption offset by solar PV and the community's independent use of diesel buses for transport, and the non-integrated configuration with hydrogen produced at the bus refuelling location operated independently of the WWTP. The system response was analysed using a Microsoft Excel simulation model with hourly time steps over a 12-month time frame. The model included a control scheme for the reliable supply of hydrogen for public transport and oxygen to the WWTP, and considered expected reductions in carbon intensity of the national grid, level of solar PV curtailment, electrolyser efficiency and size of the solar PV system. Results showed that by 2031, when Australia's national electricity is forecast to achieve a carbon intensity of less than 0.186 kg CO2-e/kWh, integrating water electrolysis at a municipal WWTP for producing hydrogen for use in local hydrogen buses produced less carbon emissions than continuing to use diesel buses and offsetting emissions by exporting renewable electricity to the grid. By 2034, an annual reduction of 390 t–CO2–e is expected after changing to the integrated configuration. Considering electrolyser efficiency improvements and curtailment of renewable electricity, the reduction increases to 872.8 t–CO2–e.

Optimal renewable energy export strategies of islands: Hydrogen or electricity?

Renewable energy has the characteristics of wide distribution, sustainable use and low impact on the environment, which is suitable for application and promotion in the island area. Given the concerns about wind and PV curtailment of energy-rich islands, it is potentially a good idea to export extra renewable energy to the mainland. The aim of this paper is to investigate the economic viability of transforming renewable energy into exportable electricity or hydrogen. A comprehensive renewable energy system model is developed based on the P-graph to simulate an energy system, which integrates electricity, heat and hydrogen on a virtual island. Solar, wind, wave and biomass are the main renewable energy sources in the developed energy system. The objective includes the construction cost, operating cost, and also environmental cost, which is related to the greenhouse gas footprint. Findings from the case study show that extra renewable energy exporting by electricity is cheaper than using hydrogen for the studied island, and the optimal dispatch structure can deliver 51 GWh of electricity annually for 292 M CNY (about 42 M EUR). A sensitivity analysis of export prices and renewable energy uncertainty verifies the economics of electricity export.

Bus Voltage Violations under Different Solar Radiation Profiles and Load Changes with Optimally Placed and Sized PV Systems

This study mainly discusses the implications of solar radiation profiles and changes in load with respect to base load conditions on the PV placement, size, voltage violations, and curtailment cost of PV generation in the network. The PV installation is optimized using yearly solar radiation profiles, low, medium, and high, corresponding to three different locations. The network in the study is represented as a multiphase, with provision for the installation of both single- and three-phase PV systems. For the different load changes in either one of the phases or all three phases, the optimal placement and size of PV inverters are discussed. It is indicated that with load increase in all three phases, for low solar radiation profiles, the placement and size of PVs remain non-uniform, while for medium and high solar radiation, the distribution becomes comparatively uniform throughout the network. However, with a load increase in one of the phases, for low solar radiation, optimal placement compensates with three-phase PV installation, while for medium/high solar, the corresponding load increase phase contributes to greater PV installation. The voltage rise is observed at both load-connected and non-load-connected buses. Such buses in the network are those that form the common junction with the branches connected to another set of buses having optimally placed PVs. The voltage violations are experienced at the feeder end buses with single-phase PV installation, not only in the phase having a connected load but also in one of the other phases.

Worst CVaR based energy management for generalized energy storage enabled building-integrated energy systems

Generalized energy storage (GES) can reduce the renewable energy curtailment, carbon emission and operational cost risk in the building-integrated energy system (BIES) energy management when faced with uncertainties of multi-energy loads and PV. In this context, GES integrated with the differentiated building thermal load-based virtual energy storage (VES) is proposed in the energy management model of BIES. Specifically, the differentiated building thermal load VES is introduced by differentiated personal factors (e.g., metabolic rate and clothing insulation) based on the predicted mean vote. Furthermore, a worst conditional value at risk (WCVaR) energy management method is developed to evaluate the operational cost risk of BIES. Meanwhile, possible probability distribution uncertainties of PV, electric and thermal loads are all fully considered by a boxlike uncertainty set. Then, the proposed WCVaR model is transformed into a linearized model by the Lagrange duality theory. Finally, the whole energy management model is solved by the CPLEX solver. Case studies and comparative analysis are performed based on a representative BIES. Numerical results show that the proposed model can reduce 33.55% of operational cost, 74.25% of carbon trading cost, and 16.96% of PV curtailment cost for BIES compared with that without GES. In addition, the conditional value at risk (CVaR) with the proposed WCVaR method ($5700.22) is between that with the traditional CVaR method considering multiple operational scenarios ($5684.68) and that with the traditional CVaR method only including the worst operational scenario ($6043.48), which indicates that the proposed WCVaR method can avoid overly-high and overly-low operational cost risks.

Reducing solar PV curtailment through demand-side management and economic dispatch in Karnataka, India

India has set 2070 as the target year to achieve carbon neutrality, while carbon-intensive fossil fuels are still dominating its energy system. In the next five decades, economically optimized energy transition towards renewables is crucial for India to reduce CO2 emissions in an affordable manner. India has installed a large fleet of solar PV, and thus, maximizing their capacity factors plays an influential role in energy transition. This study examines how the state of Karnataka managed to enhance solar PV capacity factor by two-thirds with substantially reduced curtailment from 2017 to 2019. We built, calibrated, and validated a Mixed-Integer Linear Programming (MILP) model with detailed hourly data to quantify the impacts of two major policy changes, being shifting electricity consumption of irrigation from night-time to daytime (load shift) and dispatching electricity generation units by their merit order (economic dispatch). Our results indicate that these two measures could explain about 20% and 70% of the capacity factor increase, respectively, which is equivalent to reducing the cost of solar electricity by about 40%. India and other countries may further expand these policies for accelerating and optimizing energy transition.

Optimal economic dispatch of hybrid microgrids integrating Energy Storage Systems with Grid-Forming Converters

New control strategies based on Grid-Forming converters make possible the operation of isolated microgrids without the support of synchronous generation. This paper proposes an Energy Management System algorithm that optimizes the operation of a microgrid, maximizing the integration of renewable energy and considering the possibility of disconnecting all synchronous generators. The algorithm is applied to a microgrid modelled with real data and two economic dispatch strategies are analysed: the first requires keeping at least one synchronous generator connected to provide frequency regulation following standard practice; and the second considers the disconnection of all conventional generation relying on the capabilities of Grid-Forming converters when sufficient reserve is available. The results show that the proposed strategy reduces the operational cost of the system, as well as solar PV curtailment and diesel consumption.

Multi-terminal phase-changing soft open point SDP modeling for imbalance mitigation in active distribution networks

Active distribution networks (ADNs) are capable of mitigating phase imbalance caused by various operational conditions, including uneven growth of single-phase and intermittent distributed energy resources (DERs), incurring financial losses or costly infrastructure reinforcements. In this paper, the research gap for a flexible phase imbalance mitigating solution is addressed by proposing a multi-terminal phase-changing soft open point (PC-SOP). It is explored in detail on balancing the power flows and compared with other different types and ways of connection (including two-terminal and conventional). Then operational strategies based on different cases are presented for imbalance mitigation. Semidefinite programming (SDP) relaxation is utilized to convert the original non-convex nonlinear model into an SDP model which can be solved efficiently by commercial solvers. Two case studies demonstrations are conducted on IEEE 13-node and 123-node three-phase networks. It is found that multi-terminal PC-SOPs can minimize power losses by between 5.56 % and 28.98% and have better voltage control (all buses operate in the allowed voltage range [0.94, 1.10]) and less PV curtailment (reduced by at least 6.31 MW/24 h and 0.63 MW/24 h for the two test networks separately) when compared to conventional SOP technologies.

Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China

The development of renewable energy (RE) is a critical path to achieve global climate goals and energy conversion. The understanding of Demand-side response (DR) is crucial for the stability and efficiency of renewable energy system (RES). The DR strategies are performed by coordinating various energy sources and electricity demand optimally in the operation of high penetration of renewable generations across different seasons from 2015 to 2050 using Qinghai, China as an example. The results show the reduced peak demand by DR is various in different seasons, and the shifted peak demand will be 56.8 GWh-596.5 GWh in 2050. In general, DR could cause a significant reduction of the total costs by avoiding unnecessary installed capacity from ￥2.19 billion to ￥28.62 billion in 2050. In the short-term, the structure of high-proportion RES cannot rapidly adjust to a new form. However, in the long-term, hydropower will have a large share in RES due to the ability of improving the synergistic stability of the high-proportion RES. In addition, the adoption of DR demonstrates a great potential on reducing PV curtailment and wind curtailment.

수요자원 인센티브를 통한 태양광발전 출력제한 대응 ESS 최적운영스케줄링에 관한 연구

The installation of energy storage system (ESS) is increased to solve the instability of the transmission system due to variable renewable energies such as Photovoltaic power generation (PV) and wind power generation. Meanwhile, recently, PV output is frequently curtailed since PV output produced after the ESS charging is finished causes transmission line congestion. For this congestion, it is common to increase line capacity or allocate the output curtailment for each power plant. However, since the unsettled loss occurs due to the output curtailment, the power plant operator should be given an incentive to induce the output curtailment for a specific time. Therefore, in this paper, the ESS optimal operation scheduling using the demand response transaction mechanism as an incentive is presented. From the perspective of PV operator with ESS, the charge/discharge capacity is determined in units of 15 minutes reflecting the PV curtailment and the demand response trading mechanism through mixed-integer linear programming. Uncertainty in the D-Day actual PV power output is considered as three scenarios such as Day-ahead forecasting PV power output and Day-ahead forecasting PV power output scenario with mean absolute percentage errors. Through optimal operation scheduling of ESS, transmission line overload and system congestion are suppressed by ESS charging and PV operators can secure additional benefits through the demand response trading mechanism without PV curtailment. Namely, total expected benefits can be maximized by the proposed method. As a result, an additional expansion of transmission lines or the introduction of a new incentive system can be avoided by the flexibility of PV operators.

Impact assessment of electric vehicles as curtailment mitigating mobile storage in high PV penetration grid

Electric vehicles are seen as a potential solution in reducing the fossil fuel dependence of the transport sector and could also serve as secondary storage for renewable energy. This study aims to clarify the role of EV in managing curtailment in electricity grid with high PV penetration. An energy balance analysis was conducted to assess the impact of various EV adoption rates and PV capacity growth rates on curtailment throughout a 10-year planning period. Results show that EV as mobile storage has a significant impact in reducing curtailment. In the case of Kyushu, Japan, the analysis showed that 20 GWh was sufficient by 2031. It will require 300,000 to 570,000 electric vehicles as mobile storage to reach this capacity, depending on the combinations of EV classes used. Additional capacity will only benefit spring and autumn, which does not merit an increased target due to the low capacity factor. Following the logistics growth model, the current adaption rate is insufficient to reach target volume, and external support will be necessary. EV as mobile storage can keep the curtailment to around 10%–15% but has less impact initially; thus, stalling the additional capacity until sufficient EV capacity is available might be necessary to keep the curtailment below 10%. Overall, EV as secondary storage is ideal for regions experiencing PV curtailment, and cars are only used for specific activities.

Optimal dispatch of PV inverters in unbalanced distribution systems using Reinforcement Learning

In this paper, a Reinforcement Learning (RL)-based approach to optimally dispatch PV inverters in unbalanced distribution systems is presented. The proposed approach exploits a decentralized architecture in which PV inverters are operated by agents that perform all computational processes locally; while communicating with a central agent to guarantee voltage magnitude regulation within the distribution system. The dispatch problem of PV inverters is modeled as a Markov Decision Process (MDP), enabling the use of RL algorithms. A rolling horizon strategy is used to avoid the computational burden usually associated with continuous state and action spaces, coupled with a computationally efficient learning algorithm to model the action-value function for each PV inverter. The effectiveness of the proposed decentralized RL approach is compared with the optimal solution provided by a centralized nonlinear programming (NLP) formulation. Results showed that within several executions, the proposed approach converges either to the optimal solution or to solutions with a PV curtailment excess of less than 2.5% while still enforcing voltage magnitude regulation.