Showing papers on "Grid parity published in 2014"

The economic viability of battery storage for residential solar photovoltaic systems - A review and a simulation model

Abstract: Battery storage is generally considered an effective means for reducing the intermittency of electricity generated by solar photovoltaic (PV) systems. However, currently it remains unclear when and under which conditions battery storage can be profitably operated in residential PV systems without policy support. Based on a review of previous studies that have examined the economics of integrated PV-battery systems, in this paper we devise a simulation model that investigates the economic viability of battery storage for residential PV in Germany under eight different electricity price scenarios from 2013 to 2022. In contrast to previous forward-looking studies, we assume that no premium is paid for solar photovoltaic power and/or self-consumed electricity. Additionally, we run the model with a large number of different PV and storage capacities to determine the economically optimal configuration in terms of system size. We find that already in 2013 investments in storage solutions were economically viable for small PV systems. Given the assumptions of our model, the optimal size of both residential PV systems and battery storage rises significantly in the future. Higher electricity retail prices, lower electricity wholesale prices or limited access to the electricity wholesale market add to the profitability of storage. We conclude that additional policy incentives to foster investments in battery storage for residential PV in Germany will only be necessary in the short run. At the same time, the impending profitability of integrated PV-storage systems is likely to further spur the ongoing trend toward distributed electricity generation with major implications for the electricity sector.

The Merit-Order Effect in the Italian Power Market: The Impact of Solar and Wind Generation on National Wholesale Electricity Prices

Abstract: Italy promoted one of the most generous renewable support schemes worldwide which resulted in a high increase of solar power generation. We analyze the Italian day-ahead wholesale electricity market, finding empirical evidence of the merit-order effect. Over the period 2005-2013 an increase of 1 GWh in the hourly average of daily production from solar and wind sources has, on average, reduced wholesale electricity prices by respectively 2.3 €/MWh and 4.2 €/MWh and has amplified their volatility. The impact on prices has decreased over time in correspondence with the increase in solar and wind electricity production. We estimate that, over the period 2009-2013, solar production has generated higher monetary savings than wind production, mainly because the former is more prominent than the latter. However, in the solar case, monetary savings are not sufficient to compensate the cost of the related supporting schemes which are entirely internalized within end-user tariffs, causing a reduction of the consumer surplus, while the opposite occurs in the case of wind.

Mathematical modeling of hybrid renewable energy system: A review on small hydro-solar-wind power generation

Abstract: Harnessing energy from alternative energy source has been recorded since early history. Renewable energy is abundantly found anywhere, free of cost and has non-polluting characteristics. However, these energy sources are based on the weather condition and possess inherited intermittent nature, which hinders stable power supply. Combining multiple renewable energy resources can be a possible solution to overcome defects, which not only provides reliable power but also leads to reduction in required storage capacity. Although an oversized hybrid system satisfies the load demand, it can be unnecessarily expensive. An undersized hybrid system is economical, but may not be able to meet the load demand. The optimal sizing of the renewable energy power system depends on the mathematical model of system components. This paper summarizes the mathematical modeling of various renewable energy system particularly PV, wind, hydro and storage devices. Because of the nonlinear power characteristics, wind and PV system require special techniques to extract maximum power. Hybrid system has complex control system due to integration of two (or more) different power sources. The complexity of system increases with maximum power point tracking (MPPT) techniques employed in their subsystems. This paper also summarizes mathematical modeling of various MPPT techniques for hybrid renewable energy systems.

Only Connect: Microgrids for Distribution System Restoration

Abstract: Electricity infrastructure is the cornerstone of every industrialized nation in the world. As the utility grid ages and the demand for electricity grows, the impact of major interruptions of the electricity infrastructure will be more intense. Costly power outages throughout the world caused by natural disasters such as floods and hurricanes have highlighted the importance of reinforcing the electricity infrastructure. A recent study conducted for the U.S. Department of Energy indicated that sustained power interruptions (those lasting more than 5 min) in the United States incur costs of more than US$26 billion dollars annually. Power outages caused by Hurricanes Sandy and Katrina in the United States threw into notice the crucial role of smart grid technology and the need for further investments in more comprehensive data communication and distribution management systems, distributed energy resources, energy storage facilities, additional automation, and further migration toward decentralized operations for the largely centralized power grid.

Renewable Energy Sources and Responsive Demand. Do We Need Congestion Management in the Distribution Grid

Abstract: Possible congestion management mechanisms for price-responsive electric vehicle demand in electricity distribution networks are investigated. Because a high penetration of renewable energy sources weakens the correlation between wholesale electricity prices and network demand, cost-minimizing electric vehicles may cause high peaks in network load. Managing congestion is not costly in theory but difficult to implement efficiently. Grid tariffs that are fixed ex ante, based on network load, were found to make the problem worse compared to the base-case scenario of flat tariffs. An optimal dynamic grid tariff yields desirable outcomes but is difficult to determine in case of realistic forecasting uncertainties. An iterative approach of a distribution grid capacity market has practical barriers related to IT infrastructure and computational requirements. Advance capacity allocation is more straightforward to implement, but the inter-temporal constraints of the electric vehicles continue to pose a challenge.

A Review on the Effect of Large-scale PV Generation on Power Systems

Abstract: Because of human concern for energy security and environmental deterioration, making full use of renewable energy has been a global consensus Power generation with large-scale renewable energy such as solar and wind energy has become the development trend of new power systems, resulting in increasingly prominent impact on power systems Therefore, great concerns are given from academic and engineering areas of all countries The purpose of this paper is to review the globe status of large-scale photovoltaic(PV) power generation, explore the factors affecting the interaction between solar power generation and power system, refine academic and engineering problems, and propose ideas for future research and development From the perspective of power system planning, simulation, dispatching and control, this paper discusses the modeling and simulation of large-scale photovoltaic power generation, impacts of large scale PV integration on dynamic and static characteristics of power system, and key technologies about large scale PV power generation delivery and consumption Meanwhile, suggestions for further research are proposed from the authors' point of view, offering reference for readers

A survey of influence of electrics vehicle charging on power grid

Abstract: Electric vehicle (EV) industry gets into fast growth period in China, so that charging of large scale of EV will pose inevitable impacts on power grid in the future. In this article, the main factors and modeling methods of EV charging load are analyzed; The literature reviews are carried out on EV integration and impacts on power grids, including grid access capability, power quality, power economy and environment; Additionally, the benefits and realization methods of smart charging strategy are discussed. The current research on V2G (vehicle to grid) operation are summarized as well. Finally, the unresolved problems and possible future research areas are presented.

Stochastic Information Management in Smart Grid

Abstract: Rising concerns about the efficiency, reliability, economics, and sustainability in electricity production and distribution have been driving an evolution of the traditional electric power grid toward smart grid. A key enabler of the smart grid is the two-way communications throughout the power system, based on which an advanced information system can make optimal decisions on power system operation. Due to the expected deep penetration of renewable energy sources, energy storage devices, demand side management (DSM) tools, and electric vehicles (EVs) in the future smart grid, there exist significant technical challenges on power system planning and operation. Specifically, efficient stochastic information management schemes should be developed to address the randomness in renewable power generation, buffering effect of energy storage devices, consumer behavior patterns in the context of DSM, and high mobility of EVs. In this paper, we provide a comprehensive literature survey on the stochastic information management schemes for the smart grid. We start this survey with an introduction to the smart grid system architecture and the technical challenges in information management. Various component-level modeling techniques are presented to characterize the sources of randomness in the smart grid. Built upon the component-level models, we further explore the system-level stochastic information management schemes for smart grid planning and operation. Future research directions and open research issues are identified.

Optimal Integration of Plug-In Hybrid Electric Vehicles in Microgrids

Abstract: Plug-in hybrid electric vehicles' (PHEVs) integration can result in additional electricity consumers and electricity suppliers in microgrids (MGs). This paper presents a new method for optimal integration of PHEVs in MGs, which considers the optimal number of parking numbers under optimal scheduling of PHEVs. Due to the uncertainty of solar energy, the radial basis function network (RBFN) techniques are used for forecasting photovoltaic (PV) power output. Monte Carlo simulation is used to deal with the uncertainties associated with the daily distance driven of the PHEVs, load values, and electricity market price. The objective is the minimization of total cost (TC) and optimal set of the optimization problem is found using genetic algorithm (GA) method. In order to verify the effectiveness of the proposed method, two market policies are used as case studies. The computation results can be used to evaluate the impact of PHEVs' integration on economical performance of MGs.

Dynamic Control and Optimization of Distributed Energy Resources in a Microgrid

Abstract: As we transition towards a power grid that is increasingly based on renewable resources like solar and wind, the intelligent control of distributed energy resources (DER) including photovoltaic (PV) arrays, controllable loads, energy storage and plug-in electric vehicles (EVs) will be critical to realizing a power grid that can handle both the variability and unpredictability of renewable energy sources as well as increasing system complexity. Realizing such a decentralized and dynamic infrastructure will require the ability to solve large scale problems in real-time with hundreds of thousands of DERs simultaneously online. Because of the scale of the optimization problem, we use an iterative distributed algorithm previously developed in our group to operate each DER independently and autonomously within this environment. The algorithm is deployed within a framework that allows the microgrid to dynamically adapt to changes in the operating environment. Specifically, we consider a commercial site equipped with on-site PV generation, partially curtailable load, EV charge stations and a battery electric storage (BES) unit. The site operates as a small microgrid that can participate in the wholesale market on the power grid. We report results for simulations using real data that demonstrate the ability of the optimization framework to respond dynamically in real-time to external conditions while maintaining the functional requirements of all DERs.

A New Approach to Model Load Levels in Electric Power Systems With High Renewable Penetration

Abstract: In medium- and long-term power system models, it is a common approach to approximate the demand curve by load levels in order to make the models computationally tractable. However, in such an approach, the chronological information between individual hours is lost. In this paper, we propose a novel approach to power system models which constitutes an alternative to the traditional load levels. In particular, we introduce the concept of system states as opposed to load levels, which allows us to better incorporate chronological information in power system models, thereby resulting in a more accurate representation of system outcomes such as electricity prices and total cost. Moreover, the system states can be defined taking into account various important system features at once, as opposed to load levels which are defined using just one specific feature, i.e., demand or net demand. Therefore the system states approach better captures other results such as reserve prices, which are not driven by the usual feature used to define load levels. In a case study, we compare the newly proposed methodology to a standard load level approach, which validates that the system states approach better captures power system outcomes.

Multi-criteria analysis of electricity generation mix scenarios in Tunisia

Abstract: The diversification of the national electricity generation mix has risen to the top of Tunisia׳s energy planning agenda Presently, natural gas provides 96% of the primary energy for electric power generation, but declining domestic gas reserves and a soaring electricity demand are urgently calling for alternative fuel strategies Currently discussed diversification options include the introduction of coal and nuclear power plants and/or an increased use of renewable energies This article presents a methodology to assess different electricity system transformation strategies By combining an electricity market model with a subsequent multi-criteria decision analysis (MCDA), we evaluate five power mix scenarios regarding power generation costs as well as non-economic dimensions such as energy security, environmental impact and social welfare effects Based on criteria valuations obtained during consultations with Tunisian stakeholders, a final, best-ranking electricity scenario was selected, consisting of 15% wind, 15% solar and 70% natural gas-generated electricity in the national power mix by 2030

Cost and CO2 reductions of solar photovoltaic power generation in China: Perspectives for 2020

Abstract: To improve the understanding of the cost and benefit of photovoltaic (PV) power generation in China, we analyze the per kWh cost, fossil energy replacement and level of CO2 mitigation, as well as the cost per unit of reduced CO2 of PV power generation in 2020 at the province level. Three potential PV systems are examined: large-scale PV (LSPV), building-integrated PV (BIPV), and distributed PV systems used in remote rural areas (which have very low capacities). The results show that in 2020 PV power generation could save 17.4 Mtce fossil energy and 46.5 Tg CO2, compared with 600 MWe coal-fired supercritical units. Also in 2020, the costs of solar electricity could be reduced by approximately 60% as compared to 2010, but would still be 11–74% higher than the current grid prices. The PV electricity costs vary significantly among provinces. In the economically developed eastern provinces, the PV electricity (mainly BIPV) is 0.67–0.86 RMB/kWh. This rate is close to grid parity owing to high grid prices, but the CO2 mitigation cost is high (456–693 RMB/Mg CO2). The PV electricity (mainly LSPV) in solar-resource-rich western provinces has lower cost (0.45–0.75 RMB/kWh) and lower CO2 mitigation cost (172–419 RMB/Mg CO2), but is farther from grid parity due to the low local grid price. From a cost-effective perspective, LSPV in the west provinces should be the first priority in PV deployment strategies, and should receive strong financial support from the government. This study provides a quantitative, province-specific analysis of PV power generation, which can be used to support various PV subsidy policies.