A Multiperiod OPF Model Under Renewable Generation Uncertainty and Demand Side Flexibility

Renewable energy sources such as wind and solar have received much attention in recent years and large amount of renewable generation is being integrated to the electricity networks. A fundamental challenge in power system operation is to handle the intermittent nature of the renewable generation. In this paper we present a stochastic programming approach to solve a multiperiod optimal power flow problem under renewable generation uncertainty. The proposed approach consists of two stages. In the first stage operating points for conventional power plants are determined. Second stage realizes the generation from renewable resources and optimally accommodates it by relying on demand-side flexibility. The benefits from its application are demonstrated and discussed on a 4-bus and a 39-bus systems. Numerical results show that with limited flexibility on the demand-side substantial benefits in terms of potential additional re-dispatch costs can be achieved. The scaling properties of the approach are finally analysed based on standard IEEE test cases upto 300 buses, allowing to underlined its computational efficiency.Comment: 8 pages, 10 figure

Harnessing Markets for Water Quality

This issue of IMPACT is devoted to exploring and understanding the opportunities and challenges of harnessing markets to improve water quality. It looks at how markets could be implemented to address the growing concern of nonpoint source pollution as well as point sources. Recently, the EPA proposed a water quality trading proposal, which is summarized, reviewed, and critiqued

Impact of Wind, Solar, and Other Factors on Wholesale Power Prices: An Historical Analysis—2008 through 2017

Wholesale power markets have evolved. Some of the most prominent changes over the last decade in the United States include growth in wind and solar, a reduction in the price of natural gas, weakened load growth, and an increase in the retirement of thermal power plants. Here we empirically assess the degree to which wind and solar—among other factors—have influenced wholesale electricity prices. We show that wind and solar have contributed to reductions in overall average annual wholesale electricity prices since 2008, but that natural gas prices have had the largest impact. More notable is that expansion of variable renewable energy has led to significant changes in locational, time of day, and seasonal pricing patterns in some regions. These altered pricing patterns reflect a fundamental shift, and hold important implications for the grid-system value of wind and solar, and for other electric-sector planning and operating decisions

An integrated OPF dispatching model with wind power and demand response for day-ahead markets

In the day-ahead dispatching of network-constrained electricity markets, renewable energy and distributed resources are dispatched together with conventional generation. The uncertainty and volatility associated to renewable resources represents a new paradigm to be faced for power system operation. Moreover, in various electricity markets there are mechanisms to allow the demand participation through demand response (DR) strategies. Under operational and economic restrictions, the operator each day, or even in intra-day markets, dispatchs an optimal power flow to find a feasible state of operation. The operation decisions in power markets use an optimal power flow considering unit commitment to dispatch economically generation and DR resources under security restrictions. This paper constructs a model to include demand response in the optimal power flow under wind power uncertainty. The model is formulated as a mixed-integer linear quadratic problem and evaluated through Monte-Carlo simulations. A large number of scenarios around a trajectory bid captures the uncertainty in wind power forecasting. The proposed integrated OPF model is tested on the standard IEEE 39-bus system

Exploring market designs for local energy markets : core functionalities and value proposition in the context of blockchain, IoT and prosumers

This dissertation aimed to assess the impact of innovative smart market solutions and Blockchain technology on achieving efficient localized energy markets. Trends suggest the future of renewable energy generation will involve a move away from centralized power plants, and towards a large number of smaller generation units, such as PV cells. There are clear synergies between the market dynamics of photovoltaic systems and Blockchain-enabled smart markets, which can be harnessed towards integrating new consumption patterns and energy sources, as well as connecting consumers. Successful business strategy to integrate these technologies can lead to market leadership in this new industry. Captivating consumers is a key determinant of success, and offering lower electricity prices a necessary condition. For such offering to be feasible, markets need to be more efficient, as smart microgrids are proving to be. Consequently, there came the interest to see how new local electricity markets could be set up, while taking advantage of decentralization. A peer-to-peer, auction-based, local energy market was idealized and various simulations of were ran with differing levels of participants and structure, to understand the impact on the price of electricity achieved by the market. Market size and structure were both shown to affect price at different magnitudes, suggesting an ideal setup of 25-40 participants with generation capabilities over 60% of demand. Further analysis was undertaken to understand the impact of smart meters and Blockchain integration in such a market. Afterwards, conclusions were compiled and recommendations provided for how to approach new practical implementations.Esta dissertação teve como objetivo avaliar o impacto de inovadoras soluções de mercados inteligentes e tecnologia Blockchain em mercados locais de energia. Tendencias apontam para que o futuro das energias renovaveis passe por uma maior prevalencia de paineis fotovoltaicos domesticos. As sinergias entre as atuais dinamicas em mercados eletricos e o uso da Blockchain em mercados inteligentes parecem claras, podendo ser aproveitaveis para integrar novos perfis de consumo e conectar consumidores. Sendo um novo segmento, estratégias de mercado bem conseguidas serão essencias para ganhar posição, e a capacidade de angariar consumidores será um indicador crucial de sucesso. Para tal, os mercados têm que ser mais eficientes, algo que se tem revelado factual em casos de micro sistemas. Assim, criou-se o interesse de perceber como desenhar e implementar mercados localizados de energia que beneficiem desta tendencia de desintermediação. Para tal, um mercado interativo à base de leilões de eletricidade entre consumidores foi idealizado. Posteriormente, este foi simulado repetidamente, com diferentes dimensões e estruturas, a fim de perceber o seu impacto nos preços médios alcançados. Foi mostrado que tamanho e composição afetam os preços em magnitudes diferentes, sugerindo uma dimensão ideal de 25-40 participantes, com capacidades de autogeração superiores a 60%. Análises posteriors foram desenvolvidas de modo substantive, para avaliar o impacto de contadores eletricos inteligentes e integração da Blockchain neste tipo de mercado. Finalmente, conclusões foram reunidas e transformadas em recomendações para futuras implementações práticas

An integrated multiperiod OPF model with demand response and renewable generation uncertainty

Renewable energy sources such as wind and solar have received much attention in recent years, and large amounts of renewable generation are being integrated into electricity networks. A fundamental challenge in power system operation is to handle the intermittent nature of renewable generation. In this paper, we present a stochastic programming approach to solve a multiperiod optimal power flow problem under renewable generation uncertainty. The proposed approach consists of two stages. In the first stage, operating points of the conventional power plants are determined. The second stage realizes generation from the renewable resources and optimally accommodates it by relying on the demand-side flexibilities. The proposed model is illustrated on a 4-bus and a 39-bus system. Numerical results show that substantial benefits in terms of redispatch costs can be achieved with the help of demand side flexibilities. The proposed approach is tested on the standard IEEE test networks of up to 300 buses and for a wide variety of scenarios for renewable generation

A Call to Cities: Run Out of Water or Create Resilience and Abundance?

New management choices, with new approaches to urbanization and integrated water-energy-food management, are emerging as critical to combat water stress. Urban strategies and tactics are explored in this chapter with a focus on scaling effective solutions and approaches. This includes a focus on small, modular, and integrated water-energy-food hubs; off-grid and localized “circular economy” services that are affordable, accessible, and reliable; blended finance for new technologies, infrastructure and business models, strategic plans, and policies; and urban, behavioral, and decision sciences-informed decisions and new public-private-research-driven partnerships and processes. There are two key messages: first, business as usual could lead to “running out” of water where it’s needed most—in cities and for agricultural and industrial production. Second, “innovators” and “early adopters” of market-based and data-driven efforts can help scale solutions led by people and communities investing in new ways to integrate urban water, energy, and food systems. The chapter concludes with discussion on a new, proactive “maturity” model, enabling integrated urban infrastructure systems, governance, and cross-sector innovation. This includes market-based and data-driven responses that first focus on improving quality of life, sustainability, and resilience of communities, bringing valued services via water-energy-food nexus decisions

Harnessing demand flexibility to minimize cost, facilitate renewable integration, and provide ancillary services

textRenewable energy is key to a sustainable future. However, the intermittency of most renewable sources and lack of sufficient storage in the current power grid means that reliable integration of significantly more renewables will be a challenging task. Moreover, increased integration of renewables not only increases uncertainty, but also reduces the fraction of traditional controllable generation capacity that is available to cope with supply-demand imbalances and uncertainties. Less traditional generation also means less rotating mass that provides very short term, yet very important, kinetic energy storage to the system and enables mitigation of the frequency drop subsequent to major contingencies but before controllable generation can increase production. Demand, on the other side, has been largely regarded as non-controllable and inelastic in the current setting. However, there is strong evidence that a considerable portion of the current and future demand, such as electric vehicle load, is flexible. That is, the instantaneous power delivered to it needs not to be bound to a specific trajectory. In this thesis, we focus on harnessing demand flexibility as a key to enabling more renewable integration and cost reduction. We start with a data driven analysis of the potential of flexible demands, particularly plug-in electric vehicle (PEV) load. We first show that, if left unmanaged, these loads can jeopardize grid reliability by exacerbating the peaks in the load profile and increasing the negative correlation of demand with wind energy production. Then, we propose a simple local policy with very limited information and minimal coordination that besides avoiding undesired effects, has the positive side-effect of substantially increasing the correlation of flexible demand with wind energy production. Such local policies could be readily implemented as modifications to existing "grid friendly" charging modes of plug-in electric vehicles. We then propose improved localized charging policies that counter balance intermittency by autonomously responding to frequency deviations from the nominal frequency and show that PEV load can offer a substantial amount of such ancillary services. Next, we consider the case where real-time prices are employed to provide incentives for demand response. We consider a flexible load under such a pricing scheme and obtain the optimal policy for responding to stochastic price signals to minimize the expected cost of energy. We show that this optimal policy follows a multi-threshold form and propose a recursive method to obtain these thresholds. We then extend our results to obtain optimal policies for simultaneous energy consumption and ancillary service provision by flexible loads as well as optimal policies for operation of storage assets under similar real-time stochastic prices. We prove that the optimal policy in all these cases admits a computationally efficient form. Moreover, we show that while optimal response to prices reduces energy costs, it will result in increased volatility in the aggregate demand which is undesirable. We then discuss how aggregation of flexible loads can take us a step further by transforming the loads to controllable assets that help maintain grid reliability by counterbalancing the intermittency due to renewables. We explore the value of load flexibility in the context of a restructured electricity market. To this end, we introduce a model that economically incentivizes the load to reveal its flexibility and provides cost-comfort trade-offs to the consumers. We establish the performance of our proposed model through evaluation of the price reductions that can be provided to the users compared to uncontrolled and uncoordinated consumption. We show that a key advantage of aggregation and coordination is provision of "regulation" to the system by load, which can account for a considerable price reduction. The proposed scheme is also capable of preventing distribution network overloads. Finally, we extend our flexible load coordination problem to a multi-settlement market setup and propose a stochastic programming approach in obtaining day-ahead market energy purchases and ancillary service sales. Our work demonstrates the potential of flexible loads in harnessing renewables by affecting the load patterns and providing mechanisms to mitigate the inherent intermittency of renewables in an economically efficient manner.Electrical and Computer Engineerin

Analysis of a total integration of renewable energy through a dynamic virtual power plant model and the use of hydrogen as a method of energy production stabilization

The growing need for change in the energy vector, the increasing popularity of renewable energies, as well as the European regulations to achieve zero emissions by 2050 (currently at 21.8% in Europe with a projection of 42.5% by 2030), prompt the analysis of scenarios for meeting the annual demand in three autonomous communities (Andalusia and Valencia) while considering the current electric grid and a new scenario with the most optimal distribution. This analysis involves simplifying the grid and utilizing a distributed virtual power plant (DVPP). These scenarios consider increasing the share of renewables up to 99% and implementing hydrogen-based storage technologies to evaluate their economic impact on the levelized cost of energy and how it increases as the share of renewables grows. Prices for each available technology have been obtained to achieve a more realistic approximation. Variables such as capital expenditures (CAPEX), operating expenses (OPEX), fuel costs where applicable, and replacement costs have been considered, as the project analyses the system with a 50-year outlook, and some technologies have a lifespan shorter than this period. The obtained results will be used to analyse the capacities of hydrogen plants in terms of power and storage, as well as their behaviour in balancing the grid as a supporting technology for intermittent generation sources such as wind and photovoltaic, and for managing potential energy surpluse