Optimal capacity of variable-speed pumped storage for wind power consumption based on double-layer stochastic programming

As China's wind power has been expanding, the volatility, discontinuity and uncertainty of wind power have brought great difficulties to consumption of the wind power. With the development of smart grid, it becomes possible to improve the capacity of wind power consumption by introducing real-time price and demand response theory into the market. Firstly, theories of smart meters, real-time price, and demand side response were introduced. Then taking transfer cost into consideration, a demand response model based on real-time price is proposed to optimize the load curve. At last, the wind power consumption models were built respectively according to the load curves before and after the demand response. Results show that these models can effectively reduce the abandon of wind power and increase the amount of wind power consumption.

This paper presents a spinning reserve optimization model in the energy internet with gas turbines and electric vehicles to deal with wind power uncertainty. The operator's risk preference on system security and wind power consumption is taken into account in the model based on the chance constraints. The costs of expected demand loss and wind power spillage not covered by spinning reserves are incorporated in the objective function. In order to improve computational efficiency, a method is proposed to linearize the formulation of EENS and EWS. The impacts on system security, wind power consumption, and spinning reserve scheduling under different risk preferences are systematically investigated on the IEEE reliable test system RTS79. The operation characteristics of gas turbines and electric vehicles are summarized and the optimal risk-preference-related confidence levels are found.

The volatility, uncertainty and anti-peaking characteristics of large-scale wind power greatly increase the peak regulation burden of the power grid, which leads to frequently deep peak regulation of thermal power (TP) units. As a result, the total peak regulation cost of the system increases greatly, the operation economy of TP decreases and the phenomenon of abandoned wind gets serious. However, most of the pumped storage (PS) power stations in China adopt the strategy of timing dispatch, which makes its flexibility regulation effect not exerted effectively. Based on the background, the dispatching benefit models of PS and the peak regulation cost model of TP units in the whole process are established respectively. With the objectives of maximizing dispatching benefit of PS, minimizing peak regulation cost of TP and abandoned wind power, a joint optimal dispatching strategy of PS and TP units with large-scale wind power integration is proposed. Based on the 10-unit example system, the peak regulation effect of is simulated and compared between the proposed strategy and the existing operation strategy. The results show that the proposed strategy in this paper can effectively improve the dispatching benefit of PS, the economy of TP peak regulation and the capacity of wind power consumption, which verifies the validity of the proposed strategy.

Petrobras has utilized different types of units in Marlim Field development. From converted Semi-Submersibles to turret-equipped FPSOs, many different options were made. This paper describes the main reasons for choosing the different types of production units, the conversion approach, and the process plant automation and control system - showing the evolution from one unit to another. The paper also presents the actual performance of each production unit, analyzing the operational results-opex-the main causes of production losses and the efficiency levels reached by the wells and also the process plants. Finally, the paper shows a host of new technologies applied in this development and describes the future units that are on their way to Marlim Field. Introduction The use of pilot systems and step by step development is a default procedure at Petrobras. By these means future problems or adjustments in the development plans are foreseen and theirs solutions can be provided for the next step. For the development of the Marlin field, this modular conception was adopted, utilizing subsea completions and floating production systems, and five modules were planned in addition to a pre-pilot and a pilot system. The Marlim field is located at the Northeast of Campos Basin, approximately 105 km from shore with water depths varying from 650 to 1050 meters. The field was discovered in February 1985 by the wildcat 1-RJS-219. Its approximate area is 132 km2. Estimated recoverable reserves are 1.504,3 Mm3 of 19.5° API oil and 18.3 GNm3 of associated gas. The well's water depth varies from 700 to 1050 meters, with flow lines length up to 19 km. Water injection and gas lift is required to improve the field recovery and wax removal operation is a must due to oil characteristics and low water temperature at sea bed. Until December 1998 the Marlim Field has shown an accumulated production of 36.9 Mm3 of oil and 3.1 billion Nm3 of gas. The average daily production in December 1998 was 49827 m3 /d Choice of the Units and conversion approach The experience with floating production systems, associated with the technology developed by PROCAP (Deep Water Capability Program) and PROCAP-2000 (Technological Innovation Program on Deepwater Exploitation Systems) led Petrobras to use floating production systems for the development of Marlim field. The Pre-Pilot and Pilot systems were set offside the field at shallower water depths in order to avoid further interferences with the main development. For this purpose, semi-submersible units were chosen, due to its flexibility. The Petrobras 13, priory a drilling unit operating in Campos Basin, was adapted for a long-term production test and became the pre-pilot unit. Its oil production came on stream on Mars 1991. The oil was exported to a tanker on a monobuoy and the gas was burned. In that time Petrobras had purchased some floating units available in the market. One of these units, specifically the Fortune Ugland, a former flotel, was converted into a floating production system and became the pilot system of the Marlim field. The unit was renamed as Petrobras 20 and its production came on stream on July 1992. The oil production is exported through a monobuoy system to tankers and the gas production send to shore through pipelines.

The anti-peak shaving characteristics of wind power is an important factor that limits the consumption of wind power. The use of the space-time translation capability of a battery energy storage system is one of the effective means for promoting wind power consumption. Thus, this study proposes an energy storage system smoothing wind power fluctuation control strategy considering wind power consumption to improve the utilization level and economy of an energy storage system. First, the statistical characteristics of wind power are analyzed, and the scene division principle of a multiscenario regulation of an energy storage system is formulated using a correlation coefficient. On this basis, the charging and discharging intervals of the energy storage system in each scenario are determined by comprehensively considering the wind power and the time domain distribution law of load. Then, the control strategy of energy storage system based on inter-zone control is proposed based on the division of charging and discharging intervals. During the charging interval, smoothing the upward fluctuation of wind power or reducing the amount of abandoned wind power is aimed at storing electricity. During the discharge interval, electricity is released to smooth the downward fluctuation of wind power. Finally, considering the real-time state of charge and wind power consumption of the energy storage system, a method of charging and discharging power correction based on fuzzy control is proposed. Taking the actual data of a wind farm as an example, a test is performed on a simulation platform of a combined wind storage power generation system to verify the feasibility and superiority of the proposed control strategy.

In response to the challenges of low wind power consumption and high pollution emissions from thermal power, the implementation of wind-thermal power generation rights trading is a proactive attempt to reduce wind power curtailment and promote its consumption. This study first regards the alternating bidding process between the two parties as a dynamic game, using the Rubinstein bargaining game model to determine the incremental profit allocation and optimal bidding for both parties in power generation rights trading. Secondly, an energy conservation and emission reduction model is constructed to analyze the benefits from the perspectives of standard coal consumption saving and the carbon emission reduction caused by power generation rights trading. Finally, a combined trading revenue model is established to analyze the final profit of both parties involved in the trading. The results show that the combined trading of wind-thermal power generation rights, incorporating carbon trading and green certificate trading, can effectively promote coal consumption savings in thermal power units and reduce the carbon emissions of the power industry. Moreover, it significantly increases the final profit for both parties, stimulating the enthusiasm of generators for participating in power generation rights trading, and ultimately promoting wind power consumption.

The escalating grid-connected capacity of renewable energy sources, predominantly wind and photovoltaic (PV) power, along with its inherent volatility and anti-peaking attributes, exacerbates the peaking demands on the power system. Consequently, this trend necessitates enhanced flexibility in power system peaking capabilities. In response to this challenge, this paper introduces an optimal scheduling methodology grounded in a two-stage stochastic model tailored for power systems, which incorporates thermal-storage peaking pricing. Initially, a hierarchical decision-making framework, employing the group decision hierarchy analysis method, is devised to formulate a peaking pricing strategy for thermal power and energy storage. Subsequently, acknowledging the variability of wind power, multiple scenarios are generated and consolidated through the application of k-means clustering. A two-stage stochastic optimization approach is then utilized for day-ahead pre-dispatch of thermal power and storage units, and intraday dispatch adjustments are made to accommodate the uncertainties associated with renewable energy sources by leveraging flexible resources, thereby ensuring power balance, and maximizing wind power integration. The efficacy of the proposed approach is validated through simulations conducted on the enhanced IEEE39-bus system. The numerical results show that the flexibility of the system can be effectively improved, and the wind power and photovoltaic accommodation rate is increased by 98.11 and 99.42%, respectively.

This paper describes an approach for unit start-up sequence determination during power system restoration. This approach is based on the backtracking search method, which determines the generating starting times to maximize the MWh load served over a restoration period and guarantee optimality of the start up sequence. The dynamic characteristics of different types of units and system constraints have to be considered. The shortest path, i.e., the path that requires the minimal number of switching actions, between the supplying unit and load is selected unless it is not feasible. Simulation tests, carried out on 39-bus New England test system, verify the effectiveness of the proposed method.

Numerous problems have emerged with the rapid development of wind power in Xinjiang. The predominant problem is the inhibition of the healthy development of the wind power industry by wind power curtailment in Xinjiang. In this study, wind power heating and high energy-consuming industries were coupled to increase wind power consumption in Xinjiang on the load side. The feasibility analysis of wind power heating in Dabancheng showed that the heating load characteristics coincide with the wind characteristics and the electric heating technology can fulfill the requirements for wind power heating. A business model innovation achieved a win–win situation. Furthermore, a wind power heating system was designed in Dabancheng, the boiler capacity and the heat storage capacity were calculated, and a heating system model with heat storage technology was established. Wind power heating with heat storage can improve the consumption of wind power and increase the local electric load and system adjustability. Furthermore, heating with curtailed wind power can save 2942 tons of standard coal as well as reduce 5172 tons of CO2, 2.9 tons of SO2, 22 tons of NOX, and 2 tons of soot emissions. Non-grid-connected distributed wind power was applied to the high energy-consuming coal chemical industry to reduce wind power curtailment, expand the consumption market, and reduce pollution. A multifunctional wind-photovoltaic complementary system with hydrogen energy storage coupled with traditional high energy-consuming coal chemical industry was established. The implementation plan using wind and solar energy to produce, store, and apply hydrogen energy was proven beneficial. Wind power consumption was improved on the load side. The wind power curtailment problem was reduced by increasing local load using the curtailed wind power to provide clean heat in Dabancheng and constructing the multifunctional wind–photovoltaic complementary system. This study will contribute to the healthy and sustainable development of the wind power industry in Xinjiang.

Aiming at the large-scale wind power transmission end grid wind and thermal power shared transmission channel decoupling out, the wind power output power is blocked, the transmission channel utilization rate is not high and so on. Based on a comparative analysis of wind and fire electrolytic coupling / coupling transmission operation characteristics, this paper The goal is to maximize the output power of wind power, maximize the utilization of transmission channels, and minimize the operating costs of thermal power units. Aiming at the dispatching output of wind power and thermal power units as optimization variables, a multi-objective optimization model of coupled wind power and thermal power transmission is proposed. The target differential evolution algorithm solves the model, and finally obtains a set of optimized scheduling output plans for wind and thermal power, which provides a scientific basis for operators to make scheduling decisions. Finally, a regional power grid is taken as an example to prove the rationality of the model and the effectiveness of the proposed algorithm.

Adequacy capacity and flexibility of transmission and generation equipment is the necessary factors to adapt to the gradual increase of the scale of loads and wind power. This paper proposes an integrated planning method of transmission network and thermal power units’ flexibility reformation, and gives ajoint planning mathematical model for the flexibility reformation of thermal power units and optimization of transmission network. The time sequence characteristics of load and wind power are taken into account in the proposed model to accurately describe the time sequence operation scenario of power system. The proposed mathematical model is transformed into a mixed-integer linear programming model and solved by mixed-integer linear programming algorithm. The example analysis shows that the proposed method can guarantee the expected wind power consumption, realize the precise investment for flexibility reformation of thermal power units and power grid development, and improve the economy of power system operation.

In view of the characteristics of intermittence and fluctuation of wind power output and the trend of large scale grid connection of wind power and power grid to assume the function of renewable energy consumption, this paper proposes a multi-objective coordinated planning method based on AP (Affinity Propagation) clustering algorithm combined with improved MPGA (Multi-Population Genetic Algorithm) for power grid considering wind power integration. Firstly, the AP clustering algorithm is used to cluster the typical wind farm operation scenarios. Then, the power grid planning optimization model considering wind power consumption and line load balancing rate is established. Finally, the feasibility and validity of the proposed method are verified in the IEEE 18-bus system.

One thousand and twenty‐three subjects in four different types of statutory accommodation were surveyed during a two‐week period using the Survey version of the Clifton Assessment Procedure for the Elderly. The types of accommodation were conventional residential accommodation (CRA), elderly mentally infirm homes (EMI), geriatric wards (GER), and psychogeriatric wards (PG), all within a specific geographic area. The survey was undertaken to determine prevaalence of dementia and levels of dependency in different types of unit and to ascertain if there were significant differences between them. There was a high level of both dementia and dependency in all four types of unit, but significant differences were demonstrated between different types of unit.

This paper presents an adjustable interval optimization model for the energy and reserve clearance while treating the wind power variation and uncertainty. Instead of conventional predicted intervals (PIs), adjustable intervals (AIs) as subsets of PIs are proposed as more judicious choices for economically covering wind uncertainties. Ramp-capability reserve is modeled to ensure the existence of sufficient ramp capability needed to follow up wind power variation within AIs. However, realization of wind power beyond AIs, which is no longer compensable by ramp-capability reserve, would necessarily lead to either load shedding or wind spillage. In order to optimally determine AIs, apart from the energy and reserve procurement costs, the costs associated with load shedding and wind spillage are incorporated in the objective function. The confidence level theory is employed as well for tuning the robustness and conservatism of the final solution. Performance of the proposed method is examined on several case studies on an 8-bus and modified IEEE 118-bus test systems. Sensitivity analyses are conducted to specify the impacts of important parameters on the obtained solution. The results confirm the applicability and effectiveness of the proposed methodology.

Dispatch results depend on the forecast wind power in an electric power grid. High levels of uncertainty in wind power lead to large forecast errors (FEs). Wind power FE creates an imbalance between power load demand and supply, which poses risks to the power grid. To minimise the risk caused by uncertainty in wind power, FE was analysed. The actual and forecast power of wind generations were studied to determine which factors had strong relationships with FE. After being analysed by principle component analysis, these factors were used to build an assessment model to estimate FE. According to the output of the assessment model, risk factor (RF) was defined to evaluate the risk‐level associated with wind power. Moreover, based on a grid including wind generation and fossil fuel‐fired power plants, a dispatch model was built to account for the cost of fossils fuels and RF. This dispatch model was studied to find strategies for decreasing the impact of wind power on the grid. The results from their research will increase the safety and reliability of power grids with uncertain levels of wind power and promote the widespread use of wind power.