A novel strategy for optimal scheduling of short-term electric power generation of cascaded hydroelectric plants based on particle swarm optimization (PSO) and chance-constrained programming is ...presented to maximize the expected profit at a given risk level in this paper. Based on chance-constrained programming, in which some specified probability are given to simulate some uncertainties, such as water inflows, electricity prices, unit status, and so on. This paper proposes a model for short-term scheduling optimization of cascaded hydro plants, which includes uncertainties, spatial-temporal constraints among cascaded reservoirs, etc. A hybrid particle swarm optimization (HPSO), which is embedded with evolutionary algorithms, is presented to use for the solution of global optimization problems. Catastrophe theory, which is concerned with natural evolutionary or survival-of-the-fittest, is utilized as an indication of the premature converge of PSO, and the positions of particles are further adjusted in the search space according to chaos optimization. In this way, each particle competes and cooperates with its neighbors. The proof shows that HPSO is guaranteed to converge to the global optimization solution with probability one. The model presented is solved by a combination method of HPSO and Monte Carlo simulation. Finally, a numerical example is served for demonstrating the feasibility of the method developed.
In this paper, we propose a bi-level, real-time economic dispatch method of a virtual power plant (VPP), including various distributed energy resources (DERs). Considering the different interests of ...VPPs and a system operator, the real-time economic dispatch of VPPs is described as a bi-level programming problem, where a system operator dispatches VPPs based on the price incentive mechanism on the upper level, and the VPPs provide response according to the optimal control of their DERs on the lower level. Considering the uncertainties of DERs and loads, the decision risks of a system operator on the upper level and VPPs on the lower level are further dealt with by the fuzzy chance constrained programming, such that they can make reasonable decisions according to their own preferred risks. The mapping method and the bi-level optimization method are also presented as the solutions for the proposed model. In this way, the fuzzy chance constraints and objective functions of both levels are transformed into deterministic forms and, then, are calculated dispersedly. As a result, the calculation burden of a system operator and the information privacies of VPPs all can be treated availably. The case studies verify the effectiveness of the proposed method in the end.
Background
To assess the potential prognostic value of the albumin to alkaline phosphatase ratio (AAPR) in patients with non‐small cell lung cancer (NSCLC) after surgery.
Methods
The log‐rank and ...Kaplan‐Meier analyses were performed to detect differences in survival levels between different groups. A model of Cox proportional hazards was used to perform univariate and multivariate survival analyses. Comparisons of receiver operating characteristic (ROC) curves and the likelihood ratio test (LRT) were also utilized to compare the prognostic abilities of different systems for overall survival (OS) prediction.
Results
The optimal cut‐off value of the preoperative AAPR was 0.64. A decreased AAPR was associated with several clinicopathological and clinicolaboratory variables related to cancer progression. The preoperative AAPR of patients was positively correlated with the poor prognosis of NSCLC. In multivariate analyses, the preoperative AAPR was identified as an independent prognostic factor for disease‐free survival (DFS; P = 0.001) and overall survival (OS; P = 0.003). The LRT showed that the AAPR tumor‐node‐metastasis (TNM) system presented a significantly larger χ2 value (112.4 vs. 89.2, respectively, P < 0.01) and a relatively smaller Akaike information criterion (AIC) value (2955 vs. 2977, respectively, P < 0.01) than the TNM staging system.
Conclusion
Preoperative AAPR was a potentially valuable prognostic factor in NSCLC patients who underwent surgery. Our results further showed that the AAPR‐TNM system was superior to the current TNM staging system.
Electric loads are essential for power system dynamic simulation. However, load modeling is one of the most challenging topics due to the diversity and time-varying behavior of the load. When ...considering the intervention of rapidly developing distributed generation (DG), load modeling becomes more difficult. In this paper, a new solution for determining the unknown generalized load model is proposed. The radial basis function (RBF) neural network-based sub-models of generalized load are stored in the form of a sub-model bank. A recursive Bayesian approach is used to identify the sub-models and then merge them into one generalized load model according to their probabilities. The proposed method can be implemented online and adapt to describing the diversity and time-varying behavior of the generalized load. Numerical studies are carried out using both simulation data and actual measurements. The comparisons with other load modeling methods verify the advantages of the proposed method.
Background
CITED4 belongs to the CBP/p300‐interacting transactivator with glutamic acid and aspartic acid‐rich tail (CITED) family which is induced by various cytokines and participates in ...cytokine‐induced proliferation and differentiation. CITED4 is induced by HB‐EGF in lung cancer cells. However, it is unclear whether and how CITED4 contributes to the invasion and metastasis of lung adenocarcinoma (ADC).
Methods
CITED4 expression in lung adenocarcinoma and its association with disease‐free survival (DFS) and overall survival were analyzed based on a cohort of 261 patients. The roles of CITED4 were validated via loss‐of‐function and gain‐of‐function experiments. The relationship between CITED4 and CLDN3 was validated by immunohistochemistry, Western blotting, and luciferase reporter assays. The function of the CITED4‐CTNNB1‐CLDN3 complex was fully validated and described.
Results
CITED4 expression was significantly upregulated in ADC tissues and cells and a predictor for DFS. Downregulation of CITED4 attenuated the proliferation and invasion, whereas CITED4 overexpression enhanced these effects. Overexpression and knockdown of CITED4 resulted in the upregulation and downregulation of CLDN3, respectively. Moreover, CITED4 downregulation suppressed CLDN3‐mediated ADC cell metastasis in vivo. CITED4 was highly expressed and positively correlated with CLDN3. Mechanistically, CITED4 interacted with CTNNB1 and functioned synergistically to enhance CLDN3 transcription. Importantly, CITED4 induced ADC invasion via a CLDN3‐dependent pathway. CITED4 determined the level of CLDN3, which in turn affected the sensitivity of tumors to Clostridium perfringens enterotoxin treatment.
Conclusions
The CITED4‐CTNNB1‐CLDN3 axis plays a key role in the invasion and metastasis of ADC and provides a novel therapeutic target for lung cancer treatment.
CITED4 expression is significantly upregulated in ADC tissues and cells. CITED4 interacted with CTNNB1 and functioned synergistically to enhance CLDN3 transcription. The CITED4‐CTNNB1‐CLDN3 axis plays a key role in the invasion and metastasis of ADC and provides a novel therapeutic target for lung cancer treatment.
•A two-stage robust model is formulated to aggregate an ADS as a VPP.•The parameters of the VPP includes time-varying power bounds and ramp rates.•The uncertainty of the model includes the dispatch ...orders from the TSO and the outputs of the renewable distributed generations.•A CCG algorithm with acceleration strategies is designed and applied to solve the two-stage robust model.•Results show the correctness and effectiveness of the proposed method.
An effective way to make full use of the flexibility of distributed generations in an active distribution system (ADS) is to aggregate ADS as a virtual power plant (VPP) to participate in the day-ahead energy market. This paper proposes a robust optimization model to obtain parameters of the VPP that do not depend on the information of day-ahead energy markets, such as time-varying power bounds and ramp rates. The robust model considers the uncertainty of dispatch orders from the transmission system operator (TSO) and outputs of renewable distributed generations. Furthermore, the column-and-constraint generation algorithm is applied to solve the robust model. To accelerate its solution, the period decomposition and connection method is first proposed to change the max–min sub-problem into small-scale independent linear programming problems. Second, the directional per-unit method is proposed to establish the linear relationship between uncertain dispatch orders from the TSO and the parameters of the VPP, and this relationship is substituted into the master problem to reduce iterations. Finally, the proposed method is evaluated on a modified IEEE 33-bus system and a practical 185-bus distribution system. The results verify the correctness and effectiveness of the proposed method.
Cooperation across multiple energy sectors is capable of maximizing social welfare as revealed by existing research, but such holistic dispatch can be hardly implemented in a reality where energy ...sectors are run by different stakeholders respectively. To fill this gap, energy trading among multiple self-interested stakeholders is investigated in this paper. To maximize the social welfare of the trading results, an effective pricing method, referred to as network-constrained generalized locational marginal prices, is proposed. A trading mechanism is then carefully designed to encourage stakeholders to trade at network-constrained generalized locational marginal prices, while economic properties of the resultant generalized Nash equilibrium are analyzed in depth. The effectiveness of the mechanism is validated in two integrated electricity and heat systems with different scales. Numerical comparison demonstrates that existing non-cooperative mechanisms may result in undesirable deadweight losses, while surplus sharing is a tricky issue in cooperative mechanisms, making the cooperation unstable and infeasible. On the contrary, each stakeholder may optimize its subsystem in a self-interested manner in the proposed mechanism, but the overall outcome strikingly coincides with social welfare maximization.
•A network-constrained generalized locational marginal pricing for energy trading.•A mechanism encouraging self-interested stakeholders to trade at the proposed price.•A proof that the non-cooperative mechanism maximizes social welfare.•Economic property analysis of the resultant generalized Nash equilibrium.
Renewables and environmental challenges have become the headlines of academic discussions and interactions between international communities. In recent years, economists have studied the issue of ...improving the conditions of renewables and environmental resources from various aspects. In this article, the issue of how sports management affects renewables and environmental resources and what the roles of green financing are were considered using the survey research method. The 439 Respondents to questions were invited to this web survey through environmental NGOs in China, Iran, South Korea, Japan, Vietnam, Singapore, and Kazakhstan. The significant results confirmed a unified opinion among the respondents with different work experiences about the belief in the greening of sports management. Developing the use of green financing tools, creating a "green sports management network" discourse, cultivation through various communication media to increase public knowledge of the greening of sports management, and development of green power generation for sports venues such as stadiums, swimming pools are the policies provided by this research.
•RelAtionship of sports management, renewable energy, and the environment assessed.•The role of green finance in mitigating the negative impact was quantified.•The three challenges are lack of capital, knowledge, and planning.•Green finance could mitigate the negative impacts on the environment.•The green sport management network is another proposed recommendation.
This paper proposes a multiparametric approximate dynamic programming (MADP)-based explicit online operation policy for the robust energy management problem of active distribution network (ADN). ...First, the online energy management problem is described from the perspective of distributionally robust optimization (DRO). Then, the risk-averse concept is introduced to quantitatively control the conservativeness of DRO. Considering that it is a complex online optimal problem, which is intractable for traditional algorithms, an MADP-based explicit online operation policy is proposed in this paper. Specifically, the approximate dynamic programming (ADP) algorithm is improved based on the multiparametric programming theory, according to which an explicit online operation policy can be further derived. Compared to traditional online decision-making policies, which need to execute an optimization program, the proposed policy is able to directly obtain solutions through an explicit expression. In this way, the calculation efficiency can be enhanced significantly. Cases on several test systems validate the effectiveness of the proposed method.
Energy storage use right (ESUR) is a novel concept to make more people share the energy storage (ES) and give full play to its values. However, the integrated bidding, clearing and pricing method of ...ESURs is never reported nowadays. In this paper, we design some new ESURs, including the discrete power capacity right (DPCR) and the continuous energy capacity right (CECR), to meet the different needs of subscribers for sharing the ES. The ESUR trade is formulated as a bilevel problem, in which the upper-level problem represents the bidding strategies of subscribers, and the lower-level problem represents the market clearing. A pricing strategy is proposed to make the trading effective and fair by ensuring the optimalities of problems in both two levels. Using the Karush–Kuhn–Tucker (KKT) conditions and the binary expansion technique, the bilevel model is transferred into a linear problem to facilitate solving the model. In addition, it can be theoretically proved that the profit of each participant is non-negative. Numerical experiments are provided to demonstrate the effectiveness of the proposed method. Compared with the trading of DPCR, the participants’ overall profit is increased by 23.6%–145.91% owing to the additional consideration of the trading of CECR.
•Energy storage use rights designed to share the energy storage.•An integrated bidding, clearing and pricing method of energy storage use rights.•Conversion and linearization of the bilevel model.•Proof of the non-negative profit of each participant.
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