Haoyong Chen

Analyzing oligopolistic electricity market using coevolutionary computation

This paper presents a new unified framework of electricity market analysis based on coevolutionary computation (CCEM) for both the one-shot and the repeated games of oligopolistic electricity markets. The standard Cournot model and the new Pareto improvement model are used. The linear and constant elasticity demand functions are considered. Case study shows that CCEM is highly efficient and can handle the nonlinear market models that are difficult to be handled by conventional methods. The framework presented in this paper can help to overcome the difficulties of demand function specification encountered by the Cournot models. CCEM is found to be an effective and powerful approach for electricity market analysis.

Quasi-Monte Carlo Based Probabilistic Small Signal Stability Analysis for Power Systems With Plug-In Electric Vehicle and Wind Power Integration

This paper presents a new quasi-Monte Carlo (QMC) based probabilistic small signal stability analysis (PSSSA) method to assess the dynamic effects of plug-in electric vehicles (PEVs) and wind energy conversion systems (WECSs) in power systems. The detailed dynamic model of PEVs is first proposed for stability study. To account for the stochastic behavior of PEVs and WECSs in load flow studies, the randomized model and probability density function (PDF) representing their nodal power injections are first developed, and then their stochastic injections are sampled by Sobol sequences. Finally, the distribution of system eigenvalues can be obtained by the PSSSA. The proposed QMC-based PSSSA is tested on the modified 2-area 4-machine system and New England 10-generator 39-bus system. Results showed the necessity of modeling of PEVs and WECSs, and validated the efficiency of the proposed QMC.

A coevolutionary approach to analyzing supply function equilibrium model

This paper presents a coevolutionary approach to analyzing supply function equilibrium (SFE) models of an oligopolistic electricity market. Both the affine supply function model and the piece-wise affine supply function model are considered. Different parametrization cases of the affine supply function model are analyzed. The piece-wise affine supply functions that have a large number of pieces are used to numerically estimate the equilibrium supply functions of any shapes. Simulation cases of the piece-wise affine supply function model with different peak loads, nonquadratic and nonconvex costs, and different demand elasticities are studied. An example based on the cost data from the real-world electricity industry is used to validate the approach presented in this paper. Simulation results show that the coevolutionary approach rapidly converges to SFE in the affine supply function model simulation and robustly converges to SFE in all cases of the piece-wise affine supply function model simulation. The approach is robust and flexible and has the potential to be used to solve the complicated equilibrium problems in real-world electricity markets

A Robust Approach to Optimal Power Flow With Discrete Variables

Optimal power flow (OPF) belongs to the nonlinear optimization problem with discrete variables. The interior point cutting plane method (IPCPM), which possesses the advantages of both the interior point method and the cutting plane method, becomes a very promising approach to the large-scale OPF. It employs a successive linearization process and iteratively solves the mixed integer linear programming problem. However, case studies have shown that: if the problem has multiple solutions, the optimal solutions will converge to the interior of the optimal face, and the cutting planes cannot be generated due to the failure to identify the optimal base. This paper presents a new general optimal base identification method for solving the problem. The new approach significantly improves the robustness and efficiency of IPCPM. Simulation results on IEEE test systems indicate that the algorithm proposed can not only properly deal with various types of optimal solutions but also greatly enlarge the application area of IPCPM.

Computing All Nash Equilibria of Multiplayer Games in Electricity Markets by Solving Polynomial Equations

The analysis of the Nash equilibrium (NE) in electricity markets with imperfect competition is subject to two major challenges: the treatment of multiplayer games and the determination of the existence of multiple market equilibria. To resolve these obstacles, a solution method, based on the payoff matrix approach and polynomial equations, is proposed in this paper to calculate all the Nash equilibria of multiplayer games in the electricity markets. First, the proposed method decomposes the game by means of a set of all pure strategies assigned with positive probabilities (support). For each possible support, the NE condition can be characterized by a set of polynomial equations with inequality constraints. Next, the homotopy continuation algorithm is employed to obtain all solutions of the polynomial system. Finally, all Nash equilibria can be found by verifying each solution of all polynomial systems. Two example systems, one involving the Cournot model and the other based on the supply function equilibrium (SFE) model, are applied to test the proposed method, respectively. The results show that the proposed method has the ability to identify all NE under certain conditions, indicating that the proposed algorithm is useful for providing insights into the theoretical analysis of electricity markets.

Superhydrophilic nano-TiO2 film with porous surface structure

Abstract The TiO2 films prepared from a sol–gel precursor were deposited on glass substrates using spin coating technique. Titania sols were doped with and without a pore generating agent, polyethylene glycol (PEG), to evaluate the effect of porosity on the superhydrophilicity of the coatings. The crystalline phase and surface morphology of the TiO2 thin films were characterised by XRD, SEM and scanning measurement station (SMS). Wetting behaviour of the resulting films were characterised using contact angle measurements. This particular porous surface prepared from 0·5M tetrabutyl titanate with PEG sintered at 450°C was in anatase form and has maximum specific surface area and average roughness. The results show that the PEG doped anatase TiO2 film exhibits superhydrophilic characteristic, although it is not exposed to ultraviolet irradiation. Finally, the formation mechanism and the property–structure relationship were discussed in detail.

Strategic Behavior and Equilibrium in Experimental Oligopolistic Electricity Markets

The method of experimental economics is applied to research of oligopolistic electricity markets. The design of experimental platform, principles of experimental economics and experimental design are introduced. The experiments are organized on base of the Cournot model of oligopolistic electricity markets. A set of experiments are conducted on the experimental oligopolistic markets with three generating companies (Gencos) and the experimental results are analyzed with strict statistics approaches. The results show that the market competition will converge to the results between perfect competition equilibrium and Nash equilibrium in oligopolistic electricity markets with asymmetric production cost functions and repeated play among the Gencos. The decision support tools of Gencos have significant influences on experimental results. The markets converge to static Cournot-Nash equilibrium when the bounded-rational subjects repeatedly play, equipped with the tools that can give best response strategies. The experimental method provides a complement to the theoretical research and computer simulation and has many merits in modeling realistic electricity markets.

Key Technologies for Integration of Multitype Renewable Energy Sources—Research on Multi-Timeframe Robust Scheduling/Dispatch

Large-scale integration of multitype renewable energy (RE) sources (intermittent energy sources) has become an important feature in smart grid development all over the world. It is internationally recognized that the island (or weak-tie connected) power grids are the best platforms for intermittent energy integration test and demonstration because of their abundant RE resources, scarcity of conventional energy, and technical difficulty with accommodation of intermittent energy. The ongoing research on Hainan (the second biggest island in China) power grid will achieve a comprehensive breakthrough in power grid planning, analysis, scheduling, operation, relay protection, security control, disaster prevention, and other key areas in multitype RE source integration. To be specific, this paper focuses on the key part of the research project¡aoptimal scheduling and complementary operation and a new framework of multitime-frame robust scheduling/dispatch system is first proposed, which is different from most other robust approaches and lays special emphasis on the engineering characteristics of power system operation. Simulation results based on the real data of Hainan power grid show that the approach presented is effective and will be put into online operation in the near future.

Robust scheduling of power system with significant wind power penetration

Wind power generation brings new challenges to power system scheduling due to the uncertainty caused by its imprecise prediction. Especially when multiple wind farms are taken into consideration, models and optimization methods which are good at dealing with deterministic scheduling problems do not work. Stochastic Programming (SP) has been usually applied to solve the problem with wind power uncertainty, which has many advantages and limitations. A new concept of Robust Scheduling (RS) is first proposed in this paper and the mathematical model is established. The Mixed Integer Programming (MIP) is adopted for solving the model. The paper also defines the extreme scenarios set for description of wind power uncertainty. By using it we can achieve robust schedule by avoiding the use of the probabilistic distribution of wind power, which is often hard to acquire. Case study based on the modified IEEE118 bus system proves that the RS model and optimization method are effective and can acquire a robust schedule over wind power uncertainty.

Stochastic Robust Mathematical Programming Model for Power System Optimization

This letter presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with different uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.