Afzal S. Siddiqui

Stockholm University

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Co-Authors

Chris Marnay

Lawrence Berkeley National Laboratory

Michael Städler

BEST - Bioenergy and Sustainable Technologies (Austria)

Makoto Tanaka

National Graduate Institute for Policy Studies

Yihsu Chen

University of California, Santa Cruz

Antonio J. Conejo

The Ohio State University

Judy Lai

Lawrence Berkeley National Laboratory

Ryan Firestone

Lawrence Berkeley National Laboratory

Jalal Kazempour

Technical University of Denmark

Emily S. Bartholomew

Johns Hopkins University

Hirohisa Aki

University of Tsukuba

Cooperative Institutions

New York Academy of Sciences

John Wiley & Sons (United States)

Hudson Institute

Lawrence Berkeley National Laboratory

Albert Einstein College of Medicine

Montefiore Medical Center

John Wiley & Sons (Germany)

Moss Landing Marine Laboratories

Liechtenstein Institute

Municipality of Medellín

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Strategic model for energy systems optimisation: Aspects of energy efficiency and risk management

Emilio L. Cano Javier M. Moguerza Afzal S. Siddiqui T. Ermolieva Y. Ermoliev

Industries and companies recognize that increasing efficiency of energy use and/or implementing alternative methods of production and operation with energy conservation/saving technologies may increase profit. Due to deregulation of the energy sector and the setting of targets such as the 20/20/20 in the EU, operators are now more exposed to short-term market conditions. On the other hand, they have gained the opportunity to play a more active role in securing long-term supply, managing demand, and hedging against risk while improving existing buildings' infrastructures. In the presence of deregulation and market uncertainties, there is a dilemma to choose an efficient technological portfolio in the short-term while pursuing long-term goals. The solution of this problem involves the so-called two-stage dynamic stochastic optimisation models with a rolling horizon. In this paper, a two-stage stochastic model is proposed, where some decisions (first-stage decisions) regarding investments in new energy technologies have to be taken before uncertainties are resolved, and some others (second-stage decisions) will be taken once values for uncertain parameters become known, thereby providing a trade-off between long- and short-term decisions. Investment planning and operational optimization decisions concern demand and supply sides of different energy types (electricity, heat, etc.). The demand side is affected by old and new equipment and activities including such end uses as electricity only, heating, cooling, cooking, new types of windows and buildings, and energy-saving technologies, etc. New activities may change peak loads, whereas accumulators may considerably smooth energy demand-supply processes. The proposed stochastic model is capable of dealing with short- and long-term horizons. In particular, the model avoids unrealistic end-of-the-world effects of dynamic deterministic models. The model is illustrated with examples from simulated and real test sites.

Time horizon

Deregulation

Energy supply

Investment Decisions

Investment

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Citations (2)

Achieving Emission-Reduction Goals: Multi-Period Power-System Expansion Under Short-Term Operational Uncertainty

IEEE Transactions on Power Systems (2023)

Tuomas Rintamäki Fabrício Oliveira Afzal S. Siddiqui Ahti Salo

Stochastic adaptive robust optimization is capable of handling short-term uncertainties in demand and variable renewable-energy sources that affect investment in generation and transmission capacity. We build on this setting by considering a multi-year investment horizon for finding the optimal plan for generation and transmission capacity expansion while reducing greenhouse gas emissions. In addition, we incorporate multiple hours in power-system operations to capture hydropower operations and flexibility requirements for utilizing variable renewable-energy sources such as wind and solar power. To improve the computational performance of existing exact methods for this problem, we employ Benders decomposition and solve a mixed-integer quadratic programming problem to avoid computationally expensive big-M linearizations. The results for a realistic case study for the Nordic and Baltic region indicate which investments in transmission, wind power, and flexible generation capacity are required for reducing greenhouse gas emissions. Through out-of-sample experiments, we show that the stochastic adaptive robust model leads to lower expected costs than a stochastic programming model under increasingly stringent environmental considerations.

Time horizon

Economic Dispatch

Variable renewable energy

10.1109/tpwrs.2023.3244668

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Citations (7)

Investment in Production Capacity

Springer eBooks (2016)

Antonio J. Conejo Luis Baringo Jalal Kazempour Afzal S. Siddiqui

Planner

Investment

10.1007/978-3-319-29501-5_5

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Citations (1)

Introduction

International series in management science/operations research/International series in operations research & management science (2020)

Yihsu Chen Afzal S. Siddiqui Makoto Tanaka

Scope (computer science)

Energy Sector

Investment

Power-to-Gas

10.1007/978-3-030-44866-0_1

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Direct Participation of Electrical Loads in the California Independent System Operator Markets During the Summer of 2000

Lawrence Berkeley National Laboratory (2001)

Chris Marnay Kristina S. Hamachi Mark Khavkin Afzal S. Siddiqui

California's restructured electricity markets opened on 1 April 1998. The former investor-owned utilities were functionally divided into generation, transmission, and distribution activities, all of their gas-fired generating capacity was divested, and the retail market was opened to competition. To ensure that small customers shared in the expected benefit of lower prices, the enabling legislation mandated a 10 percent rate cut for all customers, which was implemented in a simplistic way that fossilised 1996 tariff structures. Rising fuel and environmental compliance costs, together with a reduced ability to import electricity, numerous plant outages, and exercise of market power by generators drove up wholesale electricity prices steeply in 2000, while retail tariffs remained unchanged. One of the distribution/supply companies entered bankruptcy in April 2001, and another was insolvent. During this period, two sets of interruptible load programmes were in place, longstanding ones organised as special tariffs by the distribution/supply companies and hastily established ones run directly by the California Independent System Operator (CAISO). The distribution/supply company programmes were effective at reducing load during the summer of 2000, but because of the high frequency of outages required by a system on the brink of failure, customer response declined and many left the tariff. The CAISO programmes failed to attract enough participation to make a significant difference to the California supply demand imbalance. The poor performance of direct load participation in California's markets reinforces the argument for accurate pricing of electricity as a stimulus to energy efficiency investment and as a constraint on market volatility.

Electricity retailing

Mains electricity

Deregulation

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Citations (3)

Investing in Time-to-Build Projects With Uncertain Revenues and Costs: A Real Options Approach

IEEE Transactions on Engineering Management (2018)

Lauri Kauppinen Afzal S. Siddiqui Ahti Salo

Lagging public-sector investment in infrastructure and the deregulation of many industries mean that the private sector has to make decisions under multiple sources of uncertainty. We analyze such investment decisions by accounting for both multiple sources of uncertainty and the time-to-build aspect. The latter feature arises in the energy and transportation sectors, because investors can decide the rate at which the project is completed. Furthermore, two explicit sources of uncertainty represent the discounted cash inflows and outflows of the completed project. We use a finite-difference scheme to solve numerically the option value and the optimal investment threshold. Somewhat counterintuitively, with a relatively long time to build, a reduction in the growth rate of the discounted operating cost may actually lower the investment threshold. This is contrary to the outcome when the stepwise aspect is ignored in a model with uncertain price and cost. Hence, research and development efforts to enhance emerging technologies may be more relevant for infrastructure projects with long lead times.

Lagging

Investment

Option value

Investment Decisions

Deregulation

10.1109/tem.2018.2803304

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Citations (21)

Microgrid Selection and Operation for Commercial Buildings in California and New York States

Lawrence Berkeley National Laboratory (2008)

Environmental Energy Technologies Division Kristina S H Lacommare Chris Marnay Michael Städler Hirohisa Aki

The addition of storage technologies such as lead-acid batteries, flow batteries, or heat storage can potentially improve the economic and environmental attractiveness of on-site generation such as PV, fuel cells, reciprocating engines or microturbines (with or without CHP), and can contribute to enhanced demand response. Preliminary analyses for a Californian nursing home indicate that storage technologies respond effectively to time-varying electricity prices, i.e., by charging batteries during periods of low electricity prices and discharging them during peak hours. While economic results do not make a compelling case for storage, they indicate that storage technologies significantly alter the residual load profile, which may lower carbon emissions as well as energy costs depending on the test site, its load profile, and DER technology adoption.

Microgrid

Electricity demand

Source

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Citations (8)

Optimal selection of on-site generation with combined heat andpower applications

Afzal S. Siddiqui Chris Marnay Owen Bailey Kristina Hamachi-LaCommare

While demand for electricity continues to grow, expansion of the traditional electricity supply system, or macrogrid, is constrained and is unlikely to keep pace with the growing thirst western economies have for electricity. Furthermore, no compelling case has been made that perpetual improvement in the overall power quality and reliability (PQR)delivered is technically possible or economically desirable. An alternative path to providing high PQR for sensitive loads would generate close to them in microgrids, such as the Consortium for Electricity Reliability Technology Solutions (CERTS) Microgrid. Distributed generation would alleviate the pressure for endless improvement in macrogrid PQR and might allow the establishment of a sounder economically based level of universal grid service. Energy conversion from available fuels to electricity close to loads can also provide combined heat and power (CHP) opportunities that can significantly improve the economics of small-scale on-site power generation, especially in hot climates when the waste heat serves absorption cycle cooling equipment that displaces expensive on-peak electricity. An optimization model, the Distributed Energy Resources Customer Adoption Model (DER-CAM), developed at Berkeley Lab identifies the energy bill minimizing combination of on-site generation and heat recovery equipment for sites, given their electricity and heat requirements, the tariffs they face, and a menu of available equipment. DER-CAM is used to conduct a systemic energy analysis of a southern California naval base building and demonstrates atypical current economic on-site power opportunity. Results achieve cost reductions of about 15 percent with DER, depending on the tariff.Furthermore, almost all of the energy is provided on-site, indicating that modest cost savings can be achieved when the microgrid is free to select distributed generation and heat recovery equipment in order to minimize its over all costs.

Microgrid

Stand-alone power system

Cogeneration

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Citations (0)

On fault-tolerant metric dimension of supramolecular networks

Discrete Mathematics Algorithms and Applications (2024)

Afzal S. Siddiqui Khadija Mazhar Muhammad Kamran Siddiqui Muhammad Faisal Nadeem

The idea of a fault-tolerant metric dimension can be used in chemistry to examine a molecule’s structural resistance to the failure of particular atoms or chemical bonds. This is especially important when creating molecules for specific uses, like drug candidates, as they may be exposed to biological systems or the environment, which could cause certain atoms or bonds to change or break. One such is the dialkyltin complex, which has two alkyl groups joined to a tin atom. The nitrogen atom of an N-salicylidene-L-valine molecule is coupled to the alkyl groups in the dialkyltin complex-1 of N-salicylidene-L-valine, making it a useful catalyst for numerous processes in organic synthesis. The purpose of this study is to identify the fault-tolerant metric dimension of the chain in N-salicylidene-L-valine dialkyltin complex-3.

10.1142/s1793830924500022

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Citations (1)

Optimal Planning and Operation of Smart Grids with Electric Vehicle Interconnection

Journal of Energy Engineering (2012)

Michael Städler Chris Marnay M. Kloess G. Cardoso Gonçalo Mendes

Connection of electric storage technologies to smart grids will have substantial implications for building energy systems. Local storage will enable demand response. When connected to buildings, mobile storage devices, such as electric vehicles (EVs), are in competition with conventional stationary sources at the building.These EVs can change the financial and environmental attractiveness of on-site generation [e.g., photovoltaic (PV) or fuel cells (FCs)]. To examine the effect of EVs on building energy costs and carbon dioxide (CO2) emissions, a distributed-energy resources adoption problem is formulated as a mixed-integer linear program with minimization of annual building energy costs or CO2 emissions and solved for 2020 technology assumptions. The mixed-integer linear program is applied to a set of 139 different commercial buildings in California, and example results and the aggregated economic and environmental benefits are reported. Special constraints for the available PV, solar thermal, and EV parking lots at the commercial buildings are considered. The research shows that EV batteries can be used to reduce utility-related energy costs at the smart grid or commercial building due to arbitrage of energy between buildings with different tariffs. However, putting more emphasis on CO2 emissions makes stationary storage more attractive, and stationary storage capacities increase, whereas the attractiveness of EVs decreases. The limited availability of EVs at the commercial building decreases the attractiveness of EVs, and if PV is chosen by the optimization, then it is mostly used to charge the stationary storage at the commercial building and not the EVs connected to the building.

Grid connection

10.1061/(asce)ey.1943-7897.0000070

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Citations (37)